@article{moghairib_model-agnostic_2026,
	title = {A {Model}-{Agnostic} {Representation} of {Prairie} {Pothole} {Hydrology}: {Enhancing} {Generality} and {Implementation} {Across} {Hydrological} {Models}},
	volume = {62},
	copyright = {© 2026. The Author(s).},
	issn = {1944-7973},
	shorttitle = {A {Model}-{Agnostic} {Representation} of {Prairie} {Pothole} {Hydrology}},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2025WR043074},
	doi = {10.1029/2025WR043074},
	abstract = {Modeling streamflow in low-lying, flat, and pothole-dominated prairie or Arctic regions is challenging due to variable non-contributing areas that influence how runoff translates to streamflow. Several modeling approaches have been developed to represent these dynamics, but many (a) lump depressions and permit spill only after a fixed capacity is reached, (b) rely heavily on calibration, (c) are unsuitable for large basins, (d) do not account for non-pothole contributions, and/or (e) are not model-agnostic. Here we present HDSv2, a second-generation Hysteretic Depressional Storage (HDS) module that is open-source, model-agnostic, numerically robust, and grounded in long-established physical understanding of prairie potholes. HDSv2 represents dynamic contributing area and storage–discharge hysteresis, enabling realistic simulation of fill-and-spill behavior and cold-region processes. We couple HDSv2 with three hydrological and land-surface models of differing architectures: HYPE (Hydrological Predictions for the Environment), MESH (Modélisation Environnementale communautaire—Surface and Hydrology), and SUMMA (Structure for Unifying Multiple Modeling Alternatives), applied in the Smith Creek River Basin, Canada. Results show that HDSv2 improves numerical stability and process fidelity relative to the original HDS model, which exhibited instabilities affecting contributing-area simulation within HYPE. Across all host models, integrating HDSv2 produces more robust hydrographs than the original configurations and better reproduces observed relationships between depressional storage and contributing area. Although hydrograph improvements vary by host, additional performance metrics show consistent gains in both high and low flow conditions. These findings demonstrate that HDSv2 provides a transferable and scalable pathway for incorporating depressional-storage dynamics into diverse hydrological models and regions.},
	language = {en},
	number = {4},
	urldate = {2026-05-27},
	journal = {Water Resources Research},
	author = {Moghairib, Mohamed and Clark, Martyn P. and Pietroniro, Alain and Stadnyk, Tricia},
	year = {2026},
	note = {\_eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2025WR043074},
	keywords = {NALCMS},
	pages = {e2025WR043074},
}

Modeling streamflow in low-lying, flat, and pothole-dominated prairie or Arctic regions is challenging due to variable non-contributing areas that influence how runoff translates to streamflow. Several modeling approaches have been developed to represent these dynamics, but many (a) lump depressions and permit spill only after a fixed capacity is reached, (b) rely heavily on calibration, (c) are unsuitable for large basins, (d) do not account for non-pothole contributions, and/or (e) are not model-agnostic. Here we present HDSv2, a second-generation Hysteretic Depressional Storage (HDS) module that is open-source, model-agnostic, numerically robust, and grounded in long-established physical understanding of prairie potholes. HDSv2 represents dynamic contributing area and storage–discharge hysteresis, enabling realistic simulation of fill-and-spill behavior and cold-region processes. We couple HDSv2 with three hydrological and land-surface models of differing architectures: HYPE (Hydrological Predictions for the Environment), MESH (Modélisation Environnementale communautaire—Surface and Hydrology), and SUMMA (Structure for Unifying Multiple Modeling Alternatives), applied in the Smith Creek River Basin, Canada. Results show that HDSv2 improves numerical stability and process fidelity relative to the original HDS model, which exhibited instabilities affecting contributing-area simulation within HYPE. Across all host models, integrating HDSv2 produces more robust hydrographs than the original configurations and better reproduces observed relationships between depressional storage and contributing area. Although hydrograph improvements vary by host, additional performance metrics show consistent gains in both high and low flow conditions. These findings demonstrate that HDSv2 provides a transferable and scalable pathway for incorporating depressional-storage dynamics into diverse hydrological models and regions.

@article{orning_regional_2026,
	title = {A regional simulation modeling framework for evaluating invasive annual grass management across the sagebrush biome},
	volume = {315},
	issn = {0006-3207},
	url = {https://www.sciencedirect.com/science/article/pii/S0006320726000285},
	doi = {10.1016/j.biocon.2026.111720},
	abstract = {Invasive annual grasses (IAG) continue to spread within the sagebrush biome of the western United States, degrading plant communities and wildlife habitat, decreasing forage for ranching livelihoods, and heightening wildfire risk. Effective management of IAGs requires action and long-term strategic planning across the sagebrush biome, but the cumulative effects of IAG treatments over time and space are not well understood, especially over broad extents defined for strategies like the Sagebrush Conservation Design. We developed a simulation model and sampling framework that allow local-scale actions to be ‘scaled up’ to evaluate large-scale regional and biome-wide management strategy outcomes. We worked with natural resource managers and experts to co-develop a spatially explicit state-and-transition simulation model of IAG dynamics in sagebrush landscapes that can be used to evaluate alternative management strategies. We evaluated our framework by contrasting two baseline scenarios in terms of their long-term effects on the sagebrush biome. We show that focusing management efforts on moderate to high IAG cover was effective at reducing full conversion to IAGs but failed to prevent widespread establishment of IAGs in core sagebrush areas, exposing them to increased risk of wildfire and wildlife habitat degradation. The results of our model help quantify the extent of the problem that IAGs pose to sagebrush ecosystems given current knowledge and management efforts. Our framework provides a platform to explore alternative management strategy outcomes and can help managers develop informed conservation plans with realistic expectations for return on investment of resources committed to sagebrush landscapes.},
	urldate = {2026-05-28},
	journal = {Biological Conservation},
	author = {Orning, Elizabeth K. and Tarbox, Bryan C. and Jarnevich, Catherine S. and Garner, Lindy and Meldrum, James R. and Aldridge, Cameron L.},
	month = mar,
	year = {2026},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {111720},
}

Invasive annual grasses (IAG) continue to spread within the sagebrush biome of the western United States, degrading plant communities and wildlife habitat, decreasing forage for ranching livelihoods, and heightening wildfire risk. Effective management of IAGs requires action and long-term strategic planning across the sagebrush biome, but the cumulative effects of IAG treatments over time and space are not well understood, especially over broad extents defined for strategies like the Sagebrush Conservation Design. We developed a simulation model and sampling framework that allow local-scale actions to be ‘scaled up’ to evaluate large-scale regional and biome-wide management strategy outcomes. We worked with natural resource managers and experts to co-develop a spatially explicit state-and-transition simulation model of IAG dynamics in sagebrush landscapes that can be used to evaluate alternative management strategies. We evaluated our framework by contrasting two baseline scenarios in terms of their long-term effects on the sagebrush biome. We show that focusing management efforts on moderate to high IAG cover was effective at reducing full conversion to IAGs but failed to prevent widespread establishment of IAGs in core sagebrush areas, exposing them to increased risk of wildfire and wildlife habitat degradation. The results of our model help quantify the extent of the problem that IAGs pose to sagebrush ecosystems given current knowledge and management efforts. Our framework provides a platform to explore alternative management strategy outcomes and can help managers develop informed conservation plans with realistic expectations for return on investment of resources committed to sagebrush landscapes.

@article{gu_assessing_2026,
	title = {Assessing {Spring} {Phenology} {Models} with {Photosynthesis} {Integration}: {Mechanistic} {Drivers} of the {Carbon}–{Frost} {Trade}-{Off}},
	volume = {17},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {1999-4907},
	shorttitle = {Assessing {Spring} {Phenology} {Models} with {Photosynthesis} {Integration}},
	url = {https://www.mdpi.com/1999-4907/17/2/287},
	doi = {10.3390/f17020287},
	abstract = {Accurate prediction of spring phenology is critical for understanding ecosystem carbon and water dynamics under changing climates. In this study, we applied a revised optimality-based model (R-OPT) that integrates a mechanistic photosynthesis framework into the existing OPT model to simulate leaf unfolding date. We evaluated R-OPT alongside three widely used models—Growing Degree Days (GDD), Chilling–Forcing Trade-off (CFT), and Optimality-based (OPT) models—across multiple Plant Functional Types (PFTs) and sites using repeated 5-fold cross-validation. Findings reveal that R-OPT consistently outperforms the other models, achieving the lowest median RMSE (13.11 days), indicating enhanced predictive accuracy and explanatory power. Although the model incurs slightly higher complexity (median AIC = 13.44), the improvement in prediction justifies the trade-off. Our results highlight the importance of incorporating plant functional traits and environmental heterogeneity in phenological modeling. PFT-specific differences, such as the lower RMSEs for evergreen forbs and deciduous broadleaf PFTs versus larger uncertainties for drought-deciduous and semi-evergreen PFTs, underscore that current models may insufficiently capture key environmental drivers, including precipitation and partial leaf retention. Latitudinal and elevational variations in trade-off parameter a, and the prominence of leaf-level carbon assimilation traits (Aleaf) as drivers of phenology, demonstrate the critical role of physiological traits in shaping PFT-specific phenological timing. These findings have significant implications for large-scale ecosystem modeling. By linking phenology directly to photosynthetic processes, R-OPT enhances predictive skill and biological interpretability, supporting improved simulations of carbon and water fluxes. Overall, R-OPT offers a mechanistically grounded and robust framework for advancing predictive understanding of spring phenology and its ecological and climate-relevant consequences.},
	language = {en},
	number = {2},
	urldate = {2026-05-27},
	journal = {Forests},
	author = {Gu, Yating and Wu, Qianhan and Wang, Xiaorong and Wang, Yantian},
	month = feb,
	year = {2026},
	note = {Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {Terrestrial Ecoregions (Griffith 2010)},
	pages = {287},
}

Accurate prediction of spring phenology is critical for understanding ecosystem carbon and water dynamics under changing climates. In this study, we applied a revised optimality-based model (R-OPT) that integrates a mechanistic photosynthesis framework into the existing OPT model to simulate leaf unfolding date. We evaluated R-OPT alongside three widely used models—Growing Degree Days (GDD), Chilling–Forcing Trade-off (CFT), and Optimality-based (OPT) models—across multiple Plant Functional Types (PFTs) and sites using repeated 5-fold cross-validation. Findings reveal that R-OPT consistently outperforms the other models, achieving the lowest median RMSE (13.11 days), indicating enhanced predictive accuracy and explanatory power. Although the model incurs slightly higher complexity (median AIC = 13.44), the improvement in prediction justifies the trade-off. Our results highlight the importance of incorporating plant functional traits and environmental heterogeneity in phenological modeling. PFT-specific differences, such as the lower RMSEs for evergreen forbs and deciduous broadleaf PFTs versus larger uncertainties for drought-deciduous and semi-evergreen PFTs, underscore that current models may insufficiently capture key environmental drivers, including precipitation and partial leaf retention. Latitudinal and elevational variations in trade-off parameter a, and the prominence of leaf-level carbon assimilation traits (Aleaf) as drivers of phenology, demonstrate the critical role of physiological traits in shaping PFT-specific phenological timing. These findings have significant implications for large-scale ecosystem modeling. By linking phenology directly to photosynthetic processes, R-OPT enhances predictive skill and biological interpretability, supporting improved simulations of carbon and water fluxes. Overall, R-OPT offers a mechanistically grounded and robust framework for advancing predictive understanding of spring phenology and its ecological and climate-relevant consequences.

@article{ongman_bergmanns_2026,
	title = {Bergmann's rule: {Why} does body size increase with latitude?},
	volume = {40},
	copyright = {© 2026 The Author(s). Functional Ecology published by John Wiley \& Sons Ltd on behalf of British Ecological Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.},
	issn = {1365-2435},
	shorttitle = {Bergmann's rule},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/1365-2435.70281},
	doi = {10.1111/1365-2435.70281},
	abstract = {Bergmann's rule describes the tendency for endothermic body size to increase with latitude, a pattern often attributed to climatic factors. However, the underlying developmental and evolutionary mechanisms remain debated. Latitudinal gradients in temperature and precipitation are often thought to be responsible for Bergmann's rule, but climate may generate such geographical patterns via several alternative pathways. We examined geographic patterns in body size of 5596 burrowing owls (Athene cunicularia) throughout western North America to inform the underlying processes responsible for range-wide phenotypic variation. Burrowing owls followed Begmann's rule, with larger individuals in northern latitudes. We also detected a longitudinal gradient, with the largest owls in the northwest of the breeding range. We considered several mechanisms to explain geographic gradients in burrowing owl body size: developmental plasticity, reversible plasticity, local adaptation. Developmental plasticity links body size to early-life environmental conditions, causing permanent changes; reversible plasticity involves temporary physiological shifts; local adaptation reflects evolutionary changes optimizing body size to local conditions. We tested predictions generated by each of these three mechanisms to assess how resource availability and climate shape continental body size patterns in burrowing owls. Spring precipitation explained variation in adult body mass, with contrasting effects in warm versus cold climates, supporting both local adaptation to thermal extremes and reversible plasticity in response to resource availability. Drought explained variation in juvenile body mass, supporting the developmental plasticity mechanism via resource availability. Juvenile mass was more influenced by maximum temperature during the prior breeding season than by natal year conditions, suggesting that extreme heat may affect parental condition or suppress resource availability into the following year, consistent with developmental or reversible plasticity. Extreme temperatures and drought during the prior breeding season explained variation in adult tarsus length, more so than 21-year mean climate conditions or geographic gradients, supporting the developmental plasticity mechanism via drought or thermal stress. Body size of burrowing owls largely conforms to Bergmann's rule and appears to reflect both acute and evolutionary responses to resource availability and thermoregulatory mechanisms depending on whether a trait was more plastic (body mass) or more fixed (tarsus) during adulthood. Read the free Plain Language Summary for this article on the Journal blog.},
	language = {en},
	number = {4},
	urldate = {2026-05-28},
	journal = {Functional Ecology},
	author = {Ongman, Kurt M. and Lundblad, Carl G. and Conway, Courtney J.},
	year = {2026},
	note = {\_eprint: https://besjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/1365-2435.70281},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {830--843},
}

Bergmann's rule describes the tendency for endothermic body size to increase with latitude, a pattern often attributed to climatic factors. However, the underlying developmental and evolutionary mechanisms remain debated. Latitudinal gradients in temperature and precipitation are often thought to be responsible for Bergmann's rule, but climate may generate such geographical patterns via several alternative pathways. We examined geographic patterns in body size of 5596 burrowing owls (Athene cunicularia) throughout western North America to inform the underlying processes responsible for range-wide phenotypic variation. Burrowing owls followed Begmann's rule, with larger individuals in northern latitudes. We also detected a longitudinal gradient, with the largest owls in the northwest of the breeding range. We considered several mechanisms to explain geographic gradients in burrowing owl body size: developmental plasticity, reversible plasticity, local adaptation. Developmental plasticity links body size to early-life environmental conditions, causing permanent changes; reversible plasticity involves temporary physiological shifts; local adaptation reflects evolutionary changes optimizing body size to local conditions. We tested predictions generated by each of these three mechanisms to assess how resource availability and climate shape continental body size patterns in burrowing owls. Spring precipitation explained variation in adult body mass, with contrasting effects in warm versus cold climates, supporting both local adaptation to thermal extremes and reversible plasticity in response to resource availability. Drought explained variation in juvenile body mass, supporting the developmental plasticity mechanism via resource availability. Juvenile mass was more influenced by maximum temperature during the prior breeding season than by natal year conditions, suggesting that extreme heat may affect parental condition or suppress resource availability into the following year, consistent with developmental or reversible plasticity. Extreme temperatures and drought during the prior breeding season explained variation in adult tarsus length, more so than 21-year mean climate conditions or geographic gradients, supporting the developmental plasticity mechanism via drought or thermal stress. Body size of burrowing owls largely conforms to Bergmann's rule and appears to reflect both acute and evolutionary responses to resource availability and thermoregulatory mechanisms depending on whether a trait was more plastic (body mass) or more fixed (tarsus) during adulthood. Read the free Plain Language Summary for this article on the Journal blog.

@article{potash_biogeography_2026,
	title = {Biogeography and {Anthropogenic} {Development} {Shape} {Mesopredator} {Distributions} in a {Rapidly} {Developing} {Region}},
	volume = {53},
	copyright = {© 2026 John Wiley \& Sons Ltd.},
	issn = {1365-2699},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/jbi.70147},
	doi = {10.1111/jbi.70147},
	abstract = {Aim To investigate effects of anthropogenic development at regional and landscape scales on the distributions of mid-trophic level mammalian predators (mesopredators) across the southeastern United States. Location The study area encompasses seven ecoregions across a large portion of the southeastern United States. Taxon Mammalian mesopredators. Methods We compiled trail camera data from 21 studies across the southeastern United States and used occupancy modelling to assess mesopredator distributions and account for heterogeneous detection probabilities. We examined drivers of occupancy at regional and landscape scales. At the regional scale, we assessed occupancy patterns across ecoregions differing in topography, productivity, and human population growth. At the landscape scale, we analysed the influence of land cover types (forest, developed, agriculture) and non-native coyote (Canis latrans) activity on occupancy. Results Regionally, mesopredator occurrence was highest in ecoregions characterised by low productivity and greater topographic variability. Common species (predicted occupancy ≥ 0.19) showed positive associations with developed and agricultural land covers, while less common species (predicted occupancy ≤ 0.10) showed negative associations or were too rare to model. Coyote activity had mixed effects, positively associated with some species while negatively associated with others. Main Conclusions Anthropogenic development affects mesopredator communities at both regional and landscape scales, favouring generalist species that are tolerant of human-modified landscapes.},
	language = {en},
	number = {1},
	urldate = {2026-05-29},
	journal = {Journal of Biogeography},
	author = {Potash, Alex D. and Conner, L. Mike and Lashley, Marcus and Cherry, Michael and Edelman, Andrew J. and Garrison, Elina and Greene, Daniel U. and Gulsby, William and Hallett, Matthew T. and Jachowski, David S. and Taillie, Paul and McCleery, Robert A.},
	year = {2026},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/jbi.70147},
	keywords = {Terrestrial Ecoregions (Griffith 2010)},
	pages = {e70147},
}

Aim To investigate effects of anthropogenic development at regional and landscape scales on the distributions of mid-trophic level mammalian predators (mesopredators) across the southeastern United States. Location The study area encompasses seven ecoregions across a large portion of the southeastern United States. Taxon Mammalian mesopredators. Methods We compiled trail camera data from 21 studies across the southeastern United States and used occupancy modelling to assess mesopredator distributions and account for heterogeneous detection probabilities. We examined drivers of occupancy at regional and landscape scales. At the regional scale, we assessed occupancy patterns across ecoregions differing in topography, productivity, and human population growth. At the landscape scale, we analysed the influence of land cover types (forest, developed, agriculture) and non-native coyote (Canis latrans) activity on occupancy. Results Regionally, mesopredator occurrence was highest in ecoregions characterised by low productivity and greater topographic variability. Common species (predicted occupancy ≥ 0.19) showed positive associations with developed and agricultural land covers, while less common species (predicted occupancy ≤ 0.10) showed negative associations or were too rare to model. Coyote activity had mixed effects, positively associated with some species while negatively associated with others. Main Conclusions Anthropogenic development affects mesopredator communities at both regional and landscape scales, favouring generalist species that are tolerant of human-modified landscapes.

@article{kessel_canada1water_2026,
	title = {{Canada1Water}: {Hydraulic} parametrized integrated soil, bedrock and peatlands datasets},
	volume = {65},
	issn = {2352-3409},
	shorttitle = {{Canada1Water}},
	url = {https://www.sciencedirect.com/science/article/pii/S2352340926001897},
	doi = {10.1016/j.dib.2026.112636},
	abstract = {The Canada1Water (C1W) initiative is a national-scale effort to model Canada’s hydrologic cycle, integrating groundwater, surface water, and climate influences across continental Canada and shared watersheds with the United States. Soil, bedrock, and peatlands critically connect atmospheric processes, vegetation, and hydrology. Infiltration and recharge are governed by the hydraulic properties and topographic and pressure gradients, making accurate representation of surficial substrates essential in hydrological modelling. For continental-scale groundwater–surface water modelling in Canada, a 7-layer hydrostratigraphic framework was developed, with the upper two soil layers being 0–0.5 m and 0.5–1.0 m below ground surface. National coverage of mineral soils was derived from the global OpenLandMap dataset at 250 m resolution, using soil texture, bulk density, and water content at 33 and 1500 kPa from six depth intervals. These inputs were vertically averaged into two soil layers and parameterized using Rosetta v3 pedotransfer function approaches to derive residual and saturated water content, van Genuchten parameters (α and n), and saturated hydraulic conductivity. Exposed bedrock was explicitly mapped using a combination of land cover classification (NALCMS v2015 barren land and snow/ice classes) and national-scale surficial geology datasets, with depth-dependent expansion of bedrock extent in the lower soil layer. Peatlands were delineated using peatland extent products and OpenLandMap soil organic carbon content, producing a three-dimensional peat model classified into moderately decomposed, decomposed, and well-decomposed peat, each assigned depth-dependent hydraulic properties based on published literature. The final product is an 18-band raster GeoTIFF, comprising OpenLandMap soil attributes, Rosetta-derived hydraulic parameters, and specific classifications for bedrock and peatlands. The dataset provides seamless 250 m resolution coverage across all Canadian provinces and territories and extends into transboundary watersheds with the United States. By integrating mineral soils, bedrock outcrops, and peatlands into its comprehensive hydraulic parameterization, this dataset is ideally suited for supra-regional hydrological modelling.},
	urldate = {2026-05-27},
	journal = {Data in Brief},
	author = {Kessel, Eric D. and Frey, Steve K. and Lapen, David R. and Geng, Xiaoyuan and Russell, Hazen A. J.},
	month = apr,
	year = {2026},
	keywords = {NALCMS},
	pages = {112636},
}

The Canada1Water (C1W) initiative is a national-scale effort to model Canada’s hydrologic cycle, integrating groundwater, surface water, and climate influences across continental Canada and shared watersheds with the United States. Soil, bedrock, and peatlands critically connect atmospheric processes, vegetation, and hydrology. Infiltration and recharge are governed by the hydraulic properties and topographic and pressure gradients, making accurate representation of surficial substrates essential in hydrological modelling. For continental-scale groundwater–surface water modelling in Canada, a 7-layer hydrostratigraphic framework was developed, with the upper two soil layers being 0–0.5 m and 0.5–1.0 m below ground surface. National coverage of mineral soils was derived from the global OpenLandMap dataset at 250 m resolution, using soil texture, bulk density, and water content at 33 and 1500 kPa from six depth intervals. These inputs were vertically averaged into two soil layers and parameterized using Rosetta v3 pedotransfer function approaches to derive residual and saturated water content, van Genuchten parameters (α and n), and saturated hydraulic conductivity. Exposed bedrock was explicitly mapped using a combination of land cover classification (NALCMS v2015 barren land and snow/ice classes) and national-scale surficial geology datasets, with depth-dependent expansion of bedrock extent in the lower soil layer. Peatlands were delineated using peatland extent products and OpenLandMap soil organic carbon content, producing a three-dimensional peat model classified into moderately decomposed, decomposed, and well-decomposed peat, each assigned depth-dependent hydraulic properties based on published literature. The final product is an 18-band raster GeoTIFF, comprising OpenLandMap soil attributes, Rosetta-derived hydraulic parameters, and specific classifications for bedrock and peatlands. The dataset provides seamless 250 m resolution coverage across all Canadian provinces and territories and extends into transboundary watersheds with the United States. By integrating mineral soils, bedrock outcrops, and peatlands into its comprehensive hydraulic parameterization, this dataset is ideally suited for supra-regional hydrological modelling.

@article{chathuranika_climate_2026,
	title = {Climate {Change} {Impacts} on {Hydrology} in the {Upper} {James} {Watershed}, {Virginia}},
	volume = {62},
	copyright = {© 2026 The Author(s). Journal of the American Water Resources Association published by Wiley Periodicals LLC on behalf of American Water Resources Association.},
	issn = {1752-1688},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/1752-1688.70099},
	doi = {10.1111/1752-1688.70099},
	abstract = {Hydrological modeling of the Upper James Watershed (UJW), Virginia, is critical for predicting water availability, flood management, agriculture, ecosystem protection, and hydropower production under increasing climate change. The Hydrologic Engineering Center–Hydrologic Modeling System (HEC-HMS) is applied to evaluate climate change impacts on key hydrological components within the watershed. Future climate conditions were assessed for the near (NF: 2026–2050), mid (MF: 2051–2075), and far (FF: 2076–2100) periods using three Global Climate Models (GCMs) under Shared Socioeconomic Pathways SSP 2–4.5 and SSP 5–8.5. Climate data were bias-corrected using the Linear Scaling Method (LSM) and used to drive the HEC-HMS model. Results project annual precipitation reductions of 8.19\% (SSP 2–4.5) and 14.63\% (SSP 5–8.5) for 2026–2100 relative to the 1998–2022 baseline, with corresponding annual streamflow changes of a 4.16\% increase and a 0.62\% decrease, respectively. Key hydrological components, including infiltration, evapotranspiration, interception, surface runoff, and baseflow, are projected to decline across all future periods, with reductions ranging from 10.17\% (NF) to 17.00\% (FF) under SSP 2–4.5 and from 11.74\% (NF) to 30.20\% (FF) under SSP 5–8.5. These results highlight the need for improved reservoir operations, sustainable land-use practices, and enhanced flood and drought forecasting to mitigate climate impacts and support informed decision-making.},
	language = {en},
	number = {2},
	urldate = {2026-05-22},
	journal = {JAWRA Journal of the American Water Resources Association},
	author = {Chathuranika, Imiya Mudiyanselage and Ismael, Dalya},
	year = {2026},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/1752-1688.70099},
	keywords = {NALCMS},
	pages = {e70099},
}

Hydrological modeling of the Upper James Watershed (UJW), Virginia, is critical for predicting water availability, flood management, agriculture, ecosystem protection, and hydropower production under increasing climate change. The Hydrologic Engineering Center–Hydrologic Modeling System (HEC-HMS) is applied to evaluate climate change impacts on key hydrological components within the watershed. Future climate conditions were assessed for the near (NF: 2026–2050), mid (MF: 2051–2075), and far (FF: 2076–2100) periods using three Global Climate Models (GCMs) under Shared Socioeconomic Pathways SSP 2–4.5 and SSP 5–8.5. Climate data were bias-corrected using the Linear Scaling Method (LSM) and used to drive the HEC-HMS model. Results project annual precipitation reductions of 8.19% (SSP 2–4.5) and 14.63% (SSP 5–8.5) for 2026–2100 relative to the 1998–2022 baseline, with corresponding annual streamflow changes of a 4.16% increase and a 0.62% decrease, respectively. Key hydrological components, including infiltration, evapotranspiration, interception, surface runoff, and baseflow, are projected to decline across all future periods, with reductions ranging from 10.17% (NF) to 17.00% (FF) under SSP 2–4.5 and from 11.74% (NF) to 30.20% (FF) under SSP 5–8.5. These results highlight the need for improved reservoir operations, sustainable land-use practices, and enhanced flood and drought forecasting to mitigate climate impacts and support informed decision-making.

@article{nowack_combining_2026,
	title = {Combining space use with diet data to investigate foraging tactics of black bears in response to the pulsed availability of migratory caribou calves},
	volume = {21},
	issn = {1932-6203},
	url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0346054},
	doi = {10.1371/journal.pone.0346054},
	abstract = {Migratory caribou (Rangifer tarandus) is a key component of the arctic food web. Female caribou typically gather in late spring to give birth, creating a predictable, ephemeral resource pulse that can influence consumer behavior. As an omnivore, the black bear (Ursus americanus) predates on caribou neonates during calving when they are most vulnerable and occur at high densities. We studied black bears in northern Québec and Labrador interacting with the Rivière-aux-Feuilles (RAFH) and Rivière-George (RGH) migratory caribou herds. Our aim was to assess the spatial response of bears to caribou distribution during calving by investigating the potential correlation between bear movements and their relative trophic position. We expected bears with higher trophic positions to adopt behaviors favoring caribou encounters during the caribou calving period. We used GPS telemetry data from 40 bears and 319 female caribou between 2012 and 2019 to calculate movement metrics and home ranges, and to assess seasonal variation in movement patterns and shared space use between bears and caribou. We then analyzed the relationships between space use data and relative trophic position of bears obtained from stable isotope analysis of blood serum. The relative trophic position of black bears differed between study sites, with individuals in northern Québec (RAFH) exhibiting higher trophic positions than those in Labrador (RGH). Relative trophic positions varied strongly among individuals, indicating substantial individual differences in foraging strategies. Greater proportional overlap of bear ranges with caribou calving ground was associated with higher trophic positions, while higher use of caribou-preferred habitat by bears surprisingly correlated with lower relative trophic positions. The absence of a clear link between movement metrics and trophic position may reflect the inherently opportunistic foraging behavior of black bears. Additional research at the individual level is needed to gain deeper insight into black bear foraging strategies in response to pulsed resources.},
	language = {en},
	number = {4},
	urldate = {2026-05-27},
	journal = {PLOS ONE},
	author = {Nowack, Linda and Bonin, Michaël and Leclerc, Martin and Michelot, Candice and Dussault, Christian and Taillon, Joëlle and Pisapio, John and Côté, Steeve D.},
	month = apr,
	year = {2026},
	note = {Publisher: Public Library of Science},
	keywords = {NALCMS},
	pages = {e0346054},
}

Migratory caribou (Rangifer tarandus) is a key component of the arctic food web. Female caribou typically gather in late spring to give birth, creating a predictable, ephemeral resource pulse that can influence consumer behavior. As an omnivore, the black bear (Ursus americanus) predates on caribou neonates during calving when they are most vulnerable and occur at high densities. We studied black bears in northern Québec and Labrador interacting with the Rivière-aux-Feuilles (RAFH) and Rivière-George (RGH) migratory caribou herds. Our aim was to assess the spatial response of bears to caribou distribution during calving by investigating the potential correlation between bear movements and their relative trophic position. We expected bears with higher trophic positions to adopt behaviors favoring caribou encounters during the caribou calving period. We used GPS telemetry data from 40 bears and 319 female caribou between 2012 and 2019 to calculate movement metrics and home ranges, and to assess seasonal variation in movement patterns and shared space use between bears and caribou. We then analyzed the relationships between space use data and relative trophic position of bears obtained from stable isotope analysis of blood serum. The relative trophic position of black bears differed between study sites, with individuals in northern Québec (RAFH) exhibiting higher trophic positions than those in Labrador (RGH). Relative trophic positions varied strongly among individuals, indicating substantial individual differences in foraging strategies. Greater proportional overlap of bear ranges with caribou calving ground was associated with higher trophic positions, while higher use of caribou-preferred habitat by bears surprisingly correlated with lower relative trophic positions. The absence of a clear link between movement metrics and trophic position may reflect the inherently opportunistic foraging behavior of black bears. Additional research at the individual level is needed to gain deeper insight into black bear foraging strategies in response to pulsed resources.

@article{hanberry_considering_2026,
	title = {Considering tree species of the future: {Tree} species in {Mexico} predicted to have suitable current climate in the {United} {States} and {Canada}},
	volume = {15},
	issn = {2197-5620},
	shorttitle = {Considering tree species of the future},
	url = {https://www.sciencedirect.com/science/article/pii/S2197562025001289},
	doi = {10.1016/j.fecs.2025.100419},
	abstract = {Suitable climate for tree species currently located in Mexico may shift to the United States and Canada under future warming, resulting in the potential for tree species shifts, with new species gained in the USA and Canada and species losses in Mexico. To isolate dynamics, I modeled distributions of 184 commonly recorded wide-ranging or transboundary tree species of North America, including presence in Mexico, and 258 tree species primarily abundant in Mexico, including 51 endemic species, under current climate and predicted to three future climates (projected warming of 4.3–8.8 °C during 2071–2100 in North America). Secondarily, I identified patterns between species distributions and outcomes. Model accuracies were 0.98 for withheld samples, with coldest temperature as the most important variable. Species with distributions that were larger in area and lower in elevation (likely related to the modeling algorithm being able to locate more analogous climates) and higher in latitude (due to greater area in the northern North American continent) were more probable to expand distributions under warming temperatures. Predicted losses in suitable future climate conditions occurred for 36 of 184 wide-ranging species and 103 of 258 Mexican species. For wide-ranging species, losses occurred in Mexico and extended along the USA Gulf Coast, with gains in the western USA and Canada. For Mexican species, losses occurred south of Mexico, with gains in northern Mexico, the southeastern USA, and along the Pacific Coast from the USA to Canada. In Mexico, tree species overall continued to have suitable future climate conditions. In the USA, 38 of 184 wide-ranging species and 246 of 258 Mexican species may be gained in the future, and generally, predictions were for suitable climate conditions both now and in the future. In Canada, suitable future climate conditions for 35 of 184 wide-ranging species were predicted, of which 10 species were predicted to have suitable current climate conditions, and suitable future climate conditions for 80 of 258 Mexican species were predicted, of which 21 species were predicted to have suitable current climate conditions. Many tree species present in Mexico were predicted to already have a suitable current climate in the USA and Canada, which suggests a lag in ecosystem transition that may be addressed by current management to support biodiversity.},
	urldate = {2026-01-21},
	journal = {Forest Ecosystems},
	author = {Hanberry, Brice B.},
	month = apr,
	year = {2026},
	keywords = {NALCMS},
	pages = {100419},
}

Suitable climate for tree species currently located in Mexico may shift to the United States and Canada under future warming, resulting in the potential for tree species shifts, with new species gained in the USA and Canada and species losses in Mexico. To isolate dynamics, I modeled distributions of 184 commonly recorded wide-ranging or transboundary tree species of North America, including presence in Mexico, and 258 tree species primarily abundant in Mexico, including 51 endemic species, under current climate and predicted to three future climates (projected warming of 4.3–8.8 °C during 2071–2100 in North America). Secondarily, I identified patterns between species distributions and outcomes. Model accuracies were 0.98 for withheld samples, with coldest temperature as the most important variable. Species with distributions that were larger in area and lower in elevation (likely related to the modeling algorithm being able to locate more analogous climates) and higher in latitude (due to greater area in the northern North American continent) were more probable to expand distributions under warming temperatures. Predicted losses in suitable future climate conditions occurred for 36 of 184 wide-ranging species and 103 of 258 Mexican species. For wide-ranging species, losses occurred in Mexico and extended along the USA Gulf Coast, with gains in the western USA and Canada. For Mexican species, losses occurred south of Mexico, with gains in northern Mexico, the southeastern USA, and along the Pacific Coast from the USA to Canada. In Mexico, tree species overall continued to have suitable future climate conditions. In the USA, 38 of 184 wide-ranging species and 246 of 258 Mexican species may be gained in the future, and generally, predictions were for suitable climate conditions both now and in the future. In Canada, suitable future climate conditions for 35 of 184 wide-ranging species were predicted, of which 10 species were predicted to have suitable current climate conditions, and suitable future climate conditions for 80 of 258 Mexican species were predicted, of which 21 species were predicted to have suitable current climate conditions. Many tree species present in Mexico were predicted to already have a suitable current climate in the USA and Canada, which suggests a lag in ecosystem transition that may be addressed by current management to support biodiversity.

@article{bunn_data_2026,
	title = {Data to support the modelling of integrated groundwater-surface water flow in permafrost regions, using the {Carcajou} {Watershed}, {Northwest} {Territories}, {Canada}},
	volume = {66},
	issn = {2352-3409},
	url = {https://www.sciencedirect.com/science/article/pii/S235234092600332X},
	doi = {10.1016/j.dib.2026.112802},
	abstract = {{\textgreater} 50 \% of Canada's landmass is underlain by perennially frozen ground (permafrost). These permafrost regions are changing rapidly in response to a warming climate, with Canada’s arctic warming at a rate {\textgreater} 3 times higher than global average. As permafrost distribution shifts in response to this warming, it alters the water cycle, affecting both water quantity and water quality. However, large-scale hydrological models that integrate climate change impacts often lack permafrost representation. The Carcajou Regional Model Dataset contains the inputs needed to construct a standalone groundwater model or a fully integrated groundwater – surface water model of the Carcajou watershed in the Northwest Territories, Canada, a zone of transition between continuous permafrost and discontinuous permafrost. The three-dimensional geological data was created by refining national-scale mapping products, with local-scale data. Land cover, topography, and surface water flow were generated from national scale mapping products. Climate forcing data for the period from 2010 to 2016 was generated based national scale historical products. The proper approach to representing permafrost in large-scale hydrological models is largely undefined, with no consensus on conceptualization or parameterization. This dataset allows researchers to rapidly test new approaches to permafrost representation, without the need for additional data collection. The data set includes long term surface water discharge records to assess model performance and compare representations. The data set can be further adapted to simulate projected permafrost distribution scenarios and be used to forecast the effect of permafrost change on water quantity.},
	urldate = {2026-05-21},
	journal = {Data in Brief},
	author = {Bunn, Melissa I. and Khader, Omar and Kessel, Eric and Frey, Steven K. and Erler, Andre R. and Russell, Hazen A.},
	month = jun,
	year = {2026},
	keywords = {NALCMS},
	pages = {112802},
}

\textgreater 50 % of Canada's landmass is underlain by perennially frozen ground (permafrost). These permafrost regions are changing rapidly in response to a warming climate, with Canada’s arctic warming at a rate \textgreater 3 times higher than global average. As permafrost distribution shifts in response to this warming, it alters the water cycle, affecting both water quantity and water quality. However, large-scale hydrological models that integrate climate change impacts often lack permafrost representation. The Carcajou Regional Model Dataset contains the inputs needed to construct a standalone groundwater model or a fully integrated groundwater – surface water model of the Carcajou watershed in the Northwest Territories, Canada, a zone of transition between continuous permafrost and discontinuous permafrost. The three-dimensional geological data was created by refining national-scale mapping products, with local-scale data. Land cover, topography, and surface water flow were generated from national scale mapping products. Climate forcing data for the period from 2010 to 2016 was generated based national scale historical products. The proper approach to representing permafrost in large-scale hydrological models is largely undefined, with no consensus on conceptualization or parameterization. This dataset allows researchers to rapidly test new approaches to permafrost representation, without the need for additional data collection. The data set includes long term surface water discharge records to assess model performance and compare representations. The data set can be further adapted to simulate projected permafrost distribution scenarios and be used to forecast the effect of permafrost change on water quantity.

@article{connors_democratizing_2026,
	title = {Democratizing data to support the implementation of {Canada}’s {Wild} {Salmon} {Policy}},
	volume = {83},
	issn = {0706-652X},
	url = {https://cdnsciencepub.com/doi/10.1139/cjfas-2025-0250},
	doi = {10.1139/cjfas-2025-0250},
	abstract = {Canada’s Wild Salmon Policy (WSP) highlights the importance of biodiversity conservation for supporting the resilience of Pacific salmon. Two decades after its introduction, the WSP remains largely unimplemented. Monitoring and assessing the status of salmon Conservation Units and their habitats is the WSP’s foundation, enabling timely, evidence-based responses to prevent biodiversity loss. With federal progress on monitoring and assessment lagging, the Pacific Salmon Foundation created a streamlined and transparent approach. We outline our work to democratize salmon data by integrating disparate sources and publicly sharing frequently updated status assessments through the Pacific Salmon Explorer, an online data visualization tool. Further advancing the objectives of the WSP will require the federal government to prioritize sharing rapid biological status assessments, applying the precautionary approach to data-deficient Conservation Units, and integrating habitat assessments into salmon management to support biodiversity and ecosystem resilience. Additionally, efforts to improve data stewardship and accessibility and establish stronger government accountability to ensure transparent, consistent, and effective conservation actions are essential to meaningful and sustained progress.},
	urldate = {2026-05-22},
	journal = {Canadian Journal of Fisheries and Aquatic Sciences},
	author = {Connors, Katrina and Peacock, Stephanie J. and Hertz, Eric and Carturan, Bruno S. and Porter, Marc and Bryan, Katy and Drennan, Rheanna and Honka, Leah and Jones, Eileen and Belton, Kathleen},
	month = jan,
	year = {2026},
	note = {Publisher: NRC Research Press},
	keywords = {Lakes \& Rivers},
	pages = {1--21},
}

Canada’s Wild Salmon Policy (WSP) highlights the importance of biodiversity conservation for supporting the resilience of Pacific salmon. Two decades after its introduction, the WSP remains largely unimplemented. Monitoring and assessing the status of salmon Conservation Units and their habitats is the WSP’s foundation, enabling timely, evidence-based responses to prevent biodiversity loss. With federal progress on monitoring and assessment lagging, the Pacific Salmon Foundation created a streamlined and transparent approach. We outline our work to democratize salmon data by integrating disparate sources and publicly sharing frequently updated status assessments through the Pacific Salmon Explorer, an online data visualization tool. Further advancing the objectives of the WSP will require the federal government to prioritize sharing rapid biological status assessments, applying the precautionary approach to data-deficient Conservation Units, and integrating habitat assessments into salmon management to support biodiversity and ecosystem resilience. Additionally, efforts to improve data stewardship and accessibility and establish stronger government accountability to ensure transparent, consistent, and effective conservation actions are essential to meaningful and sustained progress.

@article{liang_derivation_2026,
	title = {Derivation and evaluation of {Landsat}-derived annual aboveground biomass maps for {Arctic} and {Boreal} {North} {America}, 1984-2022},
	volume = {341},
	issn = {0034-4257},
	url = {https://www.sciencedirect.com/science/article/pii/S0034425726002166},
	doi = {10.1016/j.rse.2026.115446},
	abstract = {Arctic and boreal regions (ABRs) are experiencing rapid warming and increasingly severe wildfires, threatening their roles as global carbon sinks. High quality time series maps of aboveground biomass (AGB) are key for characterizing and attributing spatiotemporal dynamics of carbon stocks in these regions. However, existing maps at regional to global scales often lack the spatial resolution or temporal coverage needed to capture the heterogeneous and dynamic nature of Arctic-boreal AGB change. To address these limitations, we developed annual (1984-2022) 30-m resolution AGB density maps for Alaska and Canada (11.2 x 106 km2). The maps were produced by using extensive training datasets, including 45,002 unique ground plots and 100,000 km2 of airborne lidar data, and time-series spectral features derived from the Continuous Change Detection and Classification (CCDC) algorithm fitted on Landsat Collection 2 Surface Reflectance. Using the eXtreme Gradient Boosting model, we generated annual wall-to-wall maps of AGB along with associated uncertainties. Our maps suggest a ∼ 41 Pg stock of AGB at 2022, representing a 12\% increase from 1984. Our maps achieve high accuracy and low bias on holdout testing data (R2 = 0.72, Bias= -5.03\%, RMSE\% = 62.7\%), representing an average of 16.0 percentage points increase in R2 values and 22.7 percentage points decrease in relative bias compared to six existing AGB products. We show using repeat ground measurements that these maps effectively capture AGB loss and recovery due to fire and harvest, gradual AGB changes, and both live and dead tree AGB components in boreal regions. By integrating extensive calibration data with multi-decadal satellite observations and advanced machine learning techniques, these map products provide a robust tool for advancing the understanding of carbon dynamics under global change in Arctic-boreal North America.},
	urldate = {2026-05-27},
	journal = {Remote Sensing of Environment},
	author = {Liang, Wanwan and van Lier, Olivier and Friedl, Mark A. and Randerson, James T. and Rogers, Brendan M. and Burrell, Arden and Hu, Kai-Ting and Tompalski, Piotr and Macander, Matthew J. and Yang, Daryl and Morton, Douglas C. and Bullock, Eric and Lu, Jiaming and Zhang, Yingtong and Zhu, Xiaoran and Wang, Jonathan A.},
	month = aug,
	year = {2026},
	keywords = {NALCMS, Terrestrial Ecoregions (CEC 1997)},
	pages = {115446},
}

Arctic and boreal regions (ABRs) are experiencing rapid warming and increasingly severe wildfires, threatening their roles as global carbon sinks. High quality time series maps of aboveground biomass (AGB) are key for characterizing and attributing spatiotemporal dynamics of carbon stocks in these regions. However, existing maps at regional to global scales often lack the spatial resolution or temporal coverage needed to capture the heterogeneous and dynamic nature of Arctic-boreal AGB change. To address these limitations, we developed annual (1984-2022) 30-m resolution AGB density maps for Alaska and Canada (11.2 x 106 km2). The maps were produced by using extensive training datasets, including 45,002 unique ground plots and 100,000 km2 of airborne lidar data, and time-series spectral features derived from the Continuous Change Detection and Classification (CCDC) algorithm fitted on Landsat Collection 2 Surface Reflectance. Using the eXtreme Gradient Boosting model, we generated annual wall-to-wall maps of AGB along with associated uncertainties. Our maps suggest a ∼ 41 Pg stock of AGB at 2022, representing a 12% increase from 1984. Our maps achieve high accuracy and low bias on holdout testing data (R2 = 0.72, Bias= -5.03%, RMSE% = 62.7%), representing an average of 16.0 percentage points increase in R2 values and 22.7 percentage points decrease in relative bias compared to six existing AGB products. We show using repeat ground measurements that these maps effectively capture AGB loss and recovery due to fire and harvest, gradual AGB changes, and both live and dead tree AGB components in boreal regions. By integrating extensive calibration data with multi-decadal satellite observations and advanced machine learning techniques, these map products provide a robust tool for advancing the understanding of carbon dynamics under global change in Arctic-boreal North America.

@phdthesis{santos_development_2026,
	address = {Saskatoon},
	type = {Master of {Science}},
	title = {Development of stewardship and drinking water quality indicators towards private well water safety in {Saskatchewan}},
	url = {https://hdl.handle.net/10388/18091},
	abstract = {Private domestic wells (PDW) are an important source of drinking water in Saskatchewan, especially in sparsely populated areas where the connection to municipal water systems is less viable. Given the lack of regulation of these wells, the well user becomes responsible for safeguarding their supply and the maintenance of their water systems which will be informed by their individual stewardship practices. A water quality (WQ) indicator was developed with the use of a provincial database with 4,819 groundwater testing results, with the application of a principal component analysis (PCA) to reduce the dimensionality of the dataset and identify sub-domains. The PCA grouped the parameters in five groups: hardness, salinity, heavy metals (health), heavy metals (aesthetic) and land-use contaminants. In addition, to analyze the WQ risks facing PDW users in Saskatchewan, a mixed methods approach was used to quantify the water safety in PDW, resulting in the development of a water safety indicator utilizing the results of a survey realized in Saskatchewan in 2024. These indicators were grouped in a composite called the well water safety index, which was applied to the case-study in southern Saskatchewan, allowing for the quantification of user stewardship and WQ in a single index. The WQ indicators showed an overall adequacy of the water for drinking and livestock watering, with aesthetic parameters exceeding the guidelines more often than the health-related variables. Furthermore, a discrepancy was noticed between the water safety perceived by the well users and the actual WQ encountered in their wells in addition to a heavy reliance on sensorial detection (i.e., appearance, taste, smell) for the judgment of water safety, while neglecting the possibility of the presence of invisible yet dangerous contaminants in their water supply. In conclusion, the indicators developed in this study showed promise in their practical application for groundwater management of PDW in Saskatchewan. The indicators could be further employed by developing a system available to private well users where they could input their individual data (regarding stewardship practices and their WQ results) and receive immediate feedback and links to resources tailored to their specific needs and identified areas for improvement, ultimately aiding the groundwater management in the province.},
	language = {English},
	urldate = {2026-06-01},
	school = {University of Saskatchewan},
	author = {Santos, Allana},
	year = {2026},
}

Private domestic wells (PDW) are an important source of drinking water in Saskatchewan, especially in sparsely populated areas where the connection to municipal water systems is less viable. Given the lack of regulation of these wells, the well user becomes responsible for safeguarding their supply and the maintenance of their water systems which will be informed by their individual stewardship practices. A water quality (WQ) indicator was developed with the use of a provincial database with 4,819 groundwater testing results, with the application of a principal component analysis (PCA) to reduce the dimensionality of the dataset and identify sub-domains. The PCA grouped the parameters in five groups: hardness, salinity, heavy metals (health), heavy metals (aesthetic) and land-use contaminants. In addition, to analyze the WQ risks facing PDW users in Saskatchewan, a mixed methods approach was used to quantify the water safety in PDW, resulting in the development of a water safety indicator utilizing the results of a survey realized in Saskatchewan in 2024. These indicators were grouped in a composite called the well water safety index, which was applied to the case-study in southern Saskatchewan, allowing for the quantification of user stewardship and WQ in a single index. The WQ indicators showed an overall adequacy of the water for drinking and livestock watering, with aesthetic parameters exceeding the guidelines more often than the health-related variables. Furthermore, a discrepancy was noticed between the water safety perceived by the well users and the actual WQ encountered in their wells in addition to a heavy reliance on sensorial detection (i.e., appearance, taste, smell) for the judgment of water safety, while neglecting the possibility of the presence of invisible yet dangerous contaminants in their water supply. In conclusion, the indicators developed in this study showed promise in their practical application for groundwater management of PDW in Saskatchewan. The indicators could be further employed by developing a system available to private well users where they could input their individual data (regarding stewardship practices and their WQ results) and receive immediate feedback and links to resources tailored to their specific needs and identified areas for improvement, ultimately aiding the groundwater management in the province.

@article{jorgenson_discharge_2026,
	title = {Discharge {Regimes} of {North} {American} {High}-{Latitude} {Rivers}},
	volume = {14},
	copyright = {© 2026. The Author(s).},
	issn = {2328-4277},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2025EF007169},
	doi = {10.1029/2025EF007169},
	abstract = {Regimes of river discharge, characterized by the timing and magnitude of seasonal and stochastic flow variation, are changing in northern rivers due to warming climate. However, spatial heterogeneity in discharge regimes across high-latitude regions has made it difficult to predict flows under accelerated warming. We quantified seasonal and stochastic variation in mean daily discharge from 172 rivers of Alaska and northern Canada over 2000–2022 and compared flow regimes of rivers across ecoregions, climate gradients, and cryospheric conditions. Floods were shorter and occurred later in the year, on average, in Marine West Coast Forest compared to other ecoregions. Strongest seasonal relative to stochastic variation in flows occurred in the snowmelt-dominated Northwestern Forested Mountains ecoregion. Discharge in glacial watersheds was more strongly seasonal than in non-glacial watersheds, likely due to production of meltwater in summer. Greater rainfall in the watershed was correlated with weaker seasonal variation in flow and earlier annual occurrence of high-flow anomalies. In contrast, greater snowfall resulted in strongly seasonal regimes with anomalous high flows later in the year. We also contrasted discharge regimes of 72 rivers between ∼1970–1992 and 2000–2022, finding less seasonal relative to stochastic variation in recent decades and contemporary anomalous high flows occurring later in the year relative to historic regimes. Discharge from glacial rivers was relatively resistant to change, suggesting buffering by seasonal glacial melt. Shrinking of the cryosphere and shifts in the precipitation regime due to continued warming will increase stochasticity and decrease seasonality in the flows of high-latitude rivers.},
	language = {en},
	number = {4},
	urldate = {2026-05-27},
	journal = {Earth's Future},
	author = {Jorgenson, Karen L. and Harms, Tamara K.},
	year = {2026},
	note = {\_eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2025EF007169},
	keywords = {Glaciers and Sea Ice, Terrestrial Ecoregions (CEC 1997)},
	pages = {e2025EF007169},
}

Regimes of river discharge, characterized by the timing and magnitude of seasonal and stochastic flow variation, are changing in northern rivers due to warming climate. However, spatial heterogeneity in discharge regimes across high-latitude regions has made it difficult to predict flows under accelerated warming. We quantified seasonal and stochastic variation in mean daily discharge from 172 rivers of Alaska and northern Canada over 2000–2022 and compared flow regimes of rivers across ecoregions, climate gradients, and cryospheric conditions. Floods were shorter and occurred later in the year, on average, in Marine West Coast Forest compared to other ecoregions. Strongest seasonal relative to stochastic variation in flows occurred in the snowmelt-dominated Northwestern Forested Mountains ecoregion. Discharge in glacial watersheds was more strongly seasonal than in non-glacial watersheds, likely due to production of meltwater in summer. Greater rainfall in the watershed was correlated with weaker seasonal variation in flow and earlier annual occurrence of high-flow anomalies. In contrast, greater snowfall resulted in strongly seasonal regimes with anomalous high flows later in the year. We also contrasted discharge regimes of 72 rivers between ∼1970–1992 and 2000–2022, finding less seasonal relative to stochastic variation in recent decades and contemporary anomalous high flows occurring later in the year relative to historic regimes. Discharge from glacial rivers was relatively resistant to change, suggesting buffering by seasonal glacial melt. Shrinking of the cryosphere and shifts in the precipitation regime due to continued warming will increase stochasticity and decrease seasonality in the flows of high-latitude rivers.

@article{barrett_disparity_2026,
	title = {Disparity between predicted habitat distributions of the eastern spotted skunk and striped skunk in {Florida}},
	volume = {90},
	copyright = {© 2025 The Wildlife Society},
	issn = {1937-2817},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/jwmg.70152},
	doi = {10.1002/jwmg.70152},
	abstract = {The eastern spotted skunk (Spilogale putorius) is a small mesocarnivore that has experienced population decline across its range, whereas populations of the larger striped skunk (Mephitis mephitis) have remained stable. Both skunk species occur in Florida, USA, but their occupied ranges have diverged over time, with the range of the spotted skunk markedly declining. Determining their ecological niches within the framework of species distribution models (SDMs) can help to understand their habitat use and landscape-scale interactions in Florida. We developed SDMs for both species using the presence-only model Maxent, incorporating occurrences collected from 2017–2022 from community science and research data, along with 12 environmental variables representing various landscape features (e.g., land cover, topography, fire history). We quantified the area of predicted habitat for each species, estimated their spatial overlap, and measured potential impacts from external pressures (e.g., projected urbanization, sea level rise). Owing to their range decline and habitat specialization, we expected a smaller predicted area of habitat for eastern spotted skunk, with higher potential for external pressures and minimal overlap with striped skunk habitat. Our results indicated habitat area was smaller for eastern spotted skunk (24,333 km2) than striped skunk (31,964 km2), with minimal spatial overlap (14\%). We found that eastern spotted skunk distribution occurred mostly in coastal and southern areas of Florida and was positively influenced by scrub-shrubland cover and vegetation diversity and negatively influenced by cropland and developed areas. Striped skunk distribution mostly occurred in northern and interior areas of Florida and was positively influenced by wooded edges, prairie, and wetland cover. Less-rugged topography was important to both species. Projected trends in urbanization and sea level rise more greatly threaten the habitats of eastern spotted skunk than striped skunk. We provide a detailed habitat map and a much-needed description of the ecological niche of the eastern spotted skunk in Florida, which differs from that of the striped skunk. Overall, this study can inform both statewide and species-wide conservation and management decisions for both skunk species.},
	language = {en},
	number = {2},
	urldate = {2026-05-21},
	journal = {The Journal of Wildlife Management},
	author = {Barrett, Mark A. and Doran-Myers, Darcy and Gillikin, Mike N. and Doonan, Terry J. and Braun de Torrez, Elizabeth C.},
	year = {2026},
	note = {\_eprint: https://wildlife.onlinelibrary.wiley.com/doi/pdf/10.1002/jwmg.70152},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {e70152},
}

The eastern spotted skunk (Spilogale putorius) is a small mesocarnivore that has experienced population decline across its range, whereas populations of the larger striped skunk (Mephitis mephitis) have remained stable. Both skunk species occur in Florida, USA, but their occupied ranges have diverged over time, with the range of the spotted skunk markedly declining. Determining their ecological niches within the framework of species distribution models (SDMs) can help to understand their habitat use and landscape-scale interactions in Florida. We developed SDMs for both species using the presence-only model Maxent, incorporating occurrences collected from 2017–2022 from community science and research data, along with 12 environmental variables representing various landscape features (e.g., land cover, topography, fire history). We quantified the area of predicted habitat for each species, estimated their spatial overlap, and measured potential impacts from external pressures (e.g., projected urbanization, sea level rise). Owing to their range decline and habitat specialization, we expected a smaller predicted area of habitat for eastern spotted skunk, with higher potential for external pressures and minimal overlap with striped skunk habitat. Our results indicated habitat area was smaller for eastern spotted skunk (24,333 km2) than striped skunk (31,964 km2), with minimal spatial overlap (14%). We found that eastern spotted skunk distribution occurred mostly in coastal and southern areas of Florida and was positively influenced by scrub-shrubland cover and vegetation diversity and negatively influenced by cropland and developed areas. Striped skunk distribution mostly occurred in northern and interior areas of Florida and was positively influenced by wooded edges, prairie, and wetland cover. Less-rugged topography was important to both species. Projected trends in urbanization and sea level rise more greatly threaten the habitats of eastern spotted skunk than striped skunk. We provide a detailed habitat map and a much-needed description of the ecological niche of the eastern spotted skunk in Florida, which differs from that of the striped skunk. Overall, this study can inform both statewide and species-wide conservation and management decisions for both skunk species.

@article{geddes_distribution_2026,
	title = {Distribution, frequency, and impact of herbicide-resistant weeds in {Manitoba}},
	volume = {106},
	issn = {0008-4220},
	url = {https://cdnsciencepub.com/doi/10.1139/cjps-2025-0197},
	doi = {10.1139/cjps-2025-0197},
	abstract = {Herbicide-resistant weeds are a growing concern for Manitoba farmers. Continued monitoring is essential to understand how to mitigate and manage this increasing threat to crop production. A randomized-stratified preharvest survey of 155 annual-cropped fields was conducted in 2022 to determine the distribution, frequency, and impact of herbicide-resistant weeds in Manitoba. Mature seeds were collected from all visible uncontrolled weed patches and tested for resistance to acetyl-CoA carboxylase (ACCase)-, acetolactate synthase (ALS), and 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS)-inhibiting herbicides using whole-plant bioassays. Overall, 584 weed seed samples were collected, representing 44 different species. Uncontrolled herbicide-resistant weeds occupied 72\% of the fields surveyed and about 1.5 million ha of cropland across the province. Herbicide-resistant weeds were estimated to cost Manitoba farmers \$77 million annually in reduced crop yields, quality, and increased weed management expenditures. Compared to the previous 2016 survey, a trend toward increasing ALS inhibitor-resistant broadleaf weeds and decreasing herbicide-resistant grasses was observed, with some exceptions. Eleven herbicide-resistant weed species were documented, four of which were not observed in the 2016 survey; including ALS inhibitor-resistant common chickweed (Stellaria media (L.) Vill.), pale smartweed (Persicaria lapathifolia (L.) Delarbre), Powell amaranth (Amaranthus powellii S. Watson), and spiny sowthistle (Sonchus asper (L.) Hill). Manitoba farms are increasingly affected by wild oat (Avena fatua L.) and kochia (Bassia scoparia (L.) A.J. Scott) with resistance to multiple herbicide sites-of-action, leaving few alternatives for chemical management. The increasing impact of herbicide-resistant weeds in Manitoba emphasizes the critical need for adoption of integrated weed management where nonchemical tactics augment contemporary herbicidal weed control.},
	urldate = {2026-05-27},
	journal = {Canadian Journal of Plant Science},
	author = {Geddes, Charles M. and Pittman, Mattea M. and Brown, Kim and Leeson, Julia Y.},
	month = jan,
	year = {2026},
	note = {Publisher: NRC Research Press},
	keywords = {Lakes \& Rivers},
	pages = {1--13},
}

Herbicide-resistant weeds are a growing concern for Manitoba farmers. Continued monitoring is essential to understand how to mitigate and manage this increasing threat to crop production. A randomized-stratified preharvest survey of 155 annual-cropped fields was conducted in 2022 to determine the distribution, frequency, and impact of herbicide-resistant weeds in Manitoba. Mature seeds were collected from all visible uncontrolled weed patches and tested for resistance to acetyl-CoA carboxylase (ACCase)-, acetolactate synthase (ALS), and 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS)-inhibiting herbicides using whole-plant bioassays. Overall, 584 weed seed samples were collected, representing 44 different species. Uncontrolled herbicide-resistant weeds occupied 72% of the fields surveyed and about 1.5 million ha of cropland across the province. Herbicide-resistant weeds were estimated to cost Manitoba farmers $77 million annually in reduced crop yields, quality, and increased weed management expenditures. Compared to the previous 2016 survey, a trend toward increasing ALS inhibitor-resistant broadleaf weeds and decreasing herbicide-resistant grasses was observed, with some exceptions. Eleven herbicide-resistant weed species were documented, four of which were not observed in the 2016 survey; including ALS inhibitor-resistant common chickweed (Stellaria media (L.) Vill.), pale smartweed (Persicaria lapathifolia (L.) Delarbre), Powell amaranth (Amaranthus powellii S. Watson), and spiny sowthistle (Sonchus asper (L.) Hill). Manitoba farms are increasingly affected by wild oat (Avena fatua L.) and kochia (Bassia scoparia (L.) A.J. Scott) with resistance to multiple herbicide sites-of-action, leaving few alternatives for chemical management. The increasing impact of herbicide-resistant weeds in Manitoba emphasizes the critical need for adoption of integrated weed management where nonchemical tactics augment contemporary herbicidal weed control.

@article{trombik_does_2026,
	title = {Does biotic resistance govern forest invasions by bark and ambrosia beetles?},
	volume = {2026},
	copyright = {© 2026 The Author(s). Ecography published by John Wiley \& Sons Ltd on behalf of Nordic Society Oikos},
	issn = {1600-0587},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/ecog.08164},
	doi = {10.1002/ecog.08164},
	abstract = {The theory of biotic resistance states that community diversity promotes resistance to biological invasions. This theory has been widely explored for its ability to explain variation in habitat invasibility to non-native plant species and while the theory holds in some systems, it does not in others. In the case of invasions by herbivorous insects, invasibility could be affected by diversity of plants and/or by diversity of native insects. While only a few studies have explored biotic resistance to insect invasions, limited evidence suggests that plant diversity can actually have a positive effect on invasibility via creation of niches for herbivorous insects though other studies of insect systems indicate that plant diversity has a negative effect on invasibility by diluting the density of hosts. Almost nothing is known about how native insect diversity affects resistance to invasions by other insects. Here we analyzed a unique inventory of native and non-native Scolytinae/Platypodinae (bark and ambrosia beetles) across the conterminous USA. We assessed the correlates of geographical variation in numbers of both native and non-native species per 50 × 50 km cell. We find that native tree diversity generally has positive effects on the richness of native beetle species, while the abundance of non-native hosts promotes richness of non-native beetles. We also observed that the effect of native beetle diversity on non-native Scolytinae/Platypodinae species richness is either lacking or positive. These results indicate fundamental differences between plants and insects in the way native and non-native species interact; while interspecific competition can exert a strong influence on plant invasions, it appears less important for insects. Results thus indicate that the biotic resistance hypothesis does not explain invasion patterns of bark and ambrosia beetles.},
	language = {en},
	number = {3},
	urldate = {2026-05-29},
	journal = {Ecography},
	author = {Trombik, Jiří and Šenfeldová, Soňa and Ward, Samuel F. and Atkinson, Thomas H. and Liebhold, Andrew M.},
	year = {2026},
	note = {\_eprint: https://nsojournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecog.08164},
	keywords = {Major Roads},
	pages = {e08164},
}

The theory of biotic resistance states that community diversity promotes resistance to biological invasions. This theory has been widely explored for its ability to explain variation in habitat invasibility to non-native plant species and while the theory holds in some systems, it does not in others. In the case of invasions by herbivorous insects, invasibility could be affected by diversity of plants and/or by diversity of native insects. While only a few studies have explored biotic resistance to insect invasions, limited evidence suggests that plant diversity can actually have a positive effect on invasibility via creation of niches for herbivorous insects though other studies of insect systems indicate that plant diversity has a negative effect on invasibility by diluting the density of hosts. Almost nothing is known about how native insect diversity affects resistance to invasions by other insects. Here we analyzed a unique inventory of native and non-native Scolytinae/Platypodinae (bark and ambrosia beetles) across the conterminous USA. We assessed the correlates of geographical variation in numbers of both native and non-native species per 50 × 50 km cell. We find that native tree diversity generally has positive effects on the richness of native beetle species, while the abundance of non-native hosts promotes richness of non-native beetles. We also observed that the effect of native beetle diversity on non-native Scolytinae/Platypodinae species richness is either lacking or positive. These results indicate fundamental differences between plants and insects in the way native and non-native species interact; while interspecific competition can exert a strong influence on plant invasions, it appears less important for insects. Results thus indicate that the biotic resistance hypothesis does not explain invasion patterns of bark and ambrosia beetles.

@article{sahagun_sanchez_valor_2026,
	title = {El valor económico de los servicios ecosistémicos en las Áreas {Protegidas} de {México}},
	volume = {65},
	issn = {2340-0129, 0210-5462},
	url = {https://dialnet.unirioja.es/servlet/articulo?codigo=10630162},
	abstract = {This study aimed to estimate the economic value of the ecosystem services provided by Protected Natural Areas and Areas Voluntarily Designated for Conservation in Mexico, generating baseline information to support their management and maintenance. A benefit transfer method was applied to calculate the value of ecosystem services using pre-established coefficients, and a geographic information system was used to segregate and analyze them. The results indicate that the approximate value of ecosystem services from protected areas in Mexico is 391 billion dollars, with Biosphere Reserves and Flora and Fauna Protection Areas accounting for the largest share. Regionally, the highest value is found in the Coastal Plain and Gulf of Mexico, the Yucatan Peninsula, and the Mexican Caribbean. The information helps establish reference values for the ecosystem services provided by protected areas in Mexico. It can serve as a basis for designing plans and programs to improve their management and conservation in the territory.
El objetivo del presente estudio fue estimar el valor económico de los servicios ecosistémicos provistos por las Áreas Naturales Protegidas y las Áreas Destinadas Voluntariamente para la Conservación en México para generar información de línea base que apoye su manejo y mantenimiento. Se aplicó un método de transferencia de beneficios para calcular el valor de los servicios ecosistémicos a través de coeficientes preestablecidos y se utilizó un sistema de información geográfica para su segregación y análisis. Los resultados indican que el valor aproximado de los servicios ecosistémicos de las áreas protegidas en México es de 391 mil millones de dólares siendo las Reservas de la Biosfera y las Áreas de Protección de Flora y Fauna las que concentran el monto mayor. Regionalmente el valor más alto se congrega en la Planicie Costera y Golfo de México y la Península de Yucatán y Caribe Mexicano. La información generada es de especial utilidad para establecer valores de referencia para los servicios ecosistémicos provistos por las áreas protegidas en México y puede servir de base para el diseño de planes y programas dirigidos a mejorar su manejo y conservación en el territorio.},
	language = {Spanish},
	number = {1},
	urldate = {2026-05-29},
	journal = {Cuadernos geográficos de la Universidad de Granada},
	author = {Sahagún Sánchez, Francisco Javier and Leija, Edgar G. and Espinoza Guzmán, Marco Antonio},
	year = {2026},
	note = {Publisher: Departamento de Análisis Geográfico Regional y Geografía Física
Section: Cuadernos geográficos de la Universidad de Granada},
	keywords = {NALCMS},
	pages = {198--218},
}

This study aimed to estimate the economic value of the ecosystem services provided by Protected Natural Areas and Areas Voluntarily Designated for Conservation in Mexico, generating baseline information to support their management and maintenance. A benefit transfer method was applied to calculate the value of ecosystem services using pre-established coefficients, and a geographic information system was used to segregate and analyze them. The results indicate that the approximate value of ecosystem services from protected areas in Mexico is 391 billion dollars, with Biosphere Reserves and Flora and Fauna Protection Areas accounting for the largest share. Regionally, the highest value is found in the Coastal Plain and Gulf of Mexico, the Yucatan Peninsula, and the Mexican Caribbean. The information helps establish reference values for the ecosystem services provided by protected areas in Mexico. It can serve as a basis for designing plans and programs to improve their management and conservation in the territory. El objetivo del presente estudio fue estimar el valor económico de los servicios ecosistémicos provistos por las Áreas Naturales Protegidas y las Áreas Destinadas Voluntariamente para la Conservación en México para generar información de línea base que apoye su manejo y mantenimiento. Se aplicó un método de transferencia de beneficios para calcular el valor de los servicios ecosistémicos a través de coeficientes preestablecidos y se utilizó un sistema de información geográfica para su segregación y análisis. Los resultados indican que el valor aproximado de los servicios ecosistémicos de las áreas protegidas en México es de 391 mil millones de dólares siendo las Reservas de la Biosfera y las Áreas de Protección de Flora y Fauna las que concentran el monto mayor. Regionalmente el valor más alto se congrega en la Planicie Costera y Golfo de México y la Península de Yucatán y Caribe Mexicano. La información generada es de especial utilidad para establecer valores de referencia para los servicios ecosistémicos provistos por las áreas protegidas en México y puede servir de base para el diseño de planes y programas dirigidos a mejorar su manejo y conservación en el territorio.

@article{cortes_evaluating_2026,
	title = {Evaluating ecological relationships and niche breadth among historically sympatric {Canis} taxa using isotope analysis},
	volume = {107},
	issn = {0022-2372},
	url = {https://doi.org/10.1093/jmammal/gyaf092},
	doi = {10.1093/jmammal/gyaf092},
	abstract = {Persecution of wild North American wolf-like canids (subfamily Caninae, genus Canis) by humans has severely reduced their geographic ranges and diversity. This is notably evident in the Southern Great Plains region spanning the states of Texas, Oklahoma, and New Mexico, United States. Historically, this region supported the now locally extinct Great Plains Wolf (C. lupus nubilus) and Red Wolf (C. rufus). Current wild wolf-like canid diversity largely consists of the Coyote (C. latrans), while the Mexican Wolf (C. lupus baileyi) is primarily restricted to the recovery program area. As interspecific antagonism and competition are known to affect behavior and resource use among wolf-like canids, historical sympatry raises important ecological questions. Stable isotope analysis (δ13C, δ15N) of bone collagen was employed to evaluate potential change in the isotopic niche of coyotes following wolf extirpation within the study region and to examine niche breadth and overlap among modern wolves and coyotes. Stable isotope data and radiocarbon dates were additionally obtained for a sample of wolves purported to be pre-Industrial, and niche breadth was compared to modern wolf samples. Kernel estimation density methods were used to estimate isotopic niche breadth and degree of overlap in group-wise comparisons. Results suggest a reduction in the isotopic niche breadth of coyotes following wolf extirpation, and substantial overlap in niche area between red wolves and coyotes, suggesting potential historical competition. Mexican wolves had a more constrained and divergent niche breadth, which may be shaped by habitat and prey preference as well as competition. Overlap was minimal among modern and pre-Industrial wolves, likely reflective of sample size and collection localities. These findings provide insights into how Coyote niche breadth may shift following reduced wolf presence and resource use patterns among sympatric wolf-like canids.},
	number = {1},
	urldate = {2026-05-22},
	journal = {Journal of Mammalogy},
	author = {Cortes, Celine S},
	month = feb,
	year = {2026},
	keywords = {Terrestrial Ecoregions (CEC 1997)},
	pages = {54--65},
}

Persecution of wild North American wolf-like canids (subfamily Caninae, genus Canis) by humans has severely reduced their geographic ranges and diversity. This is notably evident in the Southern Great Plains region spanning the states of Texas, Oklahoma, and New Mexico, United States. Historically, this region supported the now locally extinct Great Plains Wolf (C. lupus nubilus) and Red Wolf (C. rufus). Current wild wolf-like canid diversity largely consists of the Coyote (C. latrans), while the Mexican Wolf (C. lupus baileyi) is primarily restricted to the recovery program area. As interspecific antagonism and competition are known to affect behavior and resource use among wolf-like canids, historical sympatry raises important ecological questions. Stable isotope analysis (δ13C, δ15N) of bone collagen was employed to evaluate potential change in the isotopic niche of coyotes following wolf extirpation within the study region and to examine niche breadth and overlap among modern wolves and coyotes. Stable isotope data and radiocarbon dates were additionally obtained for a sample of wolves purported to be pre-Industrial, and niche breadth was compared to modern wolf samples. Kernel estimation density methods were used to estimate isotopic niche breadth and degree of overlap in group-wise comparisons. Results suggest a reduction in the isotopic niche breadth of coyotes following wolf extirpation, and substantial overlap in niche area between red wolves and coyotes, suggesting potential historical competition. Mexican wolves had a more constrained and divergent niche breadth, which may be shaped by habitat and prey preference as well as competition. Overlap was minimal among modern and pre-Industrial wolves, likely reflective of sample size and collection localities. These findings provide insights into how Coyote niche breadth may shift following reduced wolf presence and resource use patterns among sympatric wolf-like canids.

@phdthesis{clelland_fanning_2026,
	type = {Doctoral},
	title = {Fanning the flames: {Past} and future links between climate change and fire activity across boreal forests},
	shorttitle = {Fanning the flames},
	url = {https://etheses.durham.ac.uk/id/eprint/16487/},
	abstract = {Boreal forests are experiencing unprecedented environmental change, with increasing fire activity posing significant ecological and climatic challenges. This thesis investigates past, present and future interactions between climate and fire across the boreal biome, combining reanalysis datasets, burned area products and machine learning to examine drivers of fire occurrence and project potential changes in future burned area. Chapter 2 evaluates the reliability of three reanalysis datasets across Siberia by comparing six climate variables related to fire activity with in situ observations from meteorological stations. The datasets are mostly good representations for the studied variables but also show notable regional biases and inconsistencies, highlighting the importance of bias correction in the boreal region. Chapter 3 evaluates twelve satellite imagery-derived burned area products across Arctic-boreal North America and Russia from 2001 to 2020, identifying consistent patterns in North America but major discrepancies in southern Siberia, and highlighting the strengths, limitations and suitability of each product for various research and monitoring applications. Chapter 4 develops machine learning models to project burned area across boreal and tundra biomes from 2025 to 2100 under different climate change projections using climate model outputs. Results show strong scenario- and region-dependent increases in burned area, particularly in North America, suggesting that climate change will intensify fire regimes in many areas. The final discussion chapter combines these findings, emphasising that climate-fire relationships are non-uniform and modulated by vegetation, topography and climate. It discusses the implications of increasing fire activity for carbon accounting, ecosystem resilience and climate feedbacks, and highlights the need for adaptive fire management and further research into vegetation-fire-climate feedbacks in boreal systems. Together, the thesis provides a novel approach to understanding boreal climate-fire dynamics and underscores the urgency of addressing fire risk in a warming world.},
	language = {en},
	urldate = {2026-06-01},
	school = {Durham University},
	author = {CLELLAND, ANDREW ALISTAIR},
	year = {2026},
	keywords = {NALCMS},
}

Boreal forests are experiencing unprecedented environmental change, with increasing fire activity posing significant ecological and climatic challenges. This thesis investigates past, present and future interactions between climate and fire across the boreal biome, combining reanalysis datasets, burned area products and machine learning to examine drivers of fire occurrence and project potential changes in future burned area. Chapter 2 evaluates the reliability of three reanalysis datasets across Siberia by comparing six climate variables related to fire activity with in situ observations from meteorological stations. The datasets are mostly good representations for the studied variables but also show notable regional biases and inconsistencies, highlighting the importance of bias correction in the boreal region. Chapter 3 evaluates twelve satellite imagery-derived burned area products across Arctic-boreal North America and Russia from 2001 to 2020, identifying consistent patterns in North America but major discrepancies in southern Siberia, and highlighting the strengths, limitations and suitability of each product for various research and monitoring applications. Chapter 4 develops machine learning models to project burned area across boreal and tundra biomes from 2025 to 2100 under different climate change projections using climate model outputs. Results show strong scenario- and region-dependent increases in burned area, particularly in North America, suggesting that climate change will intensify fire regimes in many areas. The final discussion chapter combines these findings, emphasising that climate-fire relationships are non-uniform and modulated by vegetation, topography and climate. It discusses the implications of increasing fire activity for carbon accounting, ecosystem resilience and climate feedbacks, and highlights the need for adaptive fire management and further research into vegetation-fire-climate feedbacks in boreal systems. Together, the thesis provides a novel approach to understanding boreal climate-fire dynamics and underscores the urgency of addressing fire risk in a warming world.

@techreport{us_fish__wildlife_service_findings_2026,
	title = {Findings and {FONSI} for the {Multi}-{Bat} {Species} {General} {Conservation} {Plan} for {NY}, {PA}, and {WV} {\textbar} {FWS}.gov},
	url = {https://www.fws.gov/media/findings-and-fonsi-multi-bat-species-general-conservation-plan-ny-pa-and-wv},
	language = {en},
	urldate = {2026-05-29},
	author = {{U.S. Fish \& Wildlife Service}},
	month = jan,
	year = {2026},
	keywords = {Terrestrial Ecoregions (CEC 1997), Terrestrial Ecoregions (Griffith 2010)},
}

@article{dallosch_gatekeeper_2026,
	title = {Gatekeeper wetlands govern nutrient pathways in a continental basin},
	copyright = {2026 The Author(s)},
	issn = {2662-4435},
	url = {https://www.nature.com/articles/s43247-026-03535-7},
	doi = {10.1038/s43247-026-03535-7},
	abstract = {Headwater non-floodplain wetlands are often overlooked in nutrient-management strategies despite their potential to regulate downstream water quality. Here we test whether headwater non-floodplain wetlands act as nutrient gatekeepers in the Lake Winnipeg Watershed. We define wetlands as seasonally-to-persistently inundated surface-water areas mapped from satellite imagery, and combine multi-decadal observations of wetland inundation and wetland–stream connectivity (1984–2020) with observed annual total nitrogen and total phosphorus loads (1994–2020) and random forest models. Nutrient export is lowest when headwater non-floodplain wetlands remain hydrologically disconnected and increases during episodic reconnection, indicating a threshold-like shift from nutrient storage to export. The ratio of disconnected non-floodplain wetland area is the strongest negative predictor of nutrient delivery, whereas mid/high-order reaches are weaker and less consistent. These results identify intermittently connected headwater non-floodplain wetlands as basin-scale regulators of nutrient pathways and highlight protecting them as a scalable strategy to reduce eutrophication risk in climate-sensitive watersheds.},
	language = {en},
	urldate = {2026-05-22},
	journal = {Communications Earth \& Environment},
	author = {Dallosch, Michael A. and Creed, Irena F.},
	month = apr,
	year = {2026},
	note = {Publisher: Nature Publishing Group},
	keywords = {Watersheds},
}

Headwater non-floodplain wetlands are often overlooked in nutrient-management strategies despite their potential to regulate downstream water quality. Here we test whether headwater non-floodplain wetlands act as nutrient gatekeepers in the Lake Winnipeg Watershed. We define wetlands as seasonally-to-persistently inundated surface-water areas mapped from satellite imagery, and combine multi-decadal observations of wetland inundation and wetland–stream connectivity (1984–2020) with observed annual total nitrogen and total phosphorus loads (1994–2020) and random forest models. Nutrient export is lowest when headwater non-floodplain wetlands remain hydrologically disconnected and increases during episodic reconnection, indicating a threshold-like shift from nutrient storage to export. The ratio of disconnected non-floodplain wetland area is the strongest negative predictor of nutrient delivery, whereas mid/high-order reaches are weaker and less consistent. These results identify intermittently connected headwater non-floodplain wetlands as basin-scale regulators of nutrient pathways and highlight protecting them as a scalable strategy to reduce eutrophication risk in climate-sensitive watersheds.

@article{ivester_genomic_2026,
	title = {Genomic {Epidemiology} of {Fungi} {Identified} in {Bronchoalveolar} {Lavage} {Fluid} from {Asthmatic} {Horses} in the {US}},
	volume = {16},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {2076-2615},
	url = {https://www.mdpi.com/2076-2615/16/4/526},
	doi = {10.3390/ani16040526},
	abstract = {Fungal exposure is strongly implicated in the pathogenesis of asthma in horses, but the importance of specific fungi is unknown. Geographic variation in equine asthmatic endotypes is suspected and might be related to different fungal exposures due to different climatological and geographical conditions. This study had two objectives: evaluate the effect of the ecoregion upon BALF inflammatory cells and fungal community composition in horses with asthma and evaluate the effect of BALF fungal community composition upon the likelihood of neutrophilic, mastocytic and eosinophilic inflammation in these horses. Differential cytology counts were obtained from 916 BALF samples submitted from horses with poor performance and/or clinical signs of respiratory disease from five ecoregions. The effect of the ecoregion upon BALF inflammatory cell proportions was modeled using generalized linear models. Seventy banked BALF samples were subjected to sequencing of the internal transcribed spacer regions of fungal DNA. Diversity analysis was performed in QIIME, including alpha diversity metrics and the Bray–Curtis dissimilarity metric. After taxonomy was assigned, differential abundances between ecoregions and inflammatory phenotypes were estimated by generalized linear models in DESeq2. BALF neutrophil (p {\textless} 0.0001) and eosinophil (p {\textless} 0.0001) proportions varied by ecoregion, while mast cell proportions did not (p = 0.18). Alternaria, Aspergillus, Cladosporium and Epicoccum spp. were found to differ in abundance between regions. These geographical variations in fungal exposure might be responsible for differences in BALF neutrophil and eosinophil proportions between ecoregions.},
	language = {en},
	number = {4},
	urldate = {2026-05-27},
	journal = {Animals},
	author = {Ivester, Kathleen and Couetil, Laurent and Arora, Devender and Wilkes, Rebecca and Thimmapuram, Jyothi},
	month = jan,
	year = {2026},
	note = {Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {Terrestrial Ecoregions},
	pages = {526},
}

Fungal exposure is strongly implicated in the pathogenesis of asthma in horses, but the importance of specific fungi is unknown. Geographic variation in equine asthmatic endotypes is suspected and might be related to different fungal exposures due to different climatological and geographical conditions. This study had two objectives: evaluate the effect of the ecoregion upon BALF inflammatory cells and fungal community composition in horses with asthma and evaluate the effect of BALF fungal community composition upon the likelihood of neutrophilic, mastocytic and eosinophilic inflammation in these horses. Differential cytology counts were obtained from 916 BALF samples submitted from horses with poor performance and/or clinical signs of respiratory disease from five ecoregions. The effect of the ecoregion upon BALF inflammatory cell proportions was modeled using generalized linear models. Seventy banked BALF samples were subjected to sequencing of the internal transcribed spacer regions of fungal DNA. Diversity analysis was performed in QIIME, including alpha diversity metrics and the Bray–Curtis dissimilarity metric. After taxonomy was assigned, differential abundances between ecoregions and inflammatory phenotypes were estimated by generalized linear models in DESeq2. BALF neutrophil (p \textless 0.0001) and eosinophil (p \textless 0.0001) proportions varied by ecoregion, while mast cell proportions did not (p = 0.18). Alternaria, Aspergillus, Cladosporium and Epicoccum spp. were found to differ in abundance between regions. These geographical variations in fungal exposure might be responsible for differences in BALF neutrophil and eosinophil proportions between ecoregions.

@article{castle_global_2026,
	title = {Global forest dataset incongruence creates high uncertainties for conservation, climate, and development policy},
	volume = {9},
	issn = {2590-3330, 2590-3322},
	url = {https://www.cell.com/one-earth/abstract/S2590-3322(25)00384-7},
	doi = {10.1016/j.oneear.2025.101558},
	language = {English},
	number = {2},
	urldate = {2026-05-22},
	journal = {One Earth},
	author = {Castle, Sarah E. and Newton, Peter and Oldekop, Johan A. and Baylis, Kathy and Miller, Daniel C.},
	month = feb,
	year = {2026},
	note = {Publisher: Elsevier},
	keywords = {NALCMS},
}

@article{katz_habitat-based_2026,
	title = {Habitat-{Based} {Predictions} of {Bridle} {Shiner} ({Notropis} bifrenatus) in the {Northeastern} {United} {States}},
	volume = {16},
	copyright = {© 2026 The Author(s). Ecology and Evolution published by British Ecological Society and John Wiley \& Sons Ltd.},
	issn = {2045-7758},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/ece3.72413},
	doi = {10.1002/ece3.72413},
	abstract = {We sought to assess bridle shiner (Notropis bifrenatus) habitat associations at local and regional scales across southern Maine and New Hampshire. We used local habitat data at 95 Maine sites to predict occupancy with classification and regression trees (CART). We then used ensemble species distribution models (SDMs) to model the historical (1898–2008) and current (2009–2022) ranges of the species. We used the BIOMOD platform to model the association between 35 environmental variables and bridle shiner presence during both time periods and at fine (pseudo-HUC14) and coarse (HUC12) spatial scales. We then calculated the change in predicted occupied drainages to estimate the change in the species' distribution at both scales. Within a site, bridle shiners were associated with submerged aquatic vegetation, organic substrate, and watermilfoil (Myriophyllum spp.). SDMs revealed an association with Appalachian (Hemlock-)Northern Hardwood Forest, sand substrate, and low-elevation terrain (at both spatial scales). Ensemble fine-scale SDMs suggest a substantial loss of historical bridle shiner habitat in both Maine (36\% of drainages) and New Hampshire (16\%), with comparable described losses (of 21\% and 14\%) at a coarse scale. Our local and regional models may be used to focus surveys on areas with high predicted habitat suitability or to inform habitat restoration efforts.},
	language = {en},
	number = {1},
	urldate = {2026-05-27},
	journal = {Ecology and Evolution},
	author = {Katz, Lara S. and Coghlan Jr., Stephen M. and Carpenter, Matthew A. and Kinnison, Michael T. and Zydlewski, Joseph D.},
	year = {2026},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/ece3.72413},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {e72413},
}

We sought to assess bridle shiner (Notropis bifrenatus) habitat associations at local and regional scales across southern Maine and New Hampshire. We used local habitat data at 95 Maine sites to predict occupancy with classification and regression trees (CART). We then used ensemble species distribution models (SDMs) to model the historical (1898–2008) and current (2009–2022) ranges of the species. We used the BIOMOD platform to model the association between 35 environmental variables and bridle shiner presence during both time periods and at fine (pseudo-HUC14) and coarse (HUC12) spatial scales. We then calculated the change in predicted occupied drainages to estimate the change in the species' distribution at both scales. Within a site, bridle shiners were associated with submerged aquatic vegetation, organic substrate, and watermilfoil (Myriophyllum spp.). SDMs revealed an association with Appalachian (Hemlock-)Northern Hardwood Forest, sand substrate, and low-elevation terrain (at both spatial scales). Ensemble fine-scale SDMs suggest a substantial loss of historical bridle shiner habitat in both Maine (36% of drainages) and New Hampshire (16%), with comparable described losses (of 21% and 14%) at a coarse scale. Our local and regional models may be used to focus surveys on areas with high predicted habitat suitability or to inform habitat restoration efforts.

@phdthesis{augustine_has_2026,
	title = {Has physical isolation resulted in genetically and phenotypically distinct watersnake and gartersnake populations on remote {Lake} {Ontario} islands?},
	url = {https://hdl.handle.net/1974/36037},
	abstract = {Intraspecific divergence and speciation on remote marine islands are widely known. However, the processes that underly diversification on islands can occur at fine geographic scales as well, such as in islands in freshwater lakes. Dispersal-restricted organisms, such as snakes, inhabit islands throughout the North American Great Lakes, some of which are isolated from mainland populations by many kilometres of open water. I sought to test whether populations of northern water snake (Nerodia sipedon sipedon) and eastern garter snake (Thamnophis sirtalis sirtalis) on two small islands in eastern Lake Ontario {\textasciitilde}12 km from the nearest mainland—Main Duck and Yorkshire Islands—are genetically and phenotypically distinct from mainland conspecifics. To assess island-mainland genetic divergence, I used genome-wide panels of single nucleotide polymorphism markers (SNPs) derived from reduced-representation sequencing. I also tested for differences in head morphology and body size among watersnake populations. My results show that insular populations of both species are indeed genetically distinct from their mainland counterparts, but that there are differences in overall genetic structure between the two species around eastern Lake Ontario, possibly related to differences in dispersal ecology and demographic history. In watersnakes, patterns of genetic differentiation appear to be largely related to the water currents of eastern Lake Ontario. In gartersnakes, island-mainland differentiation is more subtle, with a potential contact zone between more deeply diverged lineages southeast of the outlet of Lake Ontario into the St. Lawrence River. I did not find differences in head morphology independent of body size in watersnakes, but did find differences in snout-vent length (SVL) among island and mainland populations. Aside from yielding insights on the origins of snake populations endemic to small islands in the North American Great Lakes, my findings may be useful to conservation agencies, as they may decide to manage the island populations as distinct population segments, especially if future work demonstrates that these insular populations possess unique evolutionary histories or unique adaptive traits.},
	language = {eng},
	urldate = {2026-06-01},
	author = {Augustine, Arjun},
	month = feb,
	year = {2026},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
}

Intraspecific divergence and speciation on remote marine islands are widely known. However, the processes that underly diversification on islands can occur at fine geographic scales as well, such as in islands in freshwater lakes. Dispersal-restricted organisms, such as snakes, inhabit islands throughout the North American Great Lakes, some of which are isolated from mainland populations by many kilometres of open water. I sought to test whether populations of northern water snake (Nerodia sipedon sipedon) and eastern garter snake (Thamnophis sirtalis sirtalis) on two small islands in eastern Lake Ontario ~12 km from the nearest mainland—Main Duck and Yorkshire Islands—are genetically and phenotypically distinct from mainland conspecifics. To assess island-mainland genetic divergence, I used genome-wide panels of single nucleotide polymorphism markers (SNPs) derived from reduced-representation sequencing. I also tested for differences in head morphology and body size among watersnake populations. My results show that insular populations of both species are indeed genetically distinct from their mainland counterparts, but that there are differences in overall genetic structure between the two species around eastern Lake Ontario, possibly related to differences in dispersal ecology and demographic history. In watersnakes, patterns of genetic differentiation appear to be largely related to the water currents of eastern Lake Ontario. In gartersnakes, island-mainland differentiation is more subtle, with a potential contact zone between more deeply diverged lineages southeast of the outlet of Lake Ontario into the St. Lawrence River. I did not find differences in head morphology independent of body size in watersnakes, but did find differences in snout-vent length (SVL) among island and mainland populations. Aside from yielding insights on the origins of snake populations endemic to small islands in the North American Great Lakes, my findings may be useful to conservation agencies, as they may decide to manage the island populations as distinct population segments, especially if future work demonstrates that these insular populations possess unique evolutionary histories or unique adaptive traits.

@article{mohammadimanesh_hiresnet_2026,
	title = {{HiResNet}: {A} {Low}-to-{High} {Deep} {Learning} {Framework} for {Updating} {Large}-{Scale} {Land} {Cover} {Inventory}},
	volume = {64},
	issn = {1558-0644},
	shorttitle = {{HiResNet}},
	url = {https://ieeexplore.ieee.org/document/11460176},
	doi = {10.1109/TGRS.2026.3676677},
	abstract = {Large-scale land cover (LC) mapping is critical for monitoring Earth’s surface and managing environmental changes. While machine learning (ML) and deep learning (DL) methods have significantly advanced LC mapping efforts, the reliance on high-quality training labels remains a major limitation due to their time-intensive and costly collection process. To address this challenge, we propose HiResNet, a novel DL framework that combines a multiscale feature extractor (MSFE) within convolutional neural networks (CNNs), a vision transformer (ViT) architecture, and a weakly-supervised loss function, to produce a 10 m LC map using an existing low-resolution (LR) 30 m LC map. In particular, this framework reduces the dependence on high-resolution (HR) training labels while generating HR (10 m) LC maps using Sentinel-2 imagery and LR 30 m labels. The capability of the proposed method is evaluated in the province of Ontario (ON), Canada, a region characterized by a diverse landscape and different LC types, covering approximately 1.07 million km2. The results demonstrate a remarkable capability of the proposed model to enhance spatial resolution and achieve high classification accuracy, with an overall accuracy (OA) of 89\% for large-scale LC classification. Compared to conventional methods and advanced DL architectures, such as Random Forest (RF), ViT, HRNet, SegFormer, DeepLabV3, and L2HNet, the proposed method exhibits a superior performance by handling class imbalances and extracting complex features. Furthermore, uncertainty estimation using Shannon entropy and class disagreement metrics demonstrates that the highest levels of uncertainty are associated with object edges, narrow features (e.g., rivers and roads), and complex LC classes like forests.},
	urldate = {2026-05-27},
	journal = {IEEE Transactions on Geoscience and Remote Sensing},
	author = {Mohammadimanesh, Fariba and Marjani, Mohammad and Mahdianpari, Masoud},
	year = {2026},
	keywords = {NALCMS},
	pages = {1--20},
}

Large-scale land cover (LC) mapping is critical for monitoring Earth’s surface and managing environmental changes. While machine learning (ML) and deep learning (DL) methods have significantly advanced LC mapping efforts, the reliance on high-quality training labels remains a major limitation due to their time-intensive and costly collection process. To address this challenge, we propose HiResNet, a novel DL framework that combines a multiscale feature extractor (MSFE) within convolutional neural networks (CNNs), a vision transformer (ViT) architecture, and a weakly-supervised loss function, to produce a 10 m LC map using an existing low-resolution (LR) 30 m LC map. In particular, this framework reduces the dependence on high-resolution (HR) training labels while generating HR (10 m) LC maps using Sentinel-2 imagery and LR 30 m labels. The capability of the proposed method is evaluated in the province of Ontario (ON), Canada, a region characterized by a diverse landscape and different LC types, covering approximately 1.07 million km2. The results demonstrate a remarkable capability of the proposed model to enhance spatial resolution and achieve high classification accuracy, with an overall accuracy (OA) of 89% for large-scale LC classification. Compared to conventional methods and advanced DL architectures, such as Random Forest (RF), ViT, HRNet, SegFormer, DeepLabV3, and L2HNet, the proposed method exhibits a superior performance by handling class imbalances and extracting complex features. Furthermore, uncertainty estimation using Shannon entropy and class disagreement metrics demonstrates that the highest levels of uncertainty are associated with object edges, narrow features (e.g., rivers and roads), and complex LC classes like forests.

@article{qi_how_2026,
	title = {How {Much} {Uncertainty} {Does} the {Tower} {Create} in {Tower}-{Based} {Albedo} {Observations}?},
	volume = {18},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {2072-4292},
	url = {https://www.mdpi.com/2072-4292/18/4/631},
	doi = {10.3390/rs18040631},
	abstract = {Towers often have complex structures and higher reflectances than the surrounding surfaces. To identify the uncertainty of the tower in tower-based albedo observations, a combined approach involving simulation and field observations was applied to three newly constructed towers in the Saihanba region. The simulation results demonstrate that tower presence influenced the albedo measurements, with the impact primarily controlled by tower reflectance rather than sensor height. When the tower-body albedo markedly differs from the background, systematic correction is necessary. Field validation indicates that for the towers in the Saihanba region, the contrast in albedo between the tower and the surrounding background is small, and both the simulated and observed albedos agree well with the ground measurements, with differences below 0.0075. By identifying when and how tower structures distort albedo observations, this study enhances confidence in ground-based validation and provides practical guidance for future tower design and material selection.},
	language = {en},
	number = {4},
	urldate = {2026-05-29},
	journal = {Remote Sensing},
	author = {Qi, Jinlin and Zhang, Yusha and Shi, Peirong and Wan, Huawei and Li, Chen and Wang, Ziyu and Mao, Chenzheng and Fang, Ruojing and Zhou, Hongmin},
	month = jan,
	year = {2026},
	note = {Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {NALCMS},
	pages = {631},
}

Towers often have complex structures and higher reflectances than the surrounding surfaces. To identify the uncertainty of the tower in tower-based albedo observations, a combined approach involving simulation and field observations was applied to three newly constructed towers in the Saihanba region. The simulation results demonstrate that tower presence influenced the albedo measurements, with the impact primarily controlled by tower reflectance rather than sensor height. When the tower-body albedo markedly differs from the background, systematic correction is necessary. Field validation indicates that for the towers in the Saihanba region, the contrast in albedo between the tower and the surrounding background is small, and both the simulated and observed albedos agree well with the ground measurements, with differences below 0.0075. By identifying when and how tower structures distort albedo observations, this study enhances confidence in ground-based validation and provides practical guidance for future tower design and material selection.

@article{sorensen_hydrologic_2026,
	title = {Hydrologic variability drives environmental and geospatial relationships in {Smallmouth} {Bass} (\textit{{Micropterus} dolomieu}) distribution},
	volume = {1025},
	issn = {0048-9697},
	url = {https://www.sciencedirect.com/science/article/pii/S0048969726002226},
	doi = {10.1016/j.scitotenv.2026.181562},
	abstract = {Hydrologic variation is a primary driver of stream ecosystems. Changing hydrology can lead to assemblage shifts and alterations in suitable habitat for freshwater species. As climate change is predicted to alter flow patterns in addition to increasing water temperatures, insight into relationships between species occupancy, hydrology, and temperature is critical for understanding current and future distributions. We examined how hydrologic variability, temperature, and other environmental variables interact to influence Micropterus dolomieu (Smallmouth Bass) occurrence. We used Spatial Stream Network models, allowing for the incorporation of spatial autocorrelation along streams' unique dendritic network, to examine Smallmouth Bass occupancy across a range of hydrologic variation in the Ozark-Ouachita Interior Highlands, USA. Hydrologic variation was the main driver of Smallmouth Bass occurrence, with occurrence more likely in groundwater streams with low hydrologic variation and high flow permanence. For groundwater streams, occurrence was positively associated with summer stream temperature and negatively associated with annual stream temperature. As variation increased, more variables showed significant relationships with occurrence. Distance metrics were important for all models, however as hydrologic disturbance increased, flow connected distance played a lesser role and stream distance played a greater role. Hydrologic variability was the overarching determinant of Smallmouth Bass occurrence and strongly influenced the predictive importance of environmental variables and geospatial relationships. Greater hydrologic variability resulted in stronger statistical relationships between occurrence and environmental variables and an increased importance of system connectivity. As climate change alters hydrologic processes and streams become more variable, understanding and accounting for these shifting relationships is essential.},
	urldate = {2026-05-29},
	journal = {Science of The Total Environment},
	author = {Sorensen, Sarah F. and Fox, J. Tyler and Magoulick, Daniel D.},
	month = apr,
	year = {2026},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {181562},
}

Hydrologic variation is a primary driver of stream ecosystems. Changing hydrology can lead to assemblage shifts and alterations in suitable habitat for freshwater species. As climate change is predicted to alter flow patterns in addition to increasing water temperatures, insight into relationships between species occupancy, hydrology, and temperature is critical for understanding current and future distributions. We examined how hydrologic variability, temperature, and other environmental variables interact to influence Micropterus dolomieu (Smallmouth Bass) occurrence. We used Spatial Stream Network models, allowing for the incorporation of spatial autocorrelation along streams' unique dendritic network, to examine Smallmouth Bass occupancy across a range of hydrologic variation in the Ozark-Ouachita Interior Highlands, USA. Hydrologic variation was the main driver of Smallmouth Bass occurrence, with occurrence more likely in groundwater streams with low hydrologic variation and high flow permanence. For groundwater streams, occurrence was positively associated with summer stream temperature and negatively associated with annual stream temperature. As variation increased, more variables showed significant relationships with occurrence. Distance metrics were important for all models, however as hydrologic disturbance increased, flow connected distance played a lesser role and stream distance played a greater role. Hydrologic variability was the overarching determinant of Smallmouth Bass occurrence and strongly influenced the predictive importance of environmental variables and geospatial relationships. Greater hydrologic variability resulted in stronger statistical relationships between occurrence and environmental variables and an increased importance of system connectivity. As climate change alters hydrologic processes and streams become more variable, understanding and accounting for these shifting relationships is essential.

@article{rawlins_hydrological_2026,
	title = {Hydrological {Cycle} {Intensification} and {Permafrost} {Thaw} {Drive} {Increased} {Freshwater} and {Organic} {Carbon} {Inputs} to {Northern} {Alaska} {Estuaries}},
	volume = {40},
	copyright = {© 2026. The Author(s).},
	issn = {1944-9224},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2025GB008822},
	doi = {10.1029/2025GB008822},
	abstract = {Understanding how hydrological inflows and climate change influence individual estuaries across northern Alaska is limited by a paucity of measured data, necessitating the application of suitably scaled numerical process models. This study uses an updated model to quantify freshwater discharge and dissolved organic carbon (DOC) export from the North Slope of Alaska (NSA) to coastal waters of the Beaufort Sea and examines climate-linked temporal changes. The model was applied at 1 {\textbackslash}textkm{\textbackslash} resolution across the 166,483 \{\vphantom{\}}{\textbackslash}textkm{\textasciicircum}2{\textbackslash} NSA domain over 1980–2023. Watershed inputs to coastal waters were estimated by routing along river networks to 1,039 outlets at the land-sea boundary. Key simulation parameters were evaluated to demonstrate model efficacy, then spatial and temporal patterns were quantified. Exports to specific lagoons, bays, and sounds demonstrate how landscape composition, terrestrial drainage basin size, and estuary area modulate watershed influence on coastal ecosystems across the region. Freshwater discharge and DOC export increased over the greater than four decades, associated with changes in precipitation and permafrost thaw. Surface and supra-permafrost subsurface fluxes also increased, with pronounced rises in proportional contributions via subsurface flow during summer and autumn. These changes have the potential to substantially impact salinity and trophic conditions along Alaska's Beaufort Sea coast. Our study highlights the value of model-data syntheses that resolve regional-to-local scale fluxes where observational measurements are sparse, and provides novel quantitative export metrics that will be useful to researchers, resource managers, and other stakeholders with interests in the climate, hydrology, and biogeochemistry of coastal northern Alaska.},
	language = {en},
	number = {4},
	urldate = {2026-05-29},
	journal = {Global Biogeochemical Cycles},
	author = {Rawlins, Michael A. and Connolly, Craig T. and McClelland, James W.},
	year = {2026},
	note = {\_eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2025GB008822},
	keywords = {NALCMS},
	pages = {e2025GB008822},
}

Understanding how hydrological inflows and climate change influence individual estuaries across northern Alaska is limited by a paucity of measured data, necessitating the application of suitably scaled numerical process models. This study uses an updated model to quantify freshwater discharge and dissolved organic carbon (DOC) export from the North Slope of Alaska (NSA) to coastal waters of the Beaufort Sea and examines climate-linked temporal changes. The model was applied at 1 \textkm\ resolution across the 166,483 \p̌hantom\\textkm\textasciicircum2\ NSA domain over 1980–2023. Watershed inputs to coastal waters were estimated by routing along river networks to 1,039 outlets at the land-sea boundary. Key simulation parameters were evaluated to demonstrate model efficacy, then spatial and temporal patterns were quantified. Exports to specific lagoons, bays, and sounds demonstrate how landscape composition, terrestrial drainage basin size, and estuary area modulate watershed influence on coastal ecosystems across the region. Freshwater discharge and DOC export increased over the greater than four decades, associated with changes in precipitation and permafrost thaw. Surface and supra-permafrost subsurface fluxes also increased, with pronounced rises in proportional contributions via subsurface flow during summer and autumn. These changes have the potential to substantially impact salinity and trophic conditions along Alaska's Beaufort Sea coast. Our study highlights the value of model-data syntheses that resolve regional-to-local scale fluxes where observational measurements are sparse, and provides novel quantitative export metrics that will be useful to researchers, resource managers, and other stakeholders with interests in the climate, hydrology, and biogeochemistry of coastal northern Alaska.

@article{rincon_hydrological_2026,
	title = {Hydrological and thermal regime shifts in a sub-{Arctic} river under climate change: implications of potential changes in thermal habitat for {Arctic} char and {Atlantic} salmon},
	volume = {17},
	issn = {2040-2244},
	shorttitle = {Hydrological and thermal regime shifts in a sub-{Arctic} river under climate change},
	url = {https://doi.org/10.2166/wcc.2026.417},
	doi = {10.2166/wcc.2026.417},
	abstract = {Graphical Abstract. Graph showing the work flow of the study. Legend: Graphical AbstractClimate change-driven effects are significant socio-environmental concerns in the Arctic and sub-Arctic regions. This study assesses the impact of climate change on the hydrological and thermal regimes of the Aux-Mélèzes River, an important sub-Arctic watershed in northeastern Canada. Using the process-based CEQUEAU model, we projected future (2040–2100) thermal regime shifts, validating against historical data (1980–2020) with strong performance metrics for summer flows and water temperature. Historically, the Aux-Mélèzes River has provided suitable summer habitat for Arctic char and Atlantic salmon, but projections indicate statistically significant increases in mean summer water temperature across all climate scenarios. Temperature duration curve analysis reveals a shift towards higher temperatures, with the probability of exceeding the 23 °C thermal stress threshold for key fish species increasing significantly by the century’s end. Furthermore, maximum summer water temperature projections highlight tributaries as critical warming hotspots, posing risks to fish habitat. The onset of positive water temperature is expected to decline by 45–55 days, significantly changing seasonal thermal timing. These hydrological and temperature changes represent a socio-ecological threat, emphasizing the need for adaptive management and enhanced predictive capabilities in these rapidly changing environments.},
	number = {4},
	urldate = {2026-05-29},
	journal = {Journal of Water and Climate Change},
	author = {Rincón, Eisinhower and St-Hilaire, André and Bergeron, Normand and Dugdale, Stephen},
	month = apr,
	year = {2026},
	keywords = {NALCMS},
	pages = {1032--1055},
}

Graphical Abstract. Graph showing the work flow of the study. Legend: Graphical AbstractClimate change-driven effects are significant socio-environmental concerns in the Arctic and sub-Arctic regions. This study assesses the impact of climate change on the hydrological and thermal regimes of the Aux-Mélèzes River, an important sub-Arctic watershed in northeastern Canada. Using the process-based CEQUEAU model, we projected future (2040–2100) thermal regime shifts, validating against historical data (1980–2020) with strong performance metrics for summer flows and water temperature. Historically, the Aux-Mélèzes River has provided suitable summer habitat for Arctic char and Atlantic salmon, but projections indicate statistically significant increases in mean summer water temperature across all climate scenarios. Temperature duration curve analysis reveals a shift towards higher temperatures, with the probability of exceeding the 23 °C thermal stress threshold for key fish species increasing significantly by the century’s end. Furthermore, maximum summer water temperature projections highlight tributaries as critical warming hotspots, posing risks to fish habitat. The onset of positive water temperature is expected to decline by 45–55 days, significantly changing seasonal thermal timing. These hydrological and temperature changes represent a socio-ecological threat, emphasizing the need for adaptive management and enhanced predictive capabilities in these rapidly changing environments.

@article{retamoza-gonzalez_identifying_2026,
	title = {Identifying priority restoration areas by mapping land-use change drivers},
	volume = {22},
	issn = {2667-0100},
	url = {https://www.sciencedirect.com/science/article/pii/S266701002500318X},
	doi = {10.1016/j.envc.2025.101399},
	abstract = {Land-use and land-cover (LULC) changes are key drivers of vegetation cover loss. Northwestern Mexico hosts the only Mediterranean-climate region in the country, a socio-ecosystem that, due to its distinct socioeconomic and ecological dynamics, simultaneously undergoes processes of anthropization and vegetation recovery, driven by agricultural expansion and land abandonment. In order to identify areas with high recovery and conservation potential within this socio-ecosystem, we evaluated land-cover losses, gains, and rates of change between 2015 and 2020. Using LISA spatial autocorrelation analysis, we identified clusters of anthropization and vegetation recovery, as well as priority areas for conservation actions. Overall, LULC change within the Mexican Mediterranean socio-ecosystem reached 4 \%, with coastal shrub being the land-cover type that experienced the greatest loss (64,443 ha), primarily converted to agricultural land, which expanded by 66,203 ha. Anthropization and recovery were the dominant processes in this region. High anthropization clusters were concentrated in mountainous regions and peri-urban areas along the coastal belt, likely associated with agricultural and livestock expansion, whereas recovery was concentrated in the southern portion of the study area, within large agricultural zones, possibly linked to field abandonment due to saline intrusion. Through spatial correlation analysis of change drivers, we identified five zones within the Mexican Mediterranean: Tijuana Coastal Shrubland, Ensenada Coastal Shrubland, Central Coastal Shrubland, Camalú–San Quintín Coastal Rosetophyllous Corridor, and the San Pedro Mártir Boundary Zone, where conservation and restoration efforts should be prioritized through the design and implementation of public policies regulating agricultural expansion at the expense of coastal scrub and other native vegetation types.},
	urldate = {2026-01-21},
	journal = {Environmental Challenges},
	author = {Retamoza-González, Enrique Alfonso and Eaton-González, B. Ricardo and Leyva-Aguilera, Juana Claudia and Reyes-Orta, Marisa and Arias-Rojo, Hector Manuel},
	month = mar,
	year = {2026},
	keywords = {NALCMS, Terrestrial Ecoregions},
	pages = {101399},
}

Land-use and land-cover (LULC) changes are key drivers of vegetation cover loss. Northwestern Mexico hosts the only Mediterranean-climate region in the country, a socio-ecosystem that, due to its distinct socioeconomic and ecological dynamics, simultaneously undergoes processes of anthropization and vegetation recovery, driven by agricultural expansion and land abandonment. In order to identify areas with high recovery and conservation potential within this socio-ecosystem, we evaluated land-cover losses, gains, and rates of change between 2015 and 2020. Using LISA spatial autocorrelation analysis, we identified clusters of anthropization and vegetation recovery, as well as priority areas for conservation actions. Overall, LULC change within the Mexican Mediterranean socio-ecosystem reached 4 %, with coastal shrub being the land-cover type that experienced the greatest loss (64,443 ha), primarily converted to agricultural land, which expanded by 66,203 ha. Anthropization and recovery were the dominant processes in this region. High anthropization clusters were concentrated in mountainous regions and peri-urban areas along the coastal belt, likely associated with agricultural and livestock expansion, whereas recovery was concentrated in the southern portion of the study area, within large agricultural zones, possibly linked to field abandonment due to saline intrusion. Through spatial correlation analysis of change drivers, we identified five zones within the Mexican Mediterranean: Tijuana Coastal Shrubland, Ensenada Coastal Shrubland, Central Coastal Shrubland, Camalú–San Quintín Coastal Rosetophyllous Corridor, and the San Pedro Mártir Boundary Zone, where conservation and restoration efforts should be prioritized through the design and implementation of public policies regulating agricultural expansion at the expense of coastal scrub and other native vegetation types.

@article{fox_impact_2026,
	title = {Impact of imidacloprid-based chemical control for hemlock woolly adelgid ({Adelges} tsugae) on the eastern red-backed salamander ({Plethodon} cinereus)},
	volume = {56},
	issn = {0045-5067},
	url = {https://cdnsciencepub.com/doi/10.1139/cjfr-2025-0281},
	doi = {10.1139/cjfr-2025-0281},
	abstract = {The hemlock woolly adelgid (HWA; Adelges tsugae) is an invasive insect causing widespread mortality of eastern hemlock (Tsuga canadensis) across eastern North America, altering forest structure and associated ecosystems. The insecticide imidacloprid is used for HWA control, but its persistence and potential for soil and water contamination raises concern for fossorial species. We used the eastern red-backed salamander (RBS; Plethodon cinereus) as an indicator species to assess how HWA infestation and imidacloprid treatment influence hemlock stands in southwestern Nova Scotia. We conducted line transect surveys across two HWA-infested sites—each containing four treated and four untreated 1 ha stands—and one uninfested control site with four mature hemlock stands. We applied a multi-model Akaike’s information criterion corrected for small sample sizes framework to test the effects of treatment, infestation, and environmental covariates on RBS abundance, body condition, and abundance within a zone of potential residue exposure. Treatment and infestation were the only predictors of abundance: treatment increased abundance, whereas infestation reduced it. Canopy openness, soil pH, and soil moisture did not differ significantly among stands, and none were found to be predictors of body condition or abundance within the zone of potential exposure. These results reinforce the value of integrating chemical control with long-term monitoring while biological control strategies develop.},
	urldate = {2026-05-27},
	journal = {Canadian Journal of Forest Research},
	author = {Fox, David J. and Forbes, Graham and Edge, Christopher B.},
	month = jan,
	year = {2026},
	note = {Publisher: NRC Research Press},
	keywords = {Political Boundaries},
	pages = {1--11},
}

The hemlock woolly adelgid (HWA; Adelges tsugae) is an invasive insect causing widespread mortality of eastern hemlock (Tsuga canadensis) across eastern North America, altering forest structure and associated ecosystems. The insecticide imidacloprid is used for HWA control, but its persistence and potential for soil and water contamination raises concern for fossorial species. We used the eastern red-backed salamander (RBS; Plethodon cinereus) as an indicator species to assess how HWA infestation and imidacloprid treatment influence hemlock stands in southwestern Nova Scotia. We conducted line transect surveys across two HWA-infested sites—each containing four treated and four untreated 1 ha stands—and one uninfested control site with four mature hemlock stands. We applied a multi-model Akaike’s information criterion corrected for small sample sizes framework to test the effects of treatment, infestation, and environmental covariates on RBS abundance, body condition, and abundance within a zone of potential residue exposure. Treatment and infestation were the only predictors of abundance: treatment increased abundance, whereas infestation reduced it. Canopy openness, soil pH, and soil moisture did not differ significantly among stands, and none were found to be predictors of body condition or abundance within the zone of potential exposure. These results reinforce the value of integrating chemical control with long-term monitoring while biological control strategies develop.

@incollection{hagy_important_2026,
	title = {Important {Geographies} for {Migrating} and {Wintering} {Waterfowl}},
	abstract = {This chapter identifies and describes the most important geographic regions for migrating and wintering waterfowl across North America. Although breeding habitats have historically been the focus of waterfowl conservation, this chapter emphasizes that the non-breeding period plays a critical role in shaping population dynamics. The authors use expert judgment, survey data, and conservation planning frameworks to designate regions that support large numbers of waterfowl or provide essential habitat functions. Organized primarily by flyway, these regions are described in terms of their physiography, climate, habitat resources, species assemblages, and conservation concerns. Particular attention is given to habitat loss, hydrological alteration, development pressure, and climate change, all of which pose ongoing threats to waterfowl populations. While limitations in data are acknowledged, this chapter represents one of the most comprehensive reviews of non-breeding waterfowl geographies to date and underscores the need for coordinated, annual cycle conservation strategies to sustain healthy waterfowl populations across the continent.},
	booktitle = {Migrating and {Wintering} {Waterfowl}},
	publisher = {CRC Press},
	author = {Hagy, Heath M. and Brasher, Michael G. and Fleskes, Joseph P. and Straub, Jacob N. and VonBank, Jay A. and Lafón-Terrazas, Alberto and Gonzalez, Eduardo Carrera},
	year = {2026},
	note = {Num Pages: 82},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
}

This chapter identifies and describes the most important geographic regions for migrating and wintering waterfowl across North America. Although breeding habitats have historically been the focus of waterfowl conservation, this chapter emphasizes that the non-breeding period plays a critical role in shaping population dynamics. The authors use expert judgment, survey data, and conservation planning frameworks to designate regions that support large numbers of waterfowl or provide essential habitat functions. Organized primarily by flyway, these regions are described in terms of their physiography, climate, habitat resources, species assemblages, and conservation concerns. Particular attention is given to habitat loss, hydrological alteration, development pressure, and climate change, all of which pose ongoing threats to waterfowl populations. While limitations in data are acknowledged, this chapter represents one of the most comprehensive reviews of non-breeding waterfowl geographies to date and underscores the need for coordinated, annual cycle conservation strategies to sustain healthy waterfowl populations across the continent.

@article{palmquist_james_2026,
	title = {{JAMES} {BUTTLE} {REVIEW}: {A} {Synthesis} of {Riparian} {Plant} {Water} {Use} {Over} {Two} {Decades} in {North} {American} {Drylands}},
	volume = {40},
	copyright = {© 2026 The Author(s). Hydrological Processes published by John Wiley \& Sons Ltd. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.},
	issn = {1099-1085},
	shorttitle = {{JAMES} {BUTTLE} {REVIEW}},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/hyp.70408},
	doi = {10.1002/hyp.70408},
	abstract = {Assessing riparian ecosystem water use, particularly transpiration from vegetation and evaporation from soils (‘plant water use’, hereafter), is key to developing sound water management approaches. In western North America, a multidecadal drought is reducing water availability and increasing the use of detailed water budgets. Questions related to both removal of vegetation for water salvage and budgeting water to maintain valuable riparian areas have led to a wealth of studies on riparian plant water use across dryland river systems in North America. Towards evaluating broad patterns in riparian plant water use, we synthesise results from over two decades of research, with the goal of informing water management policies and planning. This study asks: (1) Do some riparian plant communities exhibit lower plant water use than others? (2) Do riparian plant communities have higher water use under hotter climates? (3) Can statistical models based on existing data, plant communities and climate data be used to predict water use for unmeasured locations? Using hierarchical Bayesian models to synthesise data on annual and daily-scale plant water use, we show that marshes, cottonwood-willow stands and tamarisk not impacted by biocontrol use larger amounts of water at the annual scale than other vegetation communities. All plant communities have higher annual water use in hotter climates, which is likely related to a longer growing season and higher evaporative demand. Statistical models based on existing water-use data, plant communities and climate provide bounds on plant water use that can be applied to unmeasured locations and used to evaluate the effects of plant community change on water use. This synthesis produces the most complete summary of riparian plant water use in North American drylands to date and provides water use predictions across different climate and community scenarios that can be used for current and future conditions.},
	language = {en},
	number = {2},
	urldate = {2026-05-28},
	journal = {Hydrological Processes},
	author = {Palmquist, Emily C. and Nagler, Pamela and Ogle, Kiona and DiMartini, Claudia and Kennedy, Jeffrey R. and Sankey, Joel B.},
	year = {2026},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/hyp.70408},
	keywords = {Lakes \& Rivers},
	pages = {e70408},
}

Assessing riparian ecosystem water use, particularly transpiration from vegetation and evaporation from soils (‘plant water use’, hereafter), is key to developing sound water management approaches. In western North America, a multidecadal drought is reducing water availability and increasing the use of detailed water budgets. Questions related to both removal of vegetation for water salvage and budgeting water to maintain valuable riparian areas have led to a wealth of studies on riparian plant water use across dryland river systems in North America. Towards evaluating broad patterns in riparian plant water use, we synthesise results from over two decades of research, with the goal of informing water management policies and planning. This study asks: (1) Do some riparian plant communities exhibit lower plant water use than others? (2) Do riparian plant communities have higher water use under hotter climates? (3) Can statistical models based on existing data, plant communities and climate data be used to predict water use for unmeasured locations? Using hierarchical Bayesian models to synthesise data on annual and daily-scale plant water use, we show that marshes, cottonwood-willow stands and tamarisk not impacted by biocontrol use larger amounts of water at the annual scale than other vegetation communities. All plant communities have higher annual water use in hotter climates, which is likely related to a longer growing season and higher evaporative demand. Statistical models based on existing water-use data, plant communities and climate provide bounds on plant water use that can be applied to unmeasured locations and used to evaluate the effects of plant community change on water use. This synthesis produces the most complete summary of riparian plant water use in North American drylands to date and provides water use predictions across different climate and community scenarios that can be used for current and future conditions.

@article{mosso_letting_2026,
	title = {Letting {People} in: {Redefining} {Collaboration} in {Wildland}–{Urban} {Interface} {Governance}},
	volume = {n/a},
	copyright = {© 2026 The Author(s). Environmental Policy and Governance published by ERP Environment and John Wiley \& Sons Ltd.},
	issn = {1756-9338},
	shorttitle = {Letting {People} in},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/eet.70093},
	doi = {10.1002/eet.70093},
	abstract = {Intensifying wildfire regimes and expanding human settlements into wilderness areas have heightened concerns about the wildland–urban interface (WUI) due to the associated increase in fire risk. However, the WUI presents broader social-ecological challenges that go beyond wildfire risk and remain understudied. We assessed two WUI governance systems to identify challenges and opportunities for implementing adaptive governance and facilitating transdisciplinary approaches to WUI planning and management. Our approach considers WUI areas as complex social-ecological systems and the challenges of WUI planning and management as a wicked problem. Specifically, we focus on collaboration and participatory processes within WUI governance, recognizing their potential to integrate broader perspectives and facilitate the co-production of knowledge that characterizes transdisciplinary approaches. Results from policy analysis and semi-structured interviews suggest that WUI governance systems in Colorado (US) and Neuquén (Argentina) present a mix of opportunities and challenges for advancing adaptive governance and facilitating transdisciplinary approaches to WUI management. Reflexive policies (flexible and adaptable) based on minimum standards and legal sunsets (periods for policy revision and adaptation) emerged as adaptive governance enablers in both systems. However, ambiguity in the definition of social-ecological boundaries and the way in which participatory processes are currently implemented represent important challenges to adaptive governance and transdisciplinary approaches to WUI planning and management. We suggest that, to advance a more comprehensive management of WUI areas, WUI governance systems (including actors, legal frameworks, processes, etc.) should emphasize collaboration and participatory processes, facilitating active forms of community participation and the co-development of WUI management objectives.},
	language = {en},
	number = {n/a},
	urldate = {2026-05-27},
	journal = {Environmental Policy and Governance},
	author = {Mosso, Clara and Fried, Harrison and Courtney, Karissa and Salerno, Jonathan and Kampf, Stephanie and Farah, Andrea Baudoin},
	month = may,
	year = {2026},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/eet.70093},
}

Intensifying wildfire regimes and expanding human settlements into wilderness areas have heightened concerns about the wildland–urban interface (WUI) due to the associated increase in fire risk. However, the WUI presents broader social-ecological challenges that go beyond wildfire risk and remain understudied. We assessed two WUI governance systems to identify challenges and opportunities for implementing adaptive governance and facilitating transdisciplinary approaches to WUI planning and management. Our approach considers WUI areas as complex social-ecological systems and the challenges of WUI planning and management as a wicked problem. Specifically, we focus on collaboration and participatory processes within WUI governance, recognizing their potential to integrate broader perspectives and facilitate the co-production of knowledge that characterizes transdisciplinary approaches. Results from policy analysis and semi-structured interviews suggest that WUI governance systems in Colorado (US) and Neuquén (Argentina) present a mix of opportunities and challenges for advancing adaptive governance and facilitating transdisciplinary approaches to WUI management. Reflexive policies (flexible and adaptable) based on minimum standards and legal sunsets (periods for policy revision and adaptation) emerged as adaptive governance enablers in both systems. However, ambiguity in the definition of social-ecological boundaries and the way in which participatory processes are currently implemented represent important challenges to adaptive governance and transdisciplinary approaches to WUI planning and management. We suggest that, to advance a more comprehensive management of WUI areas, WUI governance systems (including actors, legal frameworks, processes, etc.) should emphasize collaboration and participatory processes, facilitating active forms of community participation and the co-development of WUI management objectives.

@article{ayala-borda_life_2026,
	title = {Life on the {Edge}: {Ecosystem} {Features} of {Lakes} {Across} a {Mountain}–{Prairie} {Elevation} {Gradient} in {Western} {Canada}},
	volume = {19},
	copyright = {© 2026 The Author(s). Ecohydrology published by John Wiley \& Sons Ltd.},
	issn = {1936-0592},
	shorttitle = {Life on the {Edge}},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/eco.70148},
	doi = {10.1002/eco.70148},
	abstract = {Ecological transition zones such as mountain elevation gradients can influence the function and productivity of lakes through changes in climatic characteristics and catchment composition (i.e., land use/land cover). However, surveys of limnological features along such ecological transition zones show variable patterns, making it difficult to extrapolate past results to regions such as the eastern slopes of the Canadian Rocky Mountains. To test the effect of elevation and gradients of environmental variability across such an ecological transition zone, we sampled 11 lakes spanning a 600 m elevation gradient between the prairies and Montane Cordillera of southwest Alberta. We analysed the catchment composition, water chemistry, lake metabolic rates (based on oxygen isotopic analysis), dissolved organic matter (DOM) composition, and zooplankton community composition and diet based on fatty acid analysis. Changes in catchment composition and water temperature along the elevation gradient were not clearly linked to DOM content or composition. Most lakes were autotrophic in summer. ERrates of gross primary production (GPP) and ecosystem respiration (ER) shifted modestly when scaled with elevation, and increased with DOM content and water temperature. Net ecosystem production (NEP = GPP − ER) decreased slightly at higher elevation and peaked at intermediate DOM levels. Zooplankton polyunsaturated fatty acid content was also unrelated to elevation but linked to lake trophic state. Overall, climatic and landscape shifts with elevation transmit inconsistent effects to the limnology of these regional lakes, possibly due to the region's overall low precipitation regime and lakes' weak hydrological connectivity with surrounding terrestrial habitats.},
	language = {en},
	number = {1},
	urldate = {2026-05-21},
	journal = {Ecohydrology},
	author = {Ayala-Borda, Paola and Lapierre, Jean-François and Rautio, Milla and Johnston, Sarah Ellen and Bogard, Matthew J.},
	year = {2026},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/eco.70148},
	keywords = {NALCMS},
	pages = {e70148},
}

Ecological transition zones such as mountain elevation gradients can influence the function and productivity of lakes through changes in climatic characteristics and catchment composition (i.e., land use/land cover). However, surveys of limnological features along such ecological transition zones show variable patterns, making it difficult to extrapolate past results to regions such as the eastern slopes of the Canadian Rocky Mountains. To test the effect of elevation and gradients of environmental variability across such an ecological transition zone, we sampled 11 lakes spanning a 600 m elevation gradient between the prairies and Montane Cordillera of southwest Alberta. We analysed the catchment composition, water chemistry, lake metabolic rates (based on oxygen isotopic analysis), dissolved organic matter (DOM) composition, and zooplankton community composition and diet based on fatty acid analysis. Changes in catchment composition and water temperature along the elevation gradient were not clearly linked to DOM content or composition. Most lakes were autotrophic in summer. ERrates of gross primary production (GPP) and ecosystem respiration (ER) shifted modestly when scaled with elevation, and increased with DOM content and water temperature. Net ecosystem production (NEP = GPP − ER) decreased slightly at higher elevation and peaked at intermediate DOM levels. Zooplankton polyunsaturated fatty acid content was also unrelated to elevation but linked to lake trophic state. Overall, climatic and landscape shifts with elevation transmit inconsistent effects to the limnology of these regional lakes, possibly due to the region's overall low precipitation regime and lakes' weak hydrological connectivity with surrounding terrestrial habitats.

@article{gupta_machine_2026,
	title = {Machine {Learning}-{Based} {Reconstructions} of {Historical} {Daily} and {Monthly} {Runoff} for the {Laurentian} {Great} {Lakes}},
	volume = {13},
	copyright = {2026 The Author(s)},
	issn = {2052-4463},
	url = {https://www.nature.com/articles/s41597-026-07000-0},
	doi = {10.1038/s41597-026-07000-0},
	abstract = {High-quality regional streamflow datasets are necessary to support local water resources planning and management in the Great Lakes basin. However, the region’s observed streamflow records are limited by the availability of surface water gauges, which go in and out of service over time. In this paper, we present a continuous reconstruction of daily streamflow from 1951–2013 at 656 gauged locations throughout the Great Lakes basin. This dataset is created using a novel regional Long Short-Term Memory (LSTM) model that integrates local climate data, physical catchment characteristics, and runoff observations from nearby gauged sites. We also use this model to estimate monthly runoff into Lakes Superior, Michigan-Huron, St. Clair, Erie, and Ontario. The daily reconstruction product will equip water managers with information to support local water resources analyses, while the monthly runoff product can help improve historical water balance estimation across the Great Lakes and provide critical context for lake level shifts under a changing climate.},
	language = {en},
	number = {1},
	urldate = {2026-05-27},
	journal = {Scientific Data},
	author = {Gupta, Rohini S. and Wi, Sungwook and Steinschneider, Scott},
	month = mar,
	year = {2026},
	note = {Publisher: Nature Publishing Group},
	keywords = {NALCMS},
	pages = {624},
}

High-quality regional streamflow datasets are necessary to support local water resources planning and management in the Great Lakes basin. However, the region’s observed streamflow records are limited by the availability of surface water gauges, which go in and out of service over time. In this paper, we present a continuous reconstruction of daily streamflow from 1951–2013 at 656 gauged locations throughout the Great Lakes basin. This dataset is created using a novel regional Long Short-Term Memory (LSTM) model that integrates local climate data, physical catchment characteristics, and runoff observations from nearby gauged sites. We also use this model to estimate monthly runoff into Lakes Superior, Michigan-Huron, St. Clair, Erie, and Ontario. The daily reconstruction product will equip water managers with information to support local water resources analyses, while the monthly runoff product can help improve historical water balance estimation across the Great Lakes and provide critical context for lake level shifts under a changing climate.

@misc{odonohue_mapscapingcom_2026,
	title = {Mapscaping.com},
	url = {https://mapscaping.com/?s=Commission+for+Environmental+Cooperation},
	language = {en-US},
	urldate = {2026-04-14},
	author = {O'Donohue, Daniel},
	year = {2026},
	keywords = {Airports, Blue Carbon, Landfills, Major Roads, PRTR, Truck Emissions},
}

@article{stanley_merging_2026,
	title = {Merging rigor and relevance in grazingland research: a comprehensive social-ecological monitoring approach},
	volume = {21},
	issn = {1750-0680},
	shorttitle = {Merging rigor and relevance in grazingland research},
	url = {https://doi.org/10.1186/s13021-026-00431-7},
	doi = {10.1186/s13021-026-00431-7},
	abstract = {Despite decades of study, current research on grazing management’s impacts on ecosystem health and its socioeconomic drivers remains too limited in scope and scale to enable adaptive, evidence-based decision making by producers. There is a pressing need for interdisciplinary research that collects ecosystem data at broader spatial and temporal scales while incorporating working farms and ranches. Such efforts are critical for informing grazing decisions and understanding grazinglands’ potential to deliver ecosystem services, including climate mitigation, water cycling, resilience, and rural livelihoods.},
	language = {en},
	number = {1},
	urldate = {2026-05-29},
	journal = {Carbon Balance and Management},
	author = {Stanley, Paige L. and Kuhl, Alexandria S. and Maciel, Isabella C.F. and Cotrufo, M. Francesca and Goodwin, Douglas J. and Hodbod, Jennifer and Anderson, Martha C. and Scasta, John D. and Peirce, Erika S. and Branecky, Micaela and Brokus, Sarah and Clement, Robert J. and DeLay, Nathan D. and Derner, Justin D. and MathisonSlee, Morgan and Mitchell, Rebecca and Patterson, Erica L. and Zhang, Yao and Asher, Jeremiah and Gao, Feng and Manning, Dale T. and O’Neil, Glenn and Pallickara, Sangmi L. and Paustian, Keith and Raven, Matt R. and Sacramento, Joao P. and Wu, Yining and Likins, Jenna M. and Bista, Dabit and Colella, Florencia and Congio, Guilhermo F.S. and Dong, Zekuan and Gordon, Ethan and Gosnell, Hannah and Guber, Andrey K. and Kearney, Sean P. and Lupi, Frank and Matin, Abdul and Nimlos, Nicole M. and Vivas, Jonathan and Gergeni, Timm M. and Smith, Ada P. and Rowntree, Jason E.},
	month = apr,
	year = {2026},
	keywords = {Terrestrial Ecoregions},
	pages = {67},
}

Despite decades of study, current research on grazing management’s impacts on ecosystem health and its socioeconomic drivers remains too limited in scope and scale to enable adaptive, evidence-based decision making by producers. There is a pressing need for interdisciplinary research that collects ecosystem data at broader spatial and temporal scales while incorporating working farms and ranches. Such efforts are critical for informing grazing decisions and understanding grazinglands’ potential to deliver ecosystem services, including climate mitigation, water cycling, resilience, and rural livelihoods.

@article{bonney_monitoring_2026,
	title = {Monitoring snow cover dynamics at 30-m resolution in higher latitude regions using {Harmonized} {Landsat} {Sentinel}-2},
	volume = {233},
	issn = {0924-2716},
	url = {https://www.sciencedirect.com/science/article/pii/S0924271626000328},
	doi = {10.1016/j.isprsjprs.2026.01.032},
	abstract = {Snow is an essential climate variable that is important for hydrology, climate, soil temperature and permafrost, vegetation, animal habitat, and socioeconomics. Wide-area snow cover dynamics (SCD), including the start and end of snow cover, are generally monitored by satellites with coarse spatial resolutions (250–1000 m) and high temporal (daily) resolutions. Higher spatial resolution (HSR) monitoring (10–30 m) has been limited to small areas because of computational constraints and infrequent cloud-free observations. Here, we develop a new method to map wide-area HSR SCD (snow start date, end date, length, periods, status) by leveraging the recently released Harmonized Landsat Sentinel-2 (HLS) v2.0, which has a 2–3-day revisit at 30-m resolution. The method is built around SpatialTemporal Asset Catalogs (STACs) and open-source Python tools. We utilize tiled datacubes, snow classification, and a model involving implausibility checking, cleaning, and finding peaks in data with gaps due to orbit frequencies and clouds. We demonstrate SCD mapping and validation across Canada’s Hudson Bay Lowlands (HBL) and an area in northern Alaska for each snow-year from 2018 to 2019 to 2023–2024 and multi-year composites (2018–2024). We also provide timing uncertainties and a quality metric for all pixels. Performance is best for snow end date, having strong relationships with both visually interpreted SCD from primarily very high-resolution imagery and measured local-scale snow depth. The combination of lower cloud cover and lower solar zenith angles during melt periods leads to lower uncertainties for snow end date compared to start date and length. Performance is better for all metrics at higher latitudes (e.g., northern Alaska), where satellite observations are more frequent due to increased orbit overlap. Although we have only completed validation for the HBL, Canada-wide products using this methodology are available publicly as STACs on the CCMEO Data Cube and will continue to be updated. Addition validation across Canada and methodology improvements are ongoing.},
	urldate = {2026-05-21},
	journal = {ISPRS Journal of Photogrammetry and Remote Sensing},
	author = {Bonney, Mitchell T. and Zhang, Yu},
	month = mar,
	year = {2026},
	keywords = {NALCMS},
	pages = {360--382},
}

Snow is an essential climate variable that is important for hydrology, climate, soil temperature and permafrost, vegetation, animal habitat, and socioeconomics. Wide-area snow cover dynamics (SCD), including the start and end of snow cover, are generally monitored by satellites with coarse spatial resolutions (250–1000 m) and high temporal (daily) resolutions. Higher spatial resolution (HSR) monitoring (10–30 m) has been limited to small areas because of computational constraints and infrequent cloud-free observations. Here, we develop a new method to map wide-area HSR SCD (snow start date, end date, length, periods, status) by leveraging the recently released Harmonized Landsat Sentinel-2 (HLS) v2.0, which has a 2–3-day revisit at 30-m resolution. The method is built around SpatialTemporal Asset Catalogs (STACs) and open-source Python tools. We utilize tiled datacubes, snow classification, and a model involving implausibility checking, cleaning, and finding peaks in data with gaps due to orbit frequencies and clouds. We demonstrate SCD mapping and validation across Canada’s Hudson Bay Lowlands (HBL) and an area in northern Alaska for each snow-year from 2018 to 2019 to 2023–2024 and multi-year composites (2018–2024). We also provide timing uncertainties and a quality metric for all pixels. Performance is best for snow end date, having strong relationships with both visually interpreted SCD from primarily very high-resolution imagery and measured local-scale snow depth. The combination of lower cloud cover and lower solar zenith angles during melt periods leads to lower uncertainties for snow end date compared to start date and length. Performance is better for all metrics at higher latitudes (e.g., northern Alaska), where satellite observations are more frequent due to increased orbit overlap. Although we have only completed validation for the HBL, Canada-wide products using this methodology are available publicly as STACs on the CCMEO Data Cube and will continue to be updated. Addition validation across Canada and methodology improvements are ongoing.

@article{taghipourjavi_demand_2026,
	title = {On demand machine learning-driven surface freeze-thaw retrieval across {Canadian} agricultural regions using {Sentinel}-1 {SAR} data},
	volume = {6},
	issn = {2673-6187},
	url = {https://www.frontiersin.org/journals/remote-sensing/articles/10.3389/frsen.2025.1728399/full},
	doi = {10.3389/frsen.2025.1728399},
	abstract = {This study explores the prediction of freeze-thaw (FT) states across agricultural fields in four Canadian provinces-Alberta, Manitoba, Saskatchewan, and Québec-using Random Forest classification and regression models. Soil temperature data at a 5 cm depth were gathered from 174 agricultural weather stations from 2016 to 2023. Sentinel-1 SAR VH radar backscatter indicators were processed using Google Earth Engine (GEE). Two modeling approaches were evaluated: a classification model trained on in situ data, where soil states were rigidly classified as either frozen or thawed, and a regression model trained against in situ soil freezing probabilities. Additionally, other site-specific ancillary variables such as latitude, altitude, crop type, and soil type were tested as potential predictors. The regression model using the Exponential Freeze-Thaw Algorithm (EFTA) derived from VH radar backscatter (VHEFTA) demonstrated strong discrimination between frozen and thawed states, and emerged as the most influential factor, accounting for over 90\% of the model’s predictive ability. Models using VHEFTA alone achieved up to 81.4\% accuracy for classifying FT state, with only a slight improvement to 82.1\% when combined with other predictors. Spatial and temporal validation showed stable accuracy (0.79–0.83) and F1-scores (0.75–0.88) across regions and years. Evaluation of model sensitivity to seasonal and temperature variability revealed that although uncertainties were not fully eliminated during transitional periods for both binary and probability-based FT models, binary-based models consistently showed lower error rates and stronger performance. The final FT model was implemented within an interactive web-based tool that generates on-demand FT maps for user-supplied regions of interest across Canadian agricultural and open-land areas.},
	language = {English},
	urldate = {2026-05-29},
	journal = {Frontiers in Remote Sensing},
	author = {Taghipourjavi, Shahabeddin and Kinnard, Christophe and Roy, Alexandre},
	month = jan,
	year = {2026},
	note = {Publisher: Frontiers},
	keywords = {NALCMS},
}

This study explores the prediction of freeze-thaw (FT) states across agricultural fields in four Canadian provinces-Alberta, Manitoba, Saskatchewan, and Québec-using Random Forest classification and regression models. Soil temperature data at a 5 cm depth were gathered from 174 agricultural weather stations from 2016 to 2023. Sentinel-1 SAR VH radar backscatter indicators were processed using Google Earth Engine (GEE). Two modeling approaches were evaluated: a classification model trained on in situ data, where soil states were rigidly classified as either frozen or thawed, and a regression model trained against in situ soil freezing probabilities. Additionally, other site-specific ancillary variables such as latitude, altitude, crop type, and soil type were tested as potential predictors. The regression model using the Exponential Freeze-Thaw Algorithm (EFTA) derived from VH radar backscatter (VHEFTA) demonstrated strong discrimination between frozen and thawed states, and emerged as the most influential factor, accounting for over 90% of the model’s predictive ability. Models using VHEFTA alone achieved up to 81.4% accuracy for classifying FT state, with only a slight improvement to 82.1% when combined with other predictors. Spatial and temporal validation showed stable accuracy (0.79–0.83) and F1-scores (0.75–0.88) across regions and years. Evaluation of model sensitivity to seasonal and temperature variability revealed that although uncertainties were not fully eliminated during transitional periods for both binary and probability-based FT models, binary-based models consistently showed lower error rates and stronger performance. The final FT model was implemented within an interactive web-based tool that generates on-demand FT maps for user-supplied regions of interest across Canadian agricultural and open-land areas.

@phdthesis{ryan_population_2026,
	address = {Ensenada, Baja California},
	type = {Doctor of {Science}},
	title = {Population dynamics of the {Least} {Tern} ({Sternula} antillarum) in {Northwest} {México} and {California}, {USA}},
	url = {https://cicese.repositorioinstitucional.mx/jspui/handle/1007/4437},
	urldate = {2026-06-01},
	school = {Centro de Investigación Científica y de Educación Superior de Ensenada},
	author = {Ryan, Thomas Patrick},
	month = mar,
	year = {2026},
	note = {Accepted: 2026-03-11T19:25:54Z},
}

@article{gorr_probabilistic_2026,
	title = {Probabilistic prediction of post-fire debris-flow runout and implications for prefire assessments of post-fire hazards},
	volume = {35},
	issn = {1049-8001},
	url = {https://doi.org/10.1071/WF25161},
	doi = {10.1071/WF25161},
	abstract = {Debris-flow runout modeling is a valuable component of the prefire assessment of post-fire hazards. The application and benefits of runout modeling are limited by uncertainty in debris-flow volume as well as model parameters related to flow mobility.In this study, we assess and reduce the uncertainty associated with flow-mobility parameters by calibrating a debris-flow runout model to 12 runoff-generated debris flows in the western United States.For each debris flow, we determined optimal flow-mobility parameters using back analyses and generated a posterior distribution of the parameters using a Bayesian approach. We assessed the relative sensitivity of the model to the flow-mobility parameters, rainfall intensification and fire burn severity when applied to three post-fire debris flows.Yield strength, one of the flow-mobility parameters, exhibits a negative, linear relationship with soil clay content. Modeled area inundated is most sensitive to the flow-mobility parameters, followed by a rainfall intensification factor.Well-constrained flow-mobility parameters will improve post-fire debris-flow runout modeling, though prefire assessments of post-fire hazards could also benefit from accounting for the effects of rainfall intensification.This study improves our ability to simulate debris-flow runout and assess associated hazards.},
	number = {2},
	urldate = {2026-05-27},
	journal = {International Journal of Wildland Fire},
	author = {Gorr, Alexander N. and McGuire, Luke A. and Youberg, Ann M. and Lindsay, Donald N.},
	month = feb,
	year = {2026},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {WF25161},
}

Debris-flow runout modeling is a valuable component of the prefire assessment of post-fire hazards. The application and benefits of runout modeling are limited by uncertainty in debris-flow volume as well as model parameters related to flow mobility.In this study, we assess and reduce the uncertainty associated with flow-mobility parameters by calibrating a debris-flow runout model to 12 runoff-generated debris flows in the western United States.For each debris flow, we determined optimal flow-mobility parameters using back analyses and generated a posterior distribution of the parameters using a Bayesian approach. We assessed the relative sensitivity of the model to the flow-mobility parameters, rainfall intensification and fire burn severity when applied to three post-fire debris flows.Yield strength, one of the flow-mobility parameters, exhibits a negative, linear relationship with soil clay content. Modeled area inundated is most sensitive to the flow-mobility parameters, followed by a rainfall intensification factor.Well-constrained flow-mobility parameters will improve post-fire debris-flow runout modeling, though prefire assessments of post-fire hazards could also benefit from accounting for the effects of rainfall intensification.This study improves our ability to simulate debris-flow runout and assess associated hazards.

@article{remolina-figueroa_relevance_2026,
	title = {Relevance of ecological and phylogenetic structure of hummingbird-plant relationships in the face of global climate change},
	volume = {24},
	issn = {2530-0644},
	url = {https://www.sciencedirect.com/science/article/pii/S2530064426000106},
	doi = {10.1016/j.pecon.2026.02.004},
	abstract = {Mutualistic interactions (e.g., pollination) are essential for maintaining biodiversity and ecosystem functioning, yet they are increasingly threatened by global climate change (GCC). In this study, we use species distribution models and range overlap analyses to assess the potential impacts of future GCC on hummingbird-plant co-occurrence networks across Mexico. To do this, we estimated temporal beta diversity to evaluate changes in community composition over time and tested how phylogenetic diversity (PD) relates to network structure—measured as species richness, number of links, and robustness—across space and time. Overall, we observed that GCC could drive important reductions of distribution areas ({\textgreater}10\%) in more than 50\% of hummingbird and plant species, leading to increased mismatch of their co-distribution patterns and reduced species richness, PD, and plant robustness in hummingbird-plant co-occurrence networks. Within assemblages, hummingbird PD was negatively related to change in hummingbird and plant richness but positively influenced future plant robustness, and plant PD was positively related to niche overlap. Our findings underscore the importance of preserving phylogenetic diversity as a buffer against climate-driven disruptions in species interactions and call for conservation strategies that incorporate multiple dimensions of biodiversity to maintain the integrity of mutualistic networks under GCC.},
	number = {2},
	urldate = {2026-05-29},
	journal = {Perspectives in Ecology and Conservation},
	author = {Remolina-Figueroa, Daniela and Prieto-Torres, David A. and Dáttilo, Wesley and Quijano-Cuervo, Luis G. and Saldaña-Reyes, Lorena I. and Navarro-Sigüenza, Adolfo G. and Arizmendi Arriaga, María del Coro},
	month = apr,
	year = {2026},
	keywords = {Terrestrial Ecoregions},
	pages = {191--198},
}

Mutualistic interactions (e.g., pollination) are essential for maintaining biodiversity and ecosystem functioning, yet they are increasingly threatened by global climate change (GCC). In this study, we use species distribution models and range overlap analyses to assess the potential impacts of future GCC on hummingbird-plant co-occurrence networks across Mexico. To do this, we estimated temporal beta diversity to evaluate changes in community composition over time and tested how phylogenetic diversity (PD) relates to network structure—measured as species richness, number of links, and robustness—across space and time. Overall, we observed that GCC could drive important reductions of distribution areas (\textgreater10%) in more than 50% of hummingbird and plant species, leading to increased mismatch of their co-distribution patterns and reduced species richness, PD, and plant robustness in hummingbird-plant co-occurrence networks. Within assemblages, hummingbird PD was negatively related to change in hummingbird and plant richness but positively influenced future plant robustness, and plant PD was positively related to niche overlap. Our findings underscore the importance of preserving phylogenetic diversity as a buffer against climate-driven disruptions in species interactions and call for conservation strategies that incorporate multiple dimensions of biodiversity to maintain the integrity of mutualistic networks under GCC.

@article{palm_roads_2026,
	title = {Roads, {Soil}, {Snow}, and {Topography} {Influence} {Genetic} {Connectivity}: {A} {Machine} {Learning} {Approach} for a {Peripheral} {American} {Badger} {Population}},
	volume = {16},
	copyright = {© 2026 The Author(s). Ecology and Evolution published by British Ecological Society and John Wiley \& Sons Ltd.},
	issn = {2045-7758},
	shorttitle = {Roads, {Soil}, {Snow}, and {Topography} {Influence} {Genetic} {Connectivity}},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/ece3.73467},
	doi = {10.1002/ece3.73467},
	abstract = {Effective management and conservation of peripheral populations require an understanding of the landscape conditions inhibiting dispersal and spatially explicit predictions of connectivity. Here, we modeled landscape resistance and genetic connectivity for the western population of an American badger subspecies (Taxidea taxus jeffersonii) across 170,000 km2 in southern British Columbia, Canada, using 116 genetic samples genotyped at 14 microsatellite loci. We used gradient boosting machine models in a corridor-based approach to predict genetic distances between pairs of individual badgers as a function of landscape variable data. Spatial genetic autocorrelation tests and our top model predicted that genetic similarities of T. t. jeffersonii were present up to 110 km. Gene diversity was lowest in the Cariboo region in the northwest portion of the study area and highest in the Okanagan region in the southeast. Our analyses suggest that the genetic connectivity of T. t. jeffersonii was impeded by colluvial soil parent material, geographic distance, steep slopes, and major roads, but was facilitated by organic and fluvial soil parent materials, and areas with relatively little snow cover during winter. Our predictive maps of landscape resistance and connectivity can help guide management actions such as habitat protection and underpass placement on major roads to promote genetic connectivity.},
	language = {en},
	number = {4},
	urldate = {2026-05-28},
	journal = {Ecology and Evolution},
	author = {Palm, Eric C. and Landguth, Erin L. and Lamy, Karina and Gorrell, Jamieson C. and Weir, Richard D. and Richardson, Emma L. and Forbes, Krystyn J. and Davis, Helen and Burgar, Joanna M.},
	year = {2026},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/ece3.73467},
	keywords = {NALCMS},
	pages = {e73467},
}

Effective management and conservation of peripheral populations require an understanding of the landscape conditions inhibiting dispersal and spatially explicit predictions of connectivity. Here, we modeled landscape resistance and genetic connectivity for the western population of an American badger subspecies (Taxidea taxus jeffersonii) across 170,000 km2 in southern British Columbia, Canada, using 116 genetic samples genotyped at 14 microsatellite loci. We used gradient boosting machine models in a corridor-based approach to predict genetic distances between pairs of individual badgers as a function of landscape variable data. Spatial genetic autocorrelation tests and our top model predicted that genetic similarities of T. t. jeffersonii were present up to 110 km. Gene diversity was lowest in the Cariboo region in the northwest portion of the study area and highest in the Okanagan region in the southeast. Our analyses suggest that the genetic connectivity of T. t. jeffersonii was impeded by colluvial soil parent material, geographic distance, steep slopes, and major roads, but was facilitated by organic and fluvial soil parent materials, and areas with relatively little snow cover during winter. Our predictive maps of landscape resistance and connectivity can help guide management actions such as habitat protection and underpass placement on major roads to promote genetic connectivity.

@article{newcomb_snow_2026,
	title = {Snow simulations predict future changes in rain-on-snow events across the upper {Gallatin} {River} watershed, a {Greater} {Yellowstone} {Ecosystem} headwater system},
	volume = {64},
	issn = {2214-5818},
	url = {https://www.sciencedirect.com/science/article/pii/S2214581826001515},
	doi = {10.1016/j.ejrh.2026.103253},
	abstract = {Study region
The upper Gallatin River watershed, an alpine headwater system in the Greater Yellowstone Ecosystem, in Wyoming and Montana.
Study focus
As global and regional air temperatures rise, mountain headwaters across the Greater Yellowstone Ecosystem (GYE) are projected to receive more precipitation falling as rain. While the hydrologic effects of this snow-to-rain transition depends on a variety of factors, it can lead to an increased occurrence of rain-on-snow (RoS) events. To investigate these changes, we used high-resolution (30 m) SnowModel simulations of the upper Gallatin River watershed. Simulations were run for 2001–2013 using two scenarios: (1) historical meteorology as control and (2) pseudo-global-warming (PGW) where control air temperature and precipitation conditions were perturbed to represent mean end-of-century conditions under a high-emissions scenario.
New hydrological insights for the region
SnowModel outputs show that changes in PGW precipitation and snow accumulation varied with elevation. Warmer air temperatures at low elevations ({\textless} 2500 m) led to less snow accumulation and less precipitation falling as snow. Colder baseline air temperatures for elevations above 2500 meters (m) resulted in minor reductions in winter snowfall fraction. For PGW simulations, spring (April-June) months experienced higher rainfall, and elevations above 2500 m experienced more RoS events. Snowpacks between 2500–3100 m generated more snowmelt during RoS events, which was reflected in the watershed average. More high-intensity melt events can affect aquatic habitat, water quality, and the accuracy of streamflow forecasts across the region.},
	urldate = {2026-05-27},
	journal = {Journal of Hydrology: Regional Studies},
	author = {Newcomb, Sarah K. and Barnhart, Theodore B. and Heldmyer, Aaron J. and Storb, Meryl B.},
	month = apr,
	year = {2026},
	keywords = {NALCMS},
	pages = {103253},
}

Study region The upper Gallatin River watershed, an alpine headwater system in the Greater Yellowstone Ecosystem, in Wyoming and Montana. Study focus As global and regional air temperatures rise, mountain headwaters across the Greater Yellowstone Ecosystem (GYE) are projected to receive more precipitation falling as rain. While the hydrologic effects of this snow-to-rain transition depends on a variety of factors, it can lead to an increased occurrence of rain-on-snow (RoS) events. To investigate these changes, we used high-resolution (30 m) SnowModel simulations of the upper Gallatin River watershed. Simulations were run for 2001–2013 using two scenarios: (1) historical meteorology as control and (2) pseudo-global-warming (PGW) where control air temperature and precipitation conditions were perturbed to represent mean end-of-century conditions under a high-emissions scenario. New hydrological insights for the region SnowModel outputs show that changes in PGW precipitation and snow accumulation varied with elevation. Warmer air temperatures at low elevations (\textless 2500 m) led to less snow accumulation and less precipitation falling as snow. Colder baseline air temperatures for elevations above 2500 meters (m) resulted in minor reductions in winter snowfall fraction. For PGW simulations, spring (April-June) months experienced higher rainfall, and elevations above 2500 m experienced more RoS events. Snowpacks between 2500–3100 m generated more snowmelt during RoS events, which was reflected in the watershed average. More high-intensity melt events can affect aquatic habitat, water quality, and the accuracy of streamflow forecasts across the region.

@article{cebulski_snowfall_2026,
	title = {Snowfall {Interception} and {Ablation} in {Needleleaf} {Canopies}: {Observations} and {Model} {Development}},
	shorttitle = {Snowfall {Interception} and {Ablation} in {Needleleaf} {Canopies}},
	url = {https://hdl.handle.net/10388/18176},
	abstract = {Snow falls on forests covering 23\% of the global landmass. Here, interception by forest canopies plays a crucial role in the terrestrial water cycle and land-atmosphere energy exchanges. Global changes in climate and vegetation cover have the potential to alter how snowfall is intercepted and subsequently partitioned between sublimation to the atmosphere or unloading, melt, and drip to the ground; however, the understanding required to investigate potential changes to water resources and energy exchanges is currently limited. In cold continental climates, up to half of annual snowfall may be lost to the atmosphere through sublimation of snow intercepted in needleleaf canopies, and in warmer climates, higher melt rates cause a large fraction of intercepted snow to reach the ground as liquid. Snow interception processes are strongly dependent on both meteorology and canopy density, leading to differing process emergence in existing theories developed in distinctive climates, seasons, and forest types. Consequently, simulations of the mass and energy balance of intercepted snow have demonstrated variable accuracy across different climates and canopy structures, introducing uncertainty into predictions by hydrological and land-surface models. Moreover, limited observations of snowfall interception and ablation in needleleaf forests have limited evaluation of existing theories across a wide range of climatic conditions and forest types, thereby hindering diagnosis of process uncertainty in existing models. The aim of this research was to evaluate the suitability of existing theories of snow interception and intercepted snow ablation in needleleaf canopies and link improved process understanding to model development and validation across a broad range of canopy structures and meteorological conditions. Expanding measurements of snow interception and canopy snow ablation processes across broader range of environmental conditions, while also better isolating individual processes, could help clarify the applicability of existing theories and guide improvements to enhance model accuracy across diverse sites. New observations of initial snow interception and throughfall, collected across a range of canopy densities and meteorological conditions when ablation processes were minimal, revealed new relationships for predicting initial snow interception and throughfall. Observations of canopy density and sub-canopy throughfall using Uncrewed Aerial Vehicle-borne Light Detection and Ranging (UAV-lidar), snow surveys, and weighed subcanopy snow buckets showed a strong linear relationship between initial interception efficiency (initial snow interception divided by snowfall) and the snow-leaf contact area. This metric accounts for the potential increase in contact area with increasing snowfall trajectory zenith angle, which is defined as the departure in degrees from a vertical plane. As a result, the snow-leaf contact area was found to be highly sensitive to wind speed in sparse canopies, increasing by a factor of 2 with an increase in wind speed from 0 to 1 m s{\textasciicircum}\{-1\}. Contrary to existing theories, no relationships were found between initial interception efficiency and canopy snow load or air temperature. These observations reveal that existing interception efficiency calculations fail in sparse canopies. A new parameterisation was developed that calculates initial snow interception and throughfall as a function of snowfall and snow-leaf contact area, which improved the simulation of throughfall across a range of canopy densities and meteorological conditions. This approach is consistent with several rainfall interception studies that also separate initial rainfall interception, evaporation, and drip processes, and compute interception as a function of canopy cover. However, it extends these existing approaches from those suited to rainfall, by accounting for changes in the snow-leaf contact area associated with the snowfall trajectory zenith angle; a necessary addition given the lower terminal fall velocity of snowflakes compared to raindrops. An evaluation of existing theories representing ablation of snow intercepted in needleleaf canopies was conducted using observations collected by a weighed hanging tree, weighed subcanopy snow buckets, tipping bucket rain gauges, weighing precipitation gauges, and eddy correlations stations, collected across a wide range of meteorological conditions, and with more direct measurements of unloading and drip than those used in previous studies. A new model that incorporates intercepted snow unloading as a function of canopy snow load, wind shear stress, and melt—coupled with a new canopy snow energy and mass balance to calculate sublimation and melt—improved simulation of intercepted snow ablation relative to previous approaches. While existing models have identified canopy snow load, wind, and melt as key predictors of unloading, they performed less well due to incomplete representation of both cold/dry-snow and melt-driven unloading processes. This resulted either from not including the wind-driven unloading process or from approximating intercepted snowmelt and associated unloading as a function of air- or ice-bulb temperature. The new relationships provide a stronger physical basis by representing wind-driven unloading through shear stress and melt-induced unloading as a function of energy balance-based intercepted snowmelt. Moreover, the ratio of snow unloading to meltwater generation during intercepted snowmelt was found to be a function of snow load, in contrast to previous work that used a constant ratio. These new canopy snow mass and energy parameterisations show potential to improve calculation of the partitioning of snowfall by interception processes in needleleaf forests within hydrological and land-surface models. An uncalibrated validation of the new canopy snow mass and energy balance parameterisation was conducted using observations from four distinctive needleleaf forests characterised by differing tree species, canopy structures, and climatic conditions. At sites where observations of canopy intercepted snow load were available, the new model reduced errors in calculating canopy snow load and the duration of snow interception. Additionally, the new model reduced errors in simulating subcanopy snow water equivalent (SWE) compared to an existing model across all four sites. The largest improvements in prediction were observed at the warm, humid maritime site and were attributed to better representation of intercepted snow melt and the melt-induced unloading process. Improved process representation also enabled clearer process-level diagnosis of the influence of snow interception on snow accumulation in differing environments. At two cold, low-wind, and lower-snowfall sites, roughly half of the annual snowfall was sublimated to the atmosphere from intercepted snow. A cold, wind-exposed site with higher annual snowfall had higher unloading rates, which reduced the relative amount of intercepted snow sublimation. In contrast, at a temperate-maritime site with high snowfall, nearly half of annual snowfall melted within the canopy and, combined with drip from this snowmelt, and melt-induced unloading, partitioned the most snowfall towards the ground of all four sites, despite the high initial interception efficiency. This research reveals variability in snowfall interception and intercepted snow ablation processes across diverse canopy densities and meteorological regimes, and shows that this variability has not been fully represented in existing models. New parameterisations of canopy snow mass and energy balance, addressing these limitations, were introduced to more explicitly represent the full range of snow interception processes. This new model provided more accurate simulations of intercepted snow load and subcanopy SWE across a broad range of climatic conditions and forest types and also improved process diagnosis, though further validation is required across a diverse range of sites.},
	language = {en},
	urldate = {2026-06-01},
	author = {Cebulski, Alex C.},
	year = {2026},
	keywords = {NALCMS},
}

Snow falls on forests covering 23% of the global landmass. Here, interception by forest canopies plays a crucial role in the terrestrial water cycle and land-atmosphere energy exchanges. Global changes in climate and vegetation cover have the potential to alter how snowfall is intercepted and subsequently partitioned between sublimation to the atmosphere or unloading, melt, and drip to the ground; however, the understanding required to investigate potential changes to water resources and energy exchanges is currently limited. In cold continental climates, up to half of annual snowfall may be lost to the atmosphere through sublimation of snow intercepted in needleleaf canopies, and in warmer climates, higher melt rates cause a large fraction of intercepted snow to reach the ground as liquid. Snow interception processes are strongly dependent on both meteorology and canopy density, leading to differing process emergence in existing theories developed in distinctive climates, seasons, and forest types. Consequently, simulations of the mass and energy balance of intercepted snow have demonstrated variable accuracy across different climates and canopy structures, introducing uncertainty into predictions by hydrological and land-surface models. Moreover, limited observations of snowfall interception and ablation in needleleaf forests have limited evaluation of existing theories across a wide range of climatic conditions and forest types, thereby hindering diagnosis of process uncertainty in existing models. The aim of this research was to evaluate the suitability of existing theories of snow interception and intercepted snow ablation in needleleaf canopies and link improved process understanding to model development and validation across a broad range of canopy structures and meteorological conditions. Expanding measurements of snow interception and canopy snow ablation processes across broader range of environmental conditions, while also better isolating individual processes, could help clarify the applicability of existing theories and guide improvements to enhance model accuracy across diverse sites. New observations of initial snow interception and throughfall, collected across a range of canopy densities and meteorological conditions when ablation processes were minimal, revealed new relationships for predicting initial snow interception and throughfall. Observations of canopy density and sub-canopy throughfall using Uncrewed Aerial Vehicle-borne Light Detection and Ranging (UAV-lidar), snow surveys, and weighed subcanopy snow buckets showed a strong linear relationship between initial interception efficiency (initial snow interception divided by snowfall) and the snow-leaf contact area. This metric accounts for the potential increase in contact area with increasing snowfall trajectory zenith angle, which is defined as the departure in degrees from a vertical plane. As a result, the snow-leaf contact area was found to be highly sensitive to wind speed in sparse canopies, increasing by a factor of 2 with an increase in wind speed from 0 to 1 m s\textasciicircum\-1\. Contrary to existing theories, no relationships were found between initial interception efficiency and canopy snow load or air temperature. These observations reveal that existing interception efficiency calculations fail in sparse canopies. A new parameterisation was developed that calculates initial snow interception and throughfall as a function of snowfall and snow-leaf contact area, which improved the simulation of throughfall across a range of canopy densities and meteorological conditions. This approach is consistent with several rainfall interception studies that also separate initial rainfall interception, evaporation, and drip processes, and compute interception as a function of canopy cover. However, it extends these existing approaches from those suited to rainfall, by accounting for changes in the snow-leaf contact area associated with the snowfall trajectory zenith angle; a necessary addition given the lower terminal fall velocity of snowflakes compared to raindrops. An evaluation of existing theories representing ablation of snow intercepted in needleleaf canopies was conducted using observations collected by a weighed hanging tree, weighed subcanopy snow buckets, tipping bucket rain gauges, weighing precipitation gauges, and eddy correlations stations, collected across a wide range of meteorological conditions, and with more direct measurements of unloading and drip than those used in previous studies. A new model that incorporates intercepted snow unloading as a function of canopy snow load, wind shear stress, and melt—coupled with a new canopy snow energy and mass balance to calculate sublimation and melt—improved simulation of intercepted snow ablation relative to previous approaches. While existing models have identified canopy snow load, wind, and melt as key predictors of unloading, they performed less well due to incomplete representation of both cold/dry-snow and melt-driven unloading processes. This resulted either from not including the wind-driven unloading process or from approximating intercepted snowmelt and associated unloading as a function of air- or ice-bulb temperature. The new relationships provide a stronger physical basis by representing wind-driven unloading through shear stress and melt-induced unloading as a function of energy balance-based intercepted snowmelt. Moreover, the ratio of snow unloading to meltwater generation during intercepted snowmelt was found to be a function of snow load, in contrast to previous work that used a constant ratio. These new canopy snow mass and energy parameterisations show potential to improve calculation of the partitioning of snowfall by interception processes in needleleaf forests within hydrological and land-surface models. An uncalibrated validation of the new canopy snow mass and energy balance parameterisation was conducted using observations from four distinctive needleleaf forests characterised by differing tree species, canopy structures, and climatic conditions. At sites where observations of canopy intercepted snow load were available, the new model reduced errors in calculating canopy snow load and the duration of snow interception. Additionally, the new model reduced errors in simulating subcanopy snow water equivalent (SWE) compared to an existing model across all four sites. The largest improvements in prediction were observed at the warm, humid maritime site and were attributed to better representation of intercepted snow melt and the melt-induced unloading process. Improved process representation also enabled clearer process-level diagnosis of the influence of snow interception on snow accumulation in differing environments. At two cold, low-wind, and lower-snowfall sites, roughly half of the annual snowfall was sublimated to the atmosphere from intercepted snow. A cold, wind-exposed site with higher annual snowfall had higher unloading rates, which reduced the relative amount of intercepted snow sublimation. In contrast, at a temperate-maritime site with high snowfall, nearly half of annual snowfall melted within the canopy and, combined with drip from this snowmelt, and melt-induced unloading, partitioned the most snowfall towards the ground of all four sites, despite the high initial interception efficiency. This research reveals variability in snowfall interception and intercepted snow ablation processes across diverse canopy densities and meteorological regimes, and shows that this variability has not been fully represented in existing models. New parameterisations of canopy snow mass and energy balance, addressing these limitations, were introduced to more explicitly represent the full range of snow interception processes. This new model provided more accurate simulations of intercepted snow load and subcanopy SWE across a broad range of climatic conditions and forest types and also improved process diagnosis, though further validation is required across a diverse range of sites.

@article{bernhardt_space-use_2026,
	title = {Space-use and nest selection by southern flying squirrels ({Glaucomys} volans) at the edge of their geographic range},
	volume = {104},
	issn = {0008-4301},
	url = {https://cdnsciencepub.com/doi/10.1139/cjz-2025-0121},
	doi = {10.1139/cjz-2025-0121},
	abstract = {Species distribution patterns at range edges can reveal effects of landscape and climate changes which can drive population expansions or contractions. Southern flying squirrel (Glaucomys volans Linnaeus, 1758) populations are common in eastern United States and southeastern Canada, and extend westwardly into the Great Plains. Space-use patterns within their range interior are well documented, though it is unclear if patterns are similar along western range edges. We tracked 10 southern flying squirrels in southeastern Kansas, USA to estimate home-range sizes and patterns in nest-site and tree selection. Forest structure and composition at western range edges differ compared to forest habitat at range interiors, and we predicted differences in home-range sizes and nest-site and tree selection patterns in Kansas compared to previous research. Mean home-range size was 1.55 ha (95\% minimum convex polygon) and 5.44 ha (95\% kernel density), similar to some populations in the interior of their range. Greater tree genera richness and average tree diameter (diameter at breast height (DBH)) increased probability of nest-site use. Nonhard mast species and greater tree DBH increased nest-tree selection probabilities. Maintaining forest diversity while allowing all tree species to reach maturity could increase available nesting habitat for southern flying squirrels on their western range periphery.},
	urldate = {2026-05-21},
	journal = {Canadian Journal of Zoology},
	author = {Bernhardt, Brandon M. and Hope, Andrew G. and Bishop, Amanda B. and Cordes, Zackary and Olexa, Jacqueline W. and Robbins, Lydia L. and Sullins, Dan S. and Ahlers, Adam A.},
	month = jan,
	year = {2026},
	note = {Publisher: NRC Research Press},
	keywords = {Political Boundaries},
	pages = {1--14},
}

Species distribution patterns at range edges can reveal effects of landscape and climate changes which can drive population expansions or contractions. Southern flying squirrel (Glaucomys volans Linnaeus, 1758) populations are common in eastern United States and southeastern Canada, and extend westwardly into the Great Plains. Space-use patterns within their range interior are well documented, though it is unclear if patterns are similar along western range edges. We tracked 10 southern flying squirrels in southeastern Kansas, USA to estimate home-range sizes and patterns in nest-site and tree selection. Forest structure and composition at western range edges differ compared to forest habitat at range interiors, and we predicted differences in home-range sizes and nest-site and tree selection patterns in Kansas compared to previous research. Mean home-range size was 1.55 ha (95% minimum convex polygon) and 5.44 ha (95% kernel density), similar to some populations in the interior of their range. Greater tree genera richness and average tree diameter (diameter at breast height (DBH)) increased probability of nest-site use. Nonhard mast species and greater tree DBH increased nest-tree selection probabilities. Maintaining forest diversity while allowing all tree species to reach maturity could increase available nesting habitat for southern flying squirrels on their western range periphery.

@article{cruz-campuzano_species_2026,
	title = {Species delimitation in a cryptic {Neotropical} {Thelephora} species complex, with insights into the phylogenetic informativeness of loci},
	volume = {0},
	issn = {0027-5514},
	url = {https://doi.org/10.1080/00275514.2026.2651040},
	doi = {10.1080/00275514.2026.2651040},
	abstract = {Thelephora is a genus of ectomycorrhizal fungi with a global distribution. Recent taxonomic efforts have revealed new species and species complexes, often distinguished by subtle morphological differences. Here, we describe Thelephora renispora, a new species resembling T. versatilis and T. pseudoversatilis, and support its recognition as a distinct taxon based on morphological traits, phylogenetic analyses of nuc rDNA internal transcribed spacer region ITS1-5.8S-ITS2 (ITS barcode) and D1–D2 domains of nuc 28S rDNA (28S), and statistical comparisons of its micromophology against closely related allies. New distribution records for T. pseudoversatilis are also provided. Additionally, we present phylogenetic informativeness analyses to assess the utility of ITS, 28S, and other markers previously used for the order Thelephorales. Our results identify the DNA-directed RNA polymerase II second-largest subunit (RPB2) as the most informative locus for delimiting species-level relationships in the Thelephorales order, whereas ITS contributes to solving interspecific relations within the Thelephora-Tomentella clade.},
	number = {0},
	urldate = {2026-05-22},
	journal = {Mycologia},
	author = {Cruz-Campuzano, Ezequiel Alberto and Avila Muñoz, Mariana and Silva-Tostado, Carla Elisa and Estrada Avendaño, Alejandro and Salas-Lizana, Rodolfo and Hernández-Navarro, Eduardo and Kennedy, Peter and Smith, Matthew E. and Miller, Kurt O. and Franck, Alan R. and Alvarez-Manjarrez, Julieta},
	month = may,
	year = {2026},
	pmid = {42096627},
	note = {Publisher: Taylor \& Francis
\_eprint: https://doi.org/10.1080/00275514.2026.2651040},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {1--21},
}

Thelephora is a genus of ectomycorrhizal fungi with a global distribution. Recent taxonomic efforts have revealed new species and species complexes, often distinguished by subtle morphological differences. Here, we describe Thelephora renispora, a new species resembling T. versatilis and T. pseudoversatilis, and support its recognition as a distinct taxon based on morphological traits, phylogenetic analyses of nuc rDNA internal transcribed spacer region ITS1-5.8S-ITS2 (ITS barcode) and D1–D2 domains of nuc 28S rDNA (28S), and statistical comparisons of its micromophology against closely related allies. New distribution records for T. pseudoversatilis are also provided. Additionally, we present phylogenetic informativeness analyses to assess the utility of ITS, 28S, and other markers previously used for the order Thelephorales. Our results identify the DNA-directed RNA polymerase II second-largest subunit (RPB2) as the most informative locus for delimiting species-level relationships in the Thelephorales order, whereas ITS contributes to solving interspecific relations within the Thelephora-Tomentella clade.

@article{langan_forgotten_2026,
	title = {The {Forgotten} {Pink} {Salmon} in the {Laurentian} {Great} {Lakes}: {An} {Unexpected} {Invasion} {With} {Insights} for {Three} {Oceans}},
	volume = {n/a},
	copyright = {© 2026 The Author(s). Fish and Fisheries published by John Wiley \& Sons Ltd. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.},
	issn = {1467-2979},
	shorttitle = {The {Forgotten} {Pink} {Salmon} in the {Laurentian} {Great} {Lakes}},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/faf.70084},
	doi = {10.1111/faf.70084},
	abstract = {Introductions of species outside their native range, such as pink salmon (Oncorhynchus gorbuscha) in the Laurentian Great Lakes, can serve as unplanned experiments that provide new insights into ecological adaptation. We synthesize available information on the understudied Great Lakes pink salmon invasion and highlight how this case can inform research and management related to expansions and invasions of this species in the Pacific, Arctic and North Atlantic Oceans. Accidentally introduced to Lake Superior in 1956, pink salmon quickly spread to all five Great Lakes, displaying unexpected behaviours and life history plasticity. This invasion history demonstrates a remarkable ability of pink salmon to establish from a small founder population, colonize large areas, produce explosive year classes to rapidly increase in abundance, and complete a full life cycle entirely in freshwater. One of the most striking changes is a shift from their rigid 2-year Pacific life cycle to a variable maturation age ranging from 1 to 4 years, likely influenced by prey availability as well as temperature and other environmental factors. We discuss implications for expansions elsewhere and outline five research themes necessary for understanding pink salmon dynamics in the Great Lakes with broader relevance for managing the species everywhere: (1) What drives rapid changes in abundance? (2) How do temperature extremes influence their ecology? (3) What causes departures from the 2-year life cycle? (4) How important is it for the phenology of life history events to match new habitats? (5) What guides pelagic movements and straying in new habitats?},
	language = {en},
	number = {n/a},
	urldate = {2026-05-27},
	journal = {Fish and Fisheries},
	author = {Langan, Joseph A. and Alsip, Peter J. and Abdelhady, Hazem U. and Bronte, Charles R. and Goldsworthy, Cory A. and Kornis, Matthew S. and Oke, Krista B. and Thorstad, Eva B. and Turschak, Benjamin A.},
	month = apr,
	year = {2026},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/faf.70084},
	keywords = {Lakes \& Rivers},
}

Introductions of species outside their native range, such as pink salmon (Oncorhynchus gorbuscha) in the Laurentian Great Lakes, can serve as unplanned experiments that provide new insights into ecological adaptation. We synthesize available information on the understudied Great Lakes pink salmon invasion and highlight how this case can inform research and management related to expansions and invasions of this species in the Pacific, Arctic and North Atlantic Oceans. Accidentally introduced to Lake Superior in 1956, pink salmon quickly spread to all five Great Lakes, displaying unexpected behaviours and life history plasticity. This invasion history demonstrates a remarkable ability of pink salmon to establish from a small founder population, colonize large areas, produce explosive year classes to rapidly increase in abundance, and complete a full life cycle entirely in freshwater. One of the most striking changes is a shift from their rigid 2-year Pacific life cycle to a variable maturation age ranging from 1 to 4 years, likely influenced by prey availability as well as temperature and other environmental factors. We discuss implications for expansions elsewhere and outline five research themes necessary for understanding pink salmon dynamics in the Great Lakes with broader relevance for managing the species everywhere: (1) What drives rapid changes in abundance? (2) How do temperature extremes influence their ecology? (3) What causes departures from the 2-year life cycle? (4) How important is it for the phenology of life history events to match new habitats? (5) What guides pelagic movements and straying in new habitats?

@article{shrestha_hydroclimate_2026,
	title = {The {Hydroclimate} of the {Ottawa} {River} {Basin} {Under} {Climate} {Change}},
	volume = {62},
	issn = {1752-1688},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/1752-1688.70082},
	doi = {10.1111/1752-1688.70082},
	abstract = {The freshwater resource of the Ottawa River basin (ORB) is vital for ecological services and economic activities in the region. With climate change impacts becoming more evident, sustainable management is imperative. As a first step, it is important to assess impacts on hydro-climatology. A coupled hydrological model (WATFLOOD-RAVEN) was set up, calibrated, and validated, with all principal reservoirs implemented using the DZTR principle. The coupled model was forced with high-resolution, bias-corrected future climate projections. Ensemble results show a warmer and wetter future. Under RCP 4.5, which recent studies suggest as the more likely pathway, mean annual precipitation and temperature may increase as much as 8.6\% and 3.2°C, respectively. Seasonal and monthly changes are more sporadic. Snowpack is expected to decrease substantially, while actual evapotranspiration increases moderately. Annual streamflow may rise by 7\%–10\%, but spring freshet streamflow is projected to shift earlier (1.1 days/decade) with a lower (12\%) peak. Other indicators, such as time to center of mass and spring pulse onset, also point to earlier shifts. Results further indicate more frequent extreme high (Q10) and low (Q90) flow conditions. Substantial increases in winter reservoir inflows are likely to raise reservoir depths and reduce capacity to store the spring freshet. Better quantification of climate change impacts will aid in developing coordinated responses to climate-related challenges.},
	language = {en},
	number = {1},
	urldate = {2026-05-29},
	journal = {JAWRA Journal of the American Water Resources Association},
	author = {Shrestha, Narayan K. and Seglenieks, Frank},
	year = {2026},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/1752-1688.70082},
	keywords = {NALCMS},
	pages = {e70082},
}

The freshwater resource of the Ottawa River basin (ORB) is vital for ecological services and economic activities in the region. With climate change impacts becoming more evident, sustainable management is imperative. As a first step, it is important to assess impacts on hydro-climatology. A coupled hydrological model (WATFLOOD-RAVEN) was set up, calibrated, and validated, with all principal reservoirs implemented using the DZTR principle. The coupled model was forced with high-resolution, bias-corrected future climate projections. Ensemble results show a warmer and wetter future. Under RCP 4.5, which recent studies suggest as the more likely pathway, mean annual precipitation and temperature may increase as much as 8.6% and 3.2°C, respectively. Seasonal and monthly changes are more sporadic. Snowpack is expected to decrease substantially, while actual evapotranspiration increases moderately. Annual streamflow may rise by 7%–10%, but spring freshet streamflow is projected to shift earlier (1.1 days/decade) with a lower (12%) peak. Other indicators, such as time to center of mass and spring pulse onset, also point to earlier shifts. Results further indicate more frequent extreme high (Q10) and low (Q90) flow conditions. Substantial increases in winter reservoir inflows are likely to raise reservoir depths and reduce capacity to store the spring freshet. Better quantification of climate change impacts will aid in developing coordinated responses to climate-related challenges.

@article{haghiri_present_2026,
	title = {The present and future of {North} {American} rainwater harvesting},
	volume = {71},
	issn = {0262-6667},
	url = {https://doi.org/10.1080/02626667.2026.2633302},
	doi = {10.1080/02626667.2026.2633302},
	abstract = {North America faces increasing water scarcity driven by climate change and population growth. This study applies the analytical hierarchy process (AHP) integrated with GIS to assess rainwater harvesting (RWH) suitability across the continent for 2020 and 2100 under the CMIP6 SSP5–8.5 scenario. Eight biophysical factors – topography, slope, soil texture, soil moisture, precipitation, NDVI, drainage density, and land cover – were analyzed using satellite and national datasets at 1/24° resolution. Expert-based AHP pairwise comparisons were used to derive criterion weights, which were then integrated through GIS-based weighted overlay analysis. Results indicate that moderately and highly suitable areas dominate, expanding from 10.55 to 10.91 million km2 (45\%) and 7.30 to 7.61 million km2 (32\%), respectively, between 2020 and 2100. Very highly suitable zones remain below 5\%. These findings reveal a subtle but positive continental trend in RWH feasibility, offering a robust geospatial foundation for climate-resilient water management and investment planning across North America.},
	number = {7},
	urldate = {2026-05-27},
	journal = {Hydrological Sciences Journal},
	author = {Haghiri, Mohammad and Meysami, Sahar and Asef, Mohammad Reza},
	month = may,
	year = {2026},
	note = {Publisher: Taylor \& Francis
\_eprint: https://doi.org/10.1080/02626667.2026.2633302},
	keywords = {NALCMS},
	pages = {1399--1414},
}

North America faces increasing water scarcity driven by climate change and population growth. This study applies the analytical hierarchy process (AHP) integrated with GIS to assess rainwater harvesting (RWH) suitability across the continent for 2020 and 2100 under the CMIP6 SSP5–8.5 scenario. Eight biophysical factors – topography, slope, soil texture, soil moisture, precipitation, NDVI, drainage density, and land cover – were analyzed using satellite and national datasets at 1/24° resolution. Expert-based AHP pairwise comparisons were used to derive criterion weights, which were then integrated through GIS-based weighted overlay analysis. Results indicate that moderately and highly suitable areas dominate, expanding from 10.55 to 10.91 million km2 (45%) and 7.30 to 7.61 million km2 (32%), respectively, between 2020 and 2100. Very highly suitable zones remain below 5%. These findings reveal a subtle but positive continental trend in RWH feasibility, offering a robust geospatial foundation for climate-resilient water management and investment planning across North America.

@article{thebault_varying_2026,
	title = {Varying the {Combination} of {Hydrological} {Models} in {Time} and {Space}: {Toward} a {More} {Accurate} {Representation} of {Streamflow} in {Large}-{Sample} {Hydrology}},
	volume = {62},
	copyright = {© 2026. The Author(s).},
	issn = {1944-7973},
	shorttitle = {Varying the {Combination} of {Hydrological} {Models} in {Time} and {Space}},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2025WR042272},
	doi = {10.1029/2025WR042272},
	abstract = {Accurate predictions of streamflow are needed to manage water resources, evaluate flooding risks, and support agriculture and industry. Many hydrological studies rely on a single model structure and parameter set applied uniformly across space and held fixed over time, limiting their ability to represent spatiotemporal changes in hydrological conditions. This study evaluates a model-agnostic, interpretable, computationally frugal approach to dynamically combine multiple models to improve streamflow simulation. The Framework for Understanding Structural Errors (FUSE) was used to create an ensemble of 78 hydrological models applied to 559 catchments across the contiguous United States. Each model was calibrated to maximize either high-flow or low-flow performance, yielding 156 simulations per catchment. The dynamic combination assigns weights to ensemble members that vary in space and time. It identifies past conditions similar to the current state, ranks simulations by performance under the identified comparable past conditions, and forms a combined simulation by equally weighting the m best-ranked models at each time step. The results show that the dynamic combination approach mitigates trade-offs between competing objectives (e.g., low flows vs. high flows) compared to static approaches. This method also reduces sampling uncertainty, thereby increasing confidence and robustness in streamflow simulations. Nevertheless, the dynamic combination also has limitations; for example, the current implementation cannot predict values outside the ensemble prediction envelope. Future work could integrate machine learning into the combination step to enable extrapolation. In addition, the method could be applied to forecasting and ungauged catchments.},
	language = {en},
	number = {5},
	urldate = {2026-05-29},
	journal = {Water Resources Research},
	author = {Thébault, C. and Knoben, W. J. M. and Addor, N. and Newman, A. J. and Clark, M. P.},
	year = {2026},
	note = {\_eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2025WR042272},
	keywords = {Political Boundaries},
	pages = {e2025WR042272},
}

Accurate predictions of streamflow are needed to manage water resources, evaluate flooding risks, and support agriculture and industry. Many hydrological studies rely on a single model structure and parameter set applied uniformly across space and held fixed over time, limiting their ability to represent spatiotemporal changes in hydrological conditions. This study evaluates a model-agnostic, interpretable, computationally frugal approach to dynamically combine multiple models to improve streamflow simulation. The Framework for Understanding Structural Errors (FUSE) was used to create an ensemble of 78 hydrological models applied to 559 catchments across the contiguous United States. Each model was calibrated to maximize either high-flow or low-flow performance, yielding 156 simulations per catchment. The dynamic combination assigns weights to ensemble members that vary in space and time. It identifies past conditions similar to the current state, ranks simulations by performance under the identified comparable past conditions, and forms a combined simulation by equally weighting the m best-ranked models at each time step. The results show that the dynamic combination approach mitigates trade-offs between competing objectives (e.g., low flows vs. high flows) compared to static approaches. This method also reduces sampling uncertainty, thereby increasing confidence and robustness in streamflow simulations. Nevertheless, the dynamic combination also has limitations; for example, the current implementation cannot predict values outside the ensemble prediction envelope. Future work could integrate machine learning into the combination step to enable extrapolation. In addition, the method could be applied to forecasting and ungauged catchments.

@article{bauer_vector_2026,
	title = {Vector {Potential} {Index}: {Bridging} {Competence} and {Contribution} as an {Integrative} {Measure} of {Relative} {Transmission} {Capability}},
	shorttitle = {Vector {Potential} {Index}},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/ece3.72705},
	doi = {10.1002/ece3.72705},
	abstract = {The Vector Potential Index (VPI) is a novel metric for evaluating and comparing the potential of blood-feeding arthropod vectors to contribute to zoonotic vector-borne disease transmission. Taking a ...},
	language = {en},
	urldate = {2026-05-21},
	author = {Bauer, Amely M. and Burkett-Cadena, Nathan D. and Reeves, Lawrence E. and Alto, Barry W. and Campbell, Lindsay P.},
	year = {2026},
	keywords = {Terrestrial Ecoregions, Terrestrial Ecoregions (CEC 1997)},
}

The Vector Potential Index (VPI) is a novel metric for evaluating and comparing the potential of blood-feeding arthropod vectors to contribute to zoonotic vector-borne disease transmission. Taking a ...

@article{wang_wetter_2026,
	title = {Wetter conditions amplify simulated deep drainage differences between grasslands and forests in the {Post} {Oak} {Savanna}},
	volume = {64},
	issn = {2214-5818},
	url = {https://www.sciencedirect.com/science/article/pii/S2214581826001084},
	doi = {10.1016/j.ejrh.2026.103210},
	abstract = {Study region
The Post Oak Savanna (POS) ecoregion of Texas, U.S.
Study focus
Woody plant encroachment in the POS has been linked to reduced groundwater recharge, but it remains unclear whether the removal of these woody plants may increase groundwater recharge rates. To evaluate differences in recharge under contrasting vegetation covers, we simulated deep drainage at 18 paired grassland–forest sites using Hydrus-1D. The simulations were analyzed to assess spatiotemporal variability in deep drainage between paired sites, with these differences serving as a proxy for potential recharge changes due to woody plant removal. Additionally, simulations were used to identify the influence of precipitation and soil texture on the magnitude of deep drainage differences between grasslands and forests.
New hydrological insights for the region
Deep drainage was consistently higher in grasslands, which also showed greater variability, while forests had more uniformly limited deep drainage. The differences in deep drainage between forested and grassland sites were larger in wetter subregions and years, with precipitation playing a stronger role than sand content. Higher precipitation amplified deep drainage increases, and soils with lower sand content promoted stronger responses of deep drainage increases than sandier soils. These findings indicate strong promise for enhancing potential recharge through woody plant removal in the POS, but this potential is limited in the southern subregion where precipitation is low. This highlights the importance of regional differences when prioritizing restoration efforts to support groundwater sustainability.},
	urldate = {2026-05-29},
	journal = {Journal of Hydrology: Regional Studies},
	author = {Wang, Mingxiu and Wyatt, Briana M. and Wilcox, Bradford P.},
	month = apr,
	year = {2026},
	keywords = {NALCMS},
	pages = {103210},
}

Study region The Post Oak Savanna (POS) ecoregion of Texas, U.S. Study focus Woody plant encroachment in the POS has been linked to reduced groundwater recharge, but it remains unclear whether the removal of these woody plants may increase groundwater recharge rates. To evaluate differences in recharge under contrasting vegetation covers, we simulated deep drainage at 18 paired grassland–forest sites using Hydrus-1D. The simulations were analyzed to assess spatiotemporal variability in deep drainage between paired sites, with these differences serving as a proxy for potential recharge changes due to woody plant removal. Additionally, simulations were used to identify the influence of precipitation and soil texture on the magnitude of deep drainage differences between grasslands and forests. New hydrological insights for the region Deep drainage was consistently higher in grasslands, which also showed greater variability, while forests had more uniformly limited deep drainage. The differences in deep drainage between forested and grassland sites were larger in wetter subregions and years, with precipitation playing a stronger role than sand content. Higher precipitation amplified deep drainage increases, and soils with lower sand content promoted stronger responses of deep drainage increases than sandier soils. These findings indicate strong promise for enhancing potential recharge through woody plant removal in the POS, but this potential is limited in the southern subregion where precipitation is low. This highlights the importance of regional differences when prioritizing restoration efforts to support groundwater sustainability.

@article{wehr_white-tailed_2026,
	title = {White-{Tailed} {Deer} {Baiting} {Altered} {Black} {Bear} {Site} {Use} but {Not} {Movements} or {Range} {Size}},
	volume = {16},
	copyright = {© 2026 The Author(s). Ecology and Evolution published by British Ecological Society and John Wiley \& Sons Ltd.},
	issn = {2045-7758},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/ece3.73015},
	doi = {10.1002/ece3.73015},
	abstract = {Intentional anthropogenic food subsidies (i.e., baiting and supplemental feeding) can have profound individual-level effects on wildlife. We assessed the influence of bait sites targeting white-tailed deer (Odocoileus virginianus) on nontarget American black bears (Ursus americanus) in Michigan's Upper Peninsula, USA. We used black bear GPS collar data collected during July–August 2013–2019 to assess differences in recursive site use metrics (i.e., number, duration, and time between visits) and movement metrics (i.e., range size, step length, and turning angle) using a before–after control-impact design. We compared site use at 116 baited and 81 unbaited control sites before (pretreatment) and after (treatment) bait applications. We compared movements between 32 GPS-monitored bear-years (i.e., individual bears monitored during July–August of each calendar year) where bait was within the bear's home range and eight bear-years where bait applications occurred outside individuals' home ranges. Bears exhibited 3 times more visits and 11 times longer durations of use at active bait sites during the treatment period than unbaited and pretreatment controls. Active bait site visits were also more nocturnal during the treatment period than visits to unbaited and pretreatment control sites. Movement metrics did not, however, differ between bears with and without bait in their home ranges regardless of treatment period. Our results support the known adaptability of black bears to anthropogenic food subsidies but indicate use of this resource did not influence larger-scale movement patterns. Our work furthers understanding of black bear behavior by explicitly identifying greater use of baited versus unbaited sites without alteration of movement metrics.},
	language = {en},
	number = {2},
	urldate = {2026-05-29},
	journal = {Ecology and Evolution},
	author = {Wehr, Nathaniel H. and Fowler, Nicholas L. and Kautz, Todd M. and Petroelje, Tyler R. and Beyer Jr, Dean E. and Belant, Jerrold L.},
	year = {2026},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/ece3.73015},
	keywords = {NALCMS},
	pages = {e73015},
}

Intentional anthropogenic food subsidies (i.e., baiting and supplemental feeding) can have profound individual-level effects on wildlife. We assessed the influence of bait sites targeting white-tailed deer (Odocoileus virginianus) on nontarget American black bears (Ursus americanus) in Michigan's Upper Peninsula, USA. We used black bear GPS collar data collected during July–August 2013–2019 to assess differences in recursive site use metrics (i.e., number, duration, and time between visits) and movement metrics (i.e., range size, step length, and turning angle) using a before–after control-impact design. We compared site use at 116 baited and 81 unbaited control sites before (pretreatment) and after (treatment) bait applications. We compared movements between 32 GPS-monitored bear-years (i.e., individual bears monitored during July–August of each calendar year) where bait was within the bear's home range and eight bear-years where bait applications occurred outside individuals' home ranges. Bears exhibited 3 times more visits and 11 times longer durations of use at active bait sites during the treatment period than unbaited and pretreatment controls. Active bait site visits were also more nocturnal during the treatment period than visits to unbaited and pretreatment control sites. Movement metrics did not, however, differ between bears with and without bait in their home ranges regardless of treatment period. Our results support the known adaptability of black bears to anthropogenic food subsidies but indicate use of this resource did not influence larger-scale movement patterns. Our work furthers understanding of black bear behavior by explicitly identifying greater use of baited versus unbaited sites without alteration of movement metrics.

@article{gordon_comparative_2025,
	title = {A comparative analysis of metacommunities reveals contrasting drivers of alpha and beta diversity in urban butterflies},
	volume = {11},
	issn = {2058-5543},
	url = {https://doi.org/10.1093/jue/juaf006},
	doi = {10.1093/jue/juaf006},
	abstract = {Urbanization reduces biodiversity and accelerates biotic homogenization, including among pollinators. However, questions remain concerning urban pollinator ecology and conservation, particularly: to what extent does pollinator alpha and beta diversity decline across urban landscapes, and what drives these patterns? We investigated the impacts of local and landscape characteristics on community diversity in four increasingly urban butterfly metacommunities, collecting data on butterfly diversity, butterfly host plant richness, flowering plant richness, and impervious surface area in the landscape. Suburban and urban metacommunities supported similarly low levels of butterfly diversity compared to a natural peri-urban metacommunity. Host plant richness increased butterfly diversity, but floral richness was correlated with reduced diversity, suggesting that many species-rich gardens are low in diversity of plants that support butterflies. In contrast, dissimilarity was driven by both local and landscape scale factors. Dissimilarities in site area and landscape impervious surface area drove overall dissimilarity, while these factors in addition to host and floral communities drove butterfly turnover (loss with replacement) and nestedness (loss without replacement). Our findings demonstrate that alpha and beta diversity are driven by different factors, and both must be considered to understand urban butterfly ecology and conservation. While butterfly species are filtered out of landscapes with high amounts of impervious surface area, even small sites can support diverse butterfly communities if they contain rich assemblages of butterfly host plants. Our comparative analysis of metacommunities provides a framework for future studies in human-altered environments.},
	number = {1},
	urldate = {2025-07-31},
	journal = {Journal of Urban Ecology},
	author = {Gordon, Susan C C and Kerr, Jeremy T},
	month = jan,
	year = {2025},
	keywords = {Political Boundaries},
}

Urbanization reduces biodiversity and accelerates biotic homogenization, including among pollinators. However, questions remain concerning urban pollinator ecology and conservation, particularly: to what extent does pollinator alpha and beta diversity decline across urban landscapes, and what drives these patterns? We investigated the impacts of local and landscape characteristics on community diversity in four increasingly urban butterfly metacommunities, collecting data on butterfly diversity, butterfly host plant richness, flowering plant richness, and impervious surface area in the landscape. Suburban and urban metacommunities supported similarly low levels of butterfly diversity compared to a natural peri-urban metacommunity. Host plant richness increased butterfly diversity, but floral richness was correlated with reduced diversity, suggesting that many species-rich gardens are low in diversity of plants that support butterflies. In contrast, dissimilarity was driven by both local and landscape scale factors. Dissimilarities in site area and landscape impervious surface area drove overall dissimilarity, while these factors in addition to host and floral communities drove butterfly turnover (loss with replacement) and nestedness (loss without replacement). Our findings demonstrate that alpha and beta diversity are driven by different factors, and both must be considered to understand urban butterfly ecology and conservation. While butterfly species are filtered out of landscapes with high amounts of impervious surface area, even small sites can support diverse butterfly communities if they contain rich assemblages of butterfly host plants. Our comparative analysis of metacommunities provides a framework for future studies in human-altered environments.

@article{mitchell_additional_2025,
	title = {Additional common milkweed would help {Canada} meet its share of the trinational eastern migratory monarch butterfly recovery target},
	volume = {10},
	url = {https://www.facetsjournal.com/doi/10.1139/facets-2024-0063},
	doi = {10.1139/facets-2024-0063},
	abstract = {The eastern migratory monarch butterfly (Danaus plexippus) population has declined by ∼84\% between 1993 and 2024. Population recovery in the Midwestern United States is limited by the availability of the monarch's main host plant for egg laying—common milkweed (Asclepias syriaca). The extent to which common milkweed availability is limiting in other breeding regions is unknown. Our objective was to determine whether Canada has enough common milkweed to support its share of the trinational eastern migratory monarch population recovery target, given ∼29 stems of common milkweed are needed to contribute one adult monarch into the fall migratory population. To meet this objective, we estimated the number of common milkweed stems in Canada using published common milkweed availability estimates by land cover type. We also estimated the size of the Canadian monarch population if the recovery target was achieved using published estimates of wintering monarch density in Mexico, fall migration survival rates, and the relative proportion of monarchs entering fall migration from Canada. We estimate that Canada currently has 484 million common milkweed stems (range: 111 million–1 billion stems) and increasing this amount by 1.61 times (i.e., by ∼295 million stems), or equivalently, by 61\%, would support the recovery target.},
	urldate = {2025-09-02},
	journal = {FACETS},
	author = {Mitchell, Greg W. and Kirby, Patrick and Duffe, Jason and Fahrig, Lenore and Girard, Judith and Johnston, Mark K. and Larrivée, Maxim and Martin, Amanda E. and Momeni-Dehaghi, Iman and Pasher, Jon and Rezek, Elizabeth and Shapiro, Elisabeth D. and Thogmartin, Wayne E. and Pouliot, Darren},
	month = jan,
	year = {2025},
	note = {Publisher: Canadian Science Publishing},
	keywords = {NALCMS},
	pages = {1--14},
}

The eastern migratory monarch butterfly (Danaus plexippus) population has declined by ∼84% between 1993 and 2024. Population recovery in the Midwestern United States is limited by the availability of the monarch's main host plant for egg laying—common milkweed (Asclepias syriaca). The extent to which common milkweed availability is limiting in other breeding regions is unknown. Our objective was to determine whether Canada has enough common milkweed to support its share of the trinational eastern migratory monarch population recovery target, given ∼29 stems of common milkweed are needed to contribute one adult monarch into the fall migratory population. To meet this objective, we estimated the number of common milkweed stems in Canada using published common milkweed availability estimates by land cover type. We also estimated the size of the Canadian monarch population if the recovery target was achieved using published estimates of wintering monarch density in Mexico, fall migration survival rates, and the relative proportion of monarchs entering fall migration from Canada. We estimate that Canada currently has 484 million common milkweed stems (range: 111 million–1 billion stems) and increasing this amount by 1.61 times (i.e., by ∼295 million stems), or equivalently, by 61%, would support the recovery target.

@mastersthesis{talbot_amelioration_2025,
	title = {Amélioration de la modélisation des variables hydrologiques et évaluation de l’impact des changements climatiques au {Québec}},
	url = {https://espace.etsmtl.ca/id/eprint/3628/},
	abstract = {Ce mémoire vise à améliorer la modélisation des variables hydrologiques et à évaluer les impacts des changements climatiques sur les bassins versants du Québec, en mettant l'accent sur l'application du modèle hydrologique WaSiM et les projections climatiques issues de CMIP6. La recherche se concentre sur trois aspects clés : l'optimisation de la configuration du modèle hydrologique, la comparaison entre les méthodes de modélisation conventionnelle et asynchrone, et l'évaluation des impacts des changements climatiques sur les variables hydrologiques.

Dans le premier volet de l’étude, trois configurations du modèle WaSiM sont comparées. La configuration intégrant la recharge de la nappe phréatique dans la calibration des paramètres du modèle, bien que moins performante en termes de reproduction des débits observés, offre une précision supérieure dans la modélisation des variables hydrologiques internes, soulignant l’importance d’une calibration multi-variable pour limiter le phénomène d’équifinalité lors de l’optimisation du modèle et améliorer la représentation des variables hydrologiques.

Le deuxième volet de l’étude compare les performances des méthodes de modélisation conventionnelle et asynchrone. L'approche asynchrone, qui élimine la dépendance aux données météorologiques historiques, présente des avantages potentiels dans les régions où les données d'observation sont limitées ou peu fiables. Toutefois, elle montre des lacunes dans la représentation temporelle des événements hydrologiques, en particulier la fonte des neiges. Cette méthode souffre d’une incohérence dans la synchronisation des processus saisonniers. Cela souligne la nécessité d’intégrer une forme de synchronicité dans la méthode asynchrone, afin d'améliorer la fiabilité des projections hydrologiques.

Le troisième volet porte sur l’évaluation des impacts des changements climatiques dans 34 bassins versants du sud du Québec. Les résultats montrent une augmentation des précipitations totales et des températures, avec une transition significative des précipitations neigeuses à la pluie, une réduction de l'accumulation de neige, et un décalage des crues printanières vers des périodes plus précoces. Les projections indiquent également une augmentation de la recharge des nappes phréatiques en hiver et au printemps, tandis que l'évapotranspiration s’intensifie durant les mois plus chauds. Les résultats de cette étude fournissent des informations cruciales pour la gestion des ressources en eau dans un contexte de changements climatiques.

Ce mémoire met en évidence l’importance d’une calibration multi-variable et l’utilisation des dernières projections climatiques pour améliorer la modélisation hydrologique.},
	language = {fr},
	urldate = {2025-07-31},
	school = {École de technologie supérieure},
	author = {Talbot, Frédéric},
	month = mar,
	year = {2025},
	keywords = {NALCMS},
}

Ce mémoire vise à améliorer la modélisation des variables hydrologiques et à évaluer les impacts des changements climatiques sur les bassins versants du Québec, en mettant l'accent sur l'application du modèle hydrologique WaSiM et les projections climatiques issues de CMIP6. La recherche se concentre sur trois aspects clés : l'optimisation de la configuration du modèle hydrologique, la comparaison entre les méthodes de modélisation conventionnelle et asynchrone, et l'évaluation des impacts des changements climatiques sur les variables hydrologiques. Dans le premier volet de l’étude, trois configurations du modèle WaSiM sont comparées. La configuration intégrant la recharge de la nappe phréatique dans la calibration des paramètres du modèle, bien que moins performante en termes de reproduction des débits observés, offre une précision supérieure dans la modélisation des variables hydrologiques internes, soulignant l’importance d’une calibration multi-variable pour limiter le phénomène d’équifinalité lors de l’optimisation du modèle et améliorer la représentation des variables hydrologiques. Le deuxième volet de l’étude compare les performances des méthodes de modélisation conventionnelle et asynchrone. L'approche asynchrone, qui élimine la dépendance aux données météorologiques historiques, présente des avantages potentiels dans les régions où les données d'observation sont limitées ou peu fiables. Toutefois, elle montre des lacunes dans la représentation temporelle des événements hydrologiques, en particulier la fonte des neiges. Cette méthode souffre d’une incohérence dans la synchronisation des processus saisonniers. Cela souligne la nécessité d’intégrer une forme de synchronicité dans la méthode asynchrone, afin d'améliorer la fiabilité des projections hydrologiques. Le troisième volet porte sur l’évaluation des impacts des changements climatiques dans 34 bassins versants du sud du Québec. Les résultats montrent une augmentation des précipitations totales et des températures, avec une transition significative des précipitations neigeuses à la pluie, une réduction de l'accumulation de neige, et un décalage des crues printanières vers des périodes plus précoces. Les projections indiquent également une augmentation de la recharge des nappes phréatiques en hiver et au printemps, tandis que l'évapotranspiration s’intensifie durant les mois plus chauds. Les résultats de cette étude fournissent des informations cruciales pour la gestion des ressources en eau dans un contexte de changements climatiques. Ce mémoire met en évidence l’importance d’une calibration multi-variable et l’utilisation des dernières projections climatiques pour améliorer la modélisation hydrologique.

@article{gomez-sanchez_antagonistic_2025,
	title = {Antagonistic climate-land use change interactions shape future distributions of a temperate snake at the northern range limit},
	volume = {10},
	issn = {2666-9005},
	url = {https://www.sciencedirect.com/science/article/pii/S2666900525000127},
	doi = {10.1016/j.ecochg.2025.100103},
	abstract = {Climate change presents a substantial threat to biodiversity, driving shifts in species distributions both independently and through interactions with land use change. In Canada, 77 \% of reptile species are considered at risk, especially near the Canada-U.S. border, where most species are at the northern range limit and where land use changes have been most pronounced. Climate change is expected to impact reptiles in this region, including snakes; however, how it will interact with land use change to affect snake distributions remains uncertain. Here, we used ensemble models, derived from three different SDM models, to investigate the potential effects of climate-land cover/use interactions on the future distribution of range-edge populations of a large threatened colubrid in Canada, Gray ratsnakes (Pantherophis spiloides). We showed climate and land cover/use change have an antagonistic effect on future environmental suitability, with greater net gains in suitability from climate alone (37–85 \%) compared to gains from the combined model (35–81 \%). Our study revealed that climate change may benefit temperate snakes, like gray ratsnakes, leading to a northward range-edge shift, but land use change may prevent colonization of new areas and persistence in areas of their current range. Our models showed that the Frontenac Arch is projected to be a key region for gray ratsnake persistence under climate change as it will mostly remain suitable due to the forest cover. These findings highlight the need for protection and restoration of habitat to help mitigate the negative effects of climate change for ratsnakes and many other similar species in Canada.},
	urldate = {2026-05-27},
	journal = {Climate Change Ecology},
	author = {Gómez-Sánchez, Andrea and Lougheed, Stephen C.},
	month = nov,
	year = {2025},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {100103},
}

Climate change presents a substantial threat to biodiversity, driving shifts in species distributions both independently and through interactions with land use change. In Canada, 77 % of reptile species are considered at risk, especially near the Canada-U.S. border, where most species are at the northern range limit and where land use changes have been most pronounced. Climate change is expected to impact reptiles in this region, including snakes; however, how it will interact with land use change to affect snake distributions remains uncertain. Here, we used ensemble models, derived from three different SDM models, to investigate the potential effects of climate-land cover/use interactions on the future distribution of range-edge populations of a large threatened colubrid in Canada, Gray ratsnakes (Pantherophis spiloides). We showed climate and land cover/use change have an antagonistic effect on future environmental suitability, with greater net gains in suitability from climate alone (37–85 %) compared to gains from the combined model (35–81 %). Our study revealed that climate change may benefit temperate snakes, like gray ratsnakes, leading to a northward range-edge shift, but land use change may prevent colonization of new areas and persistence in areas of their current range. Our models showed that the Frontenac Arch is projected to be a key region for gray ratsnake persistence under climate change as it will mostly remain suitable due to the forest cover. These findings highlight the need for protection and restoration of habitat to help mitigate the negative effects of climate change for ratsnakes and many other similar species in Canada.

@article{wilson_application_2025,
	title = {Application of fin tissue for nonlethal stable isotope analysis of small-bodied fishes},
	volume = {108},
	issn = {1573-5133},
	url = {https://doi.org/10.1007/s10641-025-01755-y},
	doi = {10.1007/s10641-025-01755-y},
	abstract = {Stable isotopes are commonly used to characterize food web structure and resource use by aquatic organisms. White muscle is generally preferred for stable isotope analysis of fishes. However, obtaining white muscle tissue typically requires lethal take or invasive sampling techniques, which are undesirable for small-bodied species or those of conservation concern. We assessed the use of fish fin as a nonlethal alternative to muscle tissue for stable isotope analysis of four small-bodied fishes native to the upper Red River drainage of Texas and Oklahoma, USA: plains minnow Hybognathus placitus, prairie chub Macrhybopsis australis, Red River shiner Alburnops bairdi, and Red River pupfish Cyprinodon rubrofluviatilis. Fin isotope values were strong predictors of both δ15N and δ13C muscle isotope values (ANCOVA: δ15N: F1,451 = 5312.09, P {\textless} 0.001; δ13C: F1,451 = 7864.39, P {\textless} 0.001), although isotopic composition varied among species for δ13C (F3,451 = 4.29, P {\textless} 0.01). Species-specific regression models indicated positive linear relationships between fin and muscle isotope values (δ15N: P {\textless} 0.001, R2 ≥ 0.80; δ13C: P {\textless} 0.001, R2 ≥ 0.83) that did not vary significantly with body size or age of individuals. We suggest minimum total length thresholds for least destructive fin clipping at 70 mm, 62 mm, and 48 mm for plains minnow, prairie chub, and Red River pupfish, respectively. Nonlethal fin clipping may not be viable for Red River shiner within the size range reported here as multiple fins were required for routine analysis. Overall, we conclude that fin tissue may be used for δ15N and δ13C assessments to mitigate lethal take of imperiled, small-bodied fishes.},
	language = {en},
	number = {12},
	urldate = {2026-01-21},
	journal = {Environmental Biology of Fishes},
	author = {Wilson, Wade M. and Rogosch, Jane S. and Collins, Scott F. and Durham, Bart W. and Mayes, Kevin B. and Robertson, Sarah M.},
	month = dec,
	year = {2025},
	keywords = {Lakes \& Rivers},
	pages = {2181--2198},
}

Stable isotopes are commonly used to characterize food web structure and resource use by aquatic organisms. White muscle is generally preferred for stable isotope analysis of fishes. However, obtaining white muscle tissue typically requires lethal take or invasive sampling techniques, which are undesirable for small-bodied species or those of conservation concern. We assessed the use of fish fin as a nonlethal alternative to muscle tissue for stable isotope analysis of four small-bodied fishes native to the upper Red River drainage of Texas and Oklahoma, USA: plains minnow Hybognathus placitus, prairie chub Macrhybopsis australis, Red River shiner Alburnops bairdi, and Red River pupfish Cyprinodon rubrofluviatilis. Fin isotope values were strong predictors of both δ15N and δ13C muscle isotope values (ANCOVA: δ15N: F1,451 = 5312.09, P \textless 0.001; δ13C: F1,451 = 7864.39, P \textless 0.001), although isotopic composition varied among species for δ13C (F3,451 = 4.29, P \textless 0.01). Species-specific regression models indicated positive linear relationships between fin and muscle isotope values (δ15N: P \textless 0.001, R2 ≥ 0.80; δ13C: P \textless 0.001, R2 ≥ 0.83) that did not vary significantly with body size or age of individuals. We suggest minimum total length thresholds for least destructive fin clipping at 70 mm, 62 mm, and 48 mm for plains minnow, prairie chub, and Red River pupfish, respectively. Nonlethal fin clipping may not be viable for Red River shiner within the size range reported here as multiple fins were required for routine analysis. Overall, we conclude that fin tissue may be used for δ15N and δ13C assessments to mitigate lethal take of imperiled, small-bodied fishes.

@article{aryal_assessing_2025,
	title = {Assessing {Climate} and {Watershed} {Controls} on {Rain}-on-{Snow} {Runoff} {Using} {XGBoost}-{SHAP} {Explainable} {AI} ({XAI})},
	volume = {15},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {2076-3263},
	url = {https://www.mdpi.com/2076-3263/15/12/467},
	doi = {10.3390/geosciences15120467},
	abstract = {Rain-on-snow (ROS) events significantly impact hydrological processes in snowy regions, yet their seasonal drivers remain poorly understood, particularly in low-elevation and low-gradient catchments. This study uses an XGBoost-SHAP explainable artificial intelligence (XAI) model to analyze meteorological and watershed controls on ROS runoff in the Laurentian Great Lakes region. We used daily discharge, precipitation, temperature, and snow depth data from 2000 to 2023, available from HYSETS, to identify ROS runoff. The XGBoost model’s performance for predicting ROS runoff was higher in winter (R2 = 0.65, Nash–Sutcliffe = 0.59) than in spring (R2 = 0.56, Nash–Sutcliffe = 0.49), indicating greater predictability in colder months. The results reveal that rainfall and temperature dominated ROS runoff generation, jointly explaining more than 60\% of total model importance, while snow depth accounted for 8–12\% depending on season. Winter runoff is predominantly governed by climatic factors—rainfall, air temperature, and their interactions—with soil permeability and slope orientation playing secondary roles. In contrast, spring runoff shows increased sensitivity to land cover characteristics, particularly agricultural and shrub cover, as vegetation-driven processes become more influential. Snow depth effects shift from predominantly negative in winter, where snow acts as storage, to positive contributions in spring at shallow to moderate depths. ROS runoff responded positively to air temperatures exceeding approximately 2.5 °C in both winter and spring. Land cover influences on ROS runoff differ by vegetation type and season. Agricultural areas consistently increase runoff in both seasons, likely due to limited infiltration, whereas shrub-dominated regions exhibit stronger runoff enhancement in spring. The seasonal shift in dominant controls underscores the importance of accounting for land–climate interactions in predicting ROS runoff under future climate scenarios. These insights are essential for improving flood forecasting, managing water resources, and developing adaptive strategies.},
	language = {en},
	number = {12},
	urldate = {2026-01-21},
	journal = {Geosciences},
	author = {Aryal, Yog},
	month = dec,
	year = {2025},
	note = {Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {NALCMS},
	pages = {467},
}

Rain-on-snow (ROS) events significantly impact hydrological processes in snowy regions, yet their seasonal drivers remain poorly understood, particularly in low-elevation and low-gradient catchments. This study uses an XGBoost-SHAP explainable artificial intelligence (XAI) model to analyze meteorological and watershed controls on ROS runoff in the Laurentian Great Lakes region. We used daily discharge, precipitation, temperature, and snow depth data from 2000 to 2023, available from HYSETS, to identify ROS runoff. The XGBoost model’s performance for predicting ROS runoff was higher in winter (R2 = 0.65, Nash–Sutcliffe = 0.59) than in spring (R2 = 0.56, Nash–Sutcliffe = 0.49), indicating greater predictability in colder months. The results reveal that rainfall and temperature dominated ROS runoff generation, jointly explaining more than 60% of total model importance, while snow depth accounted for 8–12% depending on season. Winter runoff is predominantly governed by climatic factors—rainfall, air temperature, and their interactions—with soil permeability and slope orientation playing secondary roles. In contrast, spring runoff shows increased sensitivity to land cover characteristics, particularly agricultural and shrub cover, as vegetation-driven processes become more influential. Snow depth effects shift from predominantly negative in winter, where snow acts as storage, to positive contributions in spring at shallow to moderate depths. ROS runoff responded positively to air temperatures exceeding approximately 2.5 °C in both winter and spring. Land cover influences on ROS runoff differ by vegetation type and season. Agricultural areas consistently increase runoff in both seasons, likely due to limited infiltration, whereas shrub-dominated regions exhibit stronger runoff enhancement in spring. The seasonal shift in dominant controls underscores the importance of accounting for land–climate interactions in predicting ROS runoff under future climate scenarios. These insights are essential for improving flood forecasting, managing water resources, and developing adaptive strategies.

@article{aryal_assessing_2025,
	title = {Assessing antecedent climatic and hydrological conditions and anthropogenic impacts to drive catastrophic flooding in the northeastern {United} {States}},
	volume = {6},
	issn = {2673-6187},
	url = {https://www.frontiersin.org/journals/remote-sensing/articles/10.3389/frsen.2025.1639845/full},
	doi = {10.3389/frsen.2025.1639845},
	abstract = {The northeastern US has been experiencing catastrophic flooding in recent years. Flooding in the region is occurring more frequently and with higher intensity, causing substantial economic losses. The flooding may be caused by changes in climatic and hydrological drivers such as extreme precipitation, rapid snowmelt, and saturated soil moisture conditions, along with impacts from human-driven interventions like changes in land cover and urban imperviousness. This study analyzes the abovementioned variables to indicate flood risk and understand whether they contribute to flooding in the Northeastern US region. This study utilized various remote sensing satellite products for analyzing variables to fulfil the study’s objectives, wherever possible, such as Terra Moderate Resolution Imaging Spectroradiometer (MODIS) maximum snow cover extent, Soil Moisture Active Passive (SMAP) soil moisture, Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG) precipitation, North American Land Change Monitoring System (NALCMS) land cover, and National Land Cover Database (NLCD) urban imperviousness. The region experienced wetter antecedent soil moisture conditions ({\textgreater}0.5 m3/m3) during spring due to rapid snowmelt (seasonal decline of ∼97\%) in all the periods considered in the study. Moreover, the summer precipitation fed excess water (∼50–60 mm more rainfall than the decadal average) into wetter ground conditions, overwhelming the region’s overall hydrology and water balance and causing significant flooding. In addition, ∼1,838 sq. km. of croplands and ∼1,363 sq. km. of forests transitioned into built-up areas in a decade, increasing impervious surface and further exacerbating flooding risk in the region.},
	language = {English},
	urldate = {2026-01-21},
	journal = {Frontiers in Remote Sensing},
	author = {Aryal, Aashutosh and Lakshmi, Venkataraman},
	month = sep,
	year = {2025},
	note = {Publisher: Frontiers},
	keywords = {NALCMS},
}

The northeastern US has been experiencing catastrophic flooding in recent years. Flooding in the region is occurring more frequently and with higher intensity, causing substantial economic losses. The flooding may be caused by changes in climatic and hydrological drivers such as extreme precipitation, rapid snowmelt, and saturated soil moisture conditions, along with impacts from human-driven interventions like changes in land cover and urban imperviousness. This study analyzes the abovementioned variables to indicate flood risk and understand whether they contribute to flooding in the Northeastern US region. This study utilized various remote sensing satellite products for analyzing variables to fulfil the study’s objectives, wherever possible, such as Terra Moderate Resolution Imaging Spectroradiometer (MODIS) maximum snow cover extent, Soil Moisture Active Passive (SMAP) soil moisture, Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG) precipitation, North American Land Change Monitoring System (NALCMS) land cover, and National Land Cover Database (NLCD) urban imperviousness. The region experienced wetter antecedent soil moisture conditions (\textgreater0.5 m3/m3) during spring due to rapid snowmelt (seasonal decline of ∼97%) in all the periods considered in the study. Moreover, the summer precipitation fed excess water (∼50–60 mm more rainfall than the decadal average) into wetter ground conditions, overwhelming the region’s overall hydrology and water balance and causing significant flooding. In addition, ∼1,838 sq. km. of croplands and ∼1,363 sq. km. of forests transitioned into built-up areas in a decade, increasing impervious surface and further exacerbating flooding risk in the region.

@article{dewinter_assessing_2025,
	title = {Assessing current and future areas of ecological suitability for {Lutzomyia} shannoni in {North} {America}},
	volume = {18},
	issn = {1756-3305},
	url = {https://doi.org/10.1186/s13071-025-06781-4},
	doi = {10.1186/s13071-025-06781-4},
	abstract = {In the Americas, sand flies of the Lutzomyia genus are the vectors of pathogens of human and animal health significance. Lutzomyia shannoni is suspected to transmit vesicular stomatitis virus, along with Leishmania mexicana and Leishmania infantum (causative agents of leishmaniases). Despite the suspected vector potential of Lu. shannoni, significant knowledge gaps remain, including how ongoing climate changes could facilitate their range expansion. The objectives of this study were to predict the current and future ecological suitability of regions across North America for Lu. shannoni and to identify variables driving ecological suitability.},
	language = {en},
	number = {1},
	urldate = {2025-07-31},
	journal = {Parasites \& Vectors},
	author = {DeWinter, Sydney and Nichol, Grace K. and Fernandez-Prada, Christopher and Greer, Amy L. and Weese, J. Scott and Clow, Katie M.},
	month = apr,
	year = {2025},
	keywords = {Terrestrial Ecoregions},
	pages = {154},
}

In the Americas, sand flies of the Lutzomyia genus are the vectors of pathogens of human and animal health significance. Lutzomyia shannoni is suspected to transmit vesicular stomatitis virus, along with Leishmania mexicana and Leishmania infantum (causative agents of leishmaniases). Despite the suspected vector potential of Lu. shannoni, significant knowledge gaps remain, including how ongoing climate changes could facilitate their range expansion. The objectives of this study were to predict the current and future ecological suitability of regions across North America for Lu. shannoni and to identify variables driving ecological suitability.

@article{zimmerman_assessing_2025,
	title = {Assessing shifting technology in genetic monitoring of the {North} {American} plains bison {Federal} conservation herds},
	volume = {26},
	issn = {1572-9737},
	url = {https://doi.org/10.1007/s10592-025-01694-2},
	doi = {10.1007/s10592-025-01694-2},
	abstract = {Human expansion is a major driver of both declining wildlife abundance and the contraction of species’ distributions, increasing the risk of genetic erosion and the need for genetic monitoring. Rapidly advancing technology has expanded the types of genetic data that are available for wildlife conservation. However, inferences from different genetic markers could result in different management decisions and, thus, must be considered carefully. Rebounding from near extinction in the early 1900s, the majority of North American plains bison (Bison bison bison) are managed as small and isolated herds. Microsatellite-based analyses have been used to inform management of the US Federal bison conservation herds since the early 2000s. Transitioning from monitoring with tens of multiallelic loci (e.g., microsatellite loci) to thousands of biallelic loci (e.g., single nucleotide polymorphisms [SNPs]) could increase genotyping efficiency and improve the precision of population genetic inference but would require an understanding of the inferential differences between genetic marker types. We compared microsatellite-based measures of genetic diversity, differentiation, and population structure for 20 bison conservation herds (17 Federal, 1 Tribal, 2 Canadian) to inference from SNP-based analyses for the Tribal herd and 15 of the Federal herds. Data from both genetic marker types found that all herds have remarkably high genetic diversity given the severity of the bottleneck from which these populations recovered, and that population structure was consistent with founding histories. Importantly, SNPs had greater power to describe differences in genetic diversity and groups of related herds, but only if analyses are based on 250 or more loci. Overall, we found that microsatellite and SNP data can provide comparable conservation insight, but SNPs must be carefully selected to ensure continuity in genetic monitoring and to achieve the increased precision in genetic diversity and differentiation among herds that we observed in this study.},
	language = {en},
	number = {4},
	urldate = {2025-07-31},
	journal = {Conservation Genetics},
	author = {Zimmerman, Shawna J. and Giglio, Rachael and Geremia, Chris and Jones, Lee and McCann, Blake and Smyser, Timothy J. and Moynahan, Brendan J. and Oyler-McCance, Sara J.},
	month = aug,
	year = {2025},
	keywords = {Political Boundaries},
	pages = {657--675},
}

Human expansion is a major driver of both declining wildlife abundance and the contraction of species’ distributions, increasing the risk of genetic erosion and the need for genetic monitoring. Rapidly advancing technology has expanded the types of genetic data that are available for wildlife conservation. However, inferences from different genetic markers could result in different management decisions and, thus, must be considered carefully. Rebounding from near extinction in the early 1900s, the majority of North American plains bison (Bison bison bison) are managed as small and isolated herds. Microsatellite-based analyses have been used to inform management of the US Federal bison conservation herds since the early 2000s. Transitioning from monitoring with tens of multiallelic loci (e.g., microsatellite loci) to thousands of biallelic loci (e.g., single nucleotide polymorphisms [SNPs]) could increase genotyping efficiency and improve the precision of population genetic inference but would require an understanding of the inferential differences between genetic marker types. We compared microsatellite-based measures of genetic diversity, differentiation, and population structure for 20 bison conservation herds (17 Federal, 1 Tribal, 2 Canadian) to inference from SNP-based analyses for the Tribal herd and 15 of the Federal herds. Data from both genetic marker types found that all herds have remarkably high genetic diversity given the severity of the bottleneck from which these populations recovered, and that population structure was consistent with founding histories. Importantly, SNPs had greater power to describe differences in genetic diversity and groups of related herds, but only if analyses are based on 250 or more loci. Overall, we found that microsatellite and SNP data can provide comparable conservation insight, but SNPs must be carefully selected to ensure continuity in genetic monitoring and to achieve the increased precision in genetic diversity and differentiation among herds that we observed in this study.

@article{shafeian_assessing_2025,
	title = {Assessing spatial distribution and quantification of native trees in {Saskatchewan}’s prairie landscape using remote sensing techniques},
	volume = {58},
	issn = {NULL},
	url = {https://doi.org/10.1080/22797254.2024.2438638},
	doi = {10.1080/22797254.2024.2438638},
	abstract = {The importance of trees in non-forest landscapes has been the focus of only a few studies. However, these trees provide many important ecosystem services. In this study, we mapped and quantified these trees using Sentinel-2 (S2) and very high-resolution (VHR) Google satellite imagery without any field campaigns. We performed a Random Forest (RF) classification to map the spatial distribution of native trees in different scenarios. The optimal model showed an overall accuracy and kappa of 0.99 and 0.98, respectively. We mapped 40,500 km2 of tree cover, including native tree cover (approximately 29,565 km2 ≈10.5\%), excluding plantations, regional and provincial parks, and water bodies in the Canadian prairie region of Saskatchewan. According to our results, the highest numbers of native trees were found in the eastern and northwestern parts of the study area – cluster “BLK\_1” and the “Black” soil zone, with total cover of 5,388 and 13,233 km2, respectively. The lowest numbers of native trees were found in the southwest side of the study area – cluster “BRN\_6” and the “Brown” soil zone, with total cover of 2.38 and 979.5 km2, respectively. This research is important as detecting and quantifying native trees is an integral part of studies on carbon sequestration, economics, and effective management strategies.},
	number = {1},
	urldate = {2025-05-08},
	journal = {European Journal of Remote Sensing},
	author = {Shafeian, Elham and , Bryan J., Mood and , Kenneth W., Belcher and and Laroque, Colin P.},
	month = dec,
	year = {2025},
	note = {Publisher: Taylor \& Francis
\_eprint: https://doi.org/10.1080/22797254.2024.2438638},
	keywords = {NALCMS},
	pages = {2438638},
}

The importance of trees in non-forest landscapes has been the focus of only a few studies. However, these trees provide many important ecosystem services. In this study, we mapped and quantified these trees using Sentinel-2 (S2) and very high-resolution (VHR) Google satellite imagery without any field campaigns. We performed a Random Forest (RF) classification to map the spatial distribution of native trees in different scenarios. The optimal model showed an overall accuracy and kappa of 0.99 and 0.98, respectively. We mapped 40,500 km2 of tree cover, including native tree cover (approximately 29,565 km2 ≈10.5%), excluding plantations, regional and provincial parks, and water bodies in the Canadian prairie region of Saskatchewan. According to our results, the highest numbers of native trees were found in the eastern and northwestern parts of the study area – cluster “BLK_1” and the “Black” soil zone, with total cover of 5,388 and 13,233 km2, respectively. The lowest numbers of native trees were found in the southwest side of the study area – cluster “BRN_6” and the “Brown” soil zone, with total cover of 2.38 and 979.5 km2, respectively. This research is important as detecting and quantifying native trees is an integral part of studies on carbon sequestration, economics, and effective management strategies.

@article{hanrahan_assessing_2025,
	title = {Assessing the influence of conservation implementation on water quality during surface runoff events at edge-of-field monitoring sites located in the {Laurentian} {Great} {Lakes} basin},
	volume = {80},
	issn = {0022-4561},
	url = {https://doi.org/10.1080/00224561.2025.2582435},
	doi = {10.1080/00224561.2025.2582435},
	abstract = {The Laurentian Great Lakes are a vital freshwater resource in the United States, and nonpoint source (NPS) nutrient pollution, specifically phosphorus (P) and nitrogen (N), from agricultural land use continues to negatively impact water quality throughout the Great Lakes basin. One focus of the Great Lakes Restoration Initiative (GLRI), a mechanism to coordinate conservation efforts in the Great Lakes that began in 2010, is reducing NPS nutrient pollution through the implementation of conservation practices in priority watersheds (Genesee River, Fox River, Maumee River, and Saginaw River). As part of GLRI efforts, the objective of the study presented here was to evaluate the effects of conservation implementation, specifically increasing vegetative cover on fields and in primary flowpaths through perennial or cover crop planting and grassed waterways, on surface-runoff water quality at 12 agricultural fields (six paired and six unpaired) located in priority watersheds. We determined the percentage difference in mean event response variables between the periods before and after conservation implementation at individual sites, describing patterns across sites to synthesize lessons learned from these GLRI evaluations. Generally, we found that mean event flow-weighted concentration (FWC) and yield (kilograms per hectare) decreased for suspended sediment (SS) and nitrate (NO3–-N) across many sites. Mean event FWC and yield for total P (TP) showed mixed results across sites, while mean event FWC and yield for orthophosphate generally increased across sites. These results indicate that perennial or cover crop planting and grassed waterways effectively reduce SS and NO3–-N losses in surface runoff from agricultural fields, but mitigating TP and dissolved P losses remains a challenge.},
	number = {6},
	urldate = {2026-05-27},
	journal = {Journal of Soil and Water Conservation},
	author = {Hanrahan, Brittany R. and Diebel, Matthew W. and Carvin, Rebecca B. and Dobrowolski, Edward G. and Hardebeck, Matthew J. and Kowalczk, Andrew J. and Toussant, Chad A. and Komiskey, Matthew J.},
	month = nov,
	year = {2025},
	note = {Publisher: Taylor \& Francis
\_eprint: https://doi.org/10.1080/00224561.2025.2582435},
	keywords = {Political Boundaries},
	pages = {654--678},
}

The Laurentian Great Lakes are a vital freshwater resource in the United States, and nonpoint source (NPS) nutrient pollution, specifically phosphorus (P) and nitrogen (N), from agricultural land use continues to negatively impact water quality throughout the Great Lakes basin. One focus of the Great Lakes Restoration Initiative (GLRI), a mechanism to coordinate conservation efforts in the Great Lakes that began in 2010, is reducing NPS nutrient pollution through the implementation of conservation practices in priority watersheds (Genesee River, Fox River, Maumee River, and Saginaw River). As part of GLRI efforts, the objective of the study presented here was to evaluate the effects of conservation implementation, specifically increasing vegetative cover on fields and in primary flowpaths through perennial or cover crop planting and grassed waterways, on surface-runoff water quality at 12 agricultural fields (six paired and six unpaired) located in priority watersheds. We determined the percentage difference in mean event response variables between the periods before and after conservation implementation at individual sites, describing patterns across sites to synthesize lessons learned from these GLRI evaluations. Generally, we found that mean event flow-weighted concentration (FWC) and yield (kilograms per hectare) decreased for suspended sediment (SS) and nitrate (NO3–-N) across many sites. Mean event FWC and yield for total P (TP) showed mixed results across sites, while mean event FWC and yield for orthophosphate generally increased across sites. These results indicate that perennial or cover crop planting and grassed waterways effectively reduce SS and NO3–-N losses in surface runoff from agricultural fields, but mitigating TP and dissolved P losses remains a challenge.

@article{kovacek_bcub_2025,
	title = {{BCUB} – a large-sample ungauged basin attribute dataset for {British} {Columbia}, {Canada}},
	volume = {17},
	issn = {1866-3508},
	url = {https://essd.copernicus.org/articles/17/259/2025/},
	doi = {10.5194/essd-17-259-2025},
	abstract = {The British Columbia Ungauged Basin (BCUB) dataset is an open-source, extensible dataset of attributes describing terrain, soil, land cover, and climate indices of over 1.2 million ungauged catchments in British Columbia, Canada, including trans-boundary regions. The attributes included in the dataset are similar to those found in the large-sample hydrology literature for their association with hydrological processes. The BCUB database is intended to support water resources research and practice, namely monitoring network analysis studies, or hydrological modelling where basin characterization is used for model calibration. The dataset and the complete workflow to collect and process input data, to derive stream networks, and to delineate sub-basins and extract attributes, are available under a Creative Commons BY 4.0 license. The DOI link for the BCUB dataset is https://doi.org/10.5683/SP3/JNKZVT (Kovacek and Weijs, 2023).},
	language = {English},
	number = {1},
	urldate = {2025-05-08},
	journal = {Earth System Science Data},
	author = {Kovacek, Daniel and Weijs, Steven},
	month = jan,
	year = {2025},
	note = {Publisher: Copernicus GmbH},
	keywords = {NALCMS},
	pages = {259--275},
}

The British Columbia Ungauged Basin (BCUB) dataset is an open-source, extensible dataset of attributes describing terrain, soil, land cover, and climate indices of over 1.2 million ungauged catchments in British Columbia, Canada, including trans-boundary regions. The attributes included in the dataset are similar to those found in the large-sample hydrology literature for their association with hydrological processes. The BCUB database is intended to support water resources research and practice, namely monitoring network analysis studies, or hydrological modelling where basin characterization is used for model calibration. The dataset and the complete workflow to collect and process input data, to derive stream networks, and to delineate sub-basins and extract attributes, are available under a Creative Commons BY 4.0 license. The DOI link for the BCUB dataset is https://doi.org/10.5683/SP3/JNKZVT (Kovacek and Weijs, 2023).

@article{geddes_baseline_2025,
	title = {Baseline survey of protoporphyrinogen oxidase inhibitor-resistant kochia ({Bassia} scoparia) in western {Canada}},
	volume = {105},
	issn = {0008-4220},
	url = {https://cdnsciencepub.com/doi/full/10.1139/cjps-2024-0219},
	doi = {10.1139/cjps-2024-0219},
	abstract = {Kochia (Bassia scoparia (L.) A.J. Scott) is a problematic tumbleweed that has been reported resistant to five herbicide sites-of-action. Recently, protoporphyrinogen oxidase (PPO) inhibitor-resistant kochia was documented in Saskatchewan (2021) and North Dakota (2022). However, its frequency and distribution remain unknown. Screening with saflufenacil (50 g ai ha−1) revealed PPO inhibitor resistance in two of 14 grower-submitted samples, but not in 882 samples from randomized-stratified surveys of Manitoba (2018), Saskatchewan (2019), and Alberta (2021). To date, PPO inhibitor-resistant kochia has been confirmed in two municipalities in western Canada: the Rural Municipality of Newcombe in Saskatchewan and Forty Mile County in Alberta.},
	urldate = {2025-07-31},
	journal = {Canadian Journal of Plant Science},
	author = {Geddes, Charles M. and Pittman, Mattea M. and Sharpe, Shaun M. and Leeson, Julia Y.},
	month = jan,
	year = {2025},
	note = {Publisher: NRC Research Press},
	keywords = {Lakes \& Rivers},
	pages = {1--6},
}

Kochia (Bassia scoparia (L.) A.J. Scott) is a problematic tumbleweed that has been reported resistant to five herbicide sites-of-action. Recently, protoporphyrinogen oxidase (PPO) inhibitor-resistant kochia was documented in Saskatchewan (2021) and North Dakota (2022). However, its frequency and distribution remain unknown. Screening with saflufenacil (50 g ai ha−1) revealed PPO inhibitor resistance in two of 14 grower-submitted samples, but not in 882 samples from randomized-stratified surveys of Manitoba (2018), Saskatchewan (2019), and Alberta (2021). To date, PPO inhibitor-resistant kochia has been confirmed in two municipalities in western Canada: the Rural Municipality of Newcombe in Saskatchewan and Forty Mile County in Alberta.

@phdthesis{gillespie_biodiversity_2025,
	address = {Stanford, California},
	type = {Doctor of {Philosophy}},
	title = {Biodiversity monitoring at scale with foundation models},
	url = {https://purl.stanford.edu/gz526zj7191},
	abstract = {Climate and land use change have radically altered biodiversity worldwide, spurring the need for new high-resolution methods to monitor biodiversity at a global scale. Meanwhile, the recent advent ...},
	language = {English},
	urldate = {2026-06-01},
	school = {Stanford University},
	author = {Gillespie, Lauren Estelle},
	month = jul,
	year = {2025},
}

Climate and land use change have radically altered biodiversity worldwide, spurring the need for new high-resolution methods to monitor biodiversity at a global scale. Meanwhile, the recent advent ...

@article{knoben_catchment_2025,
	title = {Catchment {Attributes} and {MEteorology} for {Large}-{Sample} {SPATially} distributed analysis ({CAMELS}-{SPAT}): streamflow observations, forcing data and geospatial data for hydrologic studies across {North} {America}},
	volume = {29},
	issn = {1027-5606},
	shorttitle = {Catchment {Attributes} and {MEteorology} for {Large}-{Sample} {SPATially} distributed analysis ({CAMELS}-{SPAT})},
	url = {https://hess.copernicus.org/articles/29/5791/2025/},
	doi = {10.5194/hess-29-5791-2025},
	abstract = {We build on the existing Catchment Attributes and MEteorology for Large-sample Studies (CAMELS) dataset to present a new dataset aimed at hydrologic studies across North America, with a particular focus on facilitating spatially distributed studies. The dataset includes basin outlines, streamflow observations, meteorological data and geospatial data for 1426 basins in the US and Canada. To facilitate a wide variety of studies, we provide the basin outlines at a lumped and semi-distributed resolution; streamflow observations at daily and hourly time steps; variables suitable for running a wide range of models obtained and derived from different meteorological datasets at daily (one dataset) and hourly (three datasets) time steps; and geospatial data and derived attributes from 11 different datasets that broadly cover climatic conditions, vegetation properties, land use and subsurface characteristics. Forcing data are provided at their original gridded resolution, as well as averaged at the basin and sub-basin level. Geospatial data are provided as maps per basin, as well as summarized as catchment attributes at the basin and sub-basin level with various statistics. Attributes are further complemented with statistics derived from the forcing data and streamflow and focus on quantifying the variability of natural processes and catchment characteristics in space and time. Our goal with this dataset is to build upon existing large-sample datasets and provide the means for a more detailed investigation of hydrologic behaviour across large geographical scales. In particular, we hope that this dataset provides others with the data needed to implement a wide range of modelling approaches and to investigate the impact of basin heterogeneity on hydrologic behaviour and similarity. The CAMELS-SPAT (Catchment Attributes and MEteorology for Large-Sample SPATially distributed analysis) dataset is available at https://doi.org/10.20383/103.01306 (Knoben et al., 2025).},
	language = {English},
	number = {20},
	urldate = {2026-01-21},
	journal = {Hydrology and Earth System Sciences},
	author = {Knoben, Wouter J. M. and Thébault, Cyril and Keshavarz, Kasra and Torres-Rojas, Laura and Chaney, Nathaniel W. and Pietroniro, Alain and Clark, Martyn P.},
	month = oct,
	year = {2025},
	note = {Publisher: Copernicus GmbH},
	keywords = {Political Boundaries},
	pages = {5791--5833},
}

We build on the existing Catchment Attributes and MEteorology for Large-sample Studies (CAMELS) dataset to present a new dataset aimed at hydrologic studies across North America, with a particular focus on facilitating spatially distributed studies. The dataset includes basin outlines, streamflow observations, meteorological data and geospatial data for 1426 basins in the US and Canada. To facilitate a wide variety of studies, we provide the basin outlines at a lumped and semi-distributed resolution; streamflow observations at daily and hourly time steps; variables suitable for running a wide range of models obtained and derived from different meteorological datasets at daily (one dataset) and hourly (three datasets) time steps; and geospatial data and derived attributes from 11 different datasets that broadly cover climatic conditions, vegetation properties, land use and subsurface characteristics. Forcing data are provided at their original gridded resolution, as well as averaged at the basin and sub-basin level. Geospatial data are provided as maps per basin, as well as summarized as catchment attributes at the basin and sub-basin level with various statistics. Attributes are further complemented with statistics derived from the forcing data and streamflow and focus on quantifying the variability of natural processes and catchment characteristics in space and time. Our goal with this dataset is to build upon existing large-sample datasets and provide the means for a more detailed investigation of hydrologic behaviour across large geographical scales. In particular, we hope that this dataset provides others with the data needed to implement a wide range of modelling approaches and to investigate the impact of basin heterogeneity on hydrologic behaviour and similarity. The CAMELS-SPAT (Catchment Attributes and MEteorology for Large-Sample SPATially distributed analysis) dataset is available at https://doi.org/10.20383/103.01306 (Knoben et al., 2025).

@article{hanberry_clarifying_2025,
	title = {Clarifying {Influences} of {Sampling} {Bias} ({Concentration}) and {Locational} {Errors} ({Uncertainties}) on {Precision} or {Generality} of {Species} {Distribution} {Models}},
	volume = {14},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {2073-445X},
	url = {https://www.mdpi.com/2073-445X/14/8/1620},
	doi = {10.3390/land14081620},
	abstract = {Locational errors and sampling bias may produce unrepresentative species distribution models. To decompose the influence of errors, I modeled species distributions of 31 mammal species from georeferenced records and random samples from range maps, with potential sources of errors added or removed, using the random forests algorithm. Errors included the addition of (1) cities, (2) administrative centers, (3) records flagged as potential errors (e.g., outliers), and (4) urban records to range map samples; the removal of (5) flagged records and (6) urban records from georeferenced records; and the addition of (7) random points and (8) clustered points to georeferenced records. I also examined separation between thinned and unthinned (i.e., locally concentrated) records and ocean and land areas. Errors generally did not perturb species distributions, particularly if errors were located within species ranges. The greatest departure relative to unaltered models (mean niche overlap values of 0.96 out of 1) was due to the addition of administrative centers at a 13\% error rate. Because locational errors overall do not occur in modern georeferenced records, outliers may provide important samples from undersampled areas. Delineating land from ocean coordinates may require a land layer at the highest available resolution and buffered to match the distance of locational uncertainty for georeferenced records. Predicted areas for species distributions increased along the spectrum of models from concentrated georeferenced records, thinned records, and random samples from range maps. Species distributions modeled with all georeferenced records will have the greatest sampling concentration (to differentiate from bias, because predictive modeling is not hypothesis testing), resulting in model locational precision, whereas species distribution models from random samples of range maps will have locational generality (rather than errors). The risk of removing samples of suitable conditions is the generation of unrepresentative models whereas the benefit of sample removal is slightly more generalized models, but which also may represent overpredictions.},
	language = {en},
	number = {8},
	urldate = {2026-01-21},
	journal = {Land},
	author = {Hanberry, Brice B.},
	month = aug,
	year = {2025},
	note = {Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {NALCMS},
	pages = {1620},
}

Locational errors and sampling bias may produce unrepresentative species distribution models. To decompose the influence of errors, I modeled species distributions of 31 mammal species from georeferenced records and random samples from range maps, with potential sources of errors added or removed, using the random forests algorithm. Errors included the addition of (1) cities, (2) administrative centers, (3) records flagged as potential errors (e.g., outliers), and (4) urban records to range map samples; the removal of (5) flagged records and (6) urban records from georeferenced records; and the addition of (7) random points and (8) clustered points to georeferenced records. I also examined separation between thinned and unthinned (i.e., locally concentrated) records and ocean and land areas. Errors generally did not perturb species distributions, particularly if errors were located within species ranges. The greatest departure relative to unaltered models (mean niche overlap values of 0.96 out of 1) was due to the addition of administrative centers at a 13% error rate. Because locational errors overall do not occur in modern georeferenced records, outliers may provide important samples from undersampled areas. Delineating land from ocean coordinates may require a land layer at the highest available resolution and buffered to match the distance of locational uncertainty for georeferenced records. Predicted areas for species distributions increased along the spectrum of models from concentrated georeferenced records, thinned records, and random samples from range maps. Species distributions modeled with all georeferenced records will have the greatest sampling concentration (to differentiate from bias, because predictive modeling is not hypothesis testing), resulting in model locational precision, whereas species distribution models from random samples of range maps will have locational generality (rather than errors). The risk of removing samples of suitable conditions is the generation of unrepresentative models whereas the benefit of sample removal is slightly more generalized models, but which also may represent overpredictions.

@article{mcpherson_climate-related_2025,
	title = {Climate-related drivers of migratory bird health in the south-central {USA}},
	volume = {n/a},
	copyright = {© 2025 The Author(s). Biological Reviews published by John Wiley \& Sons Ltd on behalf of Cambridge Philosophical Society.},
	issn = {1469-185X},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/brv.70000},
	doi = {10.1111/brv.70000},
	abstract = {Migratory birds are species of concern that play important ecological roles while also supporting recreational opportunities for the hunting and birdwatching public. Direct and indirect effects of climate variability, extremes, and change on migratory bird health manifest at the individual, population, species, and community levels. This review focuses on the effects of climate on migratory birds that spend part of their life cycles in the south-central USA. Although gaps in knowledge remain, prior studies provide a solid foundation to understand how climate affects migratory birds to inform management priorities and actions.},
	language = {en},
	number = {n/a},
	urldate = {2025-02-06},
	journal = {Biological Reviews},
	author = {McPherson, Renee A. and Alger, Katrina E. and Hofmeister, Erik},
	month = feb,
	year = {2025},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/brv.70000},
	keywords = {Terrestrial Ecoregions},
}

Migratory birds are species of concern that play important ecological roles while also supporting recreational opportunities for the hunting and birdwatching public. Direct and indirect effects of climate variability, extremes, and change on migratory bird health manifest at the individual, population, species, and community levels. This review focuses on the effects of climate on migratory birds that spend part of their life cycles in the south-central USA. Although gaps in knowledge remain, prior studies provide a solid foundation to understand how climate affects migratory birds to inform management priorities and actions.

@article{fortin_climate-sensitive_2025,
	title = {Climate-sensitive models of tree mortality based on lifetime analysis and irregular permanent-plot remeasurements},
	volume = {55},
	issn = {0045-5067},
	url = {https://cdnsciencepub.com/doi/10.1139/cjfr-2024-0205},
	doi = {10.1139/cjfr-2024-0205},
	abstract = {Climate change has driven forest growth modellers to develop different climate sensitivity implementations (CSIs) for their models. Among others, a model can rely on annual climate variables or average climate variables, such as 30-year normals. The novelty of this study was to develop a framework based on lifetime analysis to enable annual or average CSI in empirical models of tree mortality. Using this framework, we compared models of individual tree mortality based on an annual CSI with similar models relying on two average CSIs, one using interval-averaged climate variables, and the other, 30-year normals. We fitted these models to permanent-plot data of eight species in Ontario and tested the effects of summer and winter temperature as well as spring and summer precipitation in the models. Our results showed that the annual CSI was not superior to the average CSIs, but could be a valid alternative for some species. Warmer winter temperature was detrimental to the survival of Betula papyrifera, Picea glauca, and Pinus strobus, whereas greater spring and summer precipitation resulted in greater mortality occurrence for Picea mariana, Pinus banksiana, and Populus tremuloides. In most cases, the effects of climate variables were contrary to our initial hypotheses. We conclude that the effects of climate on tree mortality occurrence interact with other factors such as species distribution and ecophysiology.},
	urldate = {2026-05-27},
	journal = {Canadian Journal of Forest Research},
	author = {Fortin, Mathieu and Riofrío, José and de Melo, Lara Climaco and Ashiq, Muhammad Waseem and Sharma, Mahadev and Howard, Christina and Eskelson, Bianca N.I.},
	month = jan,
	year = {2025},
	note = {Publisher: NRC Research Press},
	keywords = {Political Boundaries},
	pages = {1--15},
}

Climate change has driven forest growth modellers to develop different climate sensitivity implementations (CSIs) for their models. Among others, a model can rely on annual climate variables or average climate variables, such as 30-year normals. The novelty of this study was to develop a framework based on lifetime analysis to enable annual or average CSI in empirical models of tree mortality. Using this framework, we compared models of individual tree mortality based on an annual CSI with similar models relying on two average CSIs, one using interval-averaged climate variables, and the other, 30-year normals. We fitted these models to permanent-plot data of eight species in Ontario and tested the effects of summer and winter temperature as well as spring and summer precipitation in the models. Our results showed that the annual CSI was not superior to the average CSIs, but could be a valid alternative for some species. Warmer winter temperature was detrimental to the survival of Betula papyrifera, Picea glauca, and Pinus strobus, whereas greater spring and summer precipitation resulted in greater mortality occurrence for Picea mariana, Pinus banksiana, and Populus tremuloides. In most cases, the effects of climate variables were contrary to our initial hypotheses. We conclude that the effects of climate on tree mortality occurrence interact with other factors such as species distribution and ecophysiology.

@article{kimmitt_comparative_2025,
	title = {Comparative {Whole} {Genome} {Phylogeography} {Reveals} {Genetic} {Distinctiveness} of {Appalachian} {Populations} of {Boreal} {Songbirds}},
	volume = {18},
	copyright = {© 2025 The Author(s). Evolutionary Applications published by John Wiley \& Sons Ltd.},
	issn = {1752-4571},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/eva.70163},
	doi = {10.1111/eva.70163},
	abstract = {Intraspecific genetic diversity across a species' geographic range is relevant to adaptive potential and long-term population persistence, and identifying genetically distinct groups within species can direct management decisions focused on conserving species-level genetic diversity. Comparative phylogeography using whole genome techniques allows for investigation of whether co-distributed species exhibit shared spatial genetic differentiation at fine spatial scales, thereby facilitating a comparative approach to both landscape and conservation genetics. By sequencing over 900 low-coverage whole genomes, we evaluated the concordance of genetic structure and diversity from 12 co-occurring species of migratory birds whose breeding ranges span adjacent North American ecogeographic regions: the vast boreal forest belt and the temperate montane Appalachian forests. We detected concordant phylogeographic patterns in 11 of 12 species wherein populations from the southern Appalachians were genetically distinct from boreal belt populations. Our results reveal that small populations persisting in the southern Appalachian Mountains consistently harbor genetic diversity that is subtly distinct from much larger, widespread boreal populations of the same species. However, in most species, levels of standing genetic diversity were not significantly different between Appalachian and boreal populations despite the drastic difference in geographic extent of these populations. We found no evidence for shared signatures of selection across the genome, suggesting that the concordance of spatial genetic structure across species emerges from species-specific patterns of molecular divergence across the genome rather than parallel patterns of selection. Conservation of the Appalachian ecosystem would likely support maintenance of distinct genetic diversity in several migratory avian species with widespread distributions.},
	language = {en},
	number = {10},
	urldate = {2026-05-27},
	journal = {Evolutionary Applications},
	author = {Kimmitt, Abigail A. and Pegan, Teresa M. and Wacker, Kristen S. and Jones, Andrew W. and Winger, Benjamin M.},
	year = {2025},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/eva.70163},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {e70163},
}

Intraspecific genetic diversity across a species' geographic range is relevant to adaptive potential and long-term population persistence, and identifying genetically distinct groups within species can direct management decisions focused on conserving species-level genetic diversity. Comparative phylogeography using whole genome techniques allows for investigation of whether co-distributed species exhibit shared spatial genetic differentiation at fine spatial scales, thereby facilitating a comparative approach to both landscape and conservation genetics. By sequencing over 900 low-coverage whole genomes, we evaluated the concordance of genetic structure and diversity from 12 co-occurring species of migratory birds whose breeding ranges span adjacent North American ecogeographic regions: the vast boreal forest belt and the temperate montane Appalachian forests. We detected concordant phylogeographic patterns in 11 of 12 species wherein populations from the southern Appalachians were genetically distinct from boreal belt populations. Our results reveal that small populations persisting in the southern Appalachian Mountains consistently harbor genetic diversity that is subtly distinct from much larger, widespread boreal populations of the same species. However, in most species, levels of standing genetic diversity were not significantly different between Appalachian and boreal populations despite the drastic difference in geographic extent of these populations. We found no evidence for shared signatures of selection across the genome, suggesting that the concordance of spatial genetic structure across species emerges from species-specific patterns of molecular divergence across the genome rather than parallel patterns of selection. Conservation of the Appalachian ecosystem would likely support maintenance of distinct genetic diversity in several migratory avian species with widespread distributions.

@article{nichol_current_2025,
	title = {Current and future ecological niche of {Dermacentor} similis {Lado} ({Acari}: {Ixodidae}) in western {North} {America}},
	issn = {0022-2585},
	shorttitle = {Current and future ecological niche of {Dermacentor} similis {Lado} ({Acari}},
	url = {https://doi.org/10.1093/jme/tjaf087},
	doi = {10.1093/jme/tjaf087},
	abstract = {Dermacentor similis Lado (Acari: Ixodidae) is a newly described tick species within western North America. These ticks were previously referred to as “western Dermacentor variabilis (Say)” and were genetically distinct from D. variabilis in eastern North America. Despite the known genetic differences, the ecology of this species was not investigated separately from eastern populations of D. variabilis. Therefore, the objectives of this study were to describe the current and future areas of ecological suitability of D. similis in western North America, and to determine the bioclimatic and environmental variables of importance for ecological suitability of this species. Twenty-nine confirmed samples of D. similis from the western United States (California, Oregon, Washington, Idaho) and Canada (British Columbia) were used in species distribution model creation via MaxEnt. Seven variables were included in the final current species distribution model of D. similis: terrestrial ecoregion, degree-days below zero degrees Celsius, Hogg’s climate moisture index, mean annual relative humidity, day of the year on which the frost-free period begins, precipitation as snow, and extreme maximum temperature over thirty years. Under current conditions, high levels of ecological suitability were observed in the Okanagan region of British Columbia, Washington (extending into Oregon and Idaho), and regions of coastal and inland California. Future ecological suitability were similar to the current ecological suitability under both climate scenarios (2041 to 2070, SSP2-4.5 and SSP3-7.0). The results of this study will inform public and animal health messaging and awareness.},
	urldate = {2025-07-31},
	journal = {Journal of Medical Entomology},
	author = {Nichol, Grace K and Kulkarni, Manisha A and Dergousoff, Shaun J and Weese, J Scott and Greer, Amy L and Clow, Katie M},
	month = jul,
	year = {2025},
	keywords = {Terrestrial Ecoregions},
	pages = {tjaf087},
}

Dermacentor similis Lado (Acari: Ixodidae) is a newly described tick species within western North America. These ticks were previously referred to as “western Dermacentor variabilis (Say)” and were genetically distinct from D. variabilis in eastern North America. Despite the known genetic differences, the ecology of this species was not investigated separately from eastern populations of D. variabilis. Therefore, the objectives of this study were to describe the current and future areas of ecological suitability of D. similis in western North America, and to determine the bioclimatic and environmental variables of importance for ecological suitability of this species. Twenty-nine confirmed samples of D. similis from the western United States (California, Oregon, Washington, Idaho) and Canada (British Columbia) were used in species distribution model creation via MaxEnt. Seven variables were included in the final current species distribution model of D. similis: terrestrial ecoregion, degree-days below zero degrees Celsius, Hogg’s climate moisture index, mean annual relative humidity, day of the year on which the frost-free period begins, precipitation as snow, and extreme maximum temperature over thirty years. Under current conditions, high levels of ecological suitability were observed in the Okanagan region of British Columbia, Washington (extending into Oregon and Idaho), and regions of coastal and inland California. Future ecological suitability were similar to the current ecological suitability under both climate scenarios (2041 to 2070, SSP2-4.5 and SSP3-7.0). The results of this study will inform public and animal health messaging and awareness.

@article{tsalickis_distinct_2025,
	title = {Distinct latitudinal gradients define {Holocene} fire trends across the southeastern {USA}},
	volume = {350},
	issn = {0277-3791},
	url = {https://www.sciencedirect.com/science/article/pii/S0277379124006632},
	doi = {10.1016/j.quascirev.2024.109161},
	abstract = {Fire is a keystone ecological process that shapes and maintains ecosystems in the southeastern United States, and yet the paleofire history of the southeast remains relatively understudied. In this study, we conducted an extensive literature review to identify paleofire datasets in the region, and then compiled, normalized, and analyzed 15 records with varied temporal lengths. We compared these data to climate parameters from transient paleoclimate model simulations to examine the spatiotemporal variability of fire and to determine its climate drivers throughout the Holocene. Our findings are based on analyzing charcoal records in conjunction with modelled surface air temperature, precipitation, and burned area fraction during three specific time intervals: the early (12–7 ka), mid (7–4 ka), and late (4–0 ka) Holocene. We find that distinct latitudinal gradients define fire trends. We argue that precipitation is the primary factor controlling fire activity in the southeastern USA, as periods with the most pronounced trends in modelled burned area fraction correspond to times of reduced precipitation. Additionally, comparing modelled data across three southeastern regions (Southern Peninsula, Eastern Coastal Plain, and Inland) reveals that fire trends in the Southern Peninsula differ from those in the rest of the southeastern USA. A significant lack of paleofire and paleoclimate data in the southeastern USA compared to pollen-based vegetation reconstructions underscores the need for the development of new paleofire records in the region.},
	urldate = {2026-05-29},
	journal = {Quaternary Science Reviews},
	author = {Tsalickis, Alexandra and Vachula, Richard S. and Karmalkar, Ambarish V. and Balascio, Nicholas L. and Waters, Matthew N.},
	month = feb,
	year = {2025},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {109161},
}

Fire is a keystone ecological process that shapes and maintains ecosystems in the southeastern United States, and yet the paleofire history of the southeast remains relatively understudied. In this study, we conducted an extensive literature review to identify paleofire datasets in the region, and then compiled, normalized, and analyzed 15 records with varied temporal lengths. We compared these data to climate parameters from transient paleoclimate model simulations to examine the spatiotemporal variability of fire and to determine its climate drivers throughout the Holocene. Our findings are based on analyzing charcoal records in conjunction with modelled surface air temperature, precipitation, and burned area fraction during three specific time intervals: the early (12–7 ka), mid (7–4 ka), and late (4–0 ka) Holocene. We find that distinct latitudinal gradients define fire trends. We argue that precipitation is the primary factor controlling fire activity in the southeastern USA, as periods with the most pronounced trends in modelled burned area fraction correspond to times of reduced precipitation. Additionally, comparing modelled data across three southeastern regions (Southern Peninsula, Eastern Coastal Plain, and Inland) reveals that fire trends in the Southern Peninsula differ from those in the rest of the southeastern USA. A significant lack of paleofire and paleoclimate data in the southeastern USA compared to pollen-based vegetation reconstructions underscores the need for the development of new paleofire records in the region.

@phdthesis{gomez_garduno_distribucion_2025,
	title = {Distribución potencial del ocelote ({Leopardus} pardalis) en las áreas naturales protegidas de {México}},
	author = {Gómez Garduño, Mariana},
	year = {2025},
	note = {Publisher: México},
	keywords = {Terrestrial Ecoregions},
}

@phdthesis{rootes_eastern_2025,
	type = {Doctor of {Philosophy}},
	title = {Eastern {Spruce} {Budworm} {In} {The} {Great} {Lakes} {Region}: {Forest} {Regeneration}, {Natural} {Enemies}, {And} {Dispersal}},
	shorttitle = {Eastern {Spruce} {Budworm} {In} {The} {Great} {Lakes} {Region}},
	url = {https://hdl.handle.net/11299/279274},
	abstract = {The eastern spruce budworm (Choristoneura fumiferana Clemens), (Lepidoptera: Tortricidae), is native to northeastern North America and feeds primarily on balsam fir (Abies balsamea (L.) Mill) and white spruce (Picea glauca (Moench) Voss). Outbreaking populations have been mapped annually in Minnesota since 1954. This dissertation examines forest regeneration in areas of northeastern Minnesota and on Isle Royale 15 years following outbreaks of spruce budworm, the natural enemy communities in both locations, and examines the potential connectedness of regional populations in Minnesota and Wisconsin by looking for evidence of dispersal over a flight season using adult trap catches and meteorological modeling. On Isle Royale, trees suffered higher mortality and negative alterations to their growth compared to similar forests in Minnesota. Those results suggest a positive correlation between moose density and adverse effects on forest regeneration in areas recovering from an outbreak of spruce budworm and support the use of wolves as predators of moose on the island to restore ecological function. Late instar larvae and pupae of spruce budworm were sampled from current outbreaks in these same locations in 2023 and 2024. Though the diversity of the parasitoid community was similar between the two locations, Isle Royale demonstrated higher rates of parasitism (18.8\% to 33.7\%) than Minnesota (10.3\% to 17.1\%), suggesting that natural enemies in both locations are capable of assisting with mediation of outbreaking spruce budworm populations. Fluctuations in populations of spruce budworm are likely related not only to natural enemy populations but dispersal of adult spruce budworms. To assess dispersal, I evaluated ten areas in northeastern Minnesota and northern Wisconsin in summer 2024 using automatic trapping methods and meteorological modeling. I found that sub-populations of spruce budworm were highly synchronized and that trap captures were predicted by captures in neighboring sites, precipitation, temperature, wind speed, and landscape composition (i.e., percent of a putative trajectory over forest or open water). Outbreaks of spruce budworm are multi-faceted, impacted by factors such as natural enemies and regional-wide dispersal, and can result in cascading effects on forest regeneration and composition.},
	language = {en},
	urldate = {2026-06-01},
	school = {University of Minnesota},
	author = {Rootes, Jessica Michelle},
	month = dec,
	year = {2025},
	keywords = {NALCMS},
}

The eastern spruce budworm (Choristoneura fumiferana Clemens), (Lepidoptera: Tortricidae), is native to northeastern North America and feeds primarily on balsam fir (Abies balsamea (L.) Mill) and white spruce (Picea glauca (Moench) Voss). Outbreaking populations have been mapped annually in Minnesota since 1954. This dissertation examines forest regeneration in areas of northeastern Minnesota and on Isle Royale 15 years following outbreaks of spruce budworm, the natural enemy communities in both locations, and examines the potential connectedness of regional populations in Minnesota and Wisconsin by looking for evidence of dispersal over a flight season using adult trap catches and meteorological modeling. On Isle Royale, trees suffered higher mortality and negative alterations to their growth compared to similar forests in Minnesota. Those results suggest a positive correlation between moose density and adverse effects on forest regeneration in areas recovering from an outbreak of spruce budworm and support the use of wolves as predators of moose on the island to restore ecological function. Late instar larvae and pupae of spruce budworm were sampled from current outbreaks in these same locations in 2023 and 2024. Though the diversity of the parasitoid community was similar between the two locations, Isle Royale demonstrated higher rates of parasitism (18.8% to 33.7%) than Minnesota (10.3% to 17.1%), suggesting that natural enemies in both locations are capable of assisting with mediation of outbreaking spruce budworm populations. Fluctuations in populations of spruce budworm are likely related not only to natural enemy populations but dispersal of adult spruce budworms. To assess dispersal, I evaluated ten areas in northeastern Minnesota and northern Wisconsin in summer 2024 using automatic trapping methods and meteorological modeling. I found that sub-populations of spruce budworm were highly synchronized and that trap captures were predicted by captures in neighboring sites, precipitation, temperature, wind speed, and landscape composition (i.e., percent of a putative trajectory over forest or open water). Outbreaks of spruce budworm are multi-faceted, impacted by factors such as natural enemies and regional-wide dispersal, and can result in cascading effects on forest regeneration and composition.

@article{zhang_ecological_2025,
	title = {Ecological network construction and land degradation risk identification in the {Yellow} {River} source area},
	volume = {28},
	issn = {2589-0042},
	url = {https://www.cell.com/iscience/abstract/S2589-0042(25)01036-3},
	doi = {10.1016/j.isci.2025.112775},
	language = {English},
	number = {7},
	urldate = {2025-07-31},
	journal = {iScience},
	author = {Zhang, Haoxiang and Song, Qian and Wang, Shiru and Zhao, Jianyun and Gao, Wenming},
	month = jul,
	year = {2025},
	note = {Publisher: Elsevier},
	keywords = {Major Roads},
}

@article{xu_ecoregion-based_2025,
	title = {Ecoregion-{Based} {Landslide} {Susceptibility} {Mapping}: {A} {Spatially} {Partitioned} {Modeling} {Strategy} for {Oregon}, {USA}},
	volume = {15},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {2076-3417},
	shorttitle = {Ecoregion-{Based} {Landslide} {Susceptibility} {Mapping}},
	url = {https://www.mdpi.com/2076-3417/15/20/11242},
	doi = {10.3390/app152011242},
	abstract = {Conventional non-partitioned Landslide Susceptibility Mapping (LSM), which neglects geospatial heterogeneity, often has limitations in accurately capturing local risk patterns. To address this challenge, this study investigated the effectiveness of localized modeling in the environmentally diverse state of Oregon, USA, by comparing ecoregion-based local models with the non-partitioned model. We partitioned Oregon into seven distinct units using the U.S. Environmental Protection Agency (EPA) Level III Ecoregions and developed one global and seven local models with the eXtreme Gradient Boosting (XGBoost) algorithm. A comprehensive evaluation framework, including the Area Under the Curve (AUC), Landslide Density (LD), and the Total Deviation Index (TDI), was used to compare the models. The results demonstrated the clear superiority of the partitioned strategy. Moreover, different ecoregions were found to have distinct dominant landslide conditioning factors, revealing strong spatial non-stationarity. Although all models generated high AUC values ({\textgreater}0.93), LD analysis showed that the local models were significantly more efficient at identifying high-risk zones. This advantage was particularly pronounced in critical, landslide-prone western areas; for instance, in the Willamette–Georgia–Puget Lowland, the local model’s LD value in the ‘very high’ susceptibility class was over 3.5 times that of the global model. High TDI values (some {\textgreater}35\%) further confirmed fundamental spatial discrepancies between the risk maps obtained by the two strategies. This research substantiated that, in geographically complex terrains, partitioned modeling is an effective approach for more accurate and reliable LSM, providing a scientific basis for developing targeted regional disaster mitigation policies.},
	language = {en},
	number = {20},
	urldate = {2026-01-21},
	journal = {Applied Sciences},
	author = {Xu, Zhixiang and Zuo, Peng and Zhao, Wen and Zhou, Zeyu and Shao, Xiangyu and Yu, Junpo and Yu, Haize and Wang, Weijie and Gan, Junwei and Duan, Jinshun and Jin, Jiming},
	month = jan,
	year = {2025},
	note = {Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {NALCMS},
	pages = {11242},
}

Conventional non-partitioned Landslide Susceptibility Mapping (LSM), which neglects geospatial heterogeneity, often has limitations in accurately capturing local risk patterns. To address this challenge, this study investigated the effectiveness of localized modeling in the environmentally diverse state of Oregon, USA, by comparing ecoregion-based local models with the non-partitioned model. We partitioned Oregon into seven distinct units using the U.S. Environmental Protection Agency (EPA) Level III Ecoregions and developed one global and seven local models with the eXtreme Gradient Boosting (XGBoost) algorithm. A comprehensive evaluation framework, including the Area Under the Curve (AUC), Landslide Density (LD), and the Total Deviation Index (TDI), was used to compare the models. The results demonstrated the clear superiority of the partitioned strategy. Moreover, different ecoregions were found to have distinct dominant landslide conditioning factors, revealing strong spatial non-stationarity. Although all models generated high AUC values (\textgreater0.93), LD analysis showed that the local models were significantly more efficient at identifying high-risk zones. This advantage was particularly pronounced in critical, landslide-prone western areas; for instance, in the Willamette–Georgia–Puget Lowland, the local model’s LD value in the ‘very high’ susceptibility class was over 3.5 times that of the global model. High TDI values (some \textgreater35%) further confirmed fundamental spatial discrepancies between the risk maps obtained by the two strategies. This research substantiated that, in geographically complex terrains, partitioned modeling is an effective approach for more accurate and reliable LSM, providing a scientific basis for developing targeted regional disaster mitigation policies.

@article{talbot_enhancing_2025,
	title = {Enhancing physically based and distributed hydrological model calibration through internal state variable constraints},
	volume = {29},
	issn = {1027-5606},
	url = {https://hess.copernicus.org/articles/29/6549/2025/},
	doi = {10.5194/hess-29-6549-2025},
	abstract = {Accurately representing hydrological processes remains a major challenge in hydrological modeling. Recent studies have demonstrated the benefits of multi-variable calibration, which integrates additional hydrological variables such as evapotranspiration and soil moisture alongside streamflow to improve model realism. However, groundwater recharge as a calibration variable remains relatively underexplored.

 This study evaluates how incorporating groundwater recharge into the calibration of the Water Balance Simulation Model (WaSiM) affects hydrological variables representation. Three configurations were tested: Baseline (BL) with streamflow-only calibration, Physical Groundwater Model (GW) with physically-based groundwater flow, and Physical Groundwater with Recharge Calibration (GW-RC), which further constrains groundwater recharge during calibration. The models were calibrated and applied to 34 catchments in Southern Québec. Their performance was evaluated using the Kling-Gupta Efficiency (KGE) for streamflow and spatial estimates of groundwater recharge derived from a previous research project conducted in the same region.

 Results indicate that while calibrating on streamflow alone produces high KGE values (median KGE = 0.83 for GW and 0.82 for BL), but it comes at the cost of misrepresenting subsurface hydrological processes. Adding groundwater recharge constraints (GW-RC) reduce streamflow performance, with a median KGE of 0.77 for GW-RC, but improves hydrological variable representation, especially in seasonal runoff patterns, where it better captures the balance between surface runoff and interflow during snowmelt. Additionally, GW-RC showed the smallest differences with the groundwater recharge estimates.

 These findings illustrate the consequence of equifinality in streamflow-based calibration, where multiple parameter sets can yield similar streamflow outputs while misrepresenting internal hydrological processes. Incorporating groundwater recharge constraints improves the representation of internal hydrological processes while maintaining strong streamflow simulation performance, which could ultimately enhance reliability of climate change adaptation and water resource management strategies.},
	language = {English},
	number = {22},
	urldate = {2026-01-21},
	journal = {Hydrology and Earth System Sciences},
	author = {Talbot, Frédéric and Sylvain, Jean-Daniel and Drolet, Guillaume and Poulin, Annie and Arsenault, Richard},
	month = nov,
	year = {2025},
	note = {Publisher: Copernicus GmbH},
	keywords = {NALCMS},
	pages = {6549--6576},
}

Accurately representing hydrological processes remains a major challenge in hydrological modeling. Recent studies have demonstrated the benefits of multi-variable calibration, which integrates additional hydrological variables such as evapotranspiration and soil moisture alongside streamflow to improve model realism. However, groundwater recharge as a calibration variable remains relatively underexplored. This study evaluates how incorporating groundwater recharge into the calibration of the Water Balance Simulation Model (WaSiM) affects hydrological variables representation. Three configurations were tested: Baseline (BL) with streamflow-only calibration, Physical Groundwater Model (GW) with physically-based groundwater flow, and Physical Groundwater with Recharge Calibration (GW-RC), which further constrains groundwater recharge during calibration. The models were calibrated and applied to 34 catchments in Southern Québec. Their performance was evaluated using the Kling-Gupta Efficiency (KGE) for streamflow and spatial estimates of groundwater recharge derived from a previous research project conducted in the same region. Results indicate that while calibrating on streamflow alone produces high KGE values (median KGE = 0.83 for GW and 0.82 for BL), but it comes at the cost of misrepresenting subsurface hydrological processes. Adding groundwater recharge constraints (GW-RC) reduce streamflow performance, with a median KGE of 0.77 for GW-RC, but improves hydrological variable representation, especially in seasonal runoff patterns, where it better captures the balance between surface runoff and interflow during snowmelt. Additionally, GW-RC showed the smallest differences with the groundwater recharge estimates. These findings illustrate the consequence of equifinality in streamflow-based calibration, where multiple parameter sets can yield similar streamflow outputs while misrepresenting internal hydrological processes. Incorporating groundwater recharge constraints improves the representation of internal hydrological processes while maintaining strong streamflow simulation performance, which could ultimately enhance reliability of climate change adaptation and water resource management strategies.

@article{abud-russell_environmental_2025,
	title = {Environmental evidence of surface manifestations of regional groundwater flows in the lower {Colorado} {River} {Basin}: the case {Mexicali} {Valley}, {Mexico}},
	volume = {31},
	issn = {2352-801X},
	shorttitle = {Environmental evidence of surface manifestations of regional groundwater flows in the lower {Colorado} {River} {Basin}},
	url = {https://www.sciencedirect.com/science/article/pii/S2352801X25001079},
	doi = {10.1016/j.gsd.2025.101510},
	abstract = {Transboundary water in the Lower Colorado River Basin, shared between Mexico and the United States, demands robust, collaborative governance frameworks to address drought and increasing water demands. Although groundwater resources have become increasingly strategic for meeting water demands in both countries, they rarely receive formal consideration in official studies. Through geospatial analysis, this research delineates for the US portion of the Lower Colorado River Basin, the spatial distribution of recharge and discharge zones within the interconnected groundwater and surface water systems to characterize the regional components of groundwater flow. Employing a methodology based on the Tóthian framework of gravity-driven groundwater flow systems, the study emphasizes the interconnection of groundwater with perennial surface water, soil taxonomy, land use and land-forms as indirect evidence of its surface manifestation throughout this basin. The results are represented in discharge and recharge zones related to regional groundwater flow. Results highlight the need for binational data homologation and integration process to strengthen the available groundwater assessment tools for sustainable management in the U.S.-Mexico border.},
	urldate = {2026-01-21},
	journal = {Groundwater for Sustainable Development},
	author = {Abud-Russell, Yussef Ricardo and Hatch-Kuri, Gonzalo and Lara, María del Carmen Carmona and Aguilar-Castillo, Tatiana},
	month = nov,
	year = {2025},
	keywords = {NALCMS},
	pages = {101510},
}

Transboundary water in the Lower Colorado River Basin, shared between Mexico and the United States, demands robust, collaborative governance frameworks to address drought and increasing water demands. Although groundwater resources have become increasingly strategic for meeting water demands in both countries, they rarely receive formal consideration in official studies. Through geospatial analysis, this research delineates for the US portion of the Lower Colorado River Basin, the spatial distribution of recharge and discharge zones within the interconnected groundwater and surface water systems to characterize the regional components of groundwater flow. Employing a methodology based on the Tóthian framework of gravity-driven groundwater flow systems, the study emphasizes the interconnection of groundwater with perennial surface water, soil taxonomy, land use and land-forms as indirect evidence of its surface manifestation throughout this basin. The results are represented in discharge and recharge zones related to regional groundwater flow. Results highlight the need for binational data homologation and integration process to strengthen the available groundwater assessment tools for sustainable management in the U.S.-Mexico border.

@article{cathcart_estimates_2025,
	title = {Estimates of critical loads and exceedances of acidity and nutrient nitrogen for mineral soils in {Canada} for 2014–2016 average annual sulfur and nitrogen atmospheric deposition},
	volume = {22},
	issn = {1726-4170},
	url = {https://bg.copernicus.org/articles/22/535/2025/},
	doi = {10.5194/bg-22-535-2025},
	abstract = {The steady-state simple mass balance model was applied to natural and semi-natural terrestrial ecosystems across Canada to produce nation-wide critical loads of acidity (maximum sulfur, CLmaxS; maximum nitrogen, CLmaxN; minimum nitrogen, CLminN) and nutrient nitrogen (CLnutN) at 250 m resolution. Parameterisation of the model for Canadian ecosystems was considered with attention to the selection of the chemical criterion for damage at a site-specific resolution, with comparison between protection levels of 5 \% and 20 \% growth reduction (approximating commonly chosen base-cation-to-aluminum ratios of 1 and 10, respectively). Other parameters explored include modelled base cation deposition and site-specific nutrient and base cation uptake estimates based on North American tree chemistry data and tree species and biomass maps. Critical loads of acidity were estimated to be low (e.g., below 500 eq. ha−1 yr−1) for much of the country, particularly above 60° N latitude, where base cation weathering rates are low due to cold annual average temperature. Exceedances were mapped relative to annual sulfur and nitrogen deposition averaged over 2014–2016. Results show that under a conservative estimate (5 \% protection level), 10 \% of Canada's protected and conserved areas in the study area experienced exceedance of some level of the soil critical load of acidity, while 70 \% experienced exceedance of the soil critical load of nutrient nitrogen.},
	language = {English},
	number = {2},
	urldate = {2025-07-31},
	journal = {Biogeosciences},
	author = {Cathcart, Hazel and Aherne, Julian and Moran, Michael D. and Savic-Jovcic, Verica and Makar, Paul A. and Cole, Amanda},
	month = jan,
	year = {2025},
	note = {Publisher: Copernicus GmbH},
	keywords = {NALCMS},
	pages = {535--554},
}

The steady-state simple mass balance model was applied to natural and semi-natural terrestrial ecosystems across Canada to produce nation-wide critical loads of acidity (maximum sulfur, CLmaxS; maximum nitrogen, CLmaxN; minimum nitrogen, CLminN) and nutrient nitrogen (CLnutN) at 250 m resolution. Parameterisation of the model for Canadian ecosystems was considered with attention to the selection of the chemical criterion for damage at a site-specific resolution, with comparison between protection levels of 5 % and 20 % growth reduction (approximating commonly chosen base-cation-to-aluminum ratios of 1 and 10, respectively). Other parameters explored include modelled base cation deposition and site-specific nutrient and base cation uptake estimates based on North American tree chemistry data and tree species and biomass maps. Critical loads of acidity were estimated to be low (e.g., below 500 eq. ha−1 yr−1) for much of the country, particularly above 60° N latitude, where base cation weathering rates are low due to cold annual average temperature. Exceedances were mapped relative to annual sulfur and nitrogen deposition averaged over 2014–2016. Results show that under a conservative estimate (5 % protection level), 10 % of Canada's protected and conserved areas in the study area experienced exceedance of some level of the soil critical load of acidity, while 70 % experienced exceedance of the soil critical load of nutrient nitrogen.

@techreport{olson_estimating_2025,
	title = {Estimating flood discharges at selected annual exceedance probabilities for unregulated, rural streams in {Vermont}, 2023},
	url = {https://pubs.usgs.gov/publication/sir20255088},
	abstract = {This report provides estimates of flood discharge at selected annual exceedance probabilities (AEPs) for streamgages in and adjacent to Vermont and equations for estimating flood discharges at AEPs of 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent (recurrence intervals of 2-, 5-, 10-, 25-, 50-, 100-, and 500-years, respectively) for ungaged, unregulated, rural streams in Vermont with drainage areas between 0.47 and 851 square miles. The equations were developed using generalized least-squares regression and flood-frequency and drainage-basin characteristics from 156 streamgages. Flood-frequency analyses were completed using data through the 2023 water year. The drainage-basin characteristics used as explanatory variables in the regression equations are drainage area, percentage of wetland area, and basin-wide mean of the average annual precipitation. The average standard errors of prediction used to estimate flood discharges at the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent AEP with these equations are 34.9, 37.1, 38.2, 41.6,...},
	language = {en},
	number = {2025-5088},
	urldate = {2026-01-21},
	institution = {U.S. Geological Survey},
	author = {Olson, Scott A.},
	year = {2025},
	doi = {10.3133/sir20255088},
	note = {ISSN: 2328-0328
Publication Title: Scientific Investigations Report},
	keywords = {NALCMS},
}

This report provides estimates of flood discharge at selected annual exceedance probabilities (AEPs) for streamgages in and adjacent to Vermont and equations for estimating flood discharges at AEPs of 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent (recurrence intervals of 2-, 5-, 10-, 25-, 50-, 100-, and 500-years, respectively) for ungaged, unregulated, rural streams in Vermont with drainage areas between 0.47 and 851 square miles. The equations were developed using generalized least-squares regression and flood-frequency and drainage-basin characteristics from 156 streamgages. Flood-frequency analyses were completed using data through the 2023 water year. The drainage-basin characteristics used as explanatory variables in the regression equations are drainage area, percentage of wetland area, and basin-wide mean of the average annual precipitation. The average standard errors of prediction used to estimate flood discharges at the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent AEP with these equations are 34.9, 37.1, 38.2, 41.6,...

@phdthesis{collinge_evaluating_2025,
	title = {Evaluating {Drivers} of {Spatial} {Distribution} for the {Endangered} {Eastern} {Red} {Bat} ({Lasiurus} borealis) {Under} {Climate} {Change}},
	url = {https://hdl.handle.net/1807/142688},
	abstract = {Understanding how climatic conditions and biotic interactions impact species distributions is essential for effective biodiversity conservation. The eastern red bat (Lasiurus borealis), a migratory species recently designated endangered in Canada, is particularly threatened by the rapid development of wind energy. Protection of this species is contingent on information about where it roosts, forages, and migrates within its range, which is currently lacking. Here, I investigated changes in the bat’s migration phenology over the past century and modelled its contemporary and future distribution based on a range of climatic, anthropogenic and biotic variables. I found that bats appear to migrate earlier in spring and later in autumn, that temperature and forest type are key to predicting their distribution, and that their seasonal range is projected to shift northward, but also contract, under climate change. These results highlight the importance of including spatial and temporal considerations in conservation planning.},
	language = {en},
	urldate = {2025-07-31},
	author = {Collinge, Germain},
	month = mar,
	year = {2025},
	keywords = {NALCMS},
}

Understanding how climatic conditions and biotic interactions impact species distributions is essential for effective biodiversity conservation. The eastern red bat (Lasiurus borealis), a migratory species recently designated endangered in Canada, is particularly threatened by the rapid development of wind energy. Protection of this species is contingent on information about where it roosts, forages, and migrates within its range, which is currently lacking. Here, I investigated changes in the bat’s migration phenology over the past century and modelled its contemporary and future distribution based on a range of climatic, anthropogenic and biotic variables. I found that bats appear to migrate earlier in spring and later in autumn, that temperature and forest type are key to predicting their distribution, and that their seasonal range is projected to shift northward, but also contract, under climate change. These results highlight the importance of including spatial and temporal considerations in conservation planning.

@phdthesis{diprima_evaluating_2025,
	title = {Evaluating the {Causes} of {Land} {Subsidence} on the {U}.{S}. {Mid}-{Atlantic} {Coast} {Measured} with {InSAR}},
	url = {https://scholars.unh.edu/honors/883},
	author = {DiPrima, Jordan},
	month = jan,
	year = {2025},
	keywords = {NALCMS},
}

@article{villaruel_evaluating_2025,
	title = {Evaluating time-lagged relationships between groundwater storage and river discharge using {GRACE}-based data: insights from the {Potomac} {Basin}},
	volume = {7},
	issn = {2515-7620},
	shorttitle = {Evaluating time-lagged relationships between groundwater storage and river discharge using {GRACE}-based data},
	url = {https://dx.doi.org/10.1088/2515-7620/ade36f},
	doi = {10.1088/2515-7620/ade36f},
	abstract = {This study evaluates the utility of a recently available GRACE-based groundwater drought index (GDI) in supporting regional water supply management, with application to the Potomac River Basin, in the U.S. Middle Atlantic region. As the primary drinking water source for the Washington Metropolitan Area (WMA), effective management of the Potomac River’s resources is critical, especially in the context of climate change, with the expected increase in severity and frequency of extreme events. Our analysis integrates 22 years of data, including GRACE-based groundwater storage (GWS) index estimates, river discharge (Q) measurements, and meteorological records, to investigate trends and predictive relationships between past GWS, as determined by the GRACE-based drought index, and streamflow. Seasonal Mann-Kendall trend analyses consistently identified severe declining trends in groundwater storage (GWS), as well as moderate declines in minimum streamflow and well water levels over the past 22 years. Granger Causality (GC) tests revealed significant time lags of 49 weeks to 22 months at weekly and monthly scales, respectively depending on a region’s hydrogeomorphic characteristics. Vector Autoregressive (VAR) Models and Forecast Error Variance Decomposition (FEVD) highlighted the variable contributions of precipitation and temperature to the GWS-Q relationship, revealing a strong autoregressive component of Q, but also reveal that GWS plays an important role, and this role increases with time. These findings underscore the interconnectedness of groundwater and surface water systems and the importance of integrated predictive models to enhance water management strategies. Incorporating GRACE-based seasonal groundwater forecasts into drought preparedness tools could bolster efforts to mitigate regional climate change impacts and improve the resilience of water resources in the Potomac River Basin. While practical use of native GRACE data has been challenging for local, small-scale applications, this study demonstrates the utility of the GRACE-based GDI in forecasting low flows and informing regional water resource management decisions during droughts.},
	language = {en},
	number = {7},
	urldate = {2025-07-31},
	journal = {Environmental Research Communications},
	author = {Villaruel, AJ and Seck, Alimatou and Schultz, Cherie},
	month = jul,
	year = {2025},
	note = {Publisher: IOP Publishing},
	keywords = {NALCMS},
	pages = {075003},
}

This study evaluates the utility of a recently available GRACE-based groundwater drought index (GDI) in supporting regional water supply management, with application to the Potomac River Basin, in the U.S. Middle Atlantic region. As the primary drinking water source for the Washington Metropolitan Area (WMA), effective management of the Potomac River’s resources is critical, especially in the context of climate change, with the expected increase in severity and frequency of extreme events. Our analysis integrates 22 years of data, including GRACE-based groundwater storage (GWS) index estimates, river discharge (Q) measurements, and meteorological records, to investigate trends and predictive relationships between past GWS, as determined by the GRACE-based drought index, and streamflow. Seasonal Mann-Kendall trend analyses consistently identified severe declining trends in groundwater storage (GWS), as well as moderate declines in minimum streamflow and well water levels over the past 22 years. Granger Causality (GC) tests revealed significant time lags of 49 weeks to 22 months at weekly and monthly scales, respectively depending on a region’s hydrogeomorphic characteristics. Vector Autoregressive (VAR) Models and Forecast Error Variance Decomposition (FEVD) highlighted the variable contributions of precipitation and temperature to the GWS-Q relationship, revealing a strong autoregressive component of Q, but also reveal that GWS plays an important role, and this role increases with time. These findings underscore the interconnectedness of groundwater and surface water systems and the importance of integrated predictive models to enhance water management strategies. Incorporating GRACE-based seasonal groundwater forecasts into drought preparedness tools could bolster efforts to mitigate regional climate change impacts and improve the resilience of water resources in the Potomac River Basin. While practical use of native GRACE data has been challenging for local, small-scale applications, this study demonstrates the utility of the GRACE-based GDI in forecasting low flows and informing regional water resource management decisions during droughts.

@phdthesis{lohman_exploring_2025,
	address = {Reno},
	type = {Master of {Science}},
	title = {Exploring regionalization techniques: {Simulation} and application in ecology},
	url = {https://scholarwolf.unr.edu/items/408d3d04-2da1-43cc-997e-d12f534ea820},
	language = {English},
	urldate = {2026-06-01},
	school = {University of Nevada - Reno},
	author = {Lohman, Madeleine},
	month = dec,
	year = {2025},
	keywords = {NALCMS},
}

@techreport{us_fish__wildlife_service_final_2025,
	title = {Final {Environmental} {Assessment} for the {Multi}-{Bat} {Species} {General} {Conservation} {Plan} for {NY}, {PA}, and {WV} {\textbar} {FWS}.gov},
	url = {https://www.fws.gov/media/final-environmental-assessment-multi-bat-species-general-conservation-plan-ny-pa-and-wv},
	language = {en},
	urldate = {2026-05-29},
	author = {{U.S. Fish \& Wildlife Service}},
	month = dec,
	year = {2025},
	keywords = {Terrestrial Ecoregions (CEC 1997), Terrestrial Ecoregions (Griffith 2010)},
}

@phdthesis{bradford_finding_2025,
	title = {Finding {Space} for the {Island} {Marble} {Butterfly}: {Modeling} the {Habitat} of a {Highly} {Endangered} {Endemic} {Butterfly} in the {Salish} {Sea} {Ecoregion}},
	shorttitle = {Finding {Space} for the {Island} {Marble} {Butterfly}},
	url = {https://cedar.wwu.edu/wwuet/1429},
	school = {Western Washington University},
	author = {Bradford, Emily},
	month = jan,
	year = {2025},
	keywords = {NALCMS},
}

@phdthesis{alexander_flexible_2025,
	title = {Flexible {Earth}: {A} {Housing} {Model} for {Adaptive} {Communities}},
	copyright = {http://rightsstatements.org/vocab/InC/1.0/},
	shorttitle = {{FLEXIBLE} {EARTH}},
	url = {https://repository.arizona.edu/handle/10150/677767},
	abstract = {Since the 19th-century Gold Rush, Americans have steadily moved westward in search of new opportunities. Even after the end of the Gold Rush, people have found reason to move: the climate, land availability, and perceived health benefits. Between 2020 and 2021, five of the top fifteen cities with the highest population increase were in Arizona, and eleven of them are located in the west (US Census Bureau). This growth has amplified the need for housing and infrastructure. Since the end of World War II, tract homes have been growing in popularity and quantity. Their modularity and repeatability allow for quick assembly, offering benefits such as privacy, perceived safety, affordability, and wide availability. The problems lie in the negative effect this construction type has on the environment, lack of consideration for climate and location, distance from amenities (therefore increasing dependence on automobiles), and the fact that these homes are not always affordable to first-time home buyers or low-income families. This work considers alternatives to conventional tract homes in the southwest through the use of traditional building materials in tandem with contemporary construction technologies. Pre-industrialization and pre-globalization architecture was designed with the location and context in mind, leading to location-specific design that relied heavily on passive strategies suited to the local climate. As the planet continues to see the effects of climate change and extreme weather become more frequent, responding to both the current and future environmental conditions is more important than ever. The solution proposed is automated earth construction, a plentiful and reusable material well-suited to arid climates. Not only is earth readily available, but it is also sound-deadening, insulating, fire-resistant, durable, and non-toxic. However, earth construction remains labor-intensive and costly - not due to the material cost, but the labor - a disadvantage that can be mitigated through computer-automated fabrication.

As computer-automated construction methods - like 3D printing - become more affordable and available, there is an opportunity to combine the speed and scalability of tract home construction with the environmental responsiveness and sustainability of more traditional methods.},
	language = {en},
	urldate = {2025-07-31},
	author = {Alexander, Oliver},
	year = {2025},
	note = {Accepted: 2025-07-16T17:40:15Z
Publisher: The University of Arizona.},
	keywords = {Climate Zones},
}

Since the 19th-century Gold Rush, Americans have steadily moved westward in search of new opportunities. Even after the end of the Gold Rush, people have found reason to move: the climate, land availability, and perceived health benefits. Between 2020 and 2021, five of the top fifteen cities with the highest population increase were in Arizona, and eleven of them are located in the west (US Census Bureau). This growth has amplified the need for housing and infrastructure. Since the end of World War II, tract homes have been growing in popularity and quantity. Their modularity and repeatability allow for quick assembly, offering benefits such as privacy, perceived safety, affordability, and wide availability. The problems lie in the negative effect this construction type has on the environment, lack of consideration for climate and location, distance from amenities (therefore increasing dependence on automobiles), and the fact that these homes are not always affordable to first-time home buyers or low-income families. This work considers alternatives to conventional tract homes in the southwest through the use of traditional building materials in tandem with contemporary construction technologies. Pre-industrialization and pre-globalization architecture was designed with the location and context in mind, leading to location-specific design that relied heavily on passive strategies suited to the local climate. As the planet continues to see the effects of climate change and extreme weather become more frequent, responding to both the current and future environmental conditions is more important than ever. The solution proposed is automated earth construction, a plentiful and reusable material well-suited to arid climates. Not only is earth readily available, but it is also sound-deadening, insulating, fire-resistant, durable, and non-toxic. However, earth construction remains labor-intensive and costly - not due to the material cost, but the labor - a disadvantage that can be mitigated through computer-automated fabrication. As computer-automated construction methods - like 3D printing - become more affordable and available, there is an opportunity to combine the speed and scalability of tract home construction with the environmental responsiveness and sustainability of more traditional methods.

@article{bellamy_forcing_2025,
	title = {Forcing {Mechanisms} of {Strong} {Surface} {Winds} in a {Dust} {Storm}–{Prone}, {High}-{Latitude} {Proglacial} {Valley}},
	url = {https://journals.ametsoc.org/view/journals/apme/64/1/JAMC-D-24-0044.1.xml},
	doi = {10.1175/JAMC-D-24-0044.1},
	abstract = {Proglacial valleys are important historical and contemporary sources of mineral dust emissions. These dust sources are situated within a complex mountainous terrain, which induce a series of superimposed meteorological phenomena. This paper assesses the forcing mechanisms of high wind speed (HWS) events in the dust storm–prone A’ą¨y Chu (Slims River) valley in southwest Yukon, Canada (60.96°N, 138.60°W). The period of 7 July 2021–30 September 2022 (≈15 months) is examined using surface meteorological stations distributed within and near the valley. A hierarchical indexing approach is applied, supported by high-resolution Weather Research and Forecasting (WRF) simulations, to identify dominant meteorological forcing mechanisms of strong wind events. Half (50.0\%) of HWS events in the valley occur under high above-valley wind speeds. Little evidence was found that off-glacier winds drive HWS, despite frequent attribution of these winds to local dust emissions in the literature. A summertime valley wind system is likely responsible for persistent nocturnal HWS near the valley delta (61.00°N, 138.52°W), contributing to the 28\% of summer HWS under distinctly calm aloft conditions. Efforts to constrain HWS characteristics from ambient conditions were not successful, partly confounded by adjacent valley wind systems. Ascertaining the configuration of phenomena responsible for high surface winds in these locations is key to yielding the predictive capacity of dust emissions from these rapidly deglaciating landscapes. Significance Statement Mineral dust emissions from high-latitude ({\textgreater}50°N) regions are poorly represented in current modeling approaches. Many dust sources are situated in a mountainous terrain, which heavily influences local wind systems. We investigated the drivers of strong surface winds in the A’ą¨y Chu valley (Canada) with a combination of surface observations and meteorological modeling. The relative importance of different meteorological systems is identified, indicating key phenomena to resolve in future efforts to simulate mineral dust emissions from this region and quantify contributions to the global dust budget.},
	language = {en},
	urldate = {2025-07-31},
	author = {Bellamy, Daniel and Nadeau, Daniel F. and King, James},
	month = jan,
	year = {2025},
	note = {Section: Journal of Applied Meteorology and Climatology},
	keywords = {NALCMS},
}

Proglacial valleys are important historical and contemporary sources of mineral dust emissions. These dust sources are situated within a complex mountainous terrain, which induce a series of superimposed meteorological phenomena. This paper assesses the forcing mechanisms of high wind speed (HWS) events in the dust storm–prone A’ą¨y Chu (Slims River) valley in southwest Yukon, Canada (60.96°N, 138.60°W). The period of 7 July 2021–30 September 2022 (≈15 months) is examined using surface meteorological stations distributed within and near the valley. A hierarchical indexing approach is applied, supported by high-resolution Weather Research and Forecasting (WRF) simulations, to identify dominant meteorological forcing mechanisms of strong wind events. Half (50.0%) of HWS events in the valley occur under high above-valley wind speeds. Little evidence was found that off-glacier winds drive HWS, despite frequent attribution of these winds to local dust emissions in the literature. A summertime valley wind system is likely responsible for persistent nocturnal HWS near the valley delta (61.00°N, 138.52°W), contributing to the 28% of summer HWS under distinctly calm aloft conditions. Efforts to constrain HWS characteristics from ambient conditions were not successful, partly confounded by adjacent valley wind systems. Ascertaining the configuration of phenomena responsible for high surface winds in these locations is key to yielding the predictive capacity of dust emissions from these rapidly deglaciating landscapes. Significance Statement Mineral dust emissions from high-latitude (\textgreater50°N) regions are poorly represented in current modeling approaches. Many dust sources are situated in a mountainous terrain, which heavily influences local wind systems. We investigated the drivers of strong surface winds in the A’ą¨y Chu valley (Canada) with a combination of surface observations and meteorological modeling. The relative importance of different meteorological systems is identified, indicating key phenomena to resolve in future efforts to simulate mineral dust emissions from this region and quantify contributions to the global dust budget.

@article{martin_coastlines_2025,
	title = {From coastlines to mountain crests: {Regional} and continental variation in {North} {American} marten diet and foraging},
	volume = {16},
	copyright = {© 2025 The Author(s). Ecosphere published by Wiley Periodicals LLC on behalf of The Ecological Society of America.},
	issn = {2150-8925},
	shorttitle = {From coastlines to mountain crests},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/ecs2.70460},
	doi = {10.1002/ecs2.70460},
	abstract = {Dietary plasticity is an important trait in an increasingly dynamic world and can reveal how species respond to changes in resource availability, intra- or interspecific interactions, and landscape structure. Small-bodied carnivores occupy a unique trophic position as both consumers and prey while also filling critical roles in species interactions and provisioning of ecological services. Nonetheless, dietary patterns and factors that influence small carnivore foraging are often poorly understood, despite the ecological importance of carnivoran taxa. Here, we examined the diet and foraging of North American martens (Martes spp.), small-bodied mustelids often described as dietary generalists whose foraging patterns are assumed to be influenced by intrinsic and extrinsic factors (e.g., habitat and geography). We used complementary analyses to consider marten diet and foraging at two spatial scales: (1) regionally, using new empirical data collected in the coastal and montane forests of western Oregon and northern California; and (2) continentally, by reviewing and synthesizing previous studies of American (Martes americana) and Pacific martens (Martes caurina) across their North American distributions. Regionally, taxonomic richness and focal prey species varied among sampling sites, while forest cover and edge density had strong, contrasting effects on marten foraging patterns. Continentally, marten diet differed among coastal and interior ecoregions, but foraging did not vary substantially among studies when considering study characteristics. Martens exhibited high dietary plasticity and consumed a remarkable diversity of food items across new and synthesized data, although small mammals and birds were omnipresent prey. A diverse diet and flexible foraging, resulting in facultative variation among and within populations rather than obligate dependence on certain prey taxa, may be an important mechanism by which martens segregate niches with other carnivores or adjust to changing biotic or abiotic conditions. Our findings highlight the need to increase information on sensitive carnivore species, with particular regard to ecological and energetic requirements, to support their continued persistence.},
	language = {en},
	number = {11},
	urldate = {2026-01-21},
	journal = {Ecosphere},
	author = {Martin, Marie E. and Delheimer, Matthew S. and Roddy, Alyssa M. and Moriarty, Katie M. and Eriksson, Charlotte E. and Gunther, Micaela S. and Hartman, Jennifer and Smith, B. Heath and Levi, Taal},
	year = {2025},
	note = {\_eprint: https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.70460},
	keywords = {Terrestrial Ecoregions (CEC 1997)},
	pages = {e70460},
}

Dietary plasticity is an important trait in an increasingly dynamic world and can reveal how species respond to changes in resource availability, intra- or interspecific interactions, and landscape structure. Small-bodied carnivores occupy a unique trophic position as both consumers and prey while also filling critical roles in species interactions and provisioning of ecological services. Nonetheless, dietary patterns and factors that influence small carnivore foraging are often poorly understood, despite the ecological importance of carnivoran taxa. Here, we examined the diet and foraging of North American martens (Martes spp.), small-bodied mustelids often described as dietary generalists whose foraging patterns are assumed to be influenced by intrinsic and extrinsic factors (e.g., habitat and geography). We used complementary analyses to consider marten diet and foraging at two spatial scales: (1) regionally, using new empirical data collected in the coastal and montane forests of western Oregon and northern California; and (2) continentally, by reviewing and synthesizing previous studies of American (Martes americana) and Pacific martens (Martes caurina) across their North American distributions. Regionally, taxonomic richness and focal prey species varied among sampling sites, while forest cover and edge density had strong, contrasting effects on marten foraging patterns. Continentally, marten diet differed among coastal and interior ecoregions, but foraging did not vary substantially among studies when considering study characteristics. Martens exhibited high dietary plasticity and consumed a remarkable diversity of food items across new and synthesized data, although small mammals and birds were omnipresent prey. A diverse diet and flexible foraging, resulting in facultative variation among and within populations rather than obligate dependence on certain prey taxa, may be an important mechanism by which martens segregate niches with other carnivores or adjust to changing biotic or abiotic conditions. Our findings highlight the need to increase information on sensitive carnivore species, with particular regard to ecological and energetic requirements, to support their continued persistence.

@article{doornik_genetic_2025,
	title = {Genetic monitoring of a long-term, large-scale experimental steelhead supplementation program},
	volume = {20},
	issn = {1932-6203},
	url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0339458},
	doi = {10.1371/journal.pone.0339458},
	abstract = {Declining salmonid populations often prompt the use of captive-reared fish to supplement wild stocks, but such programs risk negative genetic and ecological impacts. We evaluated six steelhead (Oncorhynchus mykiss) populations in the Hood Canal watershed, Puget Sound, Washington, including three supplemented and three unsupplemented control populations, over the span of 17 years to assess the effects of supplementation on several population genetics metrics. This program uniquely allowed natural spawning to occur before removing eyed eggs from redds for captive rearing, and later release as smolts or adults. Key genetic metrics—expected heterozygosity, allelic richness, and effective population size—remained stable from before to after supplementation in both the supplemented and non-supplemented populations. Parentage analyses confirmed successful reproduction by captively reared adults after they were released into the wild. These findings suggest that natural spawning prior to captive rearing, among other aspects of the program, lessened the genetic risks typically associated with artificial propagation such as loss of genetic diversity, or a reduction in effective population size. Our results highlight the potential for carefully designed supplementation programs to conserve genetic diversity and maintain effective population sizes in threatened steelhead populations.},
	language = {en},
	number = {12},
	urldate = {2026-01-21},
	journal = {PLOS ONE},
	author = {Doornik, Donald M. Van and Berejikian, Barry A. and Claiborne, Andrew M.},
	month = dec,
	year = {2025},
	note = {Publisher: Public Library of Science},
	keywords = {Lakes \& Rivers},
	pages = {e0339458},
}

Declining salmonid populations often prompt the use of captive-reared fish to supplement wild stocks, but such programs risk negative genetic and ecological impacts. We evaluated six steelhead (Oncorhynchus mykiss) populations in the Hood Canal watershed, Puget Sound, Washington, including three supplemented and three unsupplemented control populations, over the span of 17 years to assess the effects of supplementation on several population genetics metrics. This program uniquely allowed natural spawning to occur before removing eyed eggs from redds for captive rearing, and later release as smolts or adults. Key genetic metrics—expected heterozygosity, allelic richness, and effective population size—remained stable from before to after supplementation in both the supplemented and non-supplemented populations. Parentage analyses confirmed successful reproduction by captively reared adults after they were released into the wild. These findings suggest that natural spawning prior to captive rearing, among other aspects of the program, lessened the genetic risks typically associated with artificial propagation such as loss of genetic diversity, or a reduction in effective population size. Our results highlight the potential for carefully designed supplementation programs to conserve genetic diversity and maintain effective population sizes in threatened steelhead populations.

@phdthesis{gibbons_genetic_2025,
	title = {Genetic, {Morphological}, {Phenological}, and {Mycorrhizal} {Aspects} {That} {Define} {American} {Beachgrass} in {Northeastern} {Freshwater} {Ecosystems} - {College} of {Environmental} {Science} and {Forestry}},
	url = {https://experts.esf.edu/esploro/outputs/graduate/Genetic-Morphological-Phenological-and-Mycorrhizal-Aspects/99988626204826?institution=01SUNY_ESF},
	urldate = {2026-01-21},
	school = {State University of New York},
	author = {Gibbons, Clay},
	month = apr,
	year = {2025},
}

@article{home_geographic_2025,
	title = {Geographic distribution, habitat suitability, and habitat loss of plains rough fescue ({Festuca} hallii ({Vasey}) {Piper}) in {North} {America}},
	volume = {103},
	issn = {1916-2790},
	url = {https://cdnsciencepub.com/doi/full/10.1139/cjb-2025-0057},
	doi = {10.1139/cjb-2025-0057},
	abstract = {Plains rough fescue, a native species of North America's central plains, has experienced a decline due to land conversion and population fragmentation. To assess the historical distribution of this species, we employed ecological niche modeling. Presence records of Festuca hallii (Vasey) Piper were collected from the SEINet Portal Network, iNaturalist, herbaria in The United States and Canada, and Canadian conservation data centers. A model was developed using MaxEnt with 1048 records, seven climatic variables and nine soil variables. A habitat suitability map was generated illustrating the likely distribution of F. hallii before European settlement in 19th century. The species has a high probability of occurrence across the Canadian prairies, with fragmented distribution in regions of the Rocky Mountains of Alberta and United States. Good habitat for F. hallii is characterized by soil bulk density between 1.07 and 1.25 g cm−3, annual mean temperature between 0.64 and 4.14 °C, precipitation during the warmest quarter between 149.72 and 228.19 mm, soil water content between 38.9\% and 45.85\%, and precipitation seasonality between 51.53\% and 77.08\%, which were the most important predictors in the model. Of the 450 206 km2 historic range, approximately 63 273 km2, or 14.1\%, remains intact with land cover/land use data indicating grassland conversion to agriculture as the main cause of habitat loss.},
	urldate = {2026-01-21},
	journal = {Botany},
	author = {Home, Johan and Lamb, Eric G.},
	month = jan,
	year = {2025},
	note = {Publisher: NRC Research Press},
	keywords = {Terrestrial Ecoregions},
	pages = {1--14},
}

Plains rough fescue, a native species of North America's central plains, has experienced a decline due to land conversion and population fragmentation. To assess the historical distribution of this species, we employed ecological niche modeling. Presence records of Festuca hallii (Vasey) Piper were collected from the SEINet Portal Network, iNaturalist, herbaria in The United States and Canada, and Canadian conservation data centers. A model was developed using MaxEnt with 1048 records, seven climatic variables and nine soil variables. A habitat suitability map was generated illustrating the likely distribution of F. hallii before European settlement in 19th century. The species has a high probability of occurrence across the Canadian prairies, with fragmented distribution in regions of the Rocky Mountains of Alberta and United States. Good habitat for F. hallii is characterized by soil bulk density between 1.07 and 1.25 g cm−3, annual mean temperature between 0.64 and 4.14 °C, precipitation during the warmest quarter between 149.72 and 228.19 mm, soil water content between 38.9% and 45.85%, and precipitation seasonality between 51.53% and 77.08%, which were the most important predictors in the model. Of the 450 206 km2 historic range, approximately 63 273 km2, or 14.1%, remains intact with land cover/land use data indicating grassland conversion to agriculture as the main cause of habitat loss.

@techreport{bourgoin_global_2025,
	title = {Global {Forest} {Maps} for the {Year} 2020 to {Support} the {EU} {Regulation} on {Deforestation}-free {Supply} {Chains}},
	url = {https://publications.jrc.ec.europa.eu/repository/handle/JRC141702},
	abstract = {This document presents the second version of the Global map of Forest Cover for the year 2020 at 10 m spatial resolution (GFC 2020, version 2 dated 7 December 2024). This map is based on the combination of several global land cover / land use data sets and provides a spatially explicit representation of forest presence and absence for the year 2020. Additionally, this document presents a preliminary version of the Global map of Forest Types for the year 2020 (GFT 2020, version v0 dated 7 December 2024). The report presents the approaches that were developed to produce these two new maps and an analysis of the results in comparison with other international sources of information. These maps are designed to support the risk assessment in the implementation of the EU Regulation on deforestation-free supply chains (EUDR, Regulation (EU) 2023/1115), but their use is not mandatory, not exclusive and not legally binding. The primary access to this map is via the EU Observatory on Deforestation and Forest Degradation.},
	language = {en},
	urldate = {2025-05-08},
	author = {Bourgoin, Clement and Verhegghen, Astrid and Carboni, Silvia and Degreve, Lucas and Ameztoy, ARAMENDI Iban and Ceccherini, Guido and Colditz, Rene and Achard, Frederic},
	year = {2025},
	doi = {10.2760/1975879},
	note = {ISBN: 9789268262603
ISSN: 1831-9424},
	keywords = {NALCMS},
}

This document presents the second version of the Global map of Forest Cover for the year 2020 at 10 m spatial resolution (GFC 2020, version 2 dated 7 December 2024). This map is based on the combination of several global land cover / land use data sets and provides a spatially explicit representation of forest presence and absence for the year 2020. Additionally, this document presents a preliminary version of the Global map of Forest Types for the year 2020 (GFT 2020, version v0 dated 7 December 2024). The report presents the approaches that were developed to produce these two new maps and an analysis of the results in comparison with other international sources of information. These maps are designed to support the risk assessment in the implementation of the EU Regulation on deforestation-free supply chains (EUDR, Regulation (EU) 2023/1115), but their use is not mandatory, not exclusive and not legally binding. The primary access to this map is via the EU Observatory on Deforestation and Forest Degradation.

@article{neel_going_2025,
	title = {Going {With} the {Flow}? {Relative} {Importance} of {Riverine} {Hydrologic} {Connectivity} {Versus} {Tidal} {Influence} for {Spatial} {Structure} of {Genetic} {Diversity} and {Relatedness} in a {Foundational} {Submersed} {Aquatic} {Plant}},
	volume = {15},
	copyright = {© 2025 The Author(s). Ecology and Evolution published by British Ecological Society and John Wiley \& Sons Ltd.},
	issn = {2045-7758},
	shorttitle = {Going {With} the {Flow}?},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/ece3.71264},
	doi = {10.1002/ece3.71264},
	abstract = {Genetic connectivity in rivers is generally high, and levels of genotypic and genetic diversity of riverine species are expected to accumulate in downstream locations. Genetic structure of marine and estuarine species is less predictable, even though hydrologic connectivity is also expected to be relatively high in those ecosystems. These observations have been generated across different species and locations such that our understanding of the effects of hydrologic connectivity in the same river, spanning tidal and nontidal habitats, remains incomplete. To control for species and location, we quantified diversity in 941 samples of Vallisneria americana Michx. (Hydrocharitaceae) collected from 36 sites along the species' entire distribution in the tidal and nontidal Potomac River of Maryland, Virginia, and the District of Columbia, USA. Using 10 microsatellite loci, we found 507 unique multilocus genotypes (MLGs) that were collapsed to 482 multilocus lineages (MLLs). Fifty-three MLLs were found multiple times across the riverscape, accounting for over 54\% of the genotyped shoots. We found some evidence supporting connectivity throughout the river and stronger evidence that tidal regime drives genotypic and genetic structure within V. americana. Extensive clonality, including two MLLs spanning 230 and 152 km, limits diversity in the nontidal reaches and contrasts with very little evidence of clonal reproduction in tidal reaches. Genetic differentiation, structure, and pairwise relatedness of sampled shoots and MLLs also differed by tidal reach, with the nontidal Potomac having higher levels of relatedness, lower allelic diversity, and higher heterozygosity. The differences in spatial distribution of genetic diversity suggest very different outlooks for V. americana adaptation and acclimation to perturbations in tidal and nontidal regions of the Potomac, which lead to different recommendations for restoration of the same species in the same river.},
	language = {en},
	number = {5},
	urldate = {2026-05-27},
	journal = {Ecology and Evolution},
	author = {Neel, Maile C. and Marsden, Brittany W. and Engelhardt, Katharina A. M.},
	year = {2025},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/ece3.71264},
	keywords = {Political Boundaries},
	pages = {e71264},
}

Genetic connectivity in rivers is generally high, and levels of genotypic and genetic diversity of riverine species are expected to accumulate in downstream locations. Genetic structure of marine and estuarine species is less predictable, even though hydrologic connectivity is also expected to be relatively high in those ecosystems. These observations have been generated across different species and locations such that our understanding of the effects of hydrologic connectivity in the same river, spanning tidal and nontidal habitats, remains incomplete. To control for species and location, we quantified diversity in 941 samples of Vallisneria americana Michx. (Hydrocharitaceae) collected from 36 sites along the species' entire distribution in the tidal and nontidal Potomac River of Maryland, Virginia, and the District of Columbia, USA. Using 10 microsatellite loci, we found 507 unique multilocus genotypes (MLGs) that were collapsed to 482 multilocus lineages (MLLs). Fifty-three MLLs were found multiple times across the riverscape, accounting for over 54% of the genotyped shoots. We found some evidence supporting connectivity throughout the river and stronger evidence that tidal regime drives genotypic and genetic structure within V. americana. Extensive clonality, including two MLLs spanning 230 and 152 km, limits diversity in the nontidal reaches and contrasts with very little evidence of clonal reproduction in tidal reaches. Genetic differentiation, structure, and pairwise relatedness of sampled shoots and MLLs also differed by tidal reach, with the nontidal Potomac having higher levels of relatedness, lower allelic diversity, and higher heterozygosity. The differences in spatial distribution of genetic diversity suggest very different outlooks for V. americana adaptation and acclimation to perturbations in tidal and nontidal regions of the Potomac, which lead to different recommendations for restoration of the same species in the same river.

@article{donnelly_going_2025,
	title = {Going, going, gone: {Landscape} drying reduces wetland function across the {American} {West}},
	volume = {171},
	issn = {1470-160X},
	shorttitle = {Going, going, gone},
	url = {https://www.sciencedirect.com/science/article/pii/S1470160X25001013},
	doi = {10.1016/j.ecolind.2025.113172},
	abstract = {Ecosystems are rapidly transforming into non-historical configurations as a nearly inevitable consequence of climate and land use change. Water scarcity, in particular, is emerging as a new and powerful threat, forcing wetland ecosystems into altered functional states as the frequency and duration of their inundation diminish. Potential for large-scale functional loss raises concerns over environmental sustainability, as wetlands are key determinants of biodiversity in water-limited landscapes. To improve our understanding of rapid ecosystem change, we reconstructed monthly wetland surface water hydrology in the western U.S. from 1984 to 2023 using cloud computing and ∼ 150,000 satellite images to measure shifts in the timing and duration of inundations. Monitoring encompassed all freshwater palustrine and littoral systems, including anthropogenic wetlands sustained through human water use (e.g., irrigated agriculture and earthen livestock ponds). Wetland surface water was classified annually by hydroperiod (semi-permanent, seasonal, and temporary) based on monthly inundation rates and binned into functional groups based on ecological and anthropogenic associations to track patterns of change. Results were summarized at an ecoregional level to normalize heterogeneity in landscape drivers structuring trends. Findings showed that overall wetland abundance (i.e., inundated area) changed by only 0.2 \% during the forty-year study period; however, shortened inundation periods reduced semi-permanent wetlands by 24 \% and increased the combined abundance of seasonal and temporary wetlands by a nearly equal amount (23 \%). Trends suggest that semi-permanent loss acts as an early indicator of large-scale functional decline, signaling wetland ecosystems’ transition along a continuum of persistent to more ephemeral states. Functional declines were heterogeneous, with losses and gains focused in a limited number of ecoregions. High rates of semi-permanent loss were associated with overall declines in wetland abundance at the ecoregional level that exceeded 20 \% in some cases. Anthropogenic water use supported half the wetland resources measured. Proliferating agricultural-wetlands and earthen livestock ponds were drivers of wetland expansion and indicators of human adaptation to water scarcity that offset natural-wetlands losses in some ecoregions. Our analysis identifies a shortfall in large-scale governmental monitoring programs that remain focused on historical wetland threats associated with agricultural drainage and urban expansion. Outcomes from this work improve our understanding of environmental change, elevating the urgency of developing adaptive conservation strategies in light of the rapidly evolving trajectory of wetland ecosystems in the western U.S.},
	urldate = {2026-05-26},
	journal = {Ecological Indicators},
	author = {Donnelly, J. Patrick and Moore, Johnnie N. and Kimball, John S. and Jencso, Kelsey and Petrie, Mark and Naugle, David E.},
	month = feb,
	year = {2025},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {113172},
}

Ecosystems are rapidly transforming into non-historical configurations as a nearly inevitable consequence of climate and land use change. Water scarcity, in particular, is emerging as a new and powerful threat, forcing wetland ecosystems into altered functional states as the frequency and duration of their inundation diminish. Potential for large-scale functional loss raises concerns over environmental sustainability, as wetlands are key determinants of biodiversity in water-limited landscapes. To improve our understanding of rapid ecosystem change, we reconstructed monthly wetland surface water hydrology in the western U.S. from 1984 to 2023 using cloud computing and ∼ 150,000 satellite images to measure shifts in the timing and duration of inundations. Monitoring encompassed all freshwater palustrine and littoral systems, including anthropogenic wetlands sustained through human water use (e.g., irrigated agriculture and earthen livestock ponds). Wetland surface water was classified annually by hydroperiod (semi-permanent, seasonal, and temporary) based on monthly inundation rates and binned into functional groups based on ecological and anthropogenic associations to track patterns of change. Results were summarized at an ecoregional level to normalize heterogeneity in landscape drivers structuring trends. Findings showed that overall wetland abundance (i.e., inundated area) changed by only 0.2 % during the forty-year study period; however, shortened inundation periods reduced semi-permanent wetlands by 24 % and increased the combined abundance of seasonal and temporary wetlands by a nearly equal amount (23 %). Trends suggest that semi-permanent loss acts as an early indicator of large-scale functional decline, signaling wetland ecosystems’ transition along a continuum of persistent to more ephemeral states. Functional declines were heterogeneous, with losses and gains focused in a limited number of ecoregions. High rates of semi-permanent loss were associated with overall declines in wetland abundance at the ecoregional level that exceeded 20 % in some cases. Anthropogenic water use supported half the wetland resources measured. Proliferating agricultural-wetlands and earthen livestock ponds were drivers of wetland expansion and indicators of human adaptation to water scarcity that offset natural-wetlands losses in some ecoregions. Our analysis identifies a shortfall in large-scale governmental monitoring programs that remain focused on historical wetland threats associated with agricultural drainage and urban expansion. Outcomes from this work improve our understanding of environmental change, elevating the urgency of developing adaptive conservation strategies in light of the rapidly evolving trajectory of wetland ecosystems in the western U.S.

@article{lauriault_grazing_2025,
	title = {Grazing {Reduces} {Field} {Bindweed} {Infestations} in {Perennial} {Warm}-{Season} {Grass} {Pastures}},
	volume = {15},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {2073-4395},
	url = {https://www.mdpi.com/2073-4395/15/8/1832},
	doi = {10.3390/agronomy15081832},
	abstract = {Field bindweed (Convolvulus arvensis L.) is a competitive herbaceous perennial weed that reduces productivity in irrigated pastures. Grazing might reduce competition by field bindweed when it begins growth in the spring, thereby encouraging encroachment by desirable grass species during the summer. To test this hypothesis, a two-year study was conducted in two adjacent, privately owned, irrigated, warm-season perennial grass pastures (replicates) that were heavily infested with field bindweed. Study sites were near Tucumcari, NM, USA. The fields were grazed with exclosures to evaluate ungrazed management. Aboveground biomass of field bindweed, other weeds, and perennial grass were measured, and field bindweed plants were counted in May of 2018 and 2019. There was no difference between years for any variable. Other weed biomass and field bindweed biomass and plant numbers were reduced (p {\textless} 0.05) by grazing (61.68 vs. 41.67 g bindweed biomass m−2 for ungrazed and grazed management, respectively, and 108.5 and 56.8 bindweed plants m−2 for ungrazed and grazed management, respectively). Otherwise, perennial grass production was unaffected by either year or management. These results indicate that grazing can be an effective tool to reduce field bindweed competition in warm-season perennial grass pastures.},
	language = {en},
	number = {8},
	urldate = {2025-07-31},
	journal = {Agronomy},
	author = {Lauriault, Leonard M. and Schutte, Brian J. and Darapuneni, Murali K. and Martinez, Gasper K.},
	month = aug,
	year = {2025},
	note = {Number: 8
Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {Climate Zones},
	pages = {1832},
}

Field bindweed (Convolvulus arvensis L.) is a competitive herbaceous perennial weed that reduces productivity in irrigated pastures. Grazing might reduce competition by field bindweed when it begins growth in the spring, thereby encouraging encroachment by desirable grass species during the summer. To test this hypothesis, a two-year study was conducted in two adjacent, privately owned, irrigated, warm-season perennial grass pastures (replicates) that were heavily infested with field bindweed. Study sites were near Tucumcari, NM, USA. The fields were grazed with exclosures to evaluate ungrazed management. Aboveground biomass of field bindweed, other weeds, and perennial grass were measured, and field bindweed plants were counted in May of 2018 and 2019. There was no difference between years for any variable. Other weed biomass and field bindweed biomass and plant numbers were reduced (p \textless 0.05) by grazing (61.68 vs. 41.67 g bindweed biomass m−2 for ungrazed and grazed management, respectively, and 108.5 and 56.8 bindweed plants m−2 for ungrazed and grazed management, respectively). Otherwise, perennial grass production was unaffected by either year or management. These results indicate that grazing can be an effective tool to reduce field bindweed competition in warm-season perennial grass pastures.

@article{saenz-ceja_habitat_2025,
	title = {Habitat fragmentation and low patch connectivity threaten the genus {Abies} {Mill}. ({Pinaceae}) in southern {North} {America}},
	volume = {25},
	issn = {1436-378X},
	url = {https://doi.org/10.1007/s10113-025-02419-4},
	doi = {10.1007/s10113-025-02419-4},
	abstract = {Fir forests (Abies, Pinaceae) are patchily distributed in the montane ecoregions of the United States Southwest, Mexico, and northern Guatemala. We assessed habitat fragmentation for nine Abies species native to southern North America. We estimated the number of patches (NumP), mean patch size (MPS), median patch size (MedPS), mean shape index (MSI), patch density (PD), total edge (TE), mean patch edge (MPE), class area (CA), total landscape area (TLA), and percentage of class area within an ecoregion (ZLAND) based on Abies species distribution maps. Then, we calculated NumP, MPS, and ZLAND for land covers in each ecoregion between 2010 and 2020. We estimated the Integral Index of Connectivity of patches covered by Abies species according to two dispersal scenarios (0–500 m and 0–1000 m) and classified them as low, medium, or high connectivity. We also assessed the extent to which protected areas are intersected with patch connectivity levels. Most Abies species occupied small patches with low patch densities in restricted areas of each ecoregion. NumP increased significantly in conifer forests (76\%) and croplands (72\%), MPS decreased in mixed forests (39\%), conifer forests (37.4\%), and croplands (34.8\%), whereas ZLAND increased in urban areas (2.7\%). Most patches exhibited low connectivity in both dispersal scenarios; only two species hosted large medium and high connectivity patches. Moreover, at least 30\% of the distribution of two species was protected, and most of the protected extent was intersected with low connectivity patches. Our findings suggest habitat fragmentation and low patch connectivity could threaten Abies species long term.},
	language = {en},
	number = {3},
	urldate = {2025-07-31},
	journal = {Regional Environmental Change},
	author = {Sáenz-Ceja, Jesús E. and Mendoza, Manuel E.},
	month = jun,
	year = {2025},
	keywords = {NALCMS, Protected Areas, Railroads, Terrestrial Ecoregions},
	pages = {84},
}

Fir forests (Abies, Pinaceae) are patchily distributed in the montane ecoregions of the United States Southwest, Mexico, and northern Guatemala. We assessed habitat fragmentation for nine Abies species native to southern North America. We estimated the number of patches (NumP), mean patch size (MPS), median patch size (MedPS), mean shape index (MSI), patch density (PD), total edge (TE), mean patch edge (MPE), class area (CA), total landscape area (TLA), and percentage of class area within an ecoregion (ZLAND) based on Abies species distribution maps. Then, we calculated NumP, MPS, and ZLAND for land covers in each ecoregion between 2010 and 2020. We estimated the Integral Index of Connectivity of patches covered by Abies species according to two dispersal scenarios (0–500 m and 0–1000 m) and classified them as low, medium, or high connectivity. We also assessed the extent to which protected areas are intersected with patch connectivity levels. Most Abies species occupied small patches with low patch densities in restricted areas of each ecoregion. NumP increased significantly in conifer forests (76%) and croplands (72%), MPS decreased in mixed forests (39%), conifer forests (37.4%), and croplands (34.8%), whereas ZLAND increased in urban areas (2.7%). Most patches exhibited low connectivity in both dispersal scenarios; only two species hosted large medium and high connectivity patches. Moreover, at least 30% of the distribution of two species was protected, and most of the protected extent was intersected with low connectivity patches. Our findings suggest habitat fragmentation and low patch connectivity could threaten Abies species long term.

@article{annis_indirect_2025,
	title = {Indirect {Effects} and {Context} {Dependency} in {Stream} {Fish} {Invasions}},
	volume = {31},
	copyright = {© 2025 The Author(s). Diversity and Distributions published by John Wiley \& Sons Ltd.},
	issn = {1472-4642},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/ddi.13968},
	doi = {10.1111/ddi.13968},
	abstract = {Aim Invasion ecology is replete with a body of well-supported yet contradictory evidence for numerous invasion hypotheses, likely as a result of context dependency. Context dependency in invasion studies can arise in two ways: (1) apparent, when results differ between studies solely due to methodical differences, or (2) mechanistic, when results truly differ due to ecological processes. One form of apparent context dependency occurs when causally linked factors associated with invasion success (hereafter, invasion drivers) either mask or enhance each other's effect on invasion success. Mechanistic context dependency can occur when regional scale processes modify the influence of local scale invasion processes. Together, apparent and mechanistic context dependency likely give rise to conflicting support between invasion hypotheses via confounding effects of causally related invasion drivers and region-specific invasion processes. Location 2339 stream segments in two ecoregions of the United States. Methods Using local scale stream fish community data for two distinct ecoregions, we constructed identical path models to estimate the direct and indirect effects of invasion drivers on nonnative richness. We chose one variable to index invasion drivers from each of the following categories: propagule pressure, natural abiotic, anthropogenic abiotic and biotic factors. Results We found evidence of apparent context dependency through the presence of indirect effects, in which the effects of propagule pressure and biotic factors on nonnative richness were modulated by abiotic factors. The indirect effects of invasion drivers differed between both regions, providing evidence of mechanistic context dependency. Main Conclusions Apparent and mechanistic context dependency can lead to conflicting evidence between studies of invasion hypotheses. Accounting for indirect effects of invasion drivers is important in gaining a more general understanding of the invasion process. Furthermore, because indirect effects varied regionally, it is important to understand the large-scale processes that contextualise local invasion processes.},
	language = {en},
	number = {1},
	urldate = {2026-05-21},
	journal = {Diversity and Distributions},
	author = {Annis, William K. and Thompson, Lily M. and Midway, Stephen R. and Olden, Julian D. and Peoples, Brandon K.},
	year = {2025},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/ddi.13968},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {e13968},
}

Aim Invasion ecology is replete with a body of well-supported yet contradictory evidence for numerous invasion hypotheses, likely as a result of context dependency. Context dependency in invasion studies can arise in two ways: (1) apparent, when results differ between studies solely due to methodical differences, or (2) mechanistic, when results truly differ due to ecological processes. One form of apparent context dependency occurs when causally linked factors associated with invasion success (hereafter, invasion drivers) either mask or enhance each other's effect on invasion success. Mechanistic context dependency can occur when regional scale processes modify the influence of local scale invasion processes. Together, apparent and mechanistic context dependency likely give rise to conflicting support between invasion hypotheses via confounding effects of causally related invasion drivers and region-specific invasion processes. Location 2339 stream segments in two ecoregions of the United States. Methods Using local scale stream fish community data for two distinct ecoregions, we constructed identical path models to estimate the direct and indirect effects of invasion drivers on nonnative richness. We chose one variable to index invasion drivers from each of the following categories: propagule pressure, natural abiotic, anthropogenic abiotic and biotic factors. Results We found evidence of apparent context dependency through the presence of indirect effects, in which the effects of propagule pressure and biotic factors on nonnative richness were modulated by abiotic factors. The indirect effects of invasion drivers differed between both regions, providing evidence of mechanistic context dependency. Main Conclusions Apparent and mechanistic context dependency can lead to conflicting evidence between studies of invasion hypotheses. Accounting for indirect effects of invasion drivers is important in gaining a more general understanding of the invasion process. Furthermore, because indirect effects varied regionally, it is important to understand the large-scale processes that contextualise local invasion processes.

@article{ghayourmanesh_inland_2025,
	title = {Inland {Water} {Body} {Fraction} {Map} for {Canada} and {Adjacent} {Regions} at 250-m {Spatial} {Resolution}},
	volume = {51},
	issn = {0703-8992},
	url = {https://doi.org/10.1080/07038992.2025.2451934},
	doi = {10.1080/07038992.2025.2451934},
	abstract = {We present a novel raster dataset of surface inland water body fraction over Canada and neighbouring regions, including the northern parts of the United States, as well as Greenland, Iceland, and the northeastern sector of Russia, at 250-m spatial resolution. It was derived from the Global Surface Water (GSW) dataset (version 5) using a two-step resampling to ensure an accurate replication of the original data and spatial consistency in terms of extent and resolution with the Long-Term Satellite Data Records derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) sensors. Additional input data and several coastline vector shape databases were utilized to refine the delineation of waterbodies and land-ocean interface. The resulting dataset is an 8-bit signed integer map, where each pixel represents either the water fraction or a land/ocean mask. Positive values indicate water bodies within Canada, while negative values represent areas outside of Canada. This dataset provides a more precise and up-to-date tool for medium-resolution studies of surface inland water in Canada, aligning closely with satellite imagery of similar spatial resolution. The dataset is freely available through the Government of Canada’s Open Government Portal.},
	number = {1},
	urldate = {2025-07-31},
	journal = {Canadian Journal of Remote Sensing},
	author = {Ghayourmanesh, Shaheen and Trishchenko, Alexander P. and Ungureanu, Calin},
	month = dec,
	year = {2025},
	note = {Publisher: Canadian Aeronautics and Space Institute
\_eprint: https://doi.org/10.1080/07038992.2025.2451934},
	keywords = {Political Boundaries},
	pages = {2451934},
}

We present a novel raster dataset of surface inland water body fraction over Canada and neighbouring regions, including the northern parts of the United States, as well as Greenland, Iceland, and the northeastern sector of Russia, at 250-m spatial resolution. It was derived from the Global Surface Water (GSW) dataset (version 5) using a two-step resampling to ensure an accurate replication of the original data and spatial consistency in terms of extent and resolution with the Long-Term Satellite Data Records derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) sensors. Additional input data and several coastline vector shape databases were utilized to refine the delineation of waterbodies and land-ocean interface. The resulting dataset is an 8-bit signed integer map, where each pixel represents either the water fraction or a land/ocean mask. Positive values indicate water bodies within Canada, while negative values represent areas outside of Canada. This dataset provides a more precise and up-to-date tool for medium-resolution studies of surface inland water in Canada, aligning closely with satellite imagery of similar spatial resolution. The dataset is freely available through the Government of Canada’s Open Government Portal.

@article{gontijo_insect_2025,
	title = {Insect biological control: a global perspective},
	copyright = {Access rights vary by item. See individual item pages for details.},
	issn = {0171-8177},
	shorttitle = {Insect biological control},
	url = {http://repositori.irta.cat/handle/20.500.12327/4863},
	doi = {10.1127/entomologia/3237},
	abstract = {Repositori de l'Institut de Recerca i Tecnologia Agroalimentària with publications and data on agri-food research},
	language = {eng},
	urldate = {2026-01-21},
	author = {Gontijo, Lessando M. and Torres, Jorge B. and Abram, Paul K. and Alfaro-Tapia, Armando and Arredondo-Bernal, Hugo C. and Biondi, Antonio and Cloyd, Raymond A. and Costamagna, Alejandro C. and Desneux, Nicolas and D'Ottavio, Marie and Furlong, Michael J. and Greco, Nancy M. and Labbe, Roselyne and Hill, Martin and Lavandero, Blas and Tian-Hao, Li and Lomelí-Flores, José R. and Lucas, Eric and Messelink, Gerben and Rocca, Margarita and Rodriguez-Garcia, Marcela and Parra, José R. P. and Peñalver Cruz, Ainara and Sokame, Bonoukpoè Mawuko and Thackeray, Sean and Urbaneja, Alberto and Vargas, German and Zalucki, Myron P. and Zang, Lian-Sheng},
	month = sep,
	year = {2025},
	note = {Accepted: 2025-11-26T10:27:31Z
Company: IRTA Pubpro
Distributor: IRTA Pubpro
Institution: IRTA Pubpro
Label: IRTA Pubpro
Publisher: Schweizerbart Science Publishers},
	keywords = {Terrestrial Ecoregions (CEC 1997)},
}

Repositori de l'Institut de Recerca i Tecnologia Agroalimentària with publications and data on agri-food research

@article{colyn_investigating_2025,
	title = {Investigating spatial variability of ground temperatures across coastal and continental highlands in {Labrador}, northeastern {Canada}},
	volume = {11},
	url = {https://cdnsciencepub.com/doi/full/10.1139/as-2024-0079},
	doi = {10.1139/as-2024-0079},
	abstract = {Interactions between atmospheric warming, local surface conditions, and ground temperatures complicate efforts to predict future permafrost changes in regions such as Labrador, northeastern Canada, where ground temperature monitoring is limited. This study provides the first comprehensive investigation of factors influencing local-to-regional ground temperature variability in Labrador’s highland environments including in areas subject to infrastructure development. Ground surface temperature measurements (n = 100), in situ field characteristics (i.e., vegetation, soil, and topography), and remotely derived variables were collected at five sampling areas of varying latitudes and continentalities. Our analysis identified no consistent latitudinal trend in mean annual ground surface temperatures (MAGST) or permafrost occurrence probabilities. Instead, the highest permafrost probabilities were found in dry, wind-blown areas with sparse vegetation cover in Labrador’s southwest interior. Using machine learning, we identified the most important climate variables (i.e., mean annual air temperature and air temperature range) and local site characteristics (i.e., maximum understory vegetation height, snow accumulation indices) for predicting regional variability in MAGSTs. These findings will support future geohazard assessments in similar highlands and aid in the development of fine-resolution permafrost distribution maps. These data also help to establish a critical baseline of thermal conditions for evaluating the impacts of further environmental and climatic changes.},
	urldate = {2026-01-21},
	journal = {Arctic Science},
	author = {Colyn, Victoria and Way, Robert and Wang, Yifeng and Beer, Jordan and Trant, Andrew and Hermanutz, Luise and Forget, Anika and Tutton, Rosamond and Barone, Katryna and Power, Madison and Fedder, Leah and Rendell, Erin and Gaul, Nicole and Le, Nhu},
	month = jan,
	year = {2025},
	note = {Publisher: NRC Research Press},
	keywords = {Political Boundaries},
	pages = {1--26},
}

Interactions between atmospheric warming, local surface conditions, and ground temperatures complicate efforts to predict future permafrost changes in regions such as Labrador, northeastern Canada, where ground temperature monitoring is limited. This study provides the first comprehensive investigation of factors influencing local-to-regional ground temperature variability in Labrador’s highland environments including in areas subject to infrastructure development. Ground surface temperature measurements (n = 100), in situ field characteristics (i.e., vegetation, soil, and topography), and remotely derived variables were collected at five sampling areas of varying latitudes and continentalities. Our analysis identified no consistent latitudinal trend in mean annual ground surface temperatures (MAGST) or permafrost occurrence probabilities. Instead, the highest permafrost probabilities were found in dry, wind-blown areas with sparse vegetation cover in Labrador’s southwest interior. Using machine learning, we identified the most important climate variables (i.e., mean annual air temperature and air temperature range) and local site characteristics (i.e., maximum understory vegetation height, snow accumulation indices) for predicting regional variability in MAGSTs. These findings will support future geohazard assessments in similar highlands and aid in the development of fine-resolution permafrost distribution maps. These data also help to establish a critical baseline of thermal conditions for evaluating the impacts of further environmental and climatic changes.

@article{murphy_jaguar_2025,
	title = {Jaguar density estimation in {Mexico}: {The} conservation importance of considering home range orientation in spatial capture–recapture},
	volume = {7},
	copyright = {© 2025 The Author(s). Conservation Science and Practice published by Wiley Periodicals LLC on behalf of Society for Conservation Biology.},
	issn = {2578-4854},
	shorttitle = {Jaguar density estimation in {Mexico}},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/csp2.13301},
	doi = {10.1111/csp2.13301},
	abstract = {Accurate estimation of population parameters for imperiled wildlife is crucial for effective conservation decision-making. Population density is commonly used for monitoring imperiled species across space and time, and spatial capture–recapture (SCR) models can produce unbiased density estimates. However, many imperiled species are restricted to fragmented remnant habitats in landscapes severely modified by humans, which can alter animal space use in ways that violate typical SCR model assumptions, possibly cryptically biasing density estimates and misinforming conservation actions. Using data from a two-year camera-trapping survey in the Central Pacific Coast region, Mexico, we demonstrate the potential importance to endangered jaguar (Panthera onca) conservation of considering non-circular home ranges when estimating population density with SCR. Strong evidence existed that jaguars had elliptical home ranges wherein movements primarily occurred along linearly arranged coastal habitats that the camera array aligned with. Accounting for this movement with the SCR anisotropic detection function transformation, density estimates were 30\%–32\% higher than estimates from standard SCR models that assumed circular home ranges. Given much of suitable jaguar habitat in Mexico is fragmented and linearly oriented along coastlines and mountain ranges, accommodating irregular space use in SCR may be critical for obtaining reliable density estimates to inform effective jaguar conservation.},
	language = {en},
	number = {2},
	urldate = {2025-05-08},
	journal = {Conservation Science and Practice},
	author = {Murphy, Sean M. and Luja, Victor H.},
	year = {2025},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/csp2.13301},
	keywords = {NALCMS},
	pages = {e13301},
}

Accurate estimation of population parameters for imperiled wildlife is crucial for effective conservation decision-making. Population density is commonly used for monitoring imperiled species across space and time, and spatial capture–recapture (SCR) models can produce unbiased density estimates. However, many imperiled species are restricted to fragmented remnant habitats in landscapes severely modified by humans, which can alter animal space use in ways that violate typical SCR model assumptions, possibly cryptically biasing density estimates and misinforming conservation actions. Using data from a two-year camera-trapping survey in the Central Pacific Coast region, Mexico, we demonstrate the potential importance to endangered jaguar (Panthera onca) conservation of considering non-circular home ranges when estimating population density with SCR. Strong evidence existed that jaguars had elliptical home ranges wherein movements primarily occurred along linearly arranged coastal habitats that the camera array aligned with. Accounting for this movement with the SCR anisotropic detection function transformation, density estimates were 30%–32% higher than estimates from standard SCR models that assumed circular home ranges. Given much of suitable jaguar habitat in Mexico is fragmented and linearly oriented along coastlines and mountain ranges, accommodating irregular space use in SCR may be critical for obtaining reliable density estimates to inform effective jaguar conservation.

@techreport{government_of_canada_jasper_2025,
	type = {Information {Report}},
	title = {Jasper wildfire complex 2024 : fire behaviour documentation, reconstruction, and analysis.: {Fo133}-1/{433E}-{PDF} - {Government} of {Canada} {Publications} - {Canada}.ca},
	shorttitle = {Jasper wildfire complex 2024},
	url = {https://publications.gc.ca/site/eng/9.953712/publication.html},
	abstract = {Publication information / bibliographic Record.},
	language = {eng},
	number = {NOR-X-433},
	urldate = {2026-05-29},
	institution = {Natural Resources Canada, Canadian Forest Service},
	author = {Government of Canada, Public Services {and} Procurement Canada},
	year = {2025},
	note = {Last Modified: 2013-04-03},
	keywords = {NALCMS},
}

Publication information / bibliographic Record.

@article{kleeberg_landscape_2025,
	title = {Landscape associations and population genetics of a generalist carnivore at a range limit},
	volume = {20},
	issn = {1932-6203},
	url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0334492},
	doi = {10.1371/journal.pone.0334492},
	abstract = {American black bear (Ursus americanus) sightings have increased in the Oklahoma Panhandle, an area outside of the species’ historical range, prompting an assessment of bears in the region. We used camera traps and an occupancy modeling framework to identify factors influencing bear detection and space-use patterns. We used noninvasive genetic sampling techniques to evaluate genetic diversity, population structure, and bear abundance in the region. During the summers of 2022–2023, we deployed cameras at 160 sites across western Oklahoma (USA) and detected ≥1 bear at 20 sites. The most-supported model from our single-season single-species analysis indicated that bear detection was positively associated with temperature and precipitation, negatively associated with day of year, and differed between years. The most-supported model indicated that bear space use was negatively associated with elevation (β = −0.013, 85\% CI = −0.025, 0.000), and positively associated with slope (β = 0.645, 85\% CI = 0.305, 0.984) and coarse woody debris counts (β = 1.539, 85\% CI = 0.314, 2.765). We deployed 41 hair snares in Oklahoma resulting in the collection of 153 hair samples and received 69 tissue samples from black bears harvested in northeastern New Mexico. Using 11 microsatellite markers, we identified 21 (12M:9F) bears in western Oklahoma, and 69 (40M:29F) in New Mexico. We found evidence that bears occurring in Oklahoma were an extension of a previously documented population that occurred in northcentral New Mexico. We detected significant population-level heterozygote deficiency (P = 0.013) compared to expectations under Hardy-Weinberg equilibrium. Using capture with replacement models, we estimated 26 (95\% CI = 19–43) bears in western Oklahoma during 2022–2023. Our results provide baseline data on population distribution, abundance, and genetic health of bears in the region and identify factors that may drive human-bear conflicts as the bear population increases in western Oklahoma.},
	language = {en},
	number = {12},
	urldate = {2026-01-21},
	journal = {PLOS ONE},
	author = {Kleeberg, Bailey A. and Lonsinger, Robert C. and Adams, Jennifer R. and Waits, Lisette P. and Fairbanks, W. Sue},
	month = dec,
	year = {2025},
	note = {Publisher: Public Library of Science},
	keywords = {Lakes \& Rivers, Political Boundaries},
	pages = {e0334492},
}

American black bear (Ursus americanus) sightings have increased in the Oklahoma Panhandle, an area outside of the species’ historical range, prompting an assessment of bears in the region. We used camera traps and an occupancy modeling framework to identify factors influencing bear detection and space-use patterns. We used noninvasive genetic sampling techniques to evaluate genetic diversity, population structure, and bear abundance in the region. During the summers of 2022–2023, we deployed cameras at 160 sites across western Oklahoma (USA) and detected ≥1 bear at 20 sites. The most-supported model from our single-season single-species analysis indicated that bear detection was positively associated with temperature and precipitation, negatively associated with day of year, and differed between years. The most-supported model indicated that bear space use was negatively associated with elevation (β = −0.013, 85% CI = −0.025, 0.000), and positively associated with slope (β = 0.645, 85% CI = 0.305, 0.984) and coarse woody debris counts (β = 1.539, 85% CI = 0.314, 2.765). We deployed 41 hair snares in Oklahoma resulting in the collection of 153 hair samples and received 69 tissue samples from black bears harvested in northeastern New Mexico. Using 11 microsatellite markers, we identified 21 (12M:9F) bears in western Oklahoma, and 69 (40M:29F) in New Mexico. We found evidence that bears occurring in Oklahoma were an extension of a previously documented population that occurred in northcentral New Mexico. We detected significant population-level heterozygote deficiency (P = 0.013) compared to expectations under Hardy-Weinberg equilibrium. Using capture with replacement models, we estimated 26 (95% CI = 19–43) bears in western Oklahoma during 2022–2023. Our results provide baseline data on population distribution, abundance, and genetic health of bears in the region and identify factors that may drive human-bear conflicts as the bear population increases in western Oklahoma.

@article{santiago_landscape_2025,
	title = {Landscape changes and declines in {Aquila} chrysaetos ({Golden} {Eagle}) territory occupancy in southwestern {Idaho}},
	issn = {0010-5422},
	url = {https://doi.org/10.1093/ornithapp/duaf054},
	doi = {10.1093/ornithapp/duaf054},
	abstract = {Rapid loss of native shrubs and expansion of invasive annual plants like cheatgrass (Bromus tectorum) have altered North American shrub-steppe systems across extensive areas. Predators, like Aquila chrysaetos (Golden Eagle) that forage on shrub-reliant prey, may abandon historically occupied territories or increase their territory size to cope with degraded habitat. We used a multiseason Bayesian occupancy model that accounted for imperfect detection to investigate the associations between landscape cover, fire history, conspecific neighbor density, and occupancy of 36 A. chrysaetos territories in southwestern Idaho and the Morley Nelson Snake River Birds of Prey National Conservation Area, USA from 1986 to 2022. The probability of A. chrysaetos occupancy at historically occupied territories decreased 25\% from 1986 to 2022 (0.83–0.58). Once territories became vacant for 5 yr, they tended to remain vacant, suggesting that they were no longer suitable for eagles, or that no new eagles were recruiting into the population. Territory occupancy was positively associated with shrub cover (β: 0.90, 95\% CrI: 0.12 to 1.71) and negatively (albeit weakly) associated with annual herbaceous cover (β: –0.63, 95\% CrI: –1.32 to 0.05). Territories closer to other occupied territories had a lower probability of occupancy than territories with distant neighbors (β: –3.89, 95\% CrI: –4.61 to –3.14), likely because eagles compensated for degraded habitat by expanding their territories. Years since the territory last burned had a slightly positive effect on occupancy with high uncertainty and a credible interval that overlapped 0 (β: 0.28, 95\% CrI: –0.26 to 0.87). The probability of detecting eagles in an occupied territory was high (0.90) and improved in surveys conducted earlier in the day and later in the breeding season. Shrub conversion to invasive grasslands has negative bottom-up consequences on A. chrysaetos territory occupancy, which may decrease the local carrying capacity for eagles in this area.Native shrub habitat has been replaced by non-native annual grasses across wide areas in the Western U.S.We built an occupancy model to assess the effects of landscape cover on the temporal variation in Aquila chrysaetos (Golden Eagle) territory occupancyThe probability of A. chrysaetos territory occupancy decreased from 1986 to 2022Increased annual herbaceous cover and a higher density of occupied A. chrysaetos territories affected the probability of occupancy negativelyShrub cover and less frequent fires increased the probability of occupancyLandscape changes can have bottom-up effects on predators and lead to a lower carrying capacity for eagles in local areas.},
	urldate = {2026-01-21},
	journal = {Ornithological Applications},
	author = {Santiago, Ashley L and Cruz, Jennyffer and Delparte, Donna M and Kochert, Michael N and Steenhof, Karen and Weldon, Joseph M and Heath, Julie A},
	month = sep,
	year = {2025},
	keywords = {Political Boundaries},
	pages = {duaf054},
}

Rapid loss of native shrubs and expansion of invasive annual plants like cheatgrass (Bromus tectorum) have altered North American shrub-steppe systems across extensive areas. Predators, like Aquila chrysaetos (Golden Eagle) that forage on shrub-reliant prey, may abandon historically occupied territories or increase their territory size to cope with degraded habitat. We used a multiseason Bayesian occupancy model that accounted for imperfect detection to investigate the associations between landscape cover, fire history, conspecific neighbor density, and occupancy of 36 A. chrysaetos territories in southwestern Idaho and the Morley Nelson Snake River Birds of Prey National Conservation Area, USA from 1986 to 2022. The probability of A. chrysaetos occupancy at historically occupied territories decreased 25% from 1986 to 2022 (0.83–0.58). Once territories became vacant for 5 yr, they tended to remain vacant, suggesting that they were no longer suitable for eagles, or that no new eagles were recruiting into the population. Territory occupancy was positively associated with shrub cover (β: 0.90, 95% CrI: 0.12 to 1.71) and negatively (albeit weakly) associated with annual herbaceous cover (β: –0.63, 95% CrI: –1.32 to 0.05). Territories closer to other occupied territories had a lower probability of occupancy than territories with distant neighbors (β: –3.89, 95% CrI: –4.61 to –3.14), likely because eagles compensated for degraded habitat by expanding their territories. Years since the territory last burned had a slightly positive effect on occupancy with high uncertainty and a credible interval that overlapped 0 (β: 0.28, 95% CrI: –0.26 to 0.87). The probability of detecting eagles in an occupied territory was high (0.90) and improved in surveys conducted earlier in the day and later in the breeding season. Shrub conversion to invasive grasslands has negative bottom-up consequences on A. chrysaetos territory occupancy, which may decrease the local carrying capacity for eagles in this area.Native shrub habitat has been replaced by non-native annual grasses across wide areas in the Western U.S.We built an occupancy model to assess the effects of landscape cover on the temporal variation in Aquila chrysaetos (Golden Eagle) territory occupancyThe probability of A. chrysaetos territory occupancy decreased from 1986 to 2022Increased annual herbaceous cover and a higher density of occupied A. chrysaetos territories affected the probability of occupancy negativelyShrub cover and less frequent fires increased the probability of occupancyLandscape changes can have bottom-up effects on predators and lead to a lower carrying capacity for eagles in local areas.

@article{mayor_landscape_2025,
	title = {Landscape diversity promotes landscape functioning in {North} {America}},
	volume = {6},
	copyright = {2025 The Author(s)},
	issn = {2662-4435},
	url = {https://www.nature.com/articles/s43247-025-02000-1},
	doi = {10.1038/s43247-025-02000-1},
	abstract = {Biodiversity–ecosystem functioning experiments have established generally positive species richness-productivity relationships in plots of single ecosystem types, typically grassland or forest. However, it remains unclear whether these findings apply in real-world landscapes that resemble a heterogeneous mosaic of different ecosystem and plant types that interact through biotic and abiotic processes. Here, we show that landscape-level diversity, measured as number of land-cover types (different ecosystems) per 250×250 m, is positively related to landscape-wide remotely-sensed primary production across all of North America, covering 16 of 18 ecoregions of Earth. At higher landscape diversity, productivity was temporally more stable, and 20-year greening trends were accelerated. These effects occurred independent of local species diversity, suggesting emergent mechanisms at hitherto neglected levels of biological organization. Specifically, mechanisms related to interactions among land-cover types unfold at the scale of entire landscapes, similar to, but not necessarily resulting from, interactions between species within single ecosystems.},
	language = {en},
	number = {1},
	urldate = {2025-01-28},
	journal = {Communications Earth \& Environment},
	author = {Mayor, Sarah and Altermatt, Florian and Crowther, Thomas W. and Hordijk, Iris and Landauer, Simon and Oehri, Jacqueline and Chacko, Merin Reji and Schaepman, Michael E. and Schmid, Bernhard and Niklaus, Pascal A.},
	month = jan,
	year = {2025},
	note = {Publisher: Nature Publishing Group},
	keywords = {NALCMS},
	pages = {1--9},
}

Biodiversity–ecosystem functioning experiments have established generally positive species richness-productivity relationships in plots of single ecosystem types, typically grassland or forest. However, it remains unclear whether these findings apply in real-world landscapes that resemble a heterogeneous mosaic of different ecosystem and plant types that interact through biotic and abiotic processes. Here, we show that landscape-level diversity, measured as number of land-cover types (different ecosystems) per 250×250 m, is positively related to landscape-wide remotely-sensed primary production across all of North America, covering 16 of 18 ecoregions of Earth. At higher landscape diversity, productivity was temporally more stable, and 20-year greening trends were accelerated. These effects occurred independent of local species diversity, suggesting emergent mechanisms at hitherto neglected levels of biological organization. Specifically, mechanisms related to interactions among land-cover types unfold at the scale of entire landscapes, similar to, but not necessarily resulting from, interactions between species within single ecosystems.

@article{mohammadimanesh_large_2025,
	title = {Large {Scale} {Land} {Cover} {Mapping} in {Ontario}, {Canada}, {Using} a {Deep} {Learning} {Framework}},
	issn = {2151-1535},
	url = {https://ieeexplore.ieee.org/abstract/document/10982192},
	doi = {10.1109/JSTARS.2025.3566611},
	abstract = {This study addresses the challenge of large-scale land cover mapping using advanced deep learning models. While state-of-the-art deep learning methods have demonstrated promising results in various remote sensing applications, their efficiency for large-scale semantic segmentation tasks remains underexplored. A key limitation is their reliance on extensive training datasets. To address this issue, we propose a two-stage classification approach that integrates Random Forest (RF) for initial land cover mapping and MobileUNetR, a lightweight hybrid convolution-transformer model, for a refined classification. Leveraging Sentinel-1 and Sentinel-2 data, the land cover map of Ontario at spatial resolution of 10 meter, aligned with the North American Land Change Monitoring System (NALCMS) Level I legend, encompassing 11 classes, is generated. The findings of this study reveal that MobileUNeTR surpasses widely used models like UNet and PSPNet in terms of both accuracy and efficiency, underscoring its suitability for large-scale land cover mapping. In particular, an overall accuracy of 85\% and a Kappa coefficient of 0.83 are achieved with MobileUNetR, which has only about one-fourth to one-fifth the number of parameters compared to other deep learning models examined in this study. As the only deep learning model examined in this study combining convolutional and transformer blocks, MobileUNetR demonstrates the superiority of hybrid architectures for large-scale semantic segmentation. This is due to its capability in capturing both local and global features, which are essential for semantic segmentation of heterogeneous land cover classes with varying sizes and spectral signatures.},
	urldate = {2025-05-08},
	journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
	author = {Mohammadimanesh, Fariba},
	year = {2025},
	keywords = {NALCMS},
	pages = {1--15},
}

This study addresses the challenge of large-scale land cover mapping using advanced deep learning models. While state-of-the-art deep learning methods have demonstrated promising results in various remote sensing applications, their efficiency for large-scale semantic segmentation tasks remains underexplored. A key limitation is their reliance on extensive training datasets. To address this issue, we propose a two-stage classification approach that integrates Random Forest (RF) for initial land cover mapping and MobileUNetR, a lightweight hybrid convolution-transformer model, for a refined classification. Leveraging Sentinel-1 and Sentinel-2 data, the land cover map of Ontario at spatial resolution of 10 meter, aligned with the North American Land Change Monitoring System (NALCMS) Level I legend, encompassing 11 classes, is generated. The findings of this study reveal that MobileUNeTR surpasses widely used models like UNet and PSPNet in terms of both accuracy and efficiency, underscoring its suitability for large-scale land cover mapping. In particular, an overall accuracy of 85% and a Kappa coefficient of 0.83 are achieved with MobileUNetR, which has only about one-fourth to one-fifth the number of parameters compared to other deep learning models examined in this study. As the only deep learning model examined in this study combining convolutional and transformer blocks, MobileUNetR demonstrates the superiority of hybrid architectures for large-scale semantic segmentation. This is due to its capability in capturing both local and global features, which are essential for semantic segmentation of heterogeneous land cover classes with varying sizes and spectral signatures.

@article{dowell_loss_2025,
	title = {Loss of a major venom toxin gene in a {Western} {Diamondback} rattlesnake population},
	volume = {20},
	issn = {1932-6203},
	url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0319316},
	doi = {10.1371/journal.pone.0319316},
	abstract = {The biochemical complexity and evolutionary diversity of snake venom composition reflects adaptation to the diversity of prey in their diets. However, the genetic mechanisms underlying the evolutionary diversity of venoms are not well understood. Here, we explored the potential extent of and genetic basis for venom protein variation in the widely-distributed Western Diamondback rattlesnake (Crotalus atrox). As in many rattlesnake venoms, metalloproteinases (SVMPs) are the major component of C. atrox venom, with three proteins belonging to three distinct major structural SVMP classes, MDC4, MAD3a, and MPO1, constituting the most abundant SVMPs. We found that while most venom proteins, including MDC4 and MAD3a, vary little among individuals, the MPO1 protein is completely absent from some animals, most commonly those from the western part of the species’ geographic range. This distribution correlates with the previous finding of two distinct lineages within C. atrox and indicates that different ecological factors have shaped venom composition across the species’ range. We further show that the loss of MPO1 expression is not due to transcriptional down-regulation, but to independent inactivating mutations at the locus, including whole gene deletion. The recurrent inactivation of a major toxin gene within a C. atrox population may reflect relaxed selection on the maintenance of MPO1 function, but we also raise the possibility that the loss of venom components may be favored if there is a cost to producing a less effective toxin in protein-rich venoms.},
	language = {en},
	number = {7},
	urldate = {2025-07-31},
	journal = {PLOS ONE},
	author = {Dowell, Noah L. and Cahill, Elizabeth and Carroll, Sean B.},
	month = jul,
	year = {2025},
	note = {Publisher: Public Library of Science},
	keywords = {Political Boundaries},
	pages = {e0319316},
}

The biochemical complexity and evolutionary diversity of snake venom composition reflects adaptation to the diversity of prey in their diets. However, the genetic mechanisms underlying the evolutionary diversity of venoms are not well understood. Here, we explored the potential extent of and genetic basis for venom protein variation in the widely-distributed Western Diamondback rattlesnake (Crotalus atrox). As in many rattlesnake venoms, metalloproteinases (SVMPs) are the major component of C. atrox venom, with three proteins belonging to three distinct major structural SVMP classes, MDC4, MAD3a, and MPO1, constituting the most abundant SVMPs. We found that while most venom proteins, including MDC4 and MAD3a, vary little among individuals, the MPO1 protein is completely absent from some animals, most commonly those from the western part of the species’ geographic range. This distribution correlates with the previous finding of two distinct lineages within C. atrox and indicates that different ecological factors have shaped venom composition across the species’ range. We further show that the loss of MPO1 expression is not due to transcriptional down-regulation, but to independent inactivating mutations at the locus, including whole gene deletion. The recurrent inactivation of a major toxin gene within a C. atrox population may reflect relaxed selection on the maintenance of MPO1 function, but we also raise the possibility that the loss of venom components may be favored if there is a cost to producing a less effective toxin in protein-rich venoms.

@article{couloigner_mapping_2025,
	title = {Mapping {Ixodes} pacificus and {Borrelia} burgdorferi {Habitat} {Suitability} {Under} {Current} and {Mid}-{Century} {Climate} in the {Pacific} {Northwest} ({BC} and {WA})},
	volume = {25},
	issn = {1530-3667},
	url = {https://www.liebertpub.com/doi/10.1089/vbz.2024.0025},
	doi = {10.1089/vbz.2024.0025},
	abstract = {Introduction: Lyme disease is the most common vector-borne disease in the United States and Canada. The primary vector for the causative agent of Lyme disease, Borrelia burgdorferi, in the Pacific Northwest is the western blacklegged tick, Ixodes pacificus.
Materials and Methods: Using active tick surveillance data from British Columbia, Canada, and Washington State, USA, habitat suitability models using MaxEnt (maximum entropy) were developed for I. pacificus to predict its current and mid-century geographic distributions. Passive surveillance data both from BC and WA were also visualized.
Results: According to the constructed models, the number of frost-free days during the winter is the most relevant predictor of its habitat suitability, followed by summer climate moisture, ecoregion, and mean minimum fall temperature. The ensemble geographic distribution map predicts that the coastal regions and inland valleys of British Columbia and the Puget Lowlands of Washington State provide the most suitable habitats for I. pacificus. The density map of ticks submitted from passive surveillance data was overlaid on the current distribution map and demonstrates the correlation between numbers of submissions and habitat suitability. Mid-century projections, based on current climate change predictions, indicate a range expansion, especially of low and moderate suitability, from current distribution. Regarding Lyme disease risk, I. pacificus identified from both active and passive surveillance and tested positive for B. burgdorferi were found to be in areas of moderate to very high suitability for I. pacificus.
Conclusion: According to developed models, the total suitable habitat area for I. pacificus will expand in the interior regions of British Columbia and Washington State. However, the risk remains small given relatively low infection rates among I. pacificus. Further studies are required to better understand how this might change in the future.},
	number = {1},
	urldate = {2025-01-28},
	journal = {Vector-Borne and Zoonotic Diseases},
	author = {Couloigner, Isabelle and Dizon, Carl and Mak, Sunny and Dykstra, Elizabeth and Fraser, Erin and Morshed, Muhammad and Iwasawa, Stefan and Checkley, Sylvia and Cork, Susan},
	month = jan,
	year = {2025},
	note = {Publisher: Mary Ann Liebert, Inc., publishers},
	keywords = {Terrestrial Ecoregions},
	pages = {49--59},
}

Introduction: Lyme disease is the most common vector-borne disease in the United States and Canada. The primary vector for the causative agent of Lyme disease, Borrelia burgdorferi, in the Pacific Northwest is the western blacklegged tick, Ixodes pacificus. Materials and Methods: Using active tick surveillance data from British Columbia, Canada, and Washington State, USA, habitat suitability models using MaxEnt (maximum entropy) were developed for I. pacificus to predict its current and mid-century geographic distributions. Passive surveillance data both from BC and WA were also visualized. Results: According to the constructed models, the number of frost-free days during the winter is the most relevant predictor of its habitat suitability, followed by summer climate moisture, ecoregion, and mean minimum fall temperature. The ensemble geographic distribution map predicts that the coastal regions and inland valleys of British Columbia and the Puget Lowlands of Washington State provide the most suitable habitats for I. pacificus. The density map of ticks submitted from passive surveillance data was overlaid on the current distribution map and demonstrates the correlation between numbers of submissions and habitat suitability. Mid-century projections, based on current climate change predictions, indicate a range expansion, especially of low and moderate suitability, from current distribution. Regarding Lyme disease risk, I. pacificus identified from both active and passive surveillance and tested positive for B. burgdorferi were found to be in areas of moderate to very high suitability for I. pacificus. Conclusion: According to developed models, the total suitable habitat area for I. pacificus will expand in the interior regions of British Columbia and Washington State. However, the risk remains small given relatively low infection rates among I. pacificus. Further studies are required to better understand how this might change in the future.

@article{gleason_mapping_2025,
	title = {Mapping and characterizing the visual impacts of the existing {US} wind turbine fleet},
	volume = {378},
	issn = {0306-2619},
	url = {https://www.sciencedirect.com/science/article/pii/S0306261924021846},
	doi = {10.1016/j.apenergy.2024.124801},
	abstract = {Visual impacts of wind turbines have been a persistent concern for wind energy development in the United States (US) for decades and remain a major source of project delays and cancellations. Assessments of visual impacts are frequently performed at a local scale for individual projects, but a comprehensive understanding of broader geographic patterns in visual impacts across the US is lacking. This paper presents a visual impact assessment of the existing land-based wind turbine fleet of the contiguous United States (CONUS). The assessment combines geographic information systems and 3D simulation methods to account for key factors driving the visual magnitude of impacts from the installed turbines. The results indicate that, despite the deployment of approximately 70,000 turbines and over 144 gigawatts of land-based wind in the CONUS, the visual impacts are very small when measured as a proportion of land area, population, and sensitive visual resources. Nonetheless, visual impacts are not evenly distributed: people experience a concentrated share in a small number of natural settings, primarily including plains, prairies, and deserts. Finally, we find that although increased density of wind development consistently leads to visual impacts across a greater proportion of land, it does not always lead to impacts to a greater share of the population. These findings suggest that visual impacts from wind energy are generally well-mitigated across the CONUS to date but also highlight the need for a deeper understanding of landscape sensitivity and individual perceptions of wind turbines in the most heavily impacted natural settings.},
	urldate = {2026-06-09},
	journal = {Applied Energy},
	author = {Gleason, Michael and Lopez, Anthony and Rivers, Marie},
	month = jan,
	year = {2025},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {124801},
}

Visual impacts of wind turbines have been a persistent concern for wind energy development in the United States (US) for decades and remain a major source of project delays and cancellations. Assessments of visual impacts are frequently performed at a local scale for individual projects, but a comprehensive understanding of broader geographic patterns in visual impacts across the US is lacking. This paper presents a visual impact assessment of the existing land-based wind turbine fleet of the contiguous United States (CONUS). The assessment combines geographic information systems and 3D simulation methods to account for key factors driving the visual magnitude of impacts from the installed turbines. The results indicate that, despite the deployment of approximately 70,000 turbines and over 144 gigawatts of land-based wind in the CONUS, the visual impacts are very small when measured as a proportion of land area, population, and sensitive visual resources. Nonetheless, visual impacts are not evenly distributed: people experience a concentrated share in a small number of natural settings, primarily including plains, prairies, and deserts. Finally, we find that although increased density of wind development consistently leads to visual impacts across a greater proportion of land, it does not always lead to impacts to a greater share of the population. These findings suggest that visual impacts from wind energy are generally well-mitigated across the CONUS to date but also highlight the need for a deeper understanding of landscape sensitivity and individual perceptions of wind turbines in the most heavily impacted natural settings.

@article{wegscheider_modeling_2025,
	title = {Modeling nature-based restoration potential across aquatic–terrestrial boundaries},
	volume = {n/a},
	copyright = {© 2025 His Majesty the King in Right of Canada and The Author(s). Conservation Biology published by Wiley Periodicals LLC on behalf of Society for Conservation Biology. Reproduced with the permission of the Minister of Environment and Climate Change Canada.},
	issn = {1523-1739},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/cobi.70046},
	doi = {10.1111/cobi.70046},
	abstract = {Today, few watersheds remain untouched by global change processes arising from climate warming, impoundments, channelization, water extraction, pollution, and urbanization. The need for restoration has resulted in a myriad of interventions, generally performed at small scales, which have limited measurable impact in restoring biodiversity and ecosystem functions. We propose bringing nature-based restoration (also referred to as rewilding) principles to rivers and their watersheds to allow freshwater ecosystems to heal themselves and present a case study example for the Wolastoq, a transboundary watershed on North America's east coast. We aimed to identify key areas for the provision of the ecosystem function secondary productivity in the watershed and explored how the existing network of protected lands contributes to its conservation. We first developed species distribution models for 94 aquatic insects and 5 aerial insectivores and then considered human footprint and existing protected areas when employing spatial prioritization to meet 2 area-based targets (17\% and 30\% [i.e., Aichi Biodiversity Target 11 and Canada's 30×30, respectively]) for conservation or restoration of freshwater secondary production. Current conservation protection in the watershed was predicted to be insufficient to protect either ecosystem function providers or receivers of secondary production. By considering integrated conservation strategies, restoration and conservation actions can be better allocated throughout habitat patches to ensure sustained provision of ecosystem functions across the watershed. Nature-based restoration and conservation can help inform Canada's area-based targets, providing a framework for incorporating ecosystem functions into conservation planning and offering practical insights for policy and restoration efforts aimed at safeguarding biodiversity.},
	language = {en},
	number = {n/a},
	urldate = {2025-05-08},
	journal = {Conservation Biology},
	author = {Wegscheider, B. and Rideout, N. K. and Monk, W. A. and Gray, M. A. and Steeves, R. and Baird, D. J.},
	year = {2025},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/cobi.70046},
	keywords = {NALCMS},
	pages = {e70046},
}

Today, few watersheds remain untouched by global change processes arising from climate warming, impoundments, channelization, water extraction, pollution, and urbanization. The need for restoration has resulted in a myriad of interventions, generally performed at small scales, which have limited measurable impact in restoring biodiversity and ecosystem functions. We propose bringing nature-based restoration (also referred to as rewilding) principles to rivers and their watersheds to allow freshwater ecosystems to heal themselves and present a case study example for the Wolastoq, a transboundary watershed on North America's east coast. We aimed to identify key areas for the provision of the ecosystem function secondary productivity in the watershed and explored how the existing network of protected lands contributes to its conservation. We first developed species distribution models for 94 aquatic insects and 5 aerial insectivores and then considered human footprint and existing protected areas when employing spatial prioritization to meet 2 area-based targets (17% and 30% [i.e., Aichi Biodiversity Target 11 and Canada's 30×30, respectively]) for conservation or restoration of freshwater secondary production. Current conservation protection in the watershed was predicted to be insufficient to protect either ecosystem function providers or receivers of secondary production. By considering integrated conservation strategies, restoration and conservation actions can be better allocated throughout habitat patches to ensure sustained provision of ecosystem functions across the watershed. Nature-based restoration and conservation can help inform Canada's area-based targets, providing a framework for incorporating ecosystem functions into conservation planning and offering practical insights for policy and restoration efforts aimed at safeguarding biodiversity.

@techreport{paris_modeling_2025,
	title = {Modeling tools for proactive ecosystem restoration and assisted migration planning : a state of the science review and synthesis},
	shorttitle = {Modeling tools for proactive ecosystem restoration and assisted migration planning},
	url = {https://hdl.handle.net/11681/50032},
	abstract = {Decision-support modeling tools are needed to help aquatic ecosystem restoration (AER) planners understand how habitat footprints and species distributions will change in response to future changing conditions. Specifically, environmental projections and predictive model outputs that inform proactive AER planning and investments. This report provides a literature synthesis of resources and tools to create such a decision support tool. Select models identified were evaluated for applicability to AER planning using prediction confidence, user-friendliness, and suitability. This uncovered several existing, primarily terrestrially, predictive models that could be adapted to inform proactive AER planning efforts. Research efforts are still needed to fill gaps for aquatic data to train and validate predictive models, refine key drivers, and build and pilot aquatic-focused tools. Future condition vulnerability screening tools could be used to identify which proposed AER project sites are best suited for proactive AER measures, such as assisted migration, and determine if investments in more rigorous, spatially explicit, or species-specific models are needed. Species-specific assessments of habitat suitability changes and adaptive capacity can then inform restoration targets and enable end-users to achieve AER planning objectives. Such a decision support tool would improve planner ability to restore key aquatic habitats resilient to future conditions.},
	language = {en\_US},
	number = {ERDC/EL SR-25-8},
	urldate = {2026-05-29},
	author = {Paris, Sage and Pagán-Caballero, Isabel and Platz, Michelle C. and Schad, Aaron N. and Herman, Brook D. and LimnoTech, Inc and Laboratory (U.S.), Environmental and Program (U.S.), Ecosystem Management {and} Restoration Research},
	month = dec,
	year = {2025},
	note = {Publisher: Engineer Research and Development Center (U.S.)},
	keywords = {Terrestrial Ecoregions},
}

Decision-support modeling tools are needed to help aquatic ecosystem restoration (AER) planners understand how habitat footprints and species distributions will change in response to future changing conditions. Specifically, environmental projections and predictive model outputs that inform proactive AER planning and investments. This report provides a literature synthesis of resources and tools to create such a decision support tool. Select models identified were evaluated for applicability to AER planning using prediction confidence, user-friendliness, and suitability. This uncovered several existing, primarily terrestrially, predictive models that could be adapted to inform proactive AER planning efforts. Research efforts are still needed to fill gaps for aquatic data to train and validate predictive models, refine key drivers, and build and pilot aquatic-focused tools. Future condition vulnerability screening tools could be used to identify which proposed AER project sites are best suited for proactive AER measures, such as assisted migration, and determine if investments in more rigorous, spatially explicit, or species-specific models are needed. Species-specific assessments of habitat suitability changes and adaptive capacity can then inform restoration targets and enable end-users to achieve AER planning objectives. Such a decision support tool would improve planner ability to restore key aquatic habitats resilient to future conditions.

@phdthesis{demichele_multi-criteria_2025,
	address = {Anchorage, Alaska, United States},
	type = {Master of {Science}},
	title = {Multi-{Criteria} {Analysis} for {Navigating} {Wildfire} {Risk} in {Alaska}'s {Matanuska}-{Susitna} {Borough}},
	url = {https://www.proquest.com/openview/41673b80a6f8fcff933266c8f9389ccf/1?pq-origsite=gscholar&cbl=18750&diss=y},
	abstract = {Explore millions of resources from scholarly journals, books, newspapers, videos and more, on the ProQuest Platform.},
	language = {English},
	urldate = {2026-06-09},
	school = {University of Alaska Anchorage},
	author = {DeMichele, Kathleen},
	month = jan,
	year = {2025},
	keywords = {NALCMS},
}

Explore millions of resources from scholarly journals, books, newspapers, videos and more, on the ProQuest Platform.

@techreport{stackpoole_multidecadal_2025,
	title = {Multidecadal change in pesticide concentrations relative to human health benchmarks in the {Nation}’s groundwater},
	url = {https://pubs.usgs.gov/publication/sir20255081},
	abstract = {Groundwater-quality trend assessments identify aquifers that are responding to changes in pesticide use and the compounds that may pose a threat to water availability. The U.S. Geological Survey has been monitoring pesticide concentrations in groundwater for 25 principal aquifers across the conterminous United States since 1993. The groundwater well locations represent a range of soils, climate, and landforms. The wells are used to monitor groundwater underlying selected agricultural and urban settings and groundwater used for domestic supply. This study examined changes in relative concentrations, defined here as the percentage of wells with pesticide concentrations exceeding a human health benchmark (HHB). HHBs used in this report are legally enforceable drinking-water standards and nonenforceable drinking water levels. Relative pesticide concentration increases may lead to decreased water availability, as restrictions may be put in place for groundwater used as a drinking-water source.This study focused on concentration changes in 22 pesticides that were included...},
	language = {en},
	number = {2025-5081},
	urldate = {2026-01-21},
	institution = {U.S. Geological Survey},
	author = {Stackpoole, Sarah M. and Lindsey, Bruce D. and Nell, Cee S.},
	year = {2025},
	doi = {10.3133/sir20255081},
	note = {ISSN: 2328-0328
Publication Title: Scientific Investigations Report},
	keywords = {Terrestrial Ecoregions},
}

Groundwater-quality trend assessments identify aquifers that are responding to changes in pesticide use and the compounds that may pose a threat to water availability. The U.S. Geological Survey has been monitoring pesticide concentrations in groundwater for 25 principal aquifers across the conterminous United States since 1993. The groundwater well locations represent a range of soils, climate, and landforms. The wells are used to monitor groundwater underlying selected agricultural and urban settings and groundwater used for domestic supply. This study examined changes in relative concentrations, defined here as the percentage of wells with pesticide concentrations exceeding a human health benchmark (HHB). HHBs used in this report are legally enforceable drinking-water standards and nonenforceable drinking water levels. Relative pesticide concentration increases may lead to decreased water availability, as restrictions may be put in place for groundwater used as a drinking-water source.This study focused on concentration changes in 22 pesticides that were included...

@article{edwards_multiple_2025,
	title = {Multiple {Elevation}-{Dependent} {Climate} {Signals} {From} {Quantitative} {Wood} {Anatomical} {Measurements} of {Rocky} {Mountain} {Bristlecone} {Pine}},
	volume = {130},
	copyright = {© 2025. American Geophysical Union. All Rights Reserved.},
	issn = {2169-8961},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2024JG008307},
	doi = {10.1029/2024JG008307},
	abstract = {Southwestern North America has experienced significant temperature increases over the last century, leading to intensified droughts that significantly affect montane forests. Although tree-ring data have provided long-term context for this recent drought severity, the varying physiological responses of trees to climate variability make it challenging to disentangle the combined influence of temperature and soil moisture. Here we investigate complex climate-growth relationships in Rocky Mountain bristlecone pine (Pinus aristata) at a low-elevation and a high-elevation site using quantitative wood anatomy (QWA). Significant correlations with climate were found for low-elevation tree-ring width (TRW) and earlywood chronologies, including positive correlations with spring and early summer precipitation and drought indices and negative correlations with spring and early summer maximum temperatures. At high elevations, TRW and earlywood chronologies show positive responses to summer moisture, whereas latewood chronologies correlate positively with August and September maximum temperatures and negatively with August precipitation. We leverage this differing seasonality of moisture and temperature signals and compare the QWA data to known droughts. The earlywood lumen area is found to be highly responsive to drought because of its physiological reliance on water availability for maintaining turgor pressure during cell enlargement. We also observed a decline in temperature sensitivity at the high elevation site, suggesting shifts in the dominance of limiting factors. Integrating QWA with traditional dendrochronology improves interpretations of tree-ring data for use in climate reconstruction, offering detailed insights into tree physiological responses and the mix of environmental and developmental controls on cell growth.},
	language = {en},
	number = {1},
	urldate = {2026-05-26},
	journal = {Journal of Geophysical Research: Biogeosciences},
	author = {Edwards, Julie and Tintor, Will L. and Nolin, Alexandre F. and Woodhouse, Connie A. and von Arx, Georg and Anchukaitis, Kevin J.},
	year = {2025},
	note = {\_eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2024JG008307},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {e2024JG008307},
}

Southwestern North America has experienced significant temperature increases over the last century, leading to intensified droughts that significantly affect montane forests. Although tree-ring data have provided long-term context for this recent drought severity, the varying physiological responses of trees to climate variability make it challenging to disentangle the combined influence of temperature and soil moisture. Here we investigate complex climate-growth relationships in Rocky Mountain bristlecone pine (Pinus aristata) at a low-elevation and a high-elevation site using quantitative wood anatomy (QWA). Significant correlations with climate were found for low-elevation tree-ring width (TRW) and earlywood chronologies, including positive correlations with spring and early summer precipitation and drought indices and negative correlations with spring and early summer maximum temperatures. At high elevations, TRW and earlywood chronologies show positive responses to summer moisture, whereas latewood chronologies correlate positively with August and September maximum temperatures and negatively with August precipitation. We leverage this differing seasonality of moisture and temperature signals and compare the QWA data to known droughts. The earlywood lumen area is found to be highly responsive to drought because of its physiological reliance on water availability for maintaining turgor pressure during cell enlargement. We also observed a decline in temperature sensitivity at the high elevation site, suggesting shifts in the dominance of limiting factors. Integrating QWA with traditional dendrochronology improves interpretations of tree-ring data for use in climate reconstruction, offering detailed insights into tree physiological responses and the mix of environmental and developmental controls on cell growth.

@article{huff_national_2025,
	title = {National {Exposed} {Sediment} {Search} and {Inventory} ({NESSI}): {Utilizing} {Satellite} {Imagery} and {Machine} {Learning} to {Identify} {Dredged} {Sediment} {Placement} {Site} {Recovery}},
	volume = {17},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {2072-4292},
	shorttitle = {National {Exposed} {Sediment} {Search} and {Inventory} ({NESSI})},
	url = {https://www.mdpi.com/2072-4292/17/2/186},
	doi = {10.3390/rs17020186},
	abstract = {Anthropogenic activity leads to changes in sediment dynamics, creating imbalances in sediment distributions across the landscape. These imbalances can be variable within a littoral system, with adjacent areas experiencing sediment starvation and excess sediment. Historically, sediments were viewed as an inconvenient biproduct destined for disposal; however, beneficial use of dredge material (BUDM) is a practice that has grown as a preferred methodology for utilizing sediment as a resource to help alleviate the sediment imbalances within a system. BUDM enables organizations to adopt a more innovative and sustainable sediment management approach that also provides ecological, economic, and social co-benefits. Although location data are available on BUDM sites, especially in the US, there is limited understanding on how these sites evolve within the larger landscape, which is necessary for quantifying the co-benefits. To move towards BUDM more broadly, new tools need to be developed to allow researchers and managers to understand the effects and benefits of this practice. The National Exposed Sediment Search and Inventory (NESSI) was built to show the capability of using machine learning techniques to identify dredged sediments. A combination of satellite imagery data obtained and processed using Google Earth Engine and machine learning algorithms were applied at known dredged material placement sites to develop a time series of dredged material placement events and subsequent site recovery. These disturbance-to-recovery time series are then used in a landscape analysis application to better understand site evolution within the context of the surrounding areas.},
	language = {en},
	number = {2},
	urldate = {2025-01-28},
	journal = {Remote Sensing},
	author = {Huff, Thomas P. and Russ, Emily R. and Swannack, Todd M.},
	month = jan,
	year = {2025},
	note = {Number: 2
Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {NALCMS},
	pages = {186},
}

Anthropogenic activity leads to changes in sediment dynamics, creating imbalances in sediment distributions across the landscape. These imbalances can be variable within a littoral system, with adjacent areas experiencing sediment starvation and excess sediment. Historically, sediments were viewed as an inconvenient biproduct destined for disposal; however, beneficial use of dredge material (BUDM) is a practice that has grown as a preferred methodology for utilizing sediment as a resource to help alleviate the sediment imbalances within a system. BUDM enables organizations to adopt a more innovative and sustainable sediment management approach that also provides ecological, economic, and social co-benefits. Although location data are available on BUDM sites, especially in the US, there is limited understanding on how these sites evolve within the larger landscape, which is necessary for quantifying the co-benefits. To move towards BUDM more broadly, new tools need to be developed to allow researchers and managers to understand the effects and benefits of this practice. The National Exposed Sediment Search and Inventory (NESSI) was built to show the capability of using machine learning techniques to identify dredged sediments. A combination of satellite imagery data obtained and processed using Google Earth Engine and machine learning algorithms were applied at known dredged material placement sites to develop a time series of dredged material placement events and subsequent site recovery. These disturbance-to-recovery time series are then used in a landscape analysis application to better understand site evolution within the context of the surrounding areas.

@article{wanner_novel_2025,
	title = {Novel environmental variables help explain winter weather effects on activity and habitat selection of greater sage-grouse along the border of {Colorado} and {Wyoming}, {USA}},
	volume = {69},
	issn = {1432-1254},
	url = {https://doi.org/10.1007/s00484-024-02827-x},
	doi = {10.1007/s00484-024-02827-x},
	abstract = {For non-hibernating species within temperate climates, survival during severe winter weather often depends on individuals’ behavioral response and available refugia. Identifying refugia habitat that sustains populations during adverse winter conditions can be difficult and complex. This study provides an example of how modeled, biologically relevant snow and weather information can help identify important relationships between habitat selection and dynamic winter landscapes using greater sage-grouse (Centrocercus urophasianus, hereafter “sage-grouse”) as a model species. We evaluated whether sage-grouse responded to weather conditions in two ways: through (1) positive selection for refugia habitat to minimize adverse weather exposure, or (2) lowered activity level to minimize thermoregulation and locomotion expense. Our results suggested that sage-grouse respond to winter weather conditions by seeking refugia rather than changing daily activity levels. During periods of lower wind chill temperatures and greater wind speeds, sage-grouse selected areas with sheltered aspects and greater sagebrush (Artemisia spp.) cover. Broadly, sage-grouse selected winter home ranges in sagebrush shrublands characterized by higher wind chill temperatures, greater wind speeds, and greater blizzarding conditions. However, within these home ranges, sage-grouse specifically selected habitats with greater above-snow sagebrush cover, lower wind speeds, and lower blizzarding conditions. Our study underscores the importance of examining habitat selection at narrower temporal scales than entire seasons and demonstrates the value of incorporating targeted weather variables that wholistically synthesize winter conditions. This research allows identification of refugia habitat that sustain populations during winter disproportionate to their spatial extent or frequency of use, facilitating more targeted management and conservation efforts.},
	language = {en},
	number = {2},
	urldate = {2025-05-08},
	journal = {International Journal of Biometeorology},
	author = {Wanner, Caitlyn P. and Pratt, Aaron C. and Reinking, Adele K. and Liston, Glen E. and Beck, Jeffrey L.},
	month = feb,
	year = {2025},
	keywords = {NALCMS},
	pages = {469--485},
}

For non-hibernating species within temperate climates, survival during severe winter weather often depends on individuals’ behavioral response and available refugia. Identifying refugia habitat that sustains populations during adverse winter conditions can be difficult and complex. This study provides an example of how modeled, biologically relevant snow and weather information can help identify important relationships between habitat selection and dynamic winter landscapes using greater sage-grouse (Centrocercus urophasianus, hereafter “sage-grouse”) as a model species. We evaluated whether sage-grouse responded to weather conditions in two ways: through (1) positive selection for refugia habitat to minimize adverse weather exposure, or (2) lowered activity level to minimize thermoregulation and locomotion expense. Our results suggested that sage-grouse respond to winter weather conditions by seeking refugia rather than changing daily activity levels. During periods of lower wind chill temperatures and greater wind speeds, sage-grouse selected areas with sheltered aspects and greater sagebrush (Artemisia spp.) cover. Broadly, sage-grouse selected winter home ranges in sagebrush shrublands characterized by higher wind chill temperatures, greater wind speeds, and greater blizzarding conditions. However, within these home ranges, sage-grouse specifically selected habitats with greater above-snow sagebrush cover, lower wind speeds, and lower blizzarding conditions. Our study underscores the importance of examining habitat selection at narrower temporal scales than entire seasons and demonstrates the value of incorporating targeted weather variables that wholistically synthesize winter conditions. This research allows identification of refugia habitat that sustain populations during winter disproportionate to their spatial extent or frequency of use, facilitating more targeted management and conservation efforts.

@phdthesis{hovland_patterns_2025,
	title = {Patterns and {Consequences} of {Monarch} {Wintering} {Behavior} in the {Southeastern} {US}},
	url = {https://openscholar.uga.edu/record/27798},
	abstract = {Eastern North American monarchs (Danaus plexippus) employ a diversity of overwintering behaviors, including long distance migration to central Mexico, but also winter-breeding and non-breeding overwintering in the southeastern United States. Winter-breeding alters infectious disease dynamics, increasing the prevalence of the monarch parasite Ophryocystis elektroscirrha (O.E.) in winter-breeding populations. I modeled interactions between returning spring migrants and resident winter-breeding monarchs in a simulated habitat patch and found that fewer new migrants were recruited from the patch into the migration when residents were present, and that migrants eclosing in habitat patches shared with residents were more likely to be parasitized than in habitat used only by migrants. Additionally, I fit logistic regression models to associate the breeding status of winter monarchs in the Southeast with habitat characteristics. My results concur with the idea that winter-breeding monarchs use human-modified habitat and suggest non-breeding monarchs may winter in wetlands in warm regions},
	language = {eng},
	urldate = {2026-06-01},
	author = {Hovland, Charlotte Pastor},
	collaborator = {Altizer, Sonia and Hall, Richard and Lunn, Tamika},
	month = dec,
	year = {2025},
	keywords = {NALCMS},
}

Eastern North American monarchs (Danaus plexippus) employ a diversity of overwintering behaviors, including long distance migration to central Mexico, but also winter-breeding and non-breeding overwintering in the southeastern United States. Winter-breeding alters infectious disease dynamics, increasing the prevalence of the monarch parasite Ophryocystis elektroscirrha (O.E.) in winter-breeding populations. I modeled interactions between returning spring migrants and resident winter-breeding monarchs in a simulated habitat patch and found that fewer new migrants were recruited from the patch into the migration when residents were present, and that migrants eclosing in habitat patches shared with residents were more likely to be parasitized than in habitat used only by migrants. Additionally, I fit logistic regression models to associate the breeding status of winter monarchs in the Southeast with habitat characteristics. My results concur with the idea that winter-breeding monarchs use human-modified habitat and suggest non-breeding monarchs may winter in wetlands in warm regions

@phdthesis{perbet_perturbations_2025,
	address = {Quebec City, QC},
	title = {Perturbations et régénérations des forêts canadiennes par télédétection et apprentissage profond},
	url = {https://hdl.handle.net/20.500.11794/178085},
	abstract = {La forêt canadienne joue un rôle crucial en fournissant des biens et services écologiques et économiques, en régulant le climat, et en agissant comme un puits de carbone. Cependant, les perturbations forestières peuvent transformer la forêt en source de carbone. Les changements climatiques ont intensifié la fréquence et l'intensité des perturbations, et potentiellement modifié la capacité de régénération des forêts. Dans ce contexte, la surveillance précise et continue de la dynamique forestière devient stratégique pour les objectifs de carboneutralité du Canada. Plusieurs produits cartographiques développées à partir d'images satellitaires, disponibles depuis quelques années, permettent de suivre les perturbations et l'évolution de la structure des forêts. Cependant, les modèles traditionnellement utilisés rencontrent des difficultés à distinguer les perturbations mineures et les changements progressifs. De plus, les approches utilisées pour observer la croissance post-perturbation à grande échelle, sous-estiment la durée réelle de restauration. L'objectif principal de cette thèse est d'évaluer les méthodes d'apprentissage profond pour améliorer et mettre à jour les cartographies temporelles de la forêt boréale canadienne, tant en ce qui concerne les perturbations que la régénération forestière. Les deux premiers chapitres portent sur l'évaluation de l'apport des méthodes d'apprentissage profond pour la classification des perturbations forestières. Ces nouvelles approches ont d'abord été appliquées à la forêt boréale du Québec dans le premier chapitre, puis étendues à l'ensemble du territoire canadien dans le second. Le troisième chapitre vise quant à lui à évaluer une méthode d'apprentissage profond pour le suivi de la régénération de la biomasse forestière. Les résultats ont montré que l'utilisation d'un réseau de neurones convolutifs unidimensionnels pour classifier des séquences spectro-temporelles courtes améliore la classification des perturbations partielles et progressives. Les cartes de perturbations annuelles au Canada entre 1985 et 2024 présentent de nouvelles classes encore jamais cartographiées à cette échelle spatio-temporelle. En particulier, le modèle de classification à correctement identifié les défoliations moyennes et sévères et résultantes d'épidémies d'insectes forestiers. Dans le troisième chapitre, une approche combinant la série temporelle Landsat, les données de Lidar aérien et un réseau de neurones convolutifs de type Unet a permis de cartographier la biomasse aérienne. Ces cartes annuelles de biomasse ont montré leur intérêt pour observer la dynamique forestière après les perturbations sévères et identifier les zones dont la croissance était problématique. En développant ces nouveaux jeux de données à partir de modèle d'apprentissage profond, cette thèse a permis d'améliorer et de mettre à jour les connaissances sur la dynamique forestière au Canada.},
	language = {French \& English},
	urldate = {2026-06-01},
	school = {Université Laval},
	author = {Perbet, Pauline},
	year = {2025},
	keywords = {NALCMS},
}

La forêt canadienne joue un rôle crucial en fournissant des biens et services écologiques et économiques, en régulant le climat, et en agissant comme un puits de carbone. Cependant, les perturbations forestières peuvent transformer la forêt en source de carbone. Les changements climatiques ont intensifié la fréquence et l'intensité des perturbations, et potentiellement modifié la capacité de régénération des forêts. Dans ce contexte, la surveillance précise et continue de la dynamique forestière devient stratégique pour les objectifs de carboneutralité du Canada. Plusieurs produits cartographiques développées à partir d'images satellitaires, disponibles depuis quelques années, permettent de suivre les perturbations et l'évolution de la structure des forêts. Cependant, les modèles traditionnellement utilisés rencontrent des difficultés à distinguer les perturbations mineures et les changements progressifs. De plus, les approches utilisées pour observer la croissance post-perturbation à grande échelle, sous-estiment la durée réelle de restauration. L'objectif principal de cette thèse est d'évaluer les méthodes d'apprentissage profond pour améliorer et mettre à jour les cartographies temporelles de la forêt boréale canadienne, tant en ce qui concerne les perturbations que la régénération forestière. Les deux premiers chapitres portent sur l'évaluation de l'apport des méthodes d'apprentissage profond pour la classification des perturbations forestières. Ces nouvelles approches ont d'abord été appliquées à la forêt boréale du Québec dans le premier chapitre, puis étendues à l'ensemble du territoire canadien dans le second. Le troisième chapitre vise quant à lui à évaluer une méthode d'apprentissage profond pour le suivi de la régénération de la biomasse forestière. Les résultats ont montré que l'utilisation d'un réseau de neurones convolutifs unidimensionnels pour classifier des séquences spectro-temporelles courtes améliore la classification des perturbations partielles et progressives. Les cartes de perturbations annuelles au Canada entre 1985 et 2024 présentent de nouvelles classes encore jamais cartographiées à cette échelle spatio-temporelle. En particulier, le modèle de classification à correctement identifié les défoliations moyennes et sévères et résultantes d'épidémies d'insectes forestiers. Dans le troisième chapitre, une approche combinant la série temporelle Landsat, les données de Lidar aérien et un réseau de neurones convolutifs de type Unet a permis de cartographier la biomasse aérienne. Ces cartes annuelles de biomasse ont montré leur intérêt pour observer la dynamique forestière après les perturbations sévères et identifier les zones dont la croissance était problématique. En développant ces nouveaux jeux de données à partir de modèle d'apprentissage profond, cette thèse a permis d'améliorer et de mettre à jour les connaissances sur la dynamique forestière au Canada.

@article{brown_predicting_2025,
	title = {Predicting {Rapid}, {Climate}-{Driven} {Shifts} in {North} {American} {Habitat} {Suitability} for the {Purple} {Pitcher} {Plant} ({Sarracenia} purpurea {L}.)},
	volume = {14},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {2223-7747},
	url = {https://www.mdpi.com/2223-7747/14/21/3337},
	doi = {10.3390/plants14213337},
	abstract = {Climate change is shifting where suitable habitats occur for many species across the planet. Sarracenia purpurea L., the most widely distributed pitcher plant species in North America, already faces significant threats from land use change. While S. purpurea is well studied at physiological and local scales, threat assessments for this species at biogeographic scales are absent. Here, we remedy this by using Habitat Suitability Models to predict current suitable habitats and estimate climate-based shifts in the suitable habitat for S. purpurea in the near (2040) and long term (2100). The models predicted large areas of habitat loss in the southeastern United States and the western portion of the Great Lakes region by 2040. While the models also predict significant gains in suitable habitats north of the current S. purpurea range, the limited dispersal ability of this species precludes the possibility of natural migration to newly suitable habitats. Our results suggest that the degradation of considerable portions of current suitable habitats is already occurring and will continue in the future. Particularly threatened are the southern subspecies (e.g., Sarracenia purpurea subsp. venosa) of S. purpurea. We therefore urge land managers to make conservation efforts targeting threatened subspecies and encourage further the biogeographic investigation of less widely distributed congenerics of S. purpurea.},
	language = {en},
	number = {21},
	urldate = {2026-01-21},
	journal = {Plants},
	author = {Brown, Christian H. and Frick, Benjamin L. and Mohan, Jacqueline E.},
	month = jan,
	year = {2025},
	note = {Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {NALCMS},
	pages = {3337},
}

Climate change is shifting where suitable habitats occur for many species across the planet. Sarracenia purpurea L., the most widely distributed pitcher plant species in North America, already faces significant threats from land use change. While S. purpurea is well studied at physiological and local scales, threat assessments for this species at biogeographic scales are absent. Here, we remedy this by using Habitat Suitability Models to predict current suitable habitats and estimate climate-based shifts in the suitable habitat for S. purpurea in the near (2040) and long term (2100). The models predicted large areas of habitat loss in the southeastern United States and the western portion of the Great Lakes region by 2040. While the models also predict significant gains in suitable habitats north of the current S. purpurea range, the limited dispersal ability of this species precludes the possibility of natural migration to newly suitable habitats. Our results suggest that the degradation of considerable portions of current suitable habitats is already occurring and will continue in the future. Particularly threatened are the southern subspecies (e.g., Sarracenia purpurea subsp. venosa) of S. purpurea. We therefore urge land managers to make conservation efforts targeting threatened subspecies and encourage further the biogeographic investigation of less widely distributed congenerics of S. purpurea.

@article{pilat_predicting_2025,
	title = {Predicting {Suitable} {Habitat} for {Skwenkwínem} ({Claytonia} lanceolata), a {Culturally} {Significant} {Plant}, {Using} a {Reproducible} {Species} {Distribution} {Model}},
	volume = {15},
	copyright = {© 2025 His Majesty the King in Right of Canada and The Author(s). Ecology and Evolution published by British Ecological Society and John Wiley \& Sons Ltd. Reproduced with the permission of the Minister of Agriculture and Agri-Food Canada.},
	issn = {2045-7758},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/ece3.72615},
	doi = {10.1002/ece3.72615},
	abstract = {Colonialism and a changing climate have threatened culturally significant food plants and the well-being of those who rely on them. An example is skwenkwínem (western spring beauty, Claytonia lanceolata: Pursh), which has declined in quality and accessibility for the Secwépemc People of Skeetchestn Indian Band. This study aims to provide predictions and visual tools to inform Skeetchestn's conservation efforts for their skwenkwínem patches, from a computationally reproducible species distribution model. Using a set of predictors informed by qualitative interviews with Skeetchestn community members (Informed model), and the 19 bioclimatic variables from WorldClim (WorldClim model), we predicted suitable habitat for skwenkwínem over its known range. For both our total study area and Skeetchestn Territory, we predicted a decrease in suitable habitat from the present to 2081–2100, based on the WorldClim CMIP6 climate change scenario SSP 5–8.5 (worst case). These predictions use Skeetchestn's knowledge of skwenkwínem and commonly used bioclimatic predictors to support Skeetchestn's goals of food sovereignty.},
	language = {en},
	number = {12},
	urldate = {2026-05-28},
	journal = {Ecology and Evolution},
	author = {Pilat, Hannah E. and Ensing, David J. and Pither, Jason},
	year = {2025},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/ece3.72615},
	keywords = {NALCMS},
	pages = {e72615},
}

Colonialism and a changing climate have threatened culturally significant food plants and the well-being of those who rely on them. An example is skwenkwínem (western spring beauty, Claytonia lanceolata: Pursh), which has declined in quality and accessibility for the Secwépemc People of Skeetchestn Indian Band. This study aims to provide predictions and visual tools to inform Skeetchestn's conservation efforts for their skwenkwínem patches, from a computationally reproducible species distribution model. Using a set of predictors informed by qualitative interviews with Skeetchestn community members (Informed model), and the 19 bioclimatic variables from WorldClim (WorldClim model), we predicted suitable habitat for skwenkwínem over its known range. For both our total study area and Skeetchestn Territory, we predicted a decrease in suitable habitat from the present to 2081–2100, based on the WorldClim CMIP6 climate change scenario SSP 5–8.5 (worst case). These predictions use Skeetchestn's knowledge of skwenkwínem and commonly used bioclimatic predictors to support Skeetchestn's goals of food sovereignty.

@article{wilson_predicting_2025,
	title = {Predicting carbon storage in {North} {American} maritime boreal forests under combined disturbances},
	volume = {40},
	issn = {1572-9761},
	url = {https://doi.org/10.1007/s10980-025-02145-6},
	doi = {10.1007/s10980-025-02145-6},
	abstract = {Understanding how forest disturbances, such as fire and herbivory, affect carbon storage across the landscape can help inform forest management and disturbance mitigation. However, this is made difficult by uncertainties in carbon predictions and limited records of disturbance histories.},
	language = {en},
	number = {7},
	urldate = {2025-07-31},
	journal = {Landscape Ecology},
	author = {Wilson, Emmerson R. and Leroux, Shawn J. and Moran, Rachael and Whitaker, Darroch and Wiersma, Yolanda},
	month = jul,
	year = {2025},
	keywords = {NALCMS},
	pages = {131},
}

Understanding how forest disturbances, such as fire and herbivory, affect carbon storage across the landscape can help inform forest management and disturbance mitigation. However, this is made difficult by uncertainties in carbon predictions and limited records of disturbance histories.

@article{schmidt_quantifying_2025,
	title = {Quantifying {Carbon} {Pools} and {Fluxes} in {Southern} {Ontario} {Temperate} {Swamps}},
	volume = {32},
	url = {https://www.mires-and-peat.net/article/151276},
	doi = {10.19189/001c.151276},
	abstract = {Swamps are treed wetlands, which account for the highest areal extent of wetland types in Southern Ontario due to the difficulties of conversion for development and agriculture. However, little is known about the environmental factors and processes that influence carbon (C) dynamics or the resulting C stocks and fluxes therein. We studied 12 swamps across Southern Ontario for 12 consecutive months to measure the exchange of carbon dioxide (CO{\textasciitilde}2{\textasciitilde}) and methane (CH{\textasciitilde}4{\textasciitilde}) between soil and atmosphere and estimate current C stocks in soil and biomass. We found mean growing season soil respiration of CO{\textasciitilde}2{\textasciitilde} and CH{\textasciitilde}4{\textasciitilde} across the swamps ranged from 11 g m{\textasciicircum}-2{\textasciicircum} d{\textasciicircum}-1{\textasciicircum} to 49 g m{\textasciicircum}-2{\textasciicircum} d{\textasciicircum}-1{\textasciicircum} and -3 mg m{\textasciicircum}-2{\textasciicircum} d{\textasciicircum}-1{\textasciicircum} to 44 mg m{\textasciicircum}-2{\textasciicircum} d{\textasciicircum}-1{\textasciicircum}, respectively, with a water table threshold at about 20 cm where fluxes changed substantially. Biomass stored 7.92–37.0 kg m{\textasciicircum}-2{\textasciicircum} of C across the sites, and soil stored 11.6–35.5 kg m{\textasciicircum}-2{\textasciicircum}. Over the study year, the swamps functioned as C sinks and followed similar patterns of relationships to environmental conditions as bogs and fens, with little difference between hydrogeomorphic settings or canopy types.},
	language = {en},
	urldate = {2026-01-21},
	journal = {Mires and Peat},
	author = {Schmidt, Megan A. and Santia, Veronica and Price, Samantha and Khumbani, Harry A. W. and Strack, Maria},
	month = nov,
	year = {2025},
	note = {Publisher: International Mire Conservation Group and International Peatland Society},
	keywords = {Climate Zones, NALCMS, North American Forests, Population Density},
}

Swamps are treed wetlands, which account for the highest areal extent of wetland types in Southern Ontario due to the difficulties of conversion for development and agriculture. However, little is known about the environmental factors and processes that influence carbon (C) dynamics or the resulting C stocks and fluxes therein. We studied 12 swamps across Southern Ontario for 12 consecutive months to measure the exchange of carbon dioxide (CO~2~) and methane (CH~4~) between soil and atmosphere and estimate current C stocks in soil and biomass. We found mean growing season soil respiration of CO~2~ and CH~4~ across the swamps ranged from 11 g m\textasciicircum-2\textasciicircum d\textasciicircum-1\textasciicircum to 49 g m\textasciicircum-2\textasciicircum d\textasciicircum-1\textasciicircum and -3 mg m\textasciicircum-2\textasciicircum d\textasciicircum-1\textasciicircum to 44 mg m\textasciicircum-2\textasciicircum d\textasciicircum-1\textasciicircum, respectively, with a water table threshold at about 20 cm where fluxes changed substantially. Biomass stored 7.92–37.0 kg m\textasciicircum-2\textasciicircum of C across the sites, and soil stored 11.6–35.5 kg m\textasciicircum-2\textasciicircum. Over the study year, the swamps functioned as C sinks and followed similar patterns of relationships to environmental conditions as bogs and fens, with little difference between hydrogeomorphic settings or canopy types.

@article{matz_rdaforest_2025,
	title = {{RDAforest}: {Identifying} {Environmental} {Drivers} of {Polygenic} {Adaptation}},
	volume = {25},
	copyright = {© 2025 The Author(s). Molecular Ecology Resources published by John Wiley \& Sons Ltd.},
	issn = {1755-0998},
	shorttitle = {{RDAforest}},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/1755-0998.70002},
	doi = {10.1111/1755-0998.70002},
	abstract = {Identifying environmental gradients driving genetic adaptation is one of the major goals of ecological genomics. We present RDAforest, a methodology that leverages the predominantly polygenic nature of adaptation and harnesses the versatility of random forest regression to solve this problem. Instead of computing individual SNP-environment associations, RDAforest seeks to explain the overall genetic covariance structure based on multiple environmental predictors. By relying on random forest instead of linear regression, this method can detect non-linear and non-monotonous dependencies as well as all possible interactions between predictors. It also incorporates a novel procedure to select the best predictor out of several correlated ones, and uses jackknifing to model uncertainty of genetic structure determination. Lastly, our methodology incorporates delineation and plotting of “adaptive neighbourhoods”—areas on the landscape that are predicted to harbour differentially adapted individuals. Such maps can be used as a guide for planning conservation and ecological restoration efforts. We demonstrate the use of RDAforest in two simulated scenarios and one real dataset (North American grey wolves).},
	language = {en},
	number = {8},
	urldate = {2026-01-21},
	journal = {Molecular Ecology Resources},
	author = {Matz, Mikhail V. and Black, Kristina L.},
	year = {2025},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/1755-0998.70002},
	keywords = {NALCMS},
	pages = {e70002},
}

Identifying environmental gradients driving genetic adaptation is one of the major goals of ecological genomics. We present RDAforest, a methodology that leverages the predominantly polygenic nature of adaptation and harnesses the versatility of random forest regression to solve this problem. Instead of computing individual SNP-environment associations, RDAforest seeks to explain the overall genetic covariance structure based on multiple environmental predictors. By relying on random forest instead of linear regression, this method can detect non-linear and non-monotonous dependencies as well as all possible interactions between predictors. It also incorporates a novel procedure to select the best predictor out of several correlated ones, and uses jackknifing to model uncertainty of genetic structure determination. Lastly, our methodology incorporates delineation and plotting of “adaptive neighbourhoods”—areas on the landscape that are predicted to harbour differentially adapted individuals. Such maps can be used as a guide for planning conservation and ecological restoration efforts. We demonstrate the use of RDAforest in two simulated scenarios and one real dataset (North American grey wolves).

@article{acosta_alamo_rapid_2025,
	title = {Rapid {Rates} of {Change} in {Multiple} {Biodiversity} {Measures} in {Breeding} {Avian} {Assemblages}},
	volume = {17},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {1424-2818},
	url = {https://www.mdpi.com/1424-2818/17/2/127},
	doi = {10.3390/d17020127},
	abstract = {Species respond to environmental changes at different rates, resulting in no change, increased, or decreased resemblance among species assemblages. We explored the patterns of rate of change in bird diversity in five ecoregions of the United States across 30 years. We characterized the rate of change in breeding avian biodiversity using measures of species richness and assemblage dissimilarity, detecting changes in the same for 50\% and 70\% of the assemblages, respectively. Fast richness declines and species replacement were associated with rapid biotic differentiation within ecoregions, while rapid increases in richness and slowed species replacement were tied to high within-ecoregion biotic homogenization rates. Further, it was exceedingly rare for any biodiversity measured to change slowly over time; most changes were rapid. For the species assemblages studied here, changes in assemblage dissimilarity patterns were more common than changes in species richness, even though species richness has received more research attention. These results underscore the need to combine measures capturing different aspects of biodiversity (e.g., species richness and assemblage differentiation) to provide greater insight into the underlying mechanisms and pathways driving changes in biodiversity patterns.},
	language = {en},
	number = {2},
	urldate = {2025-07-31},
	journal = {Diversity},
	author = {Acosta Alamo, Marlen and Manne, Lisa L.},
	month = feb,
	year = {2025},
	note = {Number: 2
Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {Terrestrial Ecoregions, Terrestrial Ecoregions (CEC 1997)},
	pages = {127},
}

Species respond to environmental changes at different rates, resulting in no change, increased, or decreased resemblance among species assemblages. We explored the patterns of rate of change in bird diversity in five ecoregions of the United States across 30 years. We characterized the rate of change in breeding avian biodiversity using measures of species richness and assemblage dissimilarity, detecting changes in the same for 50% and 70% of the assemblages, respectively. Fast richness declines and species replacement were associated with rapid biotic differentiation within ecoregions, while rapid increases in richness and slowed species replacement were tied to high within-ecoregion biotic homogenization rates. Further, it was exceedingly rare for any biodiversity measured to change slowly over time; most changes were rapid. For the species assemblages studied here, changes in assemblage dissimilarity patterns were more common than changes in species richness, even though species richness has received more research attention. These results underscore the need to combine measures capturing different aspects of biodiversity (e.g., species richness and assemblage differentiation) to provide greater insight into the underlying mechanisms and pathways driving changes in biodiversity patterns.

@article{boulanger_recent_2025,
	title = {Recent climate change strongly impacted the population dynamic of a {North} {American} insect pest species},
	volume = {4},
	issn = {2767-3200},
	url = {https://journals.plos.org/climate/article?id=10.1371/journal.pclm.0000488},
	doi = {10.1371/journal.pclm.0000488},
	abstract = {Climate change is redefining the dynamics of forest ecosystems globally, particularly through its impact on forest pest populations such as the spruce budworm (SBW, Choristoneura fumiferana [Clem.]), a major defoliator in North American boreal forests. This study investigates the shifts in the population dynamics of spruce budworm across its range in response to recent climate change. We used a process-based, temperature-dependent ecophysiological model combined with the ERA5 reanalysis to assess changes in SBW phenology, reproduction rate, winter survival and population growth rates from 1950 to 2022 across North America. Our findings demonstrate a pronounced northward expansion of suitable climate conditions for SBW, accompanied by earlier phenological events and increased reproduction rates in northern regions. Conversely, the southern parts of its range are experiencing increased winter mortality due to warmer temperatures. This study highlights the significant impact of elevated temperatures, particularly during critical developmental windows such as spring and summer, which are pivotal for spruce budworm survival and reproduction. Additionally, our results reveal that the observed shifts in pest dynamics are more strongly driven by climate change than by changes in landscape composition and structure. We estimated that suitable growth rates have shifted northward by over 68 km on average, but this shift reached more than 200 km in the easternmost portions of its range. Climate-induced shift in suitable conditions for SBW underscores the need for adaptive forest management strategies that consider the rapid ecological changes and the potential for increased forest vulnerability due to climatic and biotic stressors. This study provides vital insights that can inform adaptive management ensuring the sustainability of forest ecosystems in the face of ongoing climate change.},
	language = {en},
	number = {2},
	urldate = {2025-07-31},
	journal = {PLOS Climate},
	author = {Boulanger, Yan and Desaint, Adèle and Martel, Véronique and Marchand, Maryse and Tonye, Salomon Massoda and Saint-Amant, Rémi and Régnière, Jacques},
	month = feb,
	year = {2025},
	note = {Publisher: Public Library of Science},
	keywords = {Political Boundaries},
	pages = {e0000488},
}

Climate change is redefining the dynamics of forest ecosystems globally, particularly through its impact on forest pest populations such as the spruce budworm (SBW, Choristoneura fumiferana [Clem.]), a major defoliator in North American boreal forests. This study investigates the shifts in the population dynamics of spruce budworm across its range in response to recent climate change. We used a process-based, temperature-dependent ecophysiological model combined with the ERA5 reanalysis to assess changes in SBW phenology, reproduction rate, winter survival and population growth rates from 1950 to 2022 across North America. Our findings demonstrate a pronounced northward expansion of suitable climate conditions for SBW, accompanied by earlier phenological events and increased reproduction rates in northern regions. Conversely, the southern parts of its range are experiencing increased winter mortality due to warmer temperatures. This study highlights the significant impact of elevated temperatures, particularly during critical developmental windows such as spring and summer, which are pivotal for spruce budworm survival and reproduction. Additionally, our results reveal that the observed shifts in pest dynamics are more strongly driven by climate change than by changes in landscape composition and structure. We estimated that suitable growth rates have shifted northward by over 68 km on average, but this shift reached more than 200 km in the easternmost portions of its range. Climate-induced shift in suitable conditions for SBW underscores the need for adaptive forest management strategies that consider the rapid ecological changes and the potential for increased forest vulnerability due to climatic and biotic stressors. This study provides vital insights that can inform adaptive management ensuring the sustainability of forest ecosystems in the face of ongoing climate change.

@article{li_reconstructing_2025,
	title = {Reconstructing {Evapotranspiration} in {British} {Columbia} {Since} 1850 {Using} {Publicly} {Available} {Tree}-{Ring} {Plots} and {Climate} {Data}},
	volume = {17},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {2072-4292},
	url = {https://www.mdpi.com/2072-4292/17/5/930},
	doi = {10.3390/rs17050930},
	abstract = {Evapotranspiration (ET) rates will be affected by climate change and increasing frequency of extreme heat events. To understand how forests may respond to probable future climate conditions, it may be helpful to look at the past relationship between climate and ET. This can be accomplished using satellite imagery since the 1980s, but prior to that, a different approach is required. Using a global ET dataset (1982 to 2010) with 1 km resolution, climate station information from 1850 to 2010, and 54 tree-ring plots from the International Tree-Ring Data Bank (ITRDB) database, ET reconstructions were developed for each vegetated pixel with point-by-point regressions in British Columbia. ET was estimated for the province of British Columbia in Canada from 1850 to 1981, using random forest, support vector machine, and convolutional neural network regressions. ET satellite images from 1982 to 2010 formed our dataset to train models for each vegetated pixel. The random forest regression outperformed the other approaches with lower errors and better robustness (adjusted R2 value = 0.69; root mean square error = 10.72 mm/month). Modeled findings indicate that ET rates are generally increasing in British Columbia (ET = 0.0064 × Year + 52.339), but there were regional effects on local ET, as only the Humid Temperate ecodomain had strong correlations of ET with mean summer temperature (r = 0.257, p {\textless} 0.01) and mean summer precipitation (r = −0.208, p {\textless} 0.05). These historical estimates provide an opportunity to observe spatiotemporal variation in ET across British Columbia and elsewhere.},
	language = {en},
	number = {5},
	urldate = {2025-07-31},
	journal = {Remote Sensing},
	author = {Li, Hang and Rex, John},
	month = jan,
	year = {2025},
	note = {Number: 5
Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {NALCMS},
	pages = {930},
}

Evapotranspiration (ET) rates will be affected by climate change and increasing frequency of extreme heat events. To understand how forests may respond to probable future climate conditions, it may be helpful to look at the past relationship between climate and ET. This can be accomplished using satellite imagery since the 1980s, but prior to that, a different approach is required. Using a global ET dataset (1982 to 2010) with 1 km resolution, climate station information from 1850 to 2010, and 54 tree-ring plots from the International Tree-Ring Data Bank (ITRDB) database, ET reconstructions were developed for each vegetated pixel with point-by-point regressions in British Columbia. ET was estimated for the province of British Columbia in Canada from 1850 to 1981, using random forest, support vector machine, and convolutional neural network regressions. ET satellite images from 1982 to 2010 formed our dataset to train models for each vegetated pixel. The random forest regression outperformed the other approaches with lower errors and better robustness (adjusted R2 value = 0.69; root mean square error = 10.72 mm/month). Modeled findings indicate that ET rates are generally increasing in British Columbia (ET = 0.0064 × Year + 52.339), but there were regional effects on local ET, as only the Humid Temperate ecodomain had strong correlations of ET with mean summer temperature (r = 0.257, p \textless 0.01) and mean summer precipitation (r = −0.208, p \textless 0.05). These historical estimates provide an opportunity to observe spatiotemporal variation in ET across British Columbia and elsewhere.

@article{babadi_ataabadi_reconstructing_2025,
	title = {Reconstructing {Historical} {Landsat} {Time} {Series} {Using} a {Transformer}-{Based} {Deep} {Learning} {Approach}: {A} {Case} {Study} in the {Canadian} {Prairies} {Region}},
	volume = {51},
	issn = {0703-8992},
	shorttitle = {Reconstructing {Historical} {Landsat} {Time} {Series} {Using} a {Transformer}-{Based} {Deep} {Learning} {Approach}},
	url = {https://doi.org/10.1080/07038992.2025.2603738},
	doi = {10.1080/07038992.2025.2603738},
	abstract = {The Landsat program is crucial for monitoring environmental changes, benefiting from its long record of moderate-spatial-resolution imagery, well-established calibration, and commitment to providing open-access data. However, the sparse and irregular observation intervals in Landsat time series pose challenges for applications requiring temporally consistent data. This study evaluates the performance of two deep learning models, CFC-mmRNN and a Transformer-based network, for reconstructing Landsat time series under varying data availability conditions. Accuracy is analyzed across spectral bands, seasons, and data densities to assess their effectiveness in handling irregular temporal gaps. The results indicate that the Transformer model outperforms CfC-mmRNN. While both models achieve similar accuracy in high-density cases, CfC-mmRNN’s performance declines sharper as data density decreases. In contrast, the Transformer model maintains the temporal structure of the reconstructed time series even at very low densities, with about two observations per year. These findings suggest that CfC-mmRNN remains effective for time series applications when sufficient observations are available, and it is directly applicable to forecasting tasks. The Transformer model, however, offers a more robust solution for reconstructing sparse Landsat time series, particularly in data-scarce conditions. This study underscores the importance of selecting an appropriate deep learning method to enhance Landsat time series reconstruction.},
	number = {1},
	urldate = {2026-05-21},
	journal = {Canadian Journal of Remote Sensing},
	author = {Babadi Ataabadi, Masoud and Pouliot, Darren and Chen, Dongmei and Oluwadare, Temitope Seun},
	month = dec,
	year = {2025},
	note = {Publisher: Taylor \& Francis
\_eprint: https://doi.org/10.1080/07038992.2025.2603738},
	keywords = {NALCMS},
	pages = {2603738},
}

The Landsat program is crucial for monitoring environmental changes, benefiting from its long record of moderate-spatial-resolution imagery, well-established calibration, and commitment to providing open-access data. However, the sparse and irregular observation intervals in Landsat time series pose challenges for applications requiring temporally consistent data. This study evaluates the performance of two deep learning models, CFC-mmRNN and a Transformer-based network, for reconstructing Landsat time series under varying data availability conditions. Accuracy is analyzed across spectral bands, seasons, and data densities to assess their effectiveness in handling irregular temporal gaps. The results indicate that the Transformer model outperforms CfC-mmRNN. While both models achieve similar accuracy in high-density cases, CfC-mmRNN’s performance declines sharper as data density decreases. In contrast, the Transformer model maintains the temporal structure of the reconstructed time series even at very low densities, with about two observations per year. These findings suggest that CfC-mmRNN remains effective for time series applications when sufficient observations are available, and it is directly applicable to forecasting tasks. The Transformer model, however, offers a more robust solution for reconstructing sparse Landsat time series, particularly in data-scarce conditions. This study underscores the importance of selecting an appropriate deep learning method to enhance Landsat time series reconstruction.

@article{drever_restoring_2025,
	title = {Restoring forest cover at diverse sites across {Canada} can balance synergies and trade-offs},
	issn = {2590-3322},
	url = {https://www.sciencedirect.com/science/article/pii/S259033222500003X},
	doi = {10.1016/j.oneear.2025.101177},
	abstract = {Swift action to restore forests is critical for mitigating climate change and preserving biodiversity. Canada has an ambitious program to plant two billion trees to help exceed the country’s emissions targets while restoring forest habitat and providing social and economic benefits. We conducted a systematic analysis of where new tree cover can maximally achieve these benefits while minimizing implementation costs. Accounting for critiques of global restoration mapping that include the overestimation of mitigation potential and inadequate biodiversity and social safeguards, we find that 19.1 Mha are available, which is much more than the approximately 1.2 Mha needed to plant two billion trees. Optimization scenarios for 1.2 Mha revealed synergies and trade-offs. Scenarios prioritizing low costs, accessibility, and high growth are concentrated in temperate and coastal areas, overlapping partly with biodiversity scenarios, but with trade-offs of higher costs. A diverse portfolio of regionally restored sites, each tailored for specific attributes, is most likely to deliver multiple benefits at the pace demanded by the current crises.},
	urldate = {2025-01-20},
	journal = {One Earth},
	author = {Drever, C. Ronnie and Long, Alison M. and Cook-Patton, Susan C. and Celanowicz, Elizabeth and Fargione, Joe and Fisher, Kathryn and Hounsell, Steve and Kurz, Werner A. and Mitchell, Matthew and Robinson, Nathaniel and Pither, Richard and Schuster, Richard and Deziel, Val and Xu, Zach},
	month = jan,
	year = {2025},
	keywords = {NALCMS},
	pages = {101177},
}

Swift action to restore forests is critical for mitigating climate change and preserving biodiversity. Canada has an ambitious program to plant two billion trees to help exceed the country’s emissions targets while restoring forest habitat and providing social and economic benefits. We conducted a systematic analysis of where new tree cover can maximally achieve these benefits while minimizing implementation costs. Accounting for critiques of global restoration mapping that include the overestimation of mitigation potential and inadequate biodiversity and social safeguards, we find that 19.1 Mha are available, which is much more than the approximately 1.2 Mha needed to plant two billion trees. Optimization scenarios for 1.2 Mha revealed synergies and trade-offs. Scenarios prioritizing low costs, accessibility, and high growth are concentrated in temperate and coastal areas, overlapping partly with biodiversity scenarios, but with trade-offs of higher costs. A diverse portfolio of regionally restored sites, each tailored for specific attributes, is most likely to deliver multiple benefits at the pace demanded by the current crises.

@article{maavara_river_2025,
	title = {River metabolism in the contiguous {United} {States}: {A} {West} of extremes},
	volume = {390},
	shorttitle = {River metabolism in the contiguous {United} {States}},
	url = {https://www.science.org/doi/abs/10.1126/science.adu9843},
	doi = {10.1126/science.adu9843},
	abstract = {River metabolism is among the most uncertain fluxes in the global carbon cycle. We present estimates for gross primary productivity (GPP) and ecosystem respiration (ER) for more than 175,000 rivers across the contiguous United States (CONUS), including metabolic responses to extreme hydrological conditions. Our model predicts an annual GPP in CONUS rivers of 10.1 teragrams of carbon per year and an ER of 18.7 teragrams of carbon per year, which implies that net ecosystem productivity (NEP; where NEP = GPP – ER) is a small contributor to river carbon dioxide emissions. More than 70\% of river metabolism occurs in the West, where regions of both extreme heterotrophy and autotrophy exist. Autotrophy is prominent across the West and is sensitive to drought, particularly in understudied biomes such as arid desert shrublands, which may indicate that global riverine uptake of carbon dioxide is higher than hypothesized.},
	number = {6773},
	urldate = {2026-01-21},
	journal = {Science},
	author = {Maavara, Taylor and Yuan, Zimin and Johnson, Andrew M. and Zhang, Shuang and Aho, Kelly S. and Brinkerhoff, Craig B. and Logozzo, Laura A. and Raymond, Peter},
	month = nov,
	year = {2025},
	note = {Publisher: American Association for the Advancement of Science},
	keywords = {NALCMS},
	pages = {622--627},
}

River metabolism is among the most uncertain fluxes in the global carbon cycle. We present estimates for gross primary productivity (GPP) and ecosystem respiration (ER) for more than 175,000 rivers across the contiguous United States (CONUS), including metabolic responses to extreme hydrological conditions. Our model predicts an annual GPP in CONUS rivers of 10.1 teragrams of carbon per year and an ER of 18.7 teragrams of carbon per year, which implies that net ecosystem productivity (NEP; where NEP = GPP – ER) is a small contributor to river carbon dioxide emissions. More than 70% of river metabolism occurs in the West, where regions of both extreme heterotrophy and autotrophy exist. Autotrophy is prominent across the West and is sensitive to drought, particularly in understudied biomes such as arid desert shrublands, which may indicate that global riverine uptake of carbon dioxide is higher than hypothesized.

@article{saunders_routine_2025,
	title = {Routine monitoring in the {Maritime} {Provinces}, {Canada} reveals novel records and range extensions for introduced red algal ({Rhodophyta}) species},
	volume = {103},
	issn = {1916-2790},
	url = {https://cdnsciencepub.com/doi/full/10.1139/cjb-2025-0029},
	doi = {10.1139/cjb-2025-0029},
	abstract = {The senior author has been studying seaweed diversity in the Maritime Provinces over the past 30 years. In recent years, ongoing baseline surveys have revealed novel species and range extensions into these coastal waters. The gradual creep of Bonnemaisonia hamifera Hariot and the first records for Antithamnion cf. sparsum Tokida, Dasysiphonia japonica (Yendo) H.-S.Kim, and Lomentaria orcadensis (Harvey) Collins in the Bay of Fundy are provided. Additionally, the first Canadian records for Bangia sp. 1Asia, Callithamnion debile Harvey, and Melanothamnus japonicus (Harvey) Díaz-Tapia \& Maggs are presented. Further, the overlooked species Bangia sp. 4BAN was encountered for the third time in Atlantic Canada joining two previous records in the Bay of Fundy from 2010 (Nova Scotia side) and 2020 (New Brunswick side). Similarly, the presence of Melanothamnus cf. eastwoodiae (Setchell \& N.L.Gardner) Díaz-Tapia \& Maggs is confirmed in Atlantic Canada having been first encountered in 2022. Finally, Dasya elegans (G.Martens) C.Agardh (previously known as Dasya baillouviana (S.G.Gmelin) Montagne) is now recognized as an introduction to the Gulf of Saint Lawrence ca. 1960 and to the Bay of Fundy presumably at some point in the past few years.},
	urldate = {2025-07-31},
	journal = {Botany},
	author = {Saunders, Gary W. and Cassidy, Margaret M. and Dankworth, Marie and Reeves, Olivia and Smith, Andrew and Taylor, Keelie E. and Moore, Tanya E. and Brooks, Cody M.},
	month = jan,
	year = {2025},
	note = {Publisher: NRC Research Press},
	keywords = {Political Boundaries},
	pages = {1--14},
}

The senior author has been studying seaweed diversity in the Maritime Provinces over the past 30 years. In recent years, ongoing baseline surveys have revealed novel species and range extensions into these coastal waters. The gradual creep of Bonnemaisonia hamifera Hariot and the first records for Antithamnion cf. sparsum Tokida, Dasysiphonia japonica (Yendo) H.-S.Kim, and Lomentaria orcadensis (Harvey) Collins in the Bay of Fundy are provided. Additionally, the first Canadian records for Bangia sp. 1Asia, Callithamnion debile Harvey, and Melanothamnus japonicus (Harvey) Díaz-Tapia & Maggs are presented. Further, the overlooked species Bangia sp. 4BAN was encountered for the third time in Atlantic Canada joining two previous records in the Bay of Fundy from 2010 (Nova Scotia side) and 2020 (New Brunswick side). Similarly, the presence of Melanothamnus cf. eastwoodiae (Setchell & N.L.Gardner) Díaz-Tapia & Maggs is confirmed in Atlantic Canada having been first encountered in 2022. Finally, Dasya elegans (G.Martens) C.Agardh (previously known as Dasya baillouviana (S.G.Gmelin) Montagne) is now recognized as an introduction to the Gulf of Saint Lawrence ca. 1960 and to the Bay of Fundy presumably at some point in the past few years.

@phdthesis{liu_science_2025,
	title = {Science {Communication} of {Coastal} {Parks} {Conservation} {Value} {Index} – {CVI}},
	url = {https://hdl.handle.net/10161/32219},
	abstract = {As climate stressors and environmental degradation intensify, coastal landscapes along the US shoreline require urgent conservation and strategic resource allocation. The Conservation Value Index (CVI), a geospatial dataset assessing coastal resilience across 88 US coastal national parks, is designed to inform conservation priorities. However, its complexity poses challenges for effective use by the client, the National Parks Conservation Association (NPCA), and other stakeholders. This project translates CVI data into science communication toolkits, enabling users to explore, interpret, and apply insights for high-level policy discussions and coastal resilience advocacy. This paper also examines the intersection of scientific data and communication, highlighting the role of visualization, narrative framing, and data quality in making complex datasets actionable.},
	language = {en\_US},
	urldate = {2025-07-31},
	author = {Liu, Hope},
	month = apr,
	year = {2025},
	keywords = {Blue Carbon},
}

As climate stressors and environmental degradation intensify, coastal landscapes along the US shoreline require urgent conservation and strategic resource allocation. The Conservation Value Index (CVI), a geospatial dataset assessing coastal resilience across 88 US coastal national parks, is designed to inform conservation priorities. However, its complexity poses challenges for effective use by the client, the National Parks Conservation Association (NPCA), and other stakeholders. This project translates CVI data into science communication toolkits, enabling users to explore, interpret, and apply insights for high-level policy discussions and coastal resilience advocacy. This paper also examines the intersection of scientific data and communication, highlighting the role of visualization, narrative framing, and data quality in making complex datasets actionable.

@article{cannizzaro_shallow_2025,
	title = {Shallow {Waters}, {Deep} {Divergence}: {Epigean} {Amphipods} {Utilize} {Shallow} {Hyporheic} {Habitats} in the {Western} {Allegheny} {Plateau}},
	volume = {2025},
	copyright = {Copyright © 2025 Andrew G. Cannizzaro and David J. Berg. Journal of Zoological Systematics and Evolutionary Research published by John Wiley \& Sons Ltd.},
	issn = {1439-0469},
	shorttitle = {Shallow {Waters}, {Deep} {Divergence}},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1155/jzs/9912359},
	doi = {10.1155/jzs/9912359},
	abstract = {Two new species of freshwater amphipods, Crangonyx ipnoecetes n. sp. and Crangonyx furnaricolus n. sp., are described from intermittent bodies of water in Vinton Furnace State Forest (VFSF), Vinton County, Ohio, USA. The descriptions of these species are based on both morphological and molecular analyses, which identify them as only distantly related despite their syntopic occurrences. These species are estimated to have last shared a common ancestor during the Late Cretaceous or early Paleogene (73–50 Ma) and to have diverged from their closest congeners towards the end of this period. Given the region occupied by these species, it is likely that their distributions were influenced by both preglacial habitats, such as the Teays River, and postglacial structures, such as Lake Tight. Our results suggest that significant gaps in knowledge still exist for the amphipod fauna of the Western Allegheny Plateau (eastern USA), with implications for taxonomy and conservation of Crangonyx as well as the natural history of the plateau and surrounding region. Furthermore, the description of these species provides additional evidence for the utilization of shallow hyporheic habitats by epigean Crangonyx spp. These habitats may play significant roles not only for these species, but for other epigean taxa as well.},
	language = {en},
	number = {1},
	urldate = {2026-05-21},
	journal = {Journal of Zoological Systematics and Evolutionary Research},
	author = {Cannizzaro, Andrew G. and Berg, David J.},
	year = {2025},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1155/jzs/9912359},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {9912359},
}

Two new species of freshwater amphipods, Crangonyx ipnoecetes n. sp. and Crangonyx furnaricolus n. sp., are described from intermittent bodies of water in Vinton Furnace State Forest (VFSF), Vinton County, Ohio, USA. The descriptions of these species are based on both morphological and molecular analyses, which identify them as only distantly related despite their syntopic occurrences. These species are estimated to have last shared a common ancestor during the Late Cretaceous or early Paleogene (73–50 Ma) and to have diverged from their closest congeners towards the end of this period. Given the region occupied by these species, it is likely that their distributions were influenced by both preglacial habitats, such as the Teays River, and postglacial structures, such as Lake Tight. Our results suggest that significant gaps in knowledge still exist for the amphipod fauna of the Western Allegheny Plateau (eastern USA), with implications for taxonomy and conservation of Crangonyx as well as the natural history of the plateau and surrounding region. Furthermore, the description of these species provides additional evidence for the utilization of shallow hyporheic habitats by epigean Crangonyx spp. These habitats may play significant roles not only for these species, but for other epigean taxa as well.

@article{dahlin_simulated_2025,
	title = {Simulated biodiversity hotspots from traditional ecological knowledge and {Western} metrics do not always overlap},
	volume = {6},
	copyright = {2025 The Author(s)},
	issn = {2662-4435},
	url = {https://www.nature.com/articles/s43247-025-02309-x},
	doi = {10.1038/s43247-025-02309-x},
	abstract = {As global change reshapes ecosystems, establishing conservation priorities is crucial for managing threatened areas with limited resources. Biodiversity hotspots, often defined by high endemism, are key in conservation management. However, these may not capture other dimensions of biodiversity, including functional and phylogenetic diversity or knowledge from Indigenous communities. Here, we demonstrate that different metrics identify different hotspots using simulated plant communities as a case study. We compiled existing data on 318 plant species, including functional trait data and Traditional Ecological Knowledge on Indigenous plant names and uses. We simulated 100,000 communities by randomly assembling species that naturally co-occur within an ecoregion, and calculated taxonomic, phylogenetic, functional, and Traditional Ecological Knowledge-based biodiversity metrics. The metrics cluster into two groups based on shared hotspot identification, with phylogenetic and functional metrics distributed between groups, and Traditional Ecological Knowledge-based metrics aligning with some metrics, but not all. This suggests that integrating Traditional Ecological Knowledge into conservation planning can expand the scope of biodiversity assessments and help recognize places of cultural significance that might otherwise be overlooked.},
	language = {en},
	number = {1},
	urldate = {2025-07-31},
	journal = {Communications Earth \& Environment},
	author = {Dahlin, Kyle J.-M. and Van Cleemput, Elisa and Adhikari, Subodh and Castillioni, Karen and Strickland, Lynette R.},
	month = may,
	year = {2025},
	note = {Publisher: Nature Publishing Group},
	keywords = {Terrestrial Ecoregions (CEC 1997)},
	pages = {350},
}

As global change reshapes ecosystems, establishing conservation priorities is crucial for managing threatened areas with limited resources. Biodiversity hotspots, often defined by high endemism, are key in conservation management. However, these may not capture other dimensions of biodiversity, including functional and phylogenetic diversity or knowledge from Indigenous communities. Here, we demonstrate that different metrics identify different hotspots using simulated plant communities as a case study. We compiled existing data on 318 plant species, including functional trait data and Traditional Ecological Knowledge on Indigenous plant names and uses. We simulated 100,000 communities by randomly assembling species that naturally co-occur within an ecoregion, and calculated taxonomic, phylogenetic, functional, and Traditional Ecological Knowledge-based biodiversity metrics. The metrics cluster into two groups based on shared hotspot identification, with phylogenetic and functional metrics distributed between groups, and Traditional Ecological Knowledge-based metrics aligning with some metrics, but not all. This suggests that integrating Traditional Ecological Knowledge into conservation planning can expand the scope of biodiversity assessments and help recognize places of cultural significance that might otherwise be overlooked.

@misc{casini_song_2025,
	title = {Song of the {Waters}},
	url = {https://songofthewaters.com/},
	abstract = {A regenerative odyssey along the great loop of north America Cultivating peace on the waterways of North AmericaBridging communities though exchanging stories and songs.Raising awareness of ourrelationship to water. WELCOME TO THE VOYAGE Follow the Song of the Waters on a musical adventure of over 6000 miles around the Great Loop of North America Knoxville},
	language = {es-CO},
	urldate = {2025-10-07},
	author = {Casini, Biko},
	month = jan,
	year = {2025},
	keywords = {Lakes \& Rivers},
}

A regenerative odyssey along the great loop of north America Cultivating peace on the waterways of North AmericaBridging communities though exchanging stories and songs.Raising awareness of ourrelationship to water. WELCOME TO THE VOYAGE Follow the Song of the Waters on a musical adventure of over 6000 miles around the Great Loop of North America Knoxville

@phdthesis{lewis_space_2025,
	address = {Missoula, MT},
	title = {Space {Use}, {Habitat} {Selection}, and {Flight} {Behavior} of {Eagles} {Across} {Northwestern} {North} {America}},
	url = {https://scholarworks.umt.edu/etd/12583/},
	abstract = {Explore millions of resources from scholarly journals, books, newspapers, videos and more, on the ProQuest Platform.},
	language = {en},
	urldate = {2026-01-21},
	school = {University of Montana},
	author = {Lewis, Stephen Bernard},
	month = dec,
	year = {2025},
	keywords = {Landfills, NALCMS},
}

Explore millions of resources from scholarly journals, books, newspapers, videos and more, on the ProQuest Platform.

@article{duran_vanegas_spatial_2025,
	title = {Spatial {Equilibrium} and the {Regional} {Effects} of {Trade} {Liberalization}: {Evidence} from {Mexico}},
	volume = {24},
	copyright = {https://creativecommons.org/licenses/by/4.0},
	issn = {1533-6239},
	shorttitle = {Spatial {Equilibrium} and the {Regional} {Effects} of {Trade} {Liberalization}},
	url = {https://account.economia.lse.ac.uk/index.php/lse-j-elaceaj/article/view/421},
	doi = {10.31389/eco.421},
	abstract = {While there is increasing evidence on the effects of trade liberalization on local labor markets, regional variation in cost and quality of living remains essential to understanding the broader welfare impacts of trade policy. This paper examines how trade liberalization influenced wage disparities between college-educated and noncollege-educated workers, as well as urban amenities, across Mexican municipalities from 1990 to 2010, during the implementation of the 1994 North American Free Trade Agreement (NAFTA). Using a detailed database that estimates each municipality’s exposure to international trade based on the lowest-cost transport route to the nearest US truck port, I find that areas more exposed to trade experienced reductions in wage gaps between college and non-college workers. However, these reductions were more pronounced in nominal wages than in real wages (adjusted for housing costs). Additionally, more exposed municipalities saw smaller improvements in urban amenities. Consequently, while low-skill workers benefited from higher nominal wages, these gains were partly offset by rising living costs and lower urban amenities. These findings highlight the importance of housing affordability and public goods provision as policy tools to address the uneven effects of trade reforms.
 
JEL Classification Codes: F1; J31; R23; R31; O15},
	number = {1},
	urldate = {2025-07-31},
	journal = {Economía},
	author = {Duran Vanegas, Juan},
	month = feb,
	year = {2025},
	keywords = {Major Roads},
}

While there is increasing evidence on the effects of trade liberalization on local labor markets, regional variation in cost and quality of living remains essential to understanding the broader welfare impacts of trade policy. This paper examines how trade liberalization influenced wage disparities between college-educated and noncollege-educated workers, as well as urban amenities, across Mexican municipalities from 1990 to 2010, during the implementation of the 1994 North American Free Trade Agreement (NAFTA). Using a detailed database that estimates each municipality’s exposure to international trade based on the lowest-cost transport route to the nearest US truck port, I find that areas more exposed to trade experienced reductions in wage gaps between college and non-college workers. However, these reductions were more pronounced in nominal wages than in real wages (adjusted for housing costs). Additionally, more exposed municipalities saw smaller improvements in urban amenities. Consequently, while low-skill workers benefited from higher nominal wages, these gains were partly offset by rising living costs and lower urban amenities. These findings highlight the importance of housing affordability and public goods provision as policy tools to address the uneven effects of trade reforms.   JEL Classification Codes: F1; J31; R23; R31; O15

@phdthesis{wang_spatiotemporal_2025,
	title = {Spatiotemporal {Dynamics} and {Climate}-{Driven} {Risk} of {Compound} {Flood} {Events} in the {Great} {Lakes} {Basin}},
	url = {https://hdl.handle.net/20.500.14721/38586},
	abstract = {Floods are among the most frequent and economically significant natural hazards affecting communities worldwide. Understanding their mechanisms, spatiotemporal patterns and projected changes is crucial to develop effective strategies for risk mitigation. This study analyzes three types of climate-driven flood events in the Great Lakes basin, driven by Rain-on-Snow (ROS), Saturation Excess flooding (SEF), and Successive Rainfall (SR), in the historical period (1985-2014) and the future period (2071-2100). Assessments are based on WRF-Hydro simulations forced by RDRS observations and eight downscaled and bias-adjusted General Circulation Models (GCMs) under SSP5-8.5 emission scenario. Based on the model outputs, the characteristics of extreme events including intensity, frequency, and seasonality, are evaluated and their contributions to the heavy runoff are investigated. Furthermore, flood risk is characterized by integrating the intensity and frequency of events with exposure and vulnerability for the Great Lakes basin. Overall, snow-related events are projected to decrease, while rain-related events are expected to increase. Single rainfall extreme events are projected to dominate future surface runoff generation, while single snowmelt events are more sensitive to climate change in the northern sub-basin. The contribution of ROS is less pronounced and is expected to decrease, whereas the SEF events show a higher contribution with an increasing impact in the future period. In addition, flood temporal and spatial correlation analyses show that future floods are likely to occur earlier, with increasing spring floods across the region. The spatial correlation between floods in the Lake Erie and Lake Michigan Basins is stronger and projected to increase, suggesting greater influence from large-scale atmospheric drivers. The seasonal shifts underscore the need for adaptive, season-specific flood management policies in the Great Lakes region. These results emphasize that the study of compound extreme events should move beyond individual event characteristics and place greater emphasis on hydroclimatic interactions and their associated impacts.},
	language = {en},
	urldate = {2026-01-21},
	school = {The University of Western Ontario},
	author = {Wang, Yuxuan},
	month = aug,
	year = {2025},
	keywords = {NALCMS},
}

Floods are among the most frequent and economically significant natural hazards affecting communities worldwide. Understanding their mechanisms, spatiotemporal patterns and projected changes is crucial to develop effective strategies for risk mitigation. This study analyzes three types of climate-driven flood events in the Great Lakes basin, driven by Rain-on-Snow (ROS), Saturation Excess flooding (SEF), and Successive Rainfall (SR), in the historical period (1985-2014) and the future period (2071-2100). Assessments are based on WRF-Hydro simulations forced by RDRS observations and eight downscaled and bias-adjusted General Circulation Models (GCMs) under SSP5-8.5 emission scenario. Based on the model outputs, the characteristics of extreme events including intensity, frequency, and seasonality, are evaluated and their contributions to the heavy runoff are investigated. Furthermore, flood risk is characterized by integrating the intensity and frequency of events with exposure and vulnerability for the Great Lakes basin. Overall, snow-related events are projected to decrease, while rain-related events are expected to increase. Single rainfall extreme events are projected to dominate future surface runoff generation, while single snowmelt events are more sensitive to climate change in the northern sub-basin. The contribution of ROS is less pronounced and is expected to decrease, whereas the SEF events show a higher contribution with an increasing impact in the future period. In addition, flood temporal and spatial correlation analyses show that future floods are likely to occur earlier, with increasing spring floods across the region. The spatial correlation between floods in the Lake Erie and Lake Michigan Basins is stronger and projected to increase, suggesting greater influence from large-scale atmospheric drivers. The seasonal shifts underscore the need for adaptive, season-specific flood management policies in the Great Lakes region. These results emphasize that the study of compound extreme events should move beyond individual event characteristics and place greater emphasis on hydroclimatic interactions and their associated impacts.

@phdthesis{lautenbach_subspecies_2025,
	type = {Doctor of {Philosophy}},
	title = {Subspecies {Delineation}, {Habitat} {Ecology}, and {Population} {Demography} of {Sharp}-{Tailed} {Grouse} in {Southcentral} {Wyoming}},
	url = {https://www.proquest.com/openview/68bd2e3c81a398a104fba4fe549d0913/1?pq-origsite=gscholar&cbl=18750&diss=y},
	abstract = {Explore millions of resources from scholarly journals, books, newspapers, videos and more, on the ProQuest Platform.},
	language = {en},
	urldate = {2026-01-21},
	school = {University of Wyoming},
	author = {Lautenbach, Jonathan D.},
	month = apr,
	year = {2025},
}

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@article{slabon_synthetic_2025,
	title = {Synthetic {Aperture} {Radar} as a {Tool} for {Tornado} {Classification} in {Forested} {Areas}},
	volume = {51},
	issn = {0703-8992},
	url = {https://doi.org/10.1080/07038992.2025.2579315},
	doi = {10.1080/07038992.2025.2579315},
	abstract = {Canada’s tornado climatology has historically been challenging to accurately assess. Many Canadian tornadoes are currently rated on the Enhanced Fujita scale using treefall as a damage indicator, though this approach may occasionally underestimate tornado intensity. In this work, we propose that the use of synthetic aperture radar (SAR) images of tornado tracks may lead to more accurate tornado ratings in tornadoes that have at least 25\% of their track consisting of forested areas. We create a replicable methodology by which SAR data can be used to classify tornadoes by generating difference images using Sentinel-1 C-Band radar data acquired before and after the tornado event. We apply this methodology to a large number of recent Canadian tornadoes. The results showed that only higher intensity tornadoes (EF3+) were detectable in the SAR change detection images. Critically, the results revealed possible misclassifications, where tornadoes originally assigned a rating of EF2 based on treefall damage indicators were visible in the SAR imagery. Our study provides a foundation for future work, providing an improved methodology for classifying tornadoes in remote forested areas.},
	number = {1},
	urldate = {2026-01-21},
	journal = {Canadian Journal of Remote Sensing},
	author = {Slabon, Sophia G. and Neish, Catherine D. and Miller, Connell S.},
	month = dec,
	year = {2025},
	note = {Publisher: Taylor \& Francis
\_eprint: https://doi.org/10.1080/07038992.2025.2579315},
	keywords = {NALCMS},
	pages = {2579315},
}

Canada’s tornado climatology has historically been challenging to accurately assess. Many Canadian tornadoes are currently rated on the Enhanced Fujita scale using treefall as a damage indicator, though this approach may occasionally underestimate tornado intensity. In this work, we propose that the use of synthetic aperture radar (SAR) images of tornado tracks may lead to more accurate tornado ratings in tornadoes that have at least 25% of their track consisting of forested areas. We create a replicable methodology by which SAR data can be used to classify tornadoes by generating difference images using Sentinel-1 C-Band radar data acquired before and after the tornado event. We apply this methodology to a large number of recent Canadian tornadoes. The results showed that only higher intensity tornadoes (EF3+) were detectable in the SAR change detection images. Critically, the results revealed possible misclassifications, where tornadoes originally assigned a rating of EF2 based on treefall damage indicators were visible in the SAR imagery. Our study provides a foundation for future work, providing an improved methodology for classifying tornadoes in remote forested areas.

@article{knoben_technical_2025,
	title = {Technical note: {How} many models do we need to simulate hydrologic processes across large geographical domains?},
	volume = {29},
	issn = {1027-5606},
	shorttitle = {Technical note},
	url = {https://hess.copernicus.org/articles/29/2361/2025/},
	doi = {10.5194/hess-29-2361-2025},
	abstract = {Robust large-domain predictions of water availability and threats require models that work well across different basins in the model domain. It is currently common to express a model's accuracy through aggregated efficiency scores such as the Nash–Sutcliffe efficiency and Kling–Gupta efficiency (KGE), and these scores often form the basis to select among competing models. However, recent work has shown that such scores are subject to considerable sampling uncertainty: the exact selection of time steps used to calculate the scores can have large impacts on the scores obtained. Here we explicitly account for this sampling uncertainty to determine the number of models that are needed to simulate hydrologic processes across large spatial domains. Using a selection of 36 conceptual models and 559 basins, our results show that model equifinality, the fact that very different models can produce simulations with very similar accuracy, makes it very difficult to unambiguously select one model over another. If models were selected based on their validation KGE scores alone, almost every model would be selected as the best model in at least some basins. When sampling uncertainty is accounted for, this number drops to 4 models being needed to cover 95 \% of investigated basins and 10 models being needed to cover all basins. We obtain similar conclusions for an objective function focused on low flows. These results suggest that, under the conditions typical of many current modelling studies, there is limited evidence that using a wide variety of different models leads to appreciable differences in simulation accuracy compared to using a smaller number of carefully chosen models.},
	language = {English},
	number = {11},
	urldate = {2025-07-31},
	journal = {Hydrology and Earth System Sciences},
	author = {Knoben, Wouter J. M. and Raman, Ashwin and Gründemann, Gaby J. and Kumar, Mukesh and Pietroniro, Alain and Shen, Chaopeng and Song, Yalan and Thébault, Cyril and van Werkhoven, Katie and Wood, Andrew W. and Clark, Martyn P.},
	month = jun,
	year = {2025},
	note = {Publisher: Copernicus GmbH},
	keywords = {Political Boundaries},
	pages = {2361--2375},
}

Robust large-domain predictions of water availability and threats require models that work well across different basins in the model domain. It is currently common to express a model's accuracy through aggregated efficiency scores such as the Nash–Sutcliffe efficiency and Kling–Gupta efficiency (KGE), and these scores often form the basis to select among competing models. However, recent work has shown that such scores are subject to considerable sampling uncertainty: the exact selection of time steps used to calculate the scores can have large impacts on the scores obtained. Here we explicitly account for this sampling uncertainty to determine the number of models that are needed to simulate hydrologic processes across large spatial domains. Using a selection of 36 conceptual models and 559 basins, our results show that model equifinality, the fact that very different models can produce simulations with very similar accuracy, makes it very difficult to unambiguously select one model over another. If models were selected based on their validation KGE scores alone, almost every model would be selected as the best model in at least some basins. When sampling uncertainty is accounted for, this number drops to 4 models being needed to cover 95 % of investigated basins and 10 models being needed to cover all basins. We obtain similar conclusions for an objective function focused on low flows. These results suggest that, under the conditions typical of many current modelling studies, there is limited evidence that using a wide variety of different models leads to appreciable differences in simulation accuracy compared to using a smaller number of carefully chosen models.

@article{regimbal_acadian_2025,
	title = {The {Acadian} {Flycatcher} is a habitat specialist, and it shows},
	volume = {20},
	copyright = {© 2025 by the author(s)},
	issn = {1712-6568},
	url = {https://ace-eco.org/vol20/iss1/art25/},
	doi = {10.5751/ACE-02892-200125},
	abstract = {Declines in North American bird populations are being driven by a suite of threats, and it can be difficult to disentangle drivers of decline for any single species, especially those with large ranges or that experience different threats in different parts of their range. Community science platforms offer new and rapidly expanding datasets to observe species across space and time. Here, we use community science databases to analyze the habitat characteristics of the Acadian Flycatcher (Empidonax virescens), a Neotropical migrant songbird that is threatened across portions of its range. The Acadian Flycatcher is often described as a habitat specialist, though often only where it is considered at risk. We use Acadian Flycatcher observations sourced from one of the biggest community science platforms, eBird, and assess habitat land cover and co-occurrence of species associated with habitat quality for each of these observations. We use publicly available land use data to assess habitat cover and assess co-occurring species using observations sourced from multiple community science platforms. Our results show the Acadian Flycatcher is largely observed in high-quality landscapes of preferred habitat (31\% deciduous forest and 11\% wetland cover) and without invasive vegetation more than bird observation sites where the Acadian Flycatcher was not detected (25\% more likely to be near preferred trees, 77\% less likely to be near invasive vegetation, p {\textless} 0.001). Our results also show an overrepresentation of urban land cover, potentially highlighting a bias in some community science data due to observer behavior. Overall, our results support land management strategies that maintain patches of native land cover and manage invasive species and highlight how community science databases can provide important information about species’ presence over space and time.},
	language = {en},
	number = {1},
	urldate = {2025-07-31},
	journal = {Avian Conservation and Ecology},
	author = {Regimbal, Nicole L. and Riskin, Shelby H.},
	month = jun,
	year = {2025},
	note = {Publisher: The Resilience Alliance},
	keywords = {NALCMS},
}

Declines in North American bird populations are being driven by a suite of threats, and it can be difficult to disentangle drivers of decline for any single species, especially those with large ranges or that experience different threats in different parts of their range. Community science platforms offer new and rapidly expanding datasets to observe species across space and time. Here, we use community science databases to analyze the habitat characteristics of the Acadian Flycatcher (Empidonax virescens), a Neotropical migrant songbird that is threatened across portions of its range. The Acadian Flycatcher is often described as a habitat specialist, though often only where it is considered at risk. We use Acadian Flycatcher observations sourced from one of the biggest community science platforms, eBird, and assess habitat land cover and co-occurrence of species associated with habitat quality for each of these observations. We use publicly available land use data to assess habitat cover and assess co-occurring species using observations sourced from multiple community science platforms. Our results show the Acadian Flycatcher is largely observed in high-quality landscapes of preferred habitat (31% deciduous forest and 11% wetland cover) and without invasive vegetation more than bird observation sites where the Acadian Flycatcher was not detected (25% more likely to be near preferred trees, 77% less likely to be near invasive vegetation, p \textless 0.001). Our results also show an overrepresentation of urban land cover, potentially highlighting a bias in some community science data due to observer behavior. Overall, our results support land management strategies that maintain patches of native land cover and manage invasive species and highlight how community science databases can provide important information about species’ presence over space and time.

@article{ryan_current_2025,
	title = {The {Current} {Status} and {Distribution} of the {Least} {Tern} {Breeding} in the {Gulf} of {California}, {México}},
	volume = {47},
	issn = {1524-4695, 1938-5390},
	url = {https://bioone.org/journals/waterbirds/volume-47/issue-4/063.047.0405/The-Current-Status-and-Distribution-of-the-Least-Tern-Breeding/10.1675/063.047.0405.full},
	doi = {10.1675/063.047.0405},
	abstract = {The California Least Tern (Sternula antillarum browni) population is declining in California, U.S.A., but little is known about the Least Tern population breeding in the Gulf of California, México. Because of this decline in California, it is important to determine current distribution, population trends, and movements in the nearby Gulf of California. Emigration from coastal California to the Gulf of California is one possible reason for the decline. We analyzed Least Tern colony counts to provide an overview of its current breeding distribution, abundance trends, and connectivity in the Gulf of California. We documented 84 nesting sites, including 61 extant, 10 historic, and 13 sites of unknown status. We estimated the Gulf of California population to be 2,400–3,500 adults, breeding in the 61 extant colonies. Colonies here were small, averaging 49 adults/colony. Most colonies occurred in the Upper Gulf, Gulf Entrance, and on the southern end of the Baja California Peninsula. We estimated a significant negative trend for the population of the Gulf of California. We found no marked individuals in the Gulf of California nesting colonies banded in California or the Baja California peninsula, indicating no regular movement away from coastal California.},
	number = {4},
	urldate = {2025-07-31},
	journal = {Waterbirds},
	author = {Ryan, Thomas P. and Palacios, Eduardo and Amador, Edgar and Lopez, Medardo Cruz and Dolinski, Lauren and Fonseca, Juanita and Alvarez, Adriana Hernández and García, Germán N. Leyva and Reyes, Francisco Jaime Martínez and Parra, Brunilda Rebeca Del Carmen Menares and Espinoza, Manuel Muñoz and Serrato, Liliana Ortiz and Cruz, Ángeles Yazmín Sánchez and Pintos, Graciela Tiburcio},
	month = mar,
	year = {2025},
	note = {Publisher: The Waterbird Society},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {1--17},
}

The California Least Tern (Sternula antillarum browni) population is declining in California, U.S.A., but little is known about the Least Tern population breeding in the Gulf of California, México. Because of this decline in California, it is important to determine current distribution, population trends, and movements in the nearby Gulf of California. Emigration from coastal California to the Gulf of California is one possible reason for the decline. We analyzed Least Tern colony counts to provide an overview of its current breeding distribution, abundance trends, and connectivity in the Gulf of California. We documented 84 nesting sites, including 61 extant, 10 historic, and 13 sites of unknown status. We estimated the Gulf of California population to be 2,400–3,500 adults, breeding in the 61 extant colonies. Colonies here were small, averaging 49 adults/colony. Most colonies occurred in the Upper Gulf, Gulf Entrance, and on the southern end of the Baja California Peninsula. We estimated a significant negative trend for the population of the Gulf of California. We found no marked individuals in the Gulf of California nesting colonies banded in California or the Baja California peninsula, indicating no regular movement away from coastal California.

@book{laako_maya_2025,
	address = {London},
	title = {The {Maya} {Forest} {Waterlands}: {Shared} {Conservation}, {Entangled} {Politics}, and {Fluid} {Borders}},
	isbn = {978-1-003-42905-0},
	shorttitle = {The {Maya} {Forest} {Waterlands}},
	abstract = {This book examines the entanglements and blurred edges of nature conservation and geopolitical relations in the borderlands of the trinational Maya Forest.
Maya Forest is an umbrella term for transboundary conservation developed by scientists and conservationists in the 1990s to protect the threatened rainforest in the borderlands of Mexico, Belize, and Guatemala. Currently, the Maya Forest is a biodiversity hotspot composed of a network of protected areas and heritage sites. However, issues related to water, land, and forests have often been treated as separate political units, and not as part of the same history. Written by two authors with decades of hands-on experience in this region, this book sheds light on the complex dynamics by which conservation and natural resource management geopolitically shape borderlands such as the Maya Forest. The book introduces the novel concept of forest waterlands as borderlands and fluid edges, which are now subject to concern by conservationists. These are entangled spaces in which conservation, peoples, and politics interact, connect, and disconnect with the nexus of waters, forests, and lands. The book sheds light on the building and mapping of the Maya Forest ecoregion, with particular attention to water as an often neglected, but unifying element. It showcases how the Maya Forest is a distinct region characterized by transformations entangled with the Maya, trails of biological stations, the shared history of chicleros (chewing-gum hunters), fluid international rivers and transboundary basins, and various geopolitical discrepancies. It offers a contemporary glimpse into the Maya Forest’s intertwined bio- and geopolitics, which urge us to rethink borders and boundaries.
This book will be of great interest to students and scholars of nature conservation, global environmental politics, geopolitics, borderlands, international relations, and natural resource management.},
	publisher = {Routledge},
	author = {Laako, Hanna and Kauffer, Edith},
	month = feb,
	year = {2025},
	doi = {10.4324/9781003429050},
	keywords = {Terrestrial Ecoregions, Terrestrial Ecoregions (Wiken 2011)},
}

This book examines the entanglements and blurred edges of nature conservation and geopolitical relations in the borderlands of the trinational Maya Forest. Maya Forest is an umbrella term for transboundary conservation developed by scientists and conservationists in the 1990s to protect the threatened rainforest in the borderlands of Mexico, Belize, and Guatemala. Currently, the Maya Forest is a biodiversity hotspot composed of a network of protected areas and heritage sites. However, issues related to water, land, and forests have often been treated as separate political units, and not as part of the same history. Written by two authors with decades of hands-on experience in this region, this book sheds light on the complex dynamics by which conservation and natural resource management geopolitically shape borderlands such as the Maya Forest. The book introduces the novel concept of forest waterlands as borderlands and fluid edges, which are now subject to concern by conservationists. These are entangled spaces in which conservation, peoples, and politics interact, connect, and disconnect with the nexus of waters, forests, and lands. The book sheds light on the building and mapping of the Maya Forest ecoregion, with particular attention to water as an often neglected, but unifying element. It showcases how the Maya Forest is a distinct region characterized by transformations entangled with the Maya, trails of biological stations, the shared history of chicleros (chewing-gum hunters), fluid international rivers and transboundary basins, and various geopolitical discrepancies. It offers a contemporary glimpse into the Maya Forest’s intertwined bio- and geopolitics, which urge us to rethink borders and boundaries. This book will be of great interest to students and scholars of nature conservation, global environmental politics, geopolitics, borderlands, international relations, and natural resource management.

@article{alamo_speed_2025,
	title = {The speed of change in climate and land cover is associated with the speed of biodiversity changes in avian assemblages of the {United} {States}},
	volume = {20},
	issn = {1932-6203},
	url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0330153},
	doi = {10.1371/journal.pone.0330153},
	abstract = {Changes in climate and land use land cover are a widely recognized threat to the stability of natural species assemblages’ composition and biodiversity. Species-specific responses to these changes can result in a rearrangement of the species composition of assemblages, altering the stability, resilience, and functioning of the ecosystems of which these assemblages are a part. We assessed the relationship between the rate of change in avian species richness and assemblage dissimilarity and the rate of change in climatic and land use land cover variables across 30 years in five ecoregions of the United States. Areas where effects of changing land use land cover and/or climate were most strongly felt were high elevations and latitudes. Rates of species replacement and loss were associated with changing environmental factors in opposite directions. Rates of change in biodiversity were more strongly predicted by rates of change in land use land cover than by rates of change in climate. For the species assemblages studied here, rapidly changing climate and/ or land use land cover was more strongly affecting total assemblage dissimilarity patterns than species richness even though species richness has received much more research attention. Trends in multiple biodiversity indices capture multiple levels of action (richness vs. assemblage dissimilarity). A study that integrates these allows us to observe the complex and changing interrelationships between biodiversity and the environment (climate and land cover), and thus, plan effectively for preservation of processes that generate patterns of biodiversity.},
	language = {en},
	number = {8},
	urldate = {2026-01-21},
	journal = {PLOS ONE},
	author = {Alamo, Marlen Acosta and Manne, Lisa L.},
	month = aug,
	year = {2025},
	note = {Publisher: Public Library of Science},
	keywords = {Elevation},
	pages = {e0330153},
}

Changes in climate and land use land cover are a widely recognized threat to the stability of natural species assemblages’ composition and biodiversity. Species-specific responses to these changes can result in a rearrangement of the species composition of assemblages, altering the stability, resilience, and functioning of the ecosystems of which these assemblages are a part. We assessed the relationship between the rate of change in avian species richness and assemblage dissimilarity and the rate of change in climatic and land use land cover variables across 30 years in five ecoregions of the United States. Areas where effects of changing land use land cover and/or climate were most strongly felt were high elevations and latitudes. Rates of species replacement and loss were associated with changing environmental factors in opposite directions. Rates of change in biodiversity were more strongly predicted by rates of change in land use land cover than by rates of change in climate. For the species assemblages studied here, rapidly changing climate and/ or land use land cover was more strongly affecting total assemblage dissimilarity patterns than species richness even though species richness has received much more research attention. Trends in multiple biodiversity indices capture multiple levels of action (richness vs. assemblage dissimilarity). A study that integrates these allows us to observe the complex and changing interrelationships between biodiversity and the environment (climate and land cover), and thus, plan effectively for preservation of processes that generate patterns of biodiversity.

@article{fendereski_tracking_2025,
	title = {Tracking changes in wetlandscape properties of the {Lake} {Winnipeg} {Watershed} using {Landsat} inundation products (1984–2020)},
	volume = {136},
	issn = {1569-8432},
	url = {https://www.sciencedirect.com/science/article/pii/S1569843225000238},
	doi = {10.1016/j.jag.2025.104376},
	abstract = {Wetlandscapes—hydrologically connected networks of wetlands—vary over time, causing changes in their provision of hydrological, biogeochemical, and ecological functions to landscapes. Here, we developed a method for mapping wetlands and extracting wetlandscape properties from Landsat-derived inundation data and applied this method to the Lake Winnipeg Watershed (LWW). We first mapped the annual (1984–2020) time series of inundated areas using a fusion of two Landsat-derived inundation products, Global Surface Water Extent (GSWE) and Dynamic Surface Water Extent (DSWE), finding that this fusion reduced omission errors from 17 \% for GSWE and 18 \% for DSWE to 8 \% overall. We then used the inundated area maps to identify the topological structure of the wetlandscape, i.e., networks composed of nodes (representing wetlands) and their links (representing hydrological connectivity among wetlands). The time series of the wetlandscape properties (number, size, and connectivity of wetlands) showed coherence with a concurrent increase in precipitation over the watershed. The LWW is transitioning to a more extensive wetland area consisting of a greater number of larger wetlands with increased connections among them (p {\textless} 0.1). With Landsat-derived inundation products widely available globally, we suggest using the method developed here to analyze changes in wetlandscape properties in other regions worldwide.},
	urldate = {2025-05-08},
	journal = {International Journal of Applied Earth Observation and Geoinformation},
	author = {Fendereski, Forough and Ma, Shizhou and Mohammady, Sassan and Spence, Christopher and Trick, Charles G. and Creed, Irena F.},
	month = feb,
	year = {2025},
	keywords = {NALCMS},
	pages = {104376},
}

Wetlandscapes—hydrologically connected networks of wetlands—vary over time, causing changes in their provision of hydrological, biogeochemical, and ecological functions to landscapes. Here, we developed a method for mapping wetlands and extracting wetlandscape properties from Landsat-derived inundation data and applied this method to the Lake Winnipeg Watershed (LWW). We first mapped the annual (1984–2020) time series of inundated areas using a fusion of two Landsat-derived inundation products, Global Surface Water Extent (GSWE) and Dynamic Surface Water Extent (DSWE), finding that this fusion reduced omission errors from 17 % for GSWE and 18 % for DSWE to 8 % overall. We then used the inundated area maps to identify the topological structure of the wetlandscape, i.e., networks composed of nodes (representing wetlands) and their links (representing hydrological connectivity among wetlands). The time series of the wetlandscape properties (number, size, and connectivity of wetlands) showed coherence with a concurrent increase in precipitation over the watershed. The LWW is transitioning to a more extensive wetland area consisting of a greater number of larger wetlands with increased connections among them (p \textless 0.1). With Landsat-derived inundation products widely available globally, we suggest using the method developed here to analyze changes in wetlandscape properties in other regions worldwide.

@article{mariotti_transforming_2025,
	title = {Transforming abandoned mines into solar farms: a pathway to renewable energy development and sustainable land use},
	volume = {2},
	issn = {2753-3751},
	shorttitle = {Transforming abandoned mines into solar farms},
	url = {https://dx.doi.org/10.1088/2753-3751/adb6a3},
	doi = {10.1088/2753-3751/adb6a3},
	abstract = {The demand for renewable energy is becoming increasingly apparent, but a significant challenge lies in the limited availability of land. To limit environmental impacts associated with new development in previously undisturbed lands, this study investigates the potential to convert abandoned mines in Florida and Pennsylvania into solar farms, aligning with federal and state-level clean energy goals and climate objectives. Thirteen abandoned mines in Florida and five in Pennsylvania were identified as suitable sites for solar farm development. These solar installations have the potential to generate up to 22\% of Florida’s and 0.017\% of Pennsylvania’s annual electricity needs. Employing various criteria such as acreage, slope, aspect, proximity to infrastructure, and insolation, the research assesses the feasibility of this conversion using advanced modeling techniques. The study was conducted in two phases: first, an in-depth spatial suitability assessment utilizing GIS tools (ArcGIS Pro) to evaluate potential mine sites based on specified criteria. Second, solar power potential and carbon emission reduction are estimated based on the use of two different solar panel setups with different installed capacity and of which one is static and the other one solar-tracking. This study underscores the importance of interdisciplinary approaches in addressing environmental and energy challenges by advancing our understanding of sustainable land use practices and contributing to the collective pursuit of clean energy objectives.},
	language = {en},
	number = {1},
	urldate = {2025-07-31},
	journal = {Environmental Research: Energy},
	author = {Mariotti, Erin and Engström, Johanna},
	month = mar,
	year = {2025},
	note = {Publisher: IOP Publishing},
	keywords = {NALCMS},
	pages = {015013},
}

The demand for renewable energy is becoming increasingly apparent, but a significant challenge lies in the limited availability of land. To limit environmental impacts associated with new development in previously undisturbed lands, this study investigates the potential to convert abandoned mines in Florida and Pennsylvania into solar farms, aligning with federal and state-level clean energy goals and climate objectives. Thirteen abandoned mines in Florida and five in Pennsylvania were identified as suitable sites for solar farm development. These solar installations have the potential to generate up to 22% of Florida’s and 0.017% of Pennsylvania’s annual electricity needs. Employing various criteria such as acreage, slope, aspect, proximity to infrastructure, and insolation, the research assesses the feasibility of this conversion using advanced modeling techniques. The study was conducted in two phases: first, an in-depth spatial suitability assessment utilizing GIS tools (ArcGIS Pro) to evaluate potential mine sites based on specified criteria. Second, solar power potential and carbon emission reduction are estimated based on the use of two different solar panel setups with different installed capacity and of which one is static and the other one solar-tracking. This study underscores the importance of interdisciplinary approaches in addressing environmental and energy challenges by advancing our understanding of sustainable land use practices and contributing to the collective pursuit of clean energy objectives.

@phdthesis{hernandez_gutierrez_nuevo_2025,
	title = {Un nuevo paquete de {R} ({TENM}) para la modelación de nicho ecológico tiempo-específico a partir de series temporales de alta resolución : evaluado en {Urocyon} cinereoargenteus y {Abronia} graminea},
	shorttitle = {Un nuevo paquete de {R} ({TENM}) para la modelación de nicho ecológico tiempo-específico a partir de series temporales de alta resolución},
	url = {https://hdl.handle.net/20.500.14330/TES01000871264},
	language = {spa},
	urldate = {2026-01-21},
	school = {Universidad Nacional Autónoma de México},
	author = {Hernández Gutiérrez, Miguel Ángel},
	year = {2025},
	keywords = {Population Density},
}

@article{boulerice_utilisation_2025,
	title = {Utilisation de l'{ADN} environnemental en milieu lotique pour informer la théorie des métacommunautés},
	url = {http://hdl.handle.net/11143/22610},
	abstract = {L’ADN environnemental (ADNe) est devenu un outil incontournable pour l’étude rapide et non invasive de la biodiversité.Cependant,son application aux systèmes de rivière dans le cadre de la théorie des métacommunautés reste largement inexplorée, les recherches s’étant principalement concentrées sur les milieux lentiques. L’un des principaux défis liés à l’utilisation des données d’ADNe dans les systèmes de rivière réside dans le transport des molécules d’ADN loin de leur site d’excrétion, ce qui peut entraîner des fausses détections. Dans ce mémoire, nous proposons une approche novatrice combinant la théorie des métacommunautés et la modélisation de l’ADN environnemental pour analyser les données d’ADNe des poissons dans les réseaux de rivière. Notre étude porte sur deux bassins versants situés dans la province de Québec, au Canada : les réseaux hydrographiques des rivières Châteauguay et Saint-François. En utilisant le partitionnement de la variation, nous avons identifié les variables qui structurent les métacommunautés de poissons à l’échelle des espèces et des sites. Nos résultats montrent que l’environnement structuré spatialement est le principal moteur des métacommunautés de poissons dans les deux réseaux étudiés, en accord avec le concept de continuum des rivières. De plus, nos analyses capturent la structure des communautés à la fois aux échelles locale et régionale : les variables environnementales non structurées spatialement reflètent les dynamiques à une échelle plus fine, tandis que les variables spatiales mettent en évidence les dynamiques à une échelle plus large. Nous avons également relié nos résultats aux caractéristiques écologiques des espèces, démontrant ainsi que le modèle reflète fidèlement les facteurs environnementaux et biologiques influençant leur distribution. L’analyse des sites révèle toutefois des différences entre les deux bassins versants. Les sites en amont du réseau de la rivière Châteauguay présentent une plus grande diversité écologique, tandis que le réseau de la rivière Saint-François se caractérise par une homogénéité plus marquée. Ces tendances suggèrent que les mécanismes de maintien de la biodiversité varient entre les deux systèmes, confirmant par ailleurs l’efficacité du modèle pour corriger les biais liés à l’ADNe. En conclusion, nos résultats soulignent l’importance d’adopter une perspective basée sur la théorie des métacommunautés pour interpréter les données d’ADN environnemental. Cette approche enrichit la compréhension des systèmes de rivière et met en lumière le potentiel de l’ADNe pour guider les stratégies de conservation et de gestion des habitats d’eau douce.},
	language = {fre},
	urldate = {2025-07-31},
	author = {Boulerice, Laurie},
	month = apr,
	year = {2025},
	note = {Publisher: Université de Sherbrooke},
	keywords = {NALCMS},
}

L’ADN environnemental (ADNe) est devenu un outil incontournable pour l’étude rapide et non invasive de la biodiversité.Cependant,son application aux systèmes de rivière dans le cadre de la théorie des métacommunautés reste largement inexplorée, les recherches s’étant principalement concentrées sur les milieux lentiques. L’un des principaux défis liés à l’utilisation des données d’ADNe dans les systèmes de rivière réside dans le transport des molécules d’ADN loin de leur site d’excrétion, ce qui peut entraîner des fausses détections. Dans ce mémoire, nous proposons une approche novatrice combinant la théorie des métacommunautés et la modélisation de l’ADN environnemental pour analyser les données d’ADNe des poissons dans les réseaux de rivière. Notre étude porte sur deux bassins versants situés dans la province de Québec, au Canada : les réseaux hydrographiques des rivières Châteauguay et Saint-François. En utilisant le partitionnement de la variation, nous avons identifié les variables qui structurent les métacommunautés de poissons à l’échelle des espèces et des sites. Nos résultats montrent que l’environnement structuré spatialement est le principal moteur des métacommunautés de poissons dans les deux réseaux étudiés, en accord avec le concept de continuum des rivières. De plus, nos analyses capturent la structure des communautés à la fois aux échelles locale et régionale : les variables environnementales non structurées spatialement reflètent les dynamiques à une échelle plus fine, tandis que les variables spatiales mettent en évidence les dynamiques à une échelle plus large. Nous avons également relié nos résultats aux caractéristiques écologiques des espèces, démontrant ainsi que le modèle reflète fidèlement les facteurs environnementaux et biologiques influençant leur distribution. L’analyse des sites révèle toutefois des différences entre les deux bassins versants. Les sites en amont du réseau de la rivière Châteauguay présentent une plus grande diversité écologique, tandis que le réseau de la rivière Saint-François se caractérise par une homogénéité plus marquée. Ces tendances suggèrent que les mécanismes de maintien de la biodiversité varient entre les deux systèmes, confirmant par ailleurs l’efficacité du modèle pour corriger les biais liés à l’ADNe. En conclusion, nos résultats soulignent l’importance d’adopter une perspective basée sur la théorie des métacommunautés pour interpréter les données d’ADN environnemental. Cette approche enrichit la compréhension des systèmes de rivière et met en lumière le potentiel de l’ADNe pour guider les stratégies de conservation et de gestion des habitats d’eau douce.

@article{sullender_warm_2025,
	title = {Warm winters, hot moose: temperature drives activity and habitat trade-offs across a cold-adapted species’ range},
	volume = {20},
	issn = {1748-9326},
	shorttitle = {Warm winters, hot moose},
	url = {https://doi.org/10.1088/1748-9326/ae263a},
	doi = {10.1088/1748-9326/ae263a},
	abstract = {Moose (Alces alces) are a cold-adapted species that may be vulnerable to overheating at relatively low temperatures in winter. Moose have two main strategies for thermal regulation: shifting activity patterns and selecting habitat that provides thermal refuge. In this study, we compared how moose use these two strategies in response to winter temperature across their latitudinal range. First, we used hidden Markov models to delineate encamped and traveling movement states for five populations of global positioning system-collared moose in relation to time of day, temperature, and snow depth. Next, we used step-selection functions to determine influential covariates of encamped locations. As air temperatures and snow depths increased, moose from all populations were more likely to remain in an encamped, relatively stationary state. All moose became less diurnal and more nocturnal at high temperatures, although the magnitude of changes in activity varied by population. Encamped northern moose selected shrubby habitat that presents foraging opportunities, whereas encamped southern moose selected for coniferous forest that provides poor forage but offers shade in southern regions. The only moose population to select for lower temperatures also experienced the warmest winter on record during our study period, which may explain this population’s low overall activity rates. Our results indicate that moose along their southern range extent are responding to elevated mid-winter temperatures by initially altering activity patterns and subsequently selecting for potential thermal refugia at the expense of foraging habitat, while northern moose were unlikely to shift habitat selection based on temperature unless faced with an anomalously warm winter. As climate change is implicated in range contraction and population declines, our findings suggest that high winter temperatures may be causing moose to not only reduce overall activity but also to forgo preferred foraging habitat in favor of prioritizing thermal refuge, thus forcing a trade-off between nutrition and thermoregulation.},
	language = {en},
	number = {12},
	urldate = {2026-01-21},
	journal = {Environmental Research Letters},
	author = {Sullender, Benjamin K and Cunningham, Calum X and Reinking, Adele K and Liston, Glen E and Levine, Rebecca L and Verzuh, Tana L and Boelman, Natalie T and Boutin, Stan and Suitor, Mike and Monteith, Kevin L and Hebblewhite, Mark and Brinkman, Todd J and Prugh, Laura R},
	month = dec,
	year = {2025},
	note = {Publisher: IOP Publishing},
	keywords = {NALCMS},
	pages = {124064},
}

Moose (Alces alces) are a cold-adapted species that may be vulnerable to overheating at relatively low temperatures in winter. Moose have two main strategies for thermal regulation: shifting activity patterns and selecting habitat that provides thermal refuge. In this study, we compared how moose use these two strategies in response to winter temperature across their latitudinal range. First, we used hidden Markov models to delineate encamped and traveling movement states for five populations of global positioning system-collared moose in relation to time of day, temperature, and snow depth. Next, we used step-selection functions to determine influential covariates of encamped locations. As air temperatures and snow depths increased, moose from all populations were more likely to remain in an encamped, relatively stationary state. All moose became less diurnal and more nocturnal at high temperatures, although the magnitude of changes in activity varied by population. Encamped northern moose selected shrubby habitat that presents foraging opportunities, whereas encamped southern moose selected for coniferous forest that provides poor forage but offers shade in southern regions. The only moose population to select for lower temperatures also experienced the warmest winter on record during our study period, which may explain this population’s low overall activity rates. Our results indicate that moose along their southern range extent are responding to elevated mid-winter temperatures by initially altering activity patterns and subsequently selecting for potential thermal refugia at the expense of foraging habitat, while northern moose were unlikely to shift habitat selection based on temperature unless faced with an anomalously warm winter. As climate change is implicated in range contraction and population declines, our findings suggest that high winter temperatures may be causing moose to not only reduce overall activity but also to forgo preferred foraging habitat in favor of prioritizing thermal refuge, thus forcing a trade-off between nutrition and thermoregulation.

@article{qiu_wildfire_2025,
	title = {Wildfire smoke exposure and mortality burden in the {USA} under climate change},
	volume = {647},
	copyright = {2025 The Author(s), under exclusive licence to Springer Nature Limited},
	issn = {1476-4687},
	url = {https://www.nature.com/articles/s41586-025-09611-w},
	doi = {10.1038/s41586-025-09611-w},
	abstract = {Wildfire activity has increased in the USA and is projected to accelerate under future climate change1–3. However, our understanding of the impacts of climate change on wildfire activity, smoke and health outcomes remains highly uncertain because of the difficulty of modelling the causal chain from climate to wildfire to air pollution and health. Here we quantify the mortality burden in the USA due to wildfire smoke fine particulate matter (PM2.5) under climate change. We construct an ensemble of statistical and machine learning models that link climate to wildfire smoke PM2.5 and empirically estimate smoke PM2.5–mortality relationships using data on all recorded deaths in the USA. We project that smoke PM2.5 could result in 71,420 excess deaths (95\% confidence interval: 34,930–98,430) per year by 2050 under a high-warming scenario (shared socioeconomic pathway scenario 3-7.0, SSP3-7.0)—a 73\% increase relative to the estimated 2011–2020 average annual excess deaths from smoke. Cumulative excess deaths from smoke PM2.5 could reach 1.9 million between 2026 and 2055. We find evidence for mortality impacts of smoke PM2.5 that last up to 3 years after exposure. When monetized, climate-driven smoke deaths result in economic damages that exceed existing estimates of climate-driven damages from all other causes combined in the USA4,5. Our research suggests that the health impacts of climate-driven wildfire smoke could be among the most important and costly consequences of a warming climate in the USA.},
	language = {en},
	number = {8091},
	urldate = {2026-01-21},
	journal = {Nature},
	author = {Qiu, Minghao and Li, Jessica and Gould, Carlos F. and Jing, Renzhi and Kelp, Makoto and Childs, Marissa L. and Wen, Jeff and Xie, Yuanyu and Lin, Meiyun and Kiang, Mathew V. and Heft-Neal, Sam and Diffenbaugh, Noah S. and Burke, Marshall},
	month = nov,
	year = {2025},
	note = {Publisher: Nature Publishing Group},
	keywords = {NALCMS},
	pages = {935--943},
}

Wildfire activity has increased in the USA and is projected to accelerate under future climate change1–3. However, our understanding of the impacts of climate change on wildfire activity, smoke and health outcomes remains highly uncertain because of the difficulty of modelling the causal chain from climate to wildfire to air pollution and health. Here we quantify the mortality burden in the USA due to wildfire smoke fine particulate matter (PM2.5) under climate change. We construct an ensemble of statistical and machine learning models that link climate to wildfire smoke PM2.5 and empirically estimate smoke PM2.5–mortality relationships using data on all recorded deaths in the USA. We project that smoke PM2.5 could result in 71,420 excess deaths (95% confidence interval: 34,930–98,430) per year by 2050 under a high-warming scenario (shared socioeconomic pathway scenario 3-7.0, SSP3-7.0)—a 73% increase relative to the estimated 2011–2020 average annual excess deaths from smoke. Cumulative excess deaths from smoke PM2.5 could reach 1.9 million between 2026 and 2055. We find evidence for mortality impacts of smoke PM2.5 that last up to 3 years after exposure. When monetized, climate-driven smoke deaths result in economic damages that exceed existing estimates of climate-driven damages from all other causes combined in the USA4,5. Our research suggests that the health impacts of climate-driven wildfire smoke could be among the most important and costly consequences of a warming climate in the USA.

@article{bourget_data_2024,
	title = {A data science approach to climate change risk assessment applied to pluvial flood occurrences for the {United} {States} and {Canada}},
	issn = {0515-0361, 1783-1350},
	url = {https://www.cambridge.org/core/journals/astin-bulletin-journal-of-the-iaa/article/data-science-approach-to-climate-change-risk-assessment-applied-to-pluvial-flood-occurrences-for-the-united-states-and-canada/E28763E2E9F9AFC003CF6806534E47F7},
	doi = {10.1017/asb.2024.19},
	abstract = {There is mounting pressure on (re)insurers to quantify the impacts of climate change, notably on the frequency and severity of claims due to weather events such as flooding. This is however a very challenging task for (re)insurers as it requires modeling at the scale of a portfolio and at a high enough spatial resolution to incorporate local climate change effects. In this paper, we introduce a data science approach to climate change risk assessment of pluvial flooding for insurance portfolios over Canada and the United States (US). The underlying flood occurrence model quantifies the financial impacts of short-term (12–48 h) precipitation dynamics over the present (2010–2030) and future climate (2040–2060) by leveraging statistical/machine learning and regional climate models. The flood occurrence model is designed for applications that do not require street-level precision as is often the case for scenario and trend analyses. It is applied at the full scale of Canada and the US over 10–25 km grids. Our analyses show that climate change and urbanization will typically increase losses over Canada and the US, while impacts are strongly heterogeneous from one state or province to another, or even within a territory. Portfolio applications highlight the importance for a (re)insurer to differentiate between future changes in hazard and exposure, as the latter may magnify or attenuate the impacts of climate change on losses.},
	language = {en},
	urldate = {2024-08-23},
	journal = {ASTIN Bulletin: The Journal of the IAA},
	author = {Bourget, Mathilde and Boudreault, Mathieu and Carozza, David A. and Boudreault, Jérémie and Raymond, Sébastien},
	month = may,
	year = {2024},
	keywords = {NALCMS},
	pages = {1--23},
}

There is mounting pressure on (re)insurers to quantify the impacts of climate change, notably on the frequency and severity of claims due to weather events such as flooding. This is however a very challenging task for (re)insurers as it requires modeling at the scale of a portfolio and at a high enough spatial resolution to incorporate local climate change effects. In this paper, we introduce a data science approach to climate change risk assessment of pluvial flooding for insurance portfolios over Canada and the United States (US). The underlying flood occurrence model quantifies the financial impacts of short-term (12–48 h) precipitation dynamics over the present (2010–2030) and future climate (2040–2060) by leveraging statistical/machine learning and regional climate models. The flood occurrence model is designed for applications that do not require street-level precision as is often the case for scenario and trend analyses. It is applied at the full scale of Canada and the US over 10–25 km grids. Our analyses show that climate change and urbanization will typically increase losses over Canada and the US, while impacts are strongly heterogeneous from one state or province to another, or even within a territory. Portfolio applications highlight the importance for a (re)insurer to differentiate between future changes in hazard and exposure, as the latter may magnify or attenuate the impacts of climate change on losses.

@article{petrakis_ensemble_2024,
	title = {An {Ensemble} {Mean} {Method} for {Remote} {Sensing} of {Actual} {Evapotranspiration} to {Estimate} {Water} {Budget} {Response} across a {Restoration} {Landscape}},
	volume = {16},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {2072-4292},
	url = {https://www.mdpi.com/2072-4292/16/12/2122},
	doi = {10.3390/rs16122122},
	abstract = {Estimates of actual evapotranspiration (ETa) are valuable for effective monitoring and management of water resources. In areas that lack ground-based monitoring networks, remote sensing allows for accurate and consistent estimates of ETa across a broad scale—though each algorithm has limitations (i.e., ground-based validation, temporal consistency, spatial resolution). We developed an ensemble mean ETa (EMET) product to incorporate advancements and reduce uncertainty among algorithms (e.g., energy-balance, optical-only), which we use to estimate vegetative water use in response to restoration practices being implemented on the ground using management interventions (i.e., fencing pastures, erosion control structures) on a private ranch in Baja California Sur, Mexico. This paper describes the development of a monthly EMET product, the assessment of changes using EMET over time and across multiple land use/land cover types, and the evaluation of differences in vegetation and water distribution between watersheds treated by restoration and their controls. We found that in the absence of a ground-based monitoring network, the EMET product is more robust than using a single ETa data product and can augment the efficacy of ETa-based studies. We then found increased ETa within the restored watershed when compared to the control sites, which we attribute to increased plant water availability.},
	language = {en},
	number = {12},
	urldate = {2024-06-28},
	journal = {Remote Sensing},
	author = {Petrakis, Roy E. and Norman, Laura M. and Villarreal, Miguel L. and Senay, Gabriel B. and Friedrichs, MacKenzie O. and Cassassuce, Florance and Gomis, Florent and Nagler, Pamela L.},
	month = jan,
	year = {2024},
	note = {Number: 12
Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {NALCMS},
	pages = {2122},
}

Estimates of actual evapotranspiration (ETa) are valuable for effective monitoring and management of water resources. In areas that lack ground-based monitoring networks, remote sensing allows for accurate and consistent estimates of ETa across a broad scale—though each algorithm has limitations (i.e., ground-based validation, temporal consistency, spatial resolution). We developed an ensemble mean ETa (EMET) product to incorporate advancements and reduce uncertainty among algorithms (e.g., energy-balance, optical-only), which we use to estimate vegetative water use in response to restoration practices being implemented on the ground using management interventions (i.e., fencing pastures, erosion control structures) on a private ranch in Baja California Sur, Mexico. This paper describes the development of a monthly EMET product, the assessment of changes using EMET over time and across multiple land use/land cover types, and the evaluation of differences in vegetation and water distribution between watersheds treated by restoration and their controls. We found that in the absence of a ground-based monitoring network, the EMET product is more robust than using a single ETa data product and can augment the efficacy of ETa-based studies. We then found increased ETa within the restored watershed when compared to the control sites, which we attribute to increased plant water availability.

@article{clelland_annual_2024,
	title = {Annual and {Seasonal} {Patterns} of {Burned} {Area} {Products} in {Arctic}-{Boreal} {North} {America} and {Russia} for 2001–2020},
	volume = {16},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {2072-4292},
	url = {https://www.mdpi.com/2072-4292/16/17/3306},
	doi = {10.3390/rs16173306},
	abstract = {Boreal and Arctic regions have warmed up to four times quicker than the rest of the planet since the 1970s. As a result, boreal and tundra ecosystems are experiencing more frequent and higher intensity extreme weather events and disturbances, such as wildfires. Yet limitations in ground and satellite data across the Arctic and boreal regions have challenged efforts to track these disturbances at regional scales. In order to effectively monitor the progression and extent of wildfires in the Arctic-boreal zone, it is essential to determine whether burned area (BA) products are accurate representations of BA. Here, we use 12 different datasets together with MODIS active fire data to determine the total yearly BA and seasonal patterns of fires in Arctic-boreal North America and Russia for the years 2001–2020. We found relatively little variability between the datasets in North America, both in terms of total BA and seasonality, with an average BA of 2.55 ± 1.24 (standard deviation) Mha/year for our analysis period, the majority (ca. 41\%) of which occurs in July. In contrast, in Russia, there are large disparities between the products—GFED5 produces over four times more BA than GFED4s in southern Siberia. These disparities occur due to the different methodologies used; dNBR (differenced Normalized Burn Ratio) of short-term composites from Landsat images used alongside hotspot data was the most consistently successful in representing BA. We stress caution using GABAM in these regions, especially for the years 2001–2013, as Landsat-7 ETM+ scan lines are mistaken as burnt patches, increasing errors of commission. On the other hand, we highlight using regional products where possible, such as ABoVE-FED or ABBA in North America, and the Talucci et al. fire perimeter product in Russia, due to their detection of smaller fires which are often missed by global products.},
	language = {en},
	number = {17},
	urldate = {2025-01-27},
	journal = {Remote Sensing},
	author = {Clelland, Andrew A. and Marshall, Gareth J. and Baxter, Robert and Potter, Stefano and Talucci, Anna C. and Rady, Joshua M. and Genet, Hélène and Rogers, Brendan M. and Natali, Susan M.},
	month = jan,
	year = {2024},
	note = {Number: 17
Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {NALCMS},
	pages = {3306},
}

Boreal and Arctic regions have warmed up to four times quicker than the rest of the planet since the 1970s. As a result, boreal and tundra ecosystems are experiencing more frequent and higher intensity extreme weather events and disturbances, such as wildfires. Yet limitations in ground and satellite data across the Arctic and boreal regions have challenged efforts to track these disturbances at regional scales. In order to effectively monitor the progression and extent of wildfires in the Arctic-boreal zone, it is essential to determine whether burned area (BA) products are accurate representations of BA. Here, we use 12 different datasets together with MODIS active fire data to determine the total yearly BA and seasonal patterns of fires in Arctic-boreal North America and Russia for the years 2001–2020. We found relatively little variability between the datasets in North America, both in terms of total BA and seasonality, with an average BA of 2.55 ± 1.24 (standard deviation) Mha/year for our analysis period, the majority (ca. 41%) of which occurs in July. In contrast, in Russia, there are large disparities between the products—GFED5 produces over four times more BA than GFED4s in southern Siberia. These disparities occur due to the different methodologies used; dNBR (differenced Normalized Burn Ratio) of short-term composites from Landsat images used alongside hotspot data was the most consistently successful in representing BA. We stress caution using GABAM in these regions, especially for the years 2001–2013, as Landsat-7 ETM+ scan lines are mistaken as burnt patches, increasing errors of commission. On the other hand, we highlight using regional products where possible, such as ABoVE-FED or ABBA in North America, and the Talucci et al. fire perimeter product in Russia, due to their detection of smaller fires which are often missed by global products.

@article{k_c_assessing_2024,
	title = {Assessing {Land}-{Cover} {Change} {Trends}, {Patterns}, and {Transitions} in {Coalfield} {Counties} of {Eastern} {Kentucky}, {USA}},
	volume = {13},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {2073-445X},
	url = {https://www.mdpi.com/2073-445X/13/9/1541},
	doi = {10.3390/land13091541},
	abstract = {Surface coal mining and reclamation have greatly reshaped eastern Kentucky’s landscape affecting its socioeconomic, environmental and climatic aspects. This study examined the land-cover changes, trends and patterns in Floyd, Knott, Letcher, Magoffin, Martin, Perry, and Pike counties from 2004 to 2019. Using a random forest classifier, land cover was categorized into seven major classes, i.e., water, barren land, developed land, forest, shrubland, herbaceous, and planted/cultivated, majorly based on Landsat images. The Kappa accuracy ranged from 75 to 89\%. The results showed a notable increase in forest area from 5052 sq km to 5305 sq km accompanied by a substantial decrease in barren land from 179 sq km to 91 sq km from 2004 to 2019. These findings demonstrated that reclamation activities positively impacted the forest expansion and reduced the barren land of the study area. Key land-cover transitions included barren land to shrubland/herbaceous, forest to shrubland, and shrubland to forest, indicating vegetation growth from 2004 to 2019. An autocorrelation analysis indicated similar land-cover types clustered together, showing effective forest restoration efforts. As surface coal mining and reclamation significantly influenced the landscapes of the coalfield counties in eastern Kentucky, this study provides a holistic perspective for understanding the repercussions of these transformations, including their effects on humans, society, and environmental health.},
	language = {en},
	number = {9},
	urldate = {2025-01-27},
	journal = {Land},
	author = {K C, Suraj and Gyawali, Buddhi R. and Lucas, Shawn and Antonious, George F. and Chiluwal, Anuj and Zourarakis, Demetrio},
	month = sep,
	year = {2024},
	note = {Number: 9
Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {NALCMS},
	pages = {1541},
}

Surface coal mining and reclamation have greatly reshaped eastern Kentucky’s landscape affecting its socioeconomic, environmental and climatic aspects. This study examined the land-cover changes, trends and patterns in Floyd, Knott, Letcher, Magoffin, Martin, Perry, and Pike counties from 2004 to 2019. Using a random forest classifier, land cover was categorized into seven major classes, i.e., water, barren land, developed land, forest, shrubland, herbaceous, and planted/cultivated, majorly based on Landsat images. The Kappa accuracy ranged from 75 to 89%. The results showed a notable increase in forest area from 5052 sq km to 5305 sq km accompanied by a substantial decrease in barren land from 179 sq km to 91 sq km from 2004 to 2019. These findings demonstrated that reclamation activities positively impacted the forest expansion and reduced the barren land of the study area. Key land-cover transitions included barren land to shrubland/herbaceous, forest to shrubland, and shrubland to forest, indicating vegetation growth from 2004 to 2019. An autocorrelation analysis indicated similar land-cover types clustered together, showing effective forest restoration efforts. As surface coal mining and reclamation significantly influenced the landscapes of the coalfield counties in eastern Kentucky, this study provides a holistic perspective for understanding the repercussions of these transformations, including their effects on humans, society, and environmental health.

@article{ogawa_bayesian_2024,
	title = {Bayesian integrated species distribution models for hierarchical resource selection by a soaring bird},
	volume = {82},
	issn = {1574-9541},
	url = {https://www.sciencedirect.com/science/article/pii/S1574954124003297},
	doi = {10.1016/j.ecoinf.2024.102787},
	abstract = {Migratory birds exhibit seasonal geographic range (hereafter, range) dynamics during the annual cycle. Few studies have examined how migratory birds select their habitats for range occupancy at the species level and space use at the individual level simultaneously. We hypothesized that environmental variables directly related to fitness components would affect the range occupancy probabilities of migrants, whereas environment variables related to movements and flights would affect the space use intensities of migrants. We built Bayesian integrated species distribution models (ISDMs) to evaluate the effects of climate conditions, wind conditions, and landcover compositions on the seasonal range dynamics of American white pelicans Pelecanus erythrorhynchos (hereafter, pelican) during summer and winter. The ISDMs estimated the summer range occupancy probabilities of pelicans with Breeding Bird Survey data, winter range occupancy probabilities with Christmas Bird Count data, and summer and winter space-use intensity rates with eBird data jointly. We evaluated the predictive performance of ISDMs using independent datasets of pelican GPS locations. Integrated species distribution models outperformed the occupancy-only models in the predictive performance of occupancy probabilities. Climate conditions had opposite effects on the range occupancy probabilities between the breeding and non-breeding grounds, whereas landcovers had relatively consistent effects on range occupancy probabilities between the seasons.},
	urldate = {2025-01-27},
	journal = {Ecological Informatics},
	author = {Ogawa, Ryo and Wang, Guiming and Burger, L. Wes and Strickland, Bronson K. and Davis, J. Brian and Cunningham, Fred L.},
	month = sep,
	year = {2024},
	keywords = {NALCMS},
	pages = {102787},
}

Migratory birds exhibit seasonal geographic range (hereafter, range) dynamics during the annual cycle. Few studies have examined how migratory birds select their habitats for range occupancy at the species level and space use at the individual level simultaneously. We hypothesized that environmental variables directly related to fitness components would affect the range occupancy probabilities of migrants, whereas environment variables related to movements and flights would affect the space use intensities of migrants. We built Bayesian integrated species distribution models (ISDMs) to evaluate the effects of climate conditions, wind conditions, and landcover compositions on the seasonal range dynamics of American white pelicans Pelecanus erythrorhynchos (hereafter, pelican) during summer and winter. The ISDMs estimated the summer range occupancy probabilities of pelicans with Breeding Bird Survey data, winter range occupancy probabilities with Christmas Bird Count data, and summer and winter space-use intensity rates with eBird data jointly. We evaluated the predictive performance of ISDMs using independent datasets of pelican GPS locations. Integrated species distribution models outperformed the occupancy-only models in the predictive performance of occupancy probabilities. Climate conditions had opposite effects on the range occupancy probabilities between the breeding and non-breeding grounds, whereas landcovers had relatively consistent effects on range occupancy probabilities between the seasons.

@article{singh_bayesian_2024,
	title = {Bayesian physical–statistical retrieval of snow water equivalent and snow depth from {X}- and {Ku}-band synthetic aperture radar – demonstration using airborne {SnowSAr} in {SnowEx}'17},
	volume = {18},
	issn = {1994-0416},
	url = {https://tc.copernicus.org/articles/18/747/2024/},
	doi = {10.5194/tc-18-747-2024},
	abstract = {A physical–statistical framework to estimate snow water equivalent (SWE) and snow depth from synthetic aperture radar (SAR) measurements is presented and applied to four SnowSAR flight-line data sets collected during the SnowEx'2017 field campaign in Grand Mesa, Colorado, USA. The physical (radar) model is used to describe the relationship between snowpack conditions and volume backscatter. The statistical model is a Bayesian inference model that seeks to estimate the joint probability distribution of volume backscatter measurements, snow density and snow depth, and physical model parameters. Prior distributions are derived from multilayer snow hydrology predictions driven by downscaled numerical weather prediction (NWP) forecasts. To reduce the signal-to-noise ratio, SnowSAR measurements at 1 m resolution were upscaled by simple averaging to 30 and 90 m resolution. To reduce the number of physical parameters, the multilayer snowpack is transformed for Bayesian inference into an equivalent one- or two-layer snowpack with the same snow mass and volume backscatter. Successful retrievals meeting NASEM (2018) science requirements are defined by absolute convergence backscatter errors ≤1.2 dB and local SnowSAR incidence angles between 30 and 45∘ for X- and Ku-band VV-pol backscatter measurements and were achieved for 75 \% to 87 \% of all grassland pixels with SWE up to 0.7 m and snow depth up to 2 m. SWE retrievals compare well with snow pit observations, showing strong skill in deep snow with average absolute SWE residuals of 5 \%–7 \% (15 \%–18 \%) for the two-layer (one-layer) retrieval algorithm. Furthermore, the spatial distributions of snow depth retrievals vis-à-vis lidar estimates have Bhattacharya coefficients above 94 \% (90 \%) for homogeneous grassland pixels at 30 m (90 m resolution), and values up to 76 \% in mixed forest and grassland areas, indicating that the retrievals closely capture snowpack spatial variability. Because NWP forecasts are available everywhere, the proposed approach could be applied to SWE and snow depth retrievals from a dedicated global snow mission.},
	language = {English},
	number = {2},
	urldate = {2024-03-13},
	journal = {The Cryosphere},
	author = {Singh, Siddharth and Durand, Michael and Kim, Edward and Barros, Ana P.},
	month = feb,
	year = {2024},
	note = {Publisher: Copernicus GmbH},
	keywords = {NALCMS},
	pages = {747--773},
}

A physical–statistical framework to estimate snow water equivalent (SWE) and snow depth from synthetic aperture radar (SAR) measurements is presented and applied to four SnowSAR flight-line data sets collected during the SnowEx'2017 field campaign in Grand Mesa, Colorado, USA. The physical (radar) model is used to describe the relationship between snowpack conditions and volume backscatter. The statistical model is a Bayesian inference model that seeks to estimate the joint probability distribution of volume backscatter measurements, snow density and snow depth, and physical model parameters. Prior distributions are derived from multilayer snow hydrology predictions driven by downscaled numerical weather prediction (NWP) forecasts. To reduce the signal-to-noise ratio, SnowSAR measurements at 1 m resolution were upscaled by simple averaging to 30 and 90 m resolution. To reduce the number of physical parameters, the multilayer snowpack is transformed for Bayesian inference into an equivalent one- or two-layer snowpack with the same snow mass and volume backscatter. Successful retrievals meeting NASEM (2018) science requirements are defined by absolute convergence backscatter errors ≤1.2 dB and local SnowSAR incidence angles between 30 and 45∘ for X- and Ku-band VV-pol backscatter measurements and were achieved for 75 % to 87 % of all grassland pixels with SWE up to 0.7 m and snow depth up to 2 m. SWE retrievals compare well with snow pit observations, showing strong skill in deep snow with average absolute SWE residuals of 5 %–7 % (15 %–18 %) for the two-layer (one-layer) retrieval algorithm. Furthermore, the spatial distributions of snow depth retrievals vis-à-vis lidar estimates have Bhattacharya coefficients above 94 % (90 %) for homogeneous grassland pixels at 30 m (90 m resolution), and values up to 76 % in mixed forest and grassland areas, indicating that the retrievals closely capture snowpack spatial variability. Because NWP forecasts are available everywhere, the proposed approach could be applied to SWE and snow depth retrievals from a dedicated global snow mission.

@article{gronewold_can_2024,
	title = {Can continental transboundary compacts hold water?},
	volume = {15},
	copyright = {2024 The Author(s)},
	issn = {2041-1723},
	url = {https://www.nature.com/articles/s41467-024-51456-w},
	doi = {10.1038/s41467-024-51456-w},
	abstract = {The growing number of threats facing continental-scale transboundary water treaties warrants contemporary evaluation of not only the political and climatological conditions under which they were constructed, but also of how different management strategies for accommodating changes in those conditions can lead to treaty success or failure. We assess these threats by highlighting key attributes and vulnerabilities of water treaties across North America that frame a diverse set of future water management priorities. While these threats are ubiquitous globally, they are particularly pronounced in North America where water-abundant basins along the border between the United States (US) and Canada contrast with arid basins along the border between the US and Mexico. We propose addressing these needs through a three-step call to action for management agencies, politicians, and the public at large to embrace a holistic perspective on transboundary water agreements.},
	language = {en},
	number = {1},
	urldate = {2024-08-23},
	journal = {Nature Communications},
	author = {Gronewold, Andrew and Bednar, Jenna and Cort, Marjorie and Rueda, Vianey and Moore, Michael and Allan, Jon},
	month = aug,
	year = {2024},
	note = {Publisher: Nature Publishing Group},
	keywords = {Political Boundaries},
	pages = {7087},
}

The growing number of threats facing continental-scale transboundary water treaties warrants contemporary evaluation of not only the political and climatological conditions under which they were constructed, but also of how different management strategies for accommodating changes in those conditions can lead to treaty success or failure. We assess these threats by highlighting key attributes and vulnerabilities of water treaties across North America that frame a diverse set of future water management priorities. While these threats are ubiquitous globally, they are particularly pronounced in North America where water-abundant basins along the border between the United States (US) and Canada contrast with arid basins along the border between the US and Mexico. We propose addressing these needs through a three-step call to action for management agencies, politicians, and the public at large to embrace a holistic perspective on transboundary water agreements.

@incollection{tecuapetla-gomez_caracterizacion_2024,
	title = {Caracterización de series de tiempo de {NDVI} en bosques mexicanos vía análisis funcional de datos aplicado a imágenes de satélite},
	isbn = {978-607-27-2346-7},
	url = {https://www.selper.org.mx/wp-content/uploads/2024/07/14.-Aplicaciones-de-la-Geomatica-AC-1.pdf},
	language = {Español},
	booktitle = {Aplicaciones geomáticas en el estudio de la sustentabilidad},
	publisher = {Universidad Autónoma de Nuevo León},
	author = {Tecuapetla-Gómez, Inder Rafael and Galicia Gómez, Berenice Fanny and Rosales Marticorena, Luis Francisco},
	year = {2024},
	keywords = {NALCMS},
}

@article{diaz-cardenas_conservation_2024,
	title = {Conservation status of {Sceloporus} lizards},
	volume = {18},
	url = {https://amphibian-reptile-conservation.org/pdfs/Volume/Vol_18_nos_1-2/ARC_18_1-2_187-199_e337.pdf},
	number = {1 \& 2},
	journal = {Amphibian and Reptile Conservation},
	author = {Díaz-Cárdenas, Brenda and Castañeda-Gaytán, Gamaliel and Pérez-Fiol, Tania and Banda-Leal, Javier and Sánchez-Romero, Abraham and Smith, Geoffrey R. and Gadsden, Héctor},
	year = {2024},
	pages = {187--199},
}

@phdthesis{hasan_creating_2024,
	title = {Creating an urban heat vulnerability index ({HVI}) in the face of climate change employing geospatial technology in {Halifax}, {Canada}},
	url = {http://library2.smu.ca/xmlui/handle/01/31900},
	abstract = {Heat waves are one of the most common weather events happening in recent decades,
posing threats to public health especially in urban built-up environments. This study employs geospatial techniques to evaluate urban heat vulnerability in the city of Halifax,
Nova Scotia, Canada. The Heat Vulnerability Index (HVI) was developed through the
utilization of the Geographic Information System (GIS), integrating exposure, sensitivity,
and adaptive capacity measures generated using Remote Sensing (GIS) and socioeconomic datasets for four years covering: 2006, 2011, 2016, 2021. The process applies an Equal Weight Approach (EWA) to assign equal importance to the 16 normalized variables considered in creating the comprehensive HVI. The overarching goal of this study was to assess heat vulnerability at a local level by offering a detailed analysis of these 16 proposed indicators in an urban setting. The results revealed that the HVI
attained its peak in the year 2021, exhibiting a variable trajectory in its scores, with all
years demonstrating a significant high-risk zone encompassing the regional center.
Findings may enable multiple stakeholders to understand spatial variability of
temperature anomalies at local level and may identify vulnerable populations at risks.},
	language = {en},
	urldate = {2024-08-12},
	author = {Hasan, Md Mehedi},
	month = mar,
	year = {2024},
	note = {Accepted: 2024-04-25T11:57:44Z
Publisher: Halifax, N.S. : Saint Mary’s University},
	keywords = {NALCMS},
}

Heat waves are one of the most common weather events happening in recent decades, posing threats to public health especially in urban built-up environments. This study employs geospatial techniques to evaluate urban heat vulnerability in the city of Halifax, Nova Scotia, Canada. The Heat Vulnerability Index (HVI) was developed through the utilization of the Geographic Information System (GIS), integrating exposure, sensitivity, and adaptive capacity measures generated using Remote Sensing (GIS) and socioeconomic datasets for four years covering: 2006, 2011, 2016, 2021. The process applies an Equal Weight Approach (EWA) to assign equal importance to the 16 normalized variables considered in creating the comprehensive HVI. The overarching goal of this study was to assess heat vulnerability at a local level by offering a detailed analysis of these 16 proposed indicators in an urban setting. The results revealed that the HVI attained its peak in the year 2021, exhibiting a variable trajectory in its scores, with all years demonstrating a significant high-risk zone encompassing the regional center. Findings may enable multiple stakeholders to understand spatial variability of temperature anomalies at local level and may identify vulnerable populations at risks.

@article{glass_decomposition_2024,
	title = {Decomposition properties of three leaf species in a beech-maple forest stream and their potential relationship to long-term changes in forest composition},
	issn = {,},
	url = {https://www.schweizerbart.de/papers/fal/detail/197/103581/Decomposition_properties_of_three_leaf_species_in_},
	doi = {10.1127/fal/2024/1538},
	language = {en},
	urldate = {2026-05-27},
	journal = {Fundamental and Applied Limnology},
	author = {Glass, Nathan T. and DeNicola, Dean M.},
	month = feb,
	year = {2024},
	note = {Publisher: Schweizerbart'sche Verlagsbuchhandlung},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {159--174},
}

@article{ke_deep_2024,
	title = {Deep learning workflow to support in-flight processing of digital aerial imagery for wildlife population surveys},
	volume = {19},
	issn = {1932-6203},
	url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0288121},
	doi = {10.1371/journal.pone.0288121},
	abstract = {Deep learning shows promise for automating detection and classification of wildlife from digital aerial imagery to support cost-efficient remote sensing solutions for wildlife population monitoring. To support in-flight orthorectification and machine learning processing to detect and classify wildlife from imagery in near real-time, we evaluated deep learning methods that address hardware limitations and the need for processing efficiencies to support the envisioned in-flight workflow. We developed an annotated dataset for a suite of marine birds from high-resolution digital aerial imagery collected over open water environments to train the models. The proposed 3-stage workflow for automated, in-flight data processing includes: 1) image filtering based on the probability of any bird occurrence, 2) bird instance detection, and 3) bird instance classification. For image filtering, we compared the performance of a binary classifier with Mask Region-based Convolutional Neural Network (Mask R-CNN) as a means of sub-setting large volumes of imagery based on the probability of at least one bird occurrence in an image. On both the validation and test datasets, the binary classifier achieved higher performance than Mask R-CNN for predicting bird occurrence at the image-level. We recommend the binary classifier over Mask R-CNN for workflow first-stage filtering. For bird instance detection, we leveraged Mask R-CNN as our detection framework and proposed an iterative refinement method to bootstrap our predicted detections from loose ground-truth annotations. We also discuss future work to address the taxonomic classification phase of the envisioned workflow.},
	language = {en},
	number = {4},
	urldate = {2024-04-24},
	journal = {PLOS ONE},
	author = {Ke, Tsung-Wei and Yu, Stella X. and Koneff, Mark D. and Fronczak, David L. and Fara, Luke J. and Harrison, Travis J. and Landolt, Kyle L. and Hlavacek, Enrika J. and Lubinski, Brian R. and White, Timothy P.},
	month = apr,
	year = {2024},
	note = {Publisher: Public Library of Science},
	keywords = {Political Boundaries},
	pages = {e0288121},
}

Deep learning shows promise for automating detection and classification of wildlife from digital aerial imagery to support cost-efficient remote sensing solutions for wildlife population monitoring. To support in-flight orthorectification and machine learning processing to detect and classify wildlife from imagery in near real-time, we evaluated deep learning methods that address hardware limitations and the need for processing efficiencies to support the envisioned in-flight workflow. We developed an annotated dataset for a suite of marine birds from high-resolution digital aerial imagery collected over open water environments to train the models. The proposed 3-stage workflow for automated, in-flight data processing includes: 1) image filtering based on the probability of any bird occurrence, 2) bird instance detection, and 3) bird instance classification. For image filtering, we compared the performance of a binary classifier with Mask Region-based Convolutional Neural Network (Mask R-CNN) as a means of sub-setting large volumes of imagery based on the probability of at least one bird occurrence in an image. On both the validation and test datasets, the binary classifier achieved higher performance than Mask R-CNN for predicting bird occurrence at the image-level. We recommend the binary classifier over Mask R-CNN for workflow first-stage filtering. For bird instance detection, we leveraged Mask R-CNN as our detection framework and proposed an iterative refinement method to bootstrap our predicted detections from loose ground-truth annotations. We also discuss future work to address the taxonomic classification phase of the envisioned workflow.

@phdthesis{pruitt_dispersal_2024,
	title = {Dispersal {Movement} and {Overwintering} {Ecology} of a {Cryptic} {Migratory} {Forest} {Owl}},
	url = {https://scholarworks.uark.edu/etd/5307},
	author = {Pruitt, Mitchell},
	month = may,
	year = {2024},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
}

@phdthesis{kalashnikov_dry_2024,
	type = {Doctor of {Philosophy} ({PhD})},
	title = {Dry {Lightning} in the {Western} {United} {States}: {Meteorological} {Conditions}, {Wildfire} {Ignition}, {Air} {Quality} {Impacts}, and {Future} {Projections}},
	copyright = {Creative Commons Attribution 4.0 International, Open},
	shorttitle = {{DRY} {LIGHTNING} {IN} {THE} {WESTERN} {UNITED} {STATES}},
	url = {https://rex.libraries.wsu.edu/esploro/outputs/doctoral/99901120940501842},
	abstract = {Cloud-to-ground lightning occurring with little to no rainfall – typically referred to as “dry lightning” – is a major source of wildfire ignition in the western United States (WUS) during summer months. Although lightning-caused wildfires occur naturally and are generally ecologically beneficial, changing climatic conditions are increasing the risk of large and severe wildfires. Motivated by these impacts, my dissertation aims to advance our understanding of dry lightning in the WUS and its associated meteorological conditions, wildfire ignitions, air quality impacts, and future projections. In the first chapter, I provide an overview of the motivations for undertaking this dissertation. In the second chapter, I use gridded air pollutant and population data to examine compound air pollution episodes in the WUS. This study demonstrates an increase in the co-occurrence of two harmful air pollutants (fine particulate matter and ground-level ozone) during the WUS wildfire season in the past two decades, and increasing population exposure to these co-occurrences of 25 million person-days per year largely driven by increasing wildfire activity. I show that the largest population exposure to co-occurring air pollution was associated with the major outbreak of dry lightning that ignited hundreds of wildfires in California during August, 2020. To better understand dry lightning in this fire-prone region, in the third chapter I examine the meteorological and geographical factors associated with dry lightning in central and northern California. I apply k-means clustering to atmospheric reanalysis data to identify four types of meteorological patterns associated with the largest dry lightning outbreaks over this region, and quantify the spatial patterns of enhanced dry lightning risk associated with each pattern. In the fourth chapter, I use radar-derived rainfall data and gridded climatological variables to investigate the precipitation amounts and biophysical factors associated with lightning-caused wildfire ignitions across the WUS. Critically, my results refine the widely-used \<2.5mm precipitation amount to define dry lightning by demonstrating that substantial regional variation exists in ignition-relevant precipitation amounts depending on local topography, vegetation, and climate. In the fifth chapter, I use Convolutional Neural Networks (CNNs) to predict cloud-to-ground lightning in the WUS at the grid cell level using a suite of reanalysis-derived meteorological variables as predictors. The CNNs are skillful at predicting lightning (domain-median AUC = 0.8) and realistically capture the year-to-year variation of lightning activity across the WUS (domain-median interannual correlation = 0.87). The CNN-based predictive models developed in this study can be applied to output from global climate models, thus enabling the ability to project future lightning and lightning-caused wildfires. In the final chapter, I summarize my findings from the four studies that comprise my dissertation. The outcomes of my research can be useful to forecasters and fire managers to anticipate possible wildfire ignitions in the present climate, and can be used to inform planning, management, and policy decisions around future lightning-caused wildfires in the WUS.},
	language = {en},
	urldate = {2024-08-23},
	school = {Washington State University},
	author = {Kalashnikov, Dmitri A.},
	collaborator = {Singh, Deepti and Moffett, Kevan B and Walden, Von P and Loikith, Paul C},
	year = {2024},
	note = {Medium: application/pdf
Publisher: Washington State University},
	keywords = {NALCMS},
}

Cloud-to-ground lightning occurring with little to no rainfall – typically referred to as “dry lightning” – is a major source of wildfire ignition in the western United States (WUS) during summer months. Although lightning-caused wildfires occur naturally and are generally ecologically beneficial, changing climatic conditions are increasing the risk of large and severe wildfires. Motivated by these impacts, my dissertation aims to advance our understanding of dry lightning in the WUS and its associated meteorological conditions, wildfire ignitions, air quality impacts, and future projections. In the first chapter, I provide an overview of the motivations for undertaking this dissertation. In the second chapter, I use gridded air pollutant and population data to examine compound air pollution episodes in the WUS. This study demonstrates an increase in the co-occurrence of two harmful air pollutants (fine particulate matter and ground-level ozone) during the WUS wildfire season in the past two decades, and increasing population exposure to these co-occurrences of 25 million person-days per year largely driven by increasing wildfire activity. I show that the largest population exposure to co-occurring air pollution was associated with the major outbreak of dry lightning that ignited hundreds of wildfires in California during August, 2020. To better understand dry lightning in this fire-prone region, in the third chapter I examine the meteorological and geographical factors associated with dry lightning in central and northern California. I apply k-means clustering to atmospheric reanalysis data to identify four types of meteorological patterns associated with the largest dry lightning outbreaks over this region, and quantify the spatial patterns of enhanced dry lightning risk associated with each pattern. In the fourth chapter, I use radar-derived rainfall data and gridded climatological variables to investigate the precipitation amounts and biophysical factors associated with lightning-caused wildfire ignitions across the WUS. Critically, my results refine the widely-used <2.5mm precipitation amount to define dry lightning by demonstrating that substantial regional variation exists in ignition-relevant precipitation amounts depending on local topography, vegetation, and climate. In the fifth chapter, I use Convolutional Neural Networks (CNNs) to predict cloud-to-ground lightning in the WUS at the grid cell level using a suite of reanalysis-derived meteorological variables as predictors. The CNNs are skillful at predicting lightning (domain-median AUC = 0.8) and realistically capture the year-to-year variation of lightning activity across the WUS (domain-median interannual correlation = 0.87). The CNN-based predictive models developed in this study can be applied to output from global climate models, thus enabling the ability to project future lightning and lightning-caused wildfires. In the final chapter, I summarize my findings from the four studies that comprise my dissertation. The outcomes of my research can be useful to forecasters and fire managers to anticipate possible wildfire ignitions in the present climate, and can be used to inform planning, management, and policy decisions around future lightning-caused wildfires in the WUS.

@article{gorr_empirical_2024,
	title = {Empirical {Models} for {Postfire} {Debris}-{Flow} {Volume} in the {Southwest} {United} {States}},
	volume = {129},
	copyright = {© 2024. American Geophysical Union. All Rights Reserved.},
	issn = {2169-9011},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2024JF007825},
	doi = {10.1029/2024JF007825},
	abstract = {Improving our ability to relate postfire debris-flow volume to rainfall characteristics, terrain attributes, and fire severity is critical for quantifying postfire sediment yields from steep landscapes and predicting changes in debris-flow hazards following fire. This is especially true in the Southwest United States (US) (Arizona and New Mexico), where fire activity has increased in recent decades. In this study, we present a database of 54 postfire debris-flow volumes that we collected across the Southwest between 2010 and 2021. We use these data to develop a multiple linear regression model for postfire debris-flow volume based on peak 30-min rainfall intensity, watershed area greater than 23°, and a soil burn severity variable. We further propose a model that utilizes only rainfall and terrain variables, as well as a model that requires only terrain attribute and fire-severity variables. These models are beneficial in scenarios where there are data limitations. We compare these new models with others developed in the western US to explore differences in the factors that control debris-flow volume across geographic regions. We find that the models introduced here more accurately predict postfire debris-flow volume in the Southwest relative to existing models. We also find that models that include sub-hourly rainfall intensity perform better than those that do not, revealing the benefits of high-resolution rainfall data for constraining postfire debris-flow volume. Results improve our ability to forecast postfire debris-flow volume in the Southwest and provide insights into relationships between rainfall intensity, terrain attributes, fire severity, and debris-flow volume.},
	language = {en},
	number = {11},
	urldate = {2026-05-27},
	journal = {Journal of Geophysical Research: Earth Surface},
	author = {Gorr, Alexander and McGuire, Luke and Youberg, Ann},
	year = {2024},
	note = {\_eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2024JF007825},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {e2024JF007825},
}

Improving our ability to relate postfire debris-flow volume to rainfall characteristics, terrain attributes, and fire severity is critical for quantifying postfire sediment yields from steep landscapes and predicting changes in debris-flow hazards following fire. This is especially true in the Southwest United States (US) (Arizona and New Mexico), where fire activity has increased in recent decades. In this study, we present a database of 54 postfire debris-flow volumes that we collected across the Southwest between 2010 and 2021. We use these data to develop a multiple linear regression model for postfire debris-flow volume based on peak 30-min rainfall intensity, watershed area greater than 23°, and a soil burn severity variable. We further propose a model that utilizes only rainfall and terrain variables, as well as a model that requires only terrain attribute and fire-severity variables. These models are beneficial in scenarios where there are data limitations. We compare these new models with others developed in the western US to explore differences in the factors that control debris-flow volume across geographic regions. We find that the models introduced here more accurately predict postfire debris-flow volume in the Southwest relative to existing models. We also find that models that include sub-hourly rainfall intensity perform better than those that do not, revealing the benefits of high-resolution rainfall data for constraining postfire debris-flow volume. Results improve our ability to forecast postfire debris-flow volume in the Southwest and provide insights into relationships between rainfall intensity, terrain attributes, fire severity, and debris-flow volume.

@article{yu_enhancing_2024,
	title = {Enhancing long short-term memory ({LSTM})-based streamflow prediction with a spatially distributed approach},
	volume = {28},
	issn = {1027-5606},
	url = {https://hess.copernicus.org/articles/28/2107/2024/},
	doi = {10.5194/hess-28-2107-2024},
	abstract = {Deep learning (DL) algorithms have previously demonstrated their effectiveness in streamflow prediction. However, in hydrological time series modelling, the performance of existing DL methods is often bound by limited spatial information, as these data-driven models are typically trained with lumped (spatially aggregated) input data. In this study, we propose a hybrid approach, namely the Spatially Recursive (SR) model, that integrates a lumped long short-term memory (LSTM) network seamlessly with a physics-based hydrological routing simulation for enhanced streamflow prediction. The lumped LSTM was trained on the basin-averaged meteorological and hydrological variables derived from 141 gauged basins located in the Great Lakes region of North America. The SR model involves applying the trained LSTM at the subbasin scale for local streamflow predictions which are then translated to the basin outlet by the hydrological routing model. We evaluated the efficacy of the SR model with respect to predicting streamflow at 224 gauged stations across the Great Lakes region and compared its performance to that of the standalone lumped LSTM model. The results indicate that the SR model achieved performance levels on par with the lumped LSTM in basins used for training the LSTM. Additionally, the SR model was able to predict streamflow more accurately on large basins (e.g., drainage area greater than 2000 km2), underscoring the substantial information loss associated with basin-wise feature aggregation. Furthermore, the SR model outperformed the lumped LSTM when applied to basins that were not part of the LSTM training (i.e., pseudo-ungauged basins). The implication of this study is that the lumped LSTM predictions, especially in large basins and ungauged basins, can be reliably improved by considering spatial heterogeneity at finer resolution via the SR model.},
	language = {English},
	number = {9},
	urldate = {2024-06-03},
	journal = {Hydrology and Earth System Sciences},
	author = {Yu, Qiutong and Tolson, Bryan A. and Shen, Hongren and Han, Ming and Mai, Juliane and Lin, Jimmy},
	month = may,
	year = {2024},
	note = {Publisher: Copernicus GmbH},
	keywords = {NALCMS},
	pages = {2107--2122},
}

Deep learning (DL) algorithms have previously demonstrated their effectiveness in streamflow prediction. However, in hydrological time series modelling, the performance of existing DL methods is often bound by limited spatial information, as these data-driven models are typically trained with lumped (spatially aggregated) input data. In this study, we propose a hybrid approach, namely the Spatially Recursive (SR) model, that integrates a lumped long short-term memory (LSTM) network seamlessly with a physics-based hydrological routing simulation for enhanced streamflow prediction. The lumped LSTM was trained on the basin-averaged meteorological and hydrological variables derived from 141 gauged basins located in the Great Lakes region of North America. The SR model involves applying the trained LSTM at the subbasin scale for local streamflow predictions which are then translated to the basin outlet by the hydrological routing model. We evaluated the efficacy of the SR model with respect to predicting streamflow at 224 gauged stations across the Great Lakes region and compared its performance to that of the standalone lumped LSTM model. The results indicate that the SR model achieved performance levels on par with the lumped LSTM in basins used for training the LSTM. Additionally, the SR model was able to predict streamflow more accurately on large basins (e.g., drainage area greater than 2000 km2), underscoring the substantial information loss associated with basin-wise feature aggregation. Furthermore, the SR model outperformed the lumped LSTM when applied to basins that were not part of the LSTM training (i.e., pseudo-ungauged basins). The implication of this study is that the lumped LSTM predictions, especially in large basins and ungauged basins, can be reliably improved by considering spatial heterogeneity at finer resolution via the SR model.

@article{engel_estimating_2024,
	title = {Estimating {Stage}-{Frequency} {Curves} for {Engineering} {Design} in {Small} {Ungauged} {Arctic} {Watersheds}},
	volume = {16},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {2073-4441},
	url = {https://www.mdpi.com/2073-4441/16/10/1321},
	doi = {10.3390/w16101321},
	abstract = {The design of hydraulic structures in the Arctic is complicated by shallow relief, which cause unique runoff processes that promote snow-damming and refreeze of runoff. We discuss the challenges encountered in modeling snowmelt runoff into two coastal freshwater lagoons in Utqiaġvik, Alaska. Stage-frequency curves with quantified uncertainty were required to design two new discharge gates that would allow snowmelt runoff flows through a proposed coastal revetment. To estimate runoff hydrographs arriving at the lagoons, we modeled snowpack accumulation and ablation using SnowModel which in turn was used to force a physically-based hydraulic runoff model (HEC-RAS). Our results demonstrate the successful development of stage-frequency curves by incorporating a Monte Carlo simulation approach that quantifies the variability in runoff timing and volume. Our process highlights the complexities of Arctic hydrology by incorporating significant delays in runoff onset due to localized snow accumulation and melting processes. This methodology not only addresses the uncertainty in snow-damming and refreeze processes which affect the arrival time of snowmelt inflow peaks, but is also adaptable for application in other challenging environments where secondary runoff processes are predominant.},
	language = {en},
	number = {10},
	urldate = {2024-06-03},
	journal = {Water},
	author = {Engel, Chandler and Wagner, Anna and Giovando, Jeremy and Ho, David and Morriss, Blaine and Deeb, Elias},
	month = jan,
	year = {2024},
	note = {Number: 10
Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {NALCMS},
	pages = {1321},
}

The design of hydraulic structures in the Arctic is complicated by shallow relief, which cause unique runoff processes that promote snow-damming and refreeze of runoff. We discuss the challenges encountered in modeling snowmelt runoff into two coastal freshwater lagoons in Utqiaġvik, Alaska. Stage-frequency curves with quantified uncertainty were required to design two new discharge gates that would allow snowmelt runoff flows through a proposed coastal revetment. To estimate runoff hydrographs arriving at the lagoons, we modeled snowpack accumulation and ablation using SnowModel which in turn was used to force a physically-based hydraulic runoff model (HEC-RAS). Our results demonstrate the successful development of stage-frequency curves by incorporating a Monte Carlo simulation approach that quantifies the variability in runoff timing and volume. Our process highlights the complexities of Arctic hydrology by incorporating significant delays in runoff onset due to localized snow accumulation and melting processes. This methodology not only addresses the uncertainty in snow-damming and refreeze processes which affect the arrival time of snowmelt inflow peaks, but is also adaptable for application in other challenging environments where secondary runoff processes are predominant.

@article{braden_estimating_2024,
	title = {Estimating forest extent across {Mexico}},
	volume = {19},
	issn = {1748-9326},
	url = {https://dx.doi.org/10.1088/1748-9326/ad193e},
	doi = {10.1088/1748-9326/ad193e},
	abstract = {Information on forest extent and tree cover is required to evaluate the status of natural resources, conservation practices, and environmental policies. The challenge is that different forest definitions, remote sensing-based (RSB) products, and data availability can lead to discrepancies in reporting total forest area. Consequently, errors in forest extent can be propagated into forest biomass and carbon estimates. Here, we present a simple approach to compare forest extent estimates from seven regional and global land or tree cover RSB products at 30 m resolution across Mexico. We found substantial differences in forest extent estimates for Mexico, ranging from 387 607 km2 to 675 239 km2. These differences were dependent on the RSB product and forest definition used. Next, we compared these RSB products with two independent forest inventory datasets at national (n = 26 220 plots) and local scales (n = 754 plots). The greatest accuracy among RSB products and forest inventory data was within the tropical moist forest (range 82\%–95\%), and the smallest was within the subtropical desert (range {\textless}10\%–80\%) and subtropical steppe ecological zones (range {\textless}10\%–60\%). We developed a forest extent agreement map by combining seven RSB products and identifying a consensus in their estimates. We found a forest area of 288 749 km2 with high forest extent agreement, and 340 661 km2 with medium forest extent agreement. The high-to-medium forest extent agreement of 629 410 km2 is comparable to the official national estimate of 656 920 km2. We found a high forest extent agreement across the Yucatan Peninsula and mountain areas in the Sierra Madre Oriental and Sierra Madre Occidental. The tropical dry forest and subtropical mountain system represent the two ecological zones with the highest areas of disagreement among RSB products. These findings show discrepancies in forest extent estimates across ecological zones in Mexico, where additional ground data and research are needed. Dataset available at https://doi.org/10.3334/ORNLDAAC/2320.},
	language = {en},
	number = {1},
	urldate = {2024-01-31},
	journal = {Environmental Research Letters},
	author = {Braden, Dustin and Mondal, Pinki and Park, Taejin and Rosa, José Armando Alanís de la and Leal, Metzli Ileana Aldrete and Lara, Rubi Angélica Cuenca and Saucedo, Rafael Mayorga and Paz, Fernando and Salas-Aguilar, Victor Manuel and Soriano-Luna, María de Los Ángeles and Vargas, Rodrigo},
	month = jan,
	year = {2024},
	note = {Publisher: IOP Publishing},
	keywords = {NALCMS},
	pages = {014083},
}

Information on forest extent and tree cover is required to evaluate the status of natural resources, conservation practices, and environmental policies. The challenge is that different forest definitions, remote sensing-based (RSB) products, and data availability can lead to discrepancies in reporting total forest area. Consequently, errors in forest extent can be propagated into forest biomass and carbon estimates. Here, we present a simple approach to compare forest extent estimates from seven regional and global land or tree cover RSB products at 30 m resolution across Mexico. We found substantial differences in forest extent estimates for Mexico, ranging from 387 607 km2 to 675 239 km2. These differences were dependent on the RSB product and forest definition used. Next, we compared these RSB products with two independent forest inventory datasets at national (n = 26 220 plots) and local scales (n = 754 plots). The greatest accuracy among RSB products and forest inventory data was within the tropical moist forest (range 82%–95%), and the smallest was within the subtropical desert (range \textless10%–80%) and subtropical steppe ecological zones (range \textless10%–60%). We developed a forest extent agreement map by combining seven RSB products and identifying a consensus in their estimates. We found a forest area of 288 749 km2 with high forest extent agreement, and 340 661 km2 with medium forest extent agreement. The high-to-medium forest extent agreement of 629 410 km2 is comparable to the official national estimate of 656 920 km2. We found a high forest extent agreement across the Yucatan Peninsula and mountain areas in the Sierra Madre Oriental and Sierra Madre Occidental. The tropical dry forest and subtropical mountain system represent the two ecological zones with the highest areas of disagreement among RSB products. These findings show discrepancies in forest extent estimates across ecological zones in Mexico, where additional ground data and research are needed. Dataset available at https://doi.org/10.3334/ORNLDAAC/2320.

@article{xin_estimation_2024,
	title = {Estimation of {Freshwater} {Discharge} from the {Gulf} of {Alaska} {Drainage} {Basins}},
	volume = {16},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {2073-4441},
	url = {https://www.mdpi.com/2073-4441/16/18/2690},
	doi = {10.3390/w16182690},
	abstract = {The freshwater discharge from catchments along the Gulf of Alaska, termed Alaska discharge, is characterized by significant quantity and variability. Owing to subarctic climate and mountainous topography, the Alaska discharge variations may deliver possible impacts beyond the local hydrology. While short-term and local discharge estimation has been frequently realized, a longer time span and a discussion on cascading impacts remain unexplored in this area. In this study, the Alaska discharge during 1982–2022 is estimated using the Soil and Water Assessment Tool (SWAT). The adequate balance between the model complexity and the functional efficiency of SWAT suits the objective well, and discharge simulation is successfully conducted after customization in melting calculations and careful calibrations. During 1982−2022, the Alaska discharge is estimated to be 14,396 ± 819 m3⋅s−1⋅yr−1, with meltwater contributing approximately 53\%. Regarding variation in the Alaska discharge, the interannual change is found to be negatively correlated with sea surface salinity anomalies in the Alaska Stream, while the decadal change positively correlates with the North Pacific Gyre Oscillation, with reasonable time lags in both cases. These new findings provide insights into the relationship between local hydrology and regional climate in this area. More importantly, we provide rare evidence that variation in freshwater discharge may affect properties beyond the local hydrology.},
	language = {en},
	number = {18},
	urldate = {2025-01-27},
	journal = {Water},
	author = {Xin, Peng and Shi, Muqing and Mitsudera, Humio and Shiraiwa, Takayuki},
	month = jan,
	year = {2024},
	note = {Number: 18
Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {NALCMS},
	pages = {2690},
}

The freshwater discharge from catchments along the Gulf of Alaska, termed Alaska discharge, is characterized by significant quantity and variability. Owing to subarctic climate and mountainous topography, the Alaska discharge variations may deliver possible impacts beyond the local hydrology. While short-term and local discharge estimation has been frequently realized, a longer time span and a discussion on cascading impacts remain unexplored in this area. In this study, the Alaska discharge during 1982–2022 is estimated using the Soil and Water Assessment Tool (SWAT). The adequate balance between the model complexity and the functional efficiency of SWAT suits the objective well, and discharge simulation is successfully conducted after customization in melting calculations and careful calibrations. During 1982−2022, the Alaska discharge is estimated to be 14,396 ± 819 m3⋅s−1⋅yr−1, with meltwater contributing approximately 53%. Regarding variation in the Alaska discharge, the interannual change is found to be negatively correlated with sea surface salinity anomalies in the Alaska Stream, while the decadal change positively correlates with the North Pacific Gyre Oscillation, with reasonable time lags in both cases. These new findings provide insights into the relationship between local hydrology and regional climate in this area. More importantly, we provide rare evidence that variation in freshwater discharge may affect properties beyond the local hydrology.

@article{barnhart_evaluating_2024,
	title = {Evaluating {Distributed} {Snow} {Model} {Resolution} and {Meteorology} {Parameterizations} {Against} {Streamflow} {Observations}: {Finer} {Is} {Not} {Always} {Better}},
	volume = {60},
	copyright = {Published 2024. This article is a U.S. Government work and is in the public domain in the USA.},
	issn = {1944-7973},
	shorttitle = {Evaluating {Distributed} {Snow} {Model} {Resolution} and {Meteorology} {Parameterizations} {Against} {Streamflow} {Observations}},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2023WR035982},
	doi = {10.1029/2023WR035982},
	abstract = {Estimating snow conditions is often done using numerical snowpack evolution models at spatial resolutions of 500 m and greater; however, snow depth in complex terrain often varies on sub-meter scales. This study investigated how the spatial distribution of simulated snow conditions varied across seven model spatial resolutions from 30 to 1,000 m and over two meteorological data sets, coarser (≈12 km) and finer (4 km). Simulated snow covered area (SCA) was compared to remotely sensed SCA and simulated watershed mean peak snow water equivalent (SWE) was compared to four streamflow statistics representing different water management-relevant aspects of the hydrograph using non-parametric correlations. April 1 SWE tended to increase with model resolution, particularly below 4,000 masl. Finer meteorology simulations produced deeper April 1 SWE than coarser meteorology simulations. Finer resolution snow simulations tended to produce longer snowmelt durations and slower snowmelt rates than coarser resolution simulations. Finer resolution simulations had better agreement with SCA for both meteorology data sets, particularly at high and low elevations. However, finer resolution simulations did not generally outperform coarser simulations in snow versus streamflow statistic correlations. Snow versus streamflow correlations were most sensitive to meteorology, watershed properties, and then resolution. Watershed physiographic properties such as wetness index may increase snow versus streamflow metric correlations while elevation and slope may decrease correlations. At watershed scales, these results suggest that simulation resolution and choice of meteorology is less important than the physiographic properties of the watershed; however, if resolving snow distribution across the landscape is important, finer-resolution simulations are useful.},
	language = {en},
	number = {7},
	urldate = {2025-01-27},
	journal = {Water Resources Research},
	author = {Barnhart, Theodore B. and Putman, Annie L. and Heldmyer, Aaron J. and Rey, David M. and Hammond, John C. and Driscoll, Jessica M. and Sexstone, Graham A.},
	year = {2024},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1029/2023WR035982},
	keywords = {NALCMS},
	pages = {e2023WR035982},
}

Estimating snow conditions is often done using numerical snowpack evolution models at spatial resolutions of 500 m and greater; however, snow depth in complex terrain often varies on sub-meter scales. This study investigated how the spatial distribution of simulated snow conditions varied across seven model spatial resolutions from 30 to 1,000 m and over two meteorological data sets, coarser (≈12 km) and finer (4 km). Simulated snow covered area (SCA) was compared to remotely sensed SCA and simulated watershed mean peak snow water equivalent (SWE) was compared to four streamflow statistics representing different water management-relevant aspects of the hydrograph using non-parametric correlations. April 1 SWE tended to increase with model resolution, particularly below 4,000 masl. Finer meteorology simulations produced deeper April 1 SWE than coarser meteorology simulations. Finer resolution snow simulations tended to produce longer snowmelt durations and slower snowmelt rates than coarser resolution simulations. Finer resolution simulations had better agreement with SCA for both meteorology data sets, particularly at high and low elevations. However, finer resolution simulations did not generally outperform coarser simulations in snow versus streamflow statistic correlations. Snow versus streamflow correlations were most sensitive to meteorology, watershed properties, and then resolution. Watershed physiographic properties such as wetness index may increase snow versus streamflow metric correlations while elevation and slope may decrease correlations. At watershed scales, these results suggest that simulation resolution and choice of meteorology is less important than the physiographic properties of the watershed; however, if resolving snow distribution across the landscape is important, finer-resolution simulations are useful.

@article{esperon-rodriguez_evaluating_2024,
	title = {Evaluating the impact of protected areas in lowering extinction risks in a biodiversity hotspot},
	volume = {297},
	issn = {0006-3207},
	url = {https://www.sciencedirect.com/science/article/pii/S0006320724002908},
	doi = {10.1016/j.biocon.2024.110728},
	abstract = {The tropics harbour the highest species number on Earth, making them critical hotspots of biodiversity. However, there is an increased extinction risk towards the tropics, aka the tropical biodiversity crisis. Today, biodiversity loss is considered the main threat humanity faces. Yet, key locations may act as refugia (areas that ensure the persistence of biodiversity under environmental changes). Here, we used a set of five environmental variables (elevation, maximum temperature of the warmest month, temperature annual range, annual precipitation, and the human footprint index) to quantify the main drivers of extinction risk inside and outside protected areas for 7609 species of terrestrial animals and vascular plants distributed across Mexico. We used ordinal logistic regressions to assess drivers of extinction risk, as defined by the IUCN Red List, and evaluate the impact of the existing network of protected areas across Mexico to lower this risk. Outside protected areas, extinction risk was the highest for mammals and the lowest for reptiles. Protected areas had a positive impact by lowering the extinction risk of birds compared to outside these areas, while the opposite was observed for mammals, reptiles, vascular plants, amphibians, and arthropods. Extinction risk was greater in regions with high annual precipitation, high maximum temperature of the warmest month, low temperature annual range, as well as in areas with high elevations and human pressures on the environement. The network of protected areas in Mexico is crucial for the conservation of biodiversity; however, this network requires revision that accounts for climate change scenarios to better protect regions facing the greatest risks.},
	urldate = {2025-01-27},
	journal = {Biological Conservation},
	author = {Esperon-Rodriguez, Manuel and Correa-Metrio, Alex and Beaumont, Linda J. and Baumgartner, John B. and Lenoir, Jonathan},
	month = sep,
	year = {2024},
	keywords = {NALCMS},
	pages = {110728},
}

The tropics harbour the highest species number on Earth, making them critical hotspots of biodiversity. However, there is an increased extinction risk towards the tropics, aka the tropical biodiversity crisis. Today, biodiversity loss is considered the main threat humanity faces. Yet, key locations may act as refugia (areas that ensure the persistence of biodiversity under environmental changes). Here, we used a set of five environmental variables (elevation, maximum temperature of the warmest month, temperature annual range, annual precipitation, and the human footprint index) to quantify the main drivers of extinction risk inside and outside protected areas for 7609 species of terrestrial animals and vascular plants distributed across Mexico. We used ordinal logistic regressions to assess drivers of extinction risk, as defined by the IUCN Red List, and evaluate the impact of the existing network of protected areas across Mexico to lower this risk. Outside protected areas, extinction risk was the highest for mammals and the lowest for reptiles. Protected areas had a positive impact by lowering the extinction risk of birds compared to outside these areas, while the opposite was observed for mammals, reptiles, vascular plants, amphibians, and arthropods. Extinction risk was greater in regions with high annual precipitation, high maximum temperature of the warmest month, low temperature annual range, as well as in areas with high elevations and human pressures on the environement. The network of protected areas in Mexico is crucial for the conservation of biodiversity; however, this network requires revision that accounts for climate change scenarios to better protect regions facing the greatest risks.

@article{kaenel_evaluation_2024,
	title = {Evaluation of {Noah}-{MP} {Snow} {Simulation} across {Site} {Conditions} in the {Western} {United} {States}},
	volume = {25},
	issn = {1525-7541, 1525-755X},
	url = {https://journals.ametsoc.org/view/journals/hydr/25/9/JHM-D-23-0211.1.xml},
	doi = {10.1175/JHM-D-23-0211.1},
	abstract = {Quantifying spatiotemporal variability in snow water resources is a challenge especially relevant for regions that rely on snowmelt for water supply. Model accuracy is often limited by uncertainties in meteorological forcings and/or suboptimal physics representation. In this study, we evaluate the performance and sensitivity of Noah land surface model with multiparameterization options (Noah-MP) snow simulations from ten model configurations across 199 sites in the western United States. Nine experiments are constrained by observed meteorology to test snow-related physics options, and the 10th experiment tests an alternative source of meteorological forcings. We find that the base case, which aligns with the National Water Model configuration and uses observation-based forcings, overestimates observed accumulated snow water equivalent (SWE) at 90\% of stations by a median of 9.6\%. The model performs better in the accumulation season at colder, drier sites and in the melt season at wetter, warmer sites. Accumulation metrics are sensitive to model configuration in two experiments, and melt metrics, in six experiments. Alterations to model physics cause changes to median accumulation metrics from −13\% to 2.3\% with the greatest change due to precipitation partitioning and to melt metrics from −10\% to 3\% with the greatest change due to surface resistance configuration. The experiment with alternative forcings causes even greater and wider-ranging changes (medians ranging from −29\% to 6\%). Not all stations share the same best-performing model configuration. At most stations, the base case is outperformed by four alternative physics options which also significantly impact snow simulation. This research provides insights into the performance and sensitivity of snow predictions across site conditions and model configurations. Significance Statement The purpose of this work is to evaluate the performance and sensitivity of a land surface model’s simulation of snow across site conditions and in response to different model configurations. This is important because estimating snow distribution is a challenge especially relevant for regions that rely on snowmelt for water supply. While land surface models can provide useful large-scale estimates, they are often limited by uncertainties in forcings and/or suboptimal physics representation. The results, which show varying model behavior across geography, climate, vegetation types, and model configurations, highlight inadequacies in model physics representation, emphasize the need for accurate meteorological forcings, and suggest that customizing model configurations to the unique characteristics of the domain could yield more accurate and useful results.},
	language = {EN},
	number = {9},
	urldate = {2025-01-27},
	journal = {Journal of Hydrometeorology},
	author = {Kaenel, Manon von and Margulis, Steven A.},
	month = sep,
	year = {2024},
	note = {Publisher: American Meteorological Society
Section: Journal of Hydrometeorology},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {1389--1406},
}

Quantifying spatiotemporal variability in snow water resources is a challenge especially relevant for regions that rely on snowmelt for water supply. Model accuracy is often limited by uncertainties in meteorological forcings and/or suboptimal physics representation. In this study, we evaluate the performance and sensitivity of Noah land surface model with multiparameterization options (Noah-MP) snow simulations from ten model configurations across 199 sites in the western United States. Nine experiments are constrained by observed meteorology to test snow-related physics options, and the 10th experiment tests an alternative source of meteorological forcings. We find that the base case, which aligns with the National Water Model configuration and uses observation-based forcings, overestimates observed accumulated snow water equivalent (SWE) at 90% of stations by a median of 9.6%. The model performs better in the accumulation season at colder, drier sites and in the melt season at wetter, warmer sites. Accumulation metrics are sensitive to model configuration in two experiments, and melt metrics, in six experiments. Alterations to model physics cause changes to median accumulation metrics from −13% to 2.3% with the greatest change due to precipitation partitioning and to melt metrics from −10% to 3% with the greatest change due to surface resistance configuration. The experiment with alternative forcings causes even greater and wider-ranging changes (medians ranging from −29% to 6%). Not all stations share the same best-performing model configuration. At most stations, the base case is outperformed by four alternative physics options which also significantly impact snow simulation. This research provides insights into the performance and sensitivity of snow predictions across site conditions and model configurations. Significance Statement The purpose of this work is to evaluate the performance and sensitivity of a land surface model’s simulation of snow across site conditions and in response to different model configurations. This is important because estimating snow distribution is a challenge especially relevant for regions that rely on snowmelt for water supply. While land surface models can provide useful large-scale estimates, they are often limited by uncertainties in forcings and/or suboptimal physics representation. The results, which show varying model behavior across geography, climate, vegetation types, and model configurations, highlight inadequacies in model physics representation, emphasize the need for accurate meteorological forcings, and suggest that customizing model configurations to the unique characteristics of the domain could yield more accurate and useful results.

@phdthesis{panos_evaluation_2024,
	type = {Master of {Science}},
	title = {Evaluation of avian use of agricultural cover crops during the winter, migration stopover, and the breeding season in {Tennessee}},
	url = {https://trace.tennessee.edu/utk_gradthes/11344},
	school = {University of Tennessee - Knoxville},
	author = {Panos, Brittany},
	month = may,
	year = {2024},
	keywords = {NALCMS},
}

@article{fernandes_evidence_2024,
	title = {Evidence of a bias-variance trade off when correcting for bias in {Sentinel} 2 forest {LAI} retrievals using radiative transfer models},
	volume = {305},
	issn = {0034-4257},
	url = {https://www.sciencedirect.com/science/article/pii/S0034425724000713},
	doi = {10.1016/j.rse.2024.114060},
	abstract = {Forest canopies exhibit spatial heterogeneity that impacts the relationship between essential climate variables such as leaf area index (LAI) or the fraction of absorbed photosynthetically active radiation (fAPAR) and bi-directional surface reflectance, and subsequently the estimation of these variables from satellite measurements. The Simplified Level 2 Prototype Processor (SL2P) allows global LAI and fAPAR mapping at 20 m resolution using Sentinel 2 imagery. Previous validation studies over forests indicate SL2P underestimates LAI by up to 50\% in comparison to in-situ reference measurements. Our study tests the hypothesis that the SL2P LAI and fAPAR bias can be reduced by replacing the spatially homogenous SAILH canopy radiative transfer model used to calibrate SL2P with the heterogenous 4SAIL2 model, together with a shoot clumping parameterization. We also hypothesized that the additional parameters involved in this new version of SL2P (SL2P-CCRS) would lead to an increase in precision error and subsequently a bias-variance trade off. SL2P-CCRS reduced LAI bias by 65\%, in comparison to SL2P, during direct validation with 1107 in-situ measurements. The LAI absolute bias reduced by ∼0.5 at LAI 3 and by ∼1 at LAI 6. SL2P-CCRS reduced fAPAR bias by 31\% compared to SL2P but {\textless}0.05 on an absolute basis. Bias reduction was accompanied by an increase in precision error so that overall uncertainty, quantified by the root mean square difference in comparison to in-situ measurements, reduced by only 6\% for LAI and 5\% for fAPAR. These findings support the hypothesis that updating SL2P with a spatially heterogeneous RTM can reduce LAI and fAPAR bias over forests. The results also support the hypothesis that there is a bias-variance trade-off for LAI, and to a lesser extent for fAPAR, when increasing the complexity of SL2P by using a radiative transfer model that accounts for spatial heterogeneity. Nevertheless, SL2P-CCRS increased the agreement rate with Global Climate Observing System uncertainty requirements from 52\% to 58\% for LAI and 32\% to 40\% for fAPAR, suggesting that the trade-off is worthwhile, and that algorithms such as SL2P-CCRS, that use a spatially heterogenous radiative transfer model, should be applied for mapping fAPAR and LAI from Sentinel-2 measurements.},
	urldate = {2024-08-12},
	journal = {Remote Sensing of Environment},
	author = {Fernandes, Richard and Djamai, Najib and Harvey, Kate and Hong, Gang and MacDougall, Camryn and Shah, Hemit and Sun, Lixin},
	month = may,
	year = {2024},
	keywords = {North American Forests},
	pages = {114060},
}

Forest canopies exhibit spatial heterogeneity that impacts the relationship between essential climate variables such as leaf area index (LAI) or the fraction of absorbed photosynthetically active radiation (fAPAR) and bi-directional surface reflectance, and subsequently the estimation of these variables from satellite measurements. The Simplified Level 2 Prototype Processor (SL2P) allows global LAI and fAPAR mapping at 20 m resolution using Sentinel 2 imagery. Previous validation studies over forests indicate SL2P underestimates LAI by up to 50% in comparison to in-situ reference measurements. Our study tests the hypothesis that the SL2P LAI and fAPAR bias can be reduced by replacing the spatially homogenous SAILH canopy radiative transfer model used to calibrate SL2P with the heterogenous 4SAIL2 model, together with a shoot clumping parameterization. We also hypothesized that the additional parameters involved in this new version of SL2P (SL2P-CCRS) would lead to an increase in precision error and subsequently a bias-variance trade off. SL2P-CCRS reduced LAI bias by 65%, in comparison to SL2P, during direct validation with 1107 in-situ measurements. The LAI absolute bias reduced by ∼0.5 at LAI 3 and by ∼1 at LAI 6. SL2P-CCRS reduced fAPAR bias by 31% compared to SL2P but \textless0.05 on an absolute basis. Bias reduction was accompanied by an increase in precision error so that overall uncertainty, quantified by the root mean square difference in comparison to in-situ measurements, reduced by only 6% for LAI and 5% for fAPAR. These findings support the hypothesis that updating SL2P with a spatially heterogeneous RTM can reduce LAI and fAPAR bias over forests. The results also support the hypothesis that there is a bias-variance trade-off for LAI, and to a lesser extent for fAPAR, when increasing the complexity of SL2P by using a radiative transfer model that accounts for spatial heterogeneity. Nevertheless, SL2P-CCRS increased the agreement rate with Global Climate Observing System uncertainty requirements from 52% to 58% for LAI and 32% to 40% for fAPAR, suggesting that the trade-off is worthwhile, and that algorithms such as SL2P-CCRS, that use a spatially heterogenous radiative transfer model, should be applied for mapping fAPAR and LAI from Sentinel-2 measurements.

@article{ariano_examining_2024,
	title = {Examining contaminant transport hotspots and their predictability across contrasted watersheds},
	volume = {196},
	issn = {1573-2959},
	url = {https://doi.org/10.1007/s10661-024-13053-8},
	doi = {10.1007/s10661-024-13053-8},
	abstract = {Hydrobiogeochemical processes governing water quantity and quality are highly variable in space and time. Focusing on thirty river locations in Québec, Canada, three water quality hotness indices were used to classify watersheds as contaminant transport hotspots. Concentration and load data for suspended solids (SS), total nitrogen (TN), and total phosphorous (TP) were used to identify transport hotspots, and results were compared across hotness indices with different data requirements. The role of hydroclimatic and physiographic characteristics on the occurrence and temporal persistence of transport hotspots was examined. Results show that the identification of transport hotspots was dependent on both the type of data and the hotness index used. Relationships between temporal and spatial predictors, however, were generally consistent. Annual transport hotspot occurrence was found to be related to temporal characteristics such as the number of dry days, potential evapotranspiration, and snow water equivalent, while hotspot temporal persistence was correlated to landcover characteristics. Stark differences in the identification of SS, TN, and TP transport hotspots were attributed to differences in mobilization processes and provided insights into dominant water and nutrient flowpaths in the studied watersheds. This study highlighted the importance of comparing contaminant dynamics across watersheds even when high-frequency water quality data or discharge data are not available. Characterizing hotspot occurrence and persistence, among hotness indices and water quality parameters, could be useful for watershed managers when identifying problematic watersheds, exploring legacy effects, and establishing a prioritization framework for areas that would benefit from enhanced routine monitoring or targeted mitigation strategies.},
	language = {en},
	number = {10},
	urldate = {2025-01-17},
	journal = {Environmental Monitoring and Assessment},
	author = {Ariano, Sarah S. and Bain, Jamie and Ali, Geneviève},
	month = sep,
	year = {2024},
	keywords = {NALCMS},
	pages = {885},
}

Hydrobiogeochemical processes governing water quantity and quality are highly variable in space and time. Focusing on thirty river locations in Québec, Canada, three water quality hotness indices were used to classify watersheds as contaminant transport hotspots. Concentration and load data for suspended solids (SS), total nitrogen (TN), and total phosphorous (TP) were used to identify transport hotspots, and results were compared across hotness indices with different data requirements. The role of hydroclimatic and physiographic characteristics on the occurrence and temporal persistence of transport hotspots was examined. Results show that the identification of transport hotspots was dependent on both the type of data and the hotness index used. Relationships between temporal and spatial predictors, however, were generally consistent. Annual transport hotspot occurrence was found to be related to temporal characteristics such as the number of dry days, potential evapotranspiration, and snow water equivalent, while hotspot temporal persistence was correlated to landcover characteristics. Stark differences in the identification of SS, TN, and TP transport hotspots were attributed to differences in mobilization processes and provided insights into dominant water and nutrient flowpaths in the studied watersheds. This study highlighted the importance of comparing contaminant dynamics across watersheds even when high-frequency water quality data or discharge data are not available. Characterizing hotspot occurrence and persistence, among hotness indices and water quality parameters, could be useful for watershed managers when identifying problematic watersheds, exploring legacy effects, and establishing a prioritization framework for areas that would benefit from enhanced routine monitoring or targeted mitigation strategies.

@article{pflug_extending_2024,
	title = {Extending the utility of space-borne snow water equivalent observations over vegetated areas with data assimilation},
	volume = {28},
	issn = {1027-5606},
	url = {https://hess.copernicus.org/articles/28/631/2024/},
	doi = {10.5194/hess-28-631-2024},
	abstract = {Snow is a vital component of the earth system, yet no snow-focused satellite remote sensing platform currently exists. In this study, we investigate how synthetic observations of snow water equivalent (SWE) representative of a synthetic aperture radar remote sensing platform could improve spatiotemporal estimates of snowpack. We use a fraternal twin observing system simulation experiment, specifically investigating how much snow simulated using widely used models and forcing data could be improved by assimilating synthetic observations of SWE. We focus this study across a 24∘×37∘ domain in the western USA and Canada, simulating snow at 250 m resolution and hourly time steps in water year 2019. We perform two data assimilation experiments, including (1) a simulation excluding synthetic observations in forests where canopies obstruct remote sensing retrievals and (2) a simulation inferring snow distribution in forested grid cells using synthetic observations from nearby canopy-free grid cells. Results found that, relative to a nature run, or assumed true simulation of snow evolution, assimilating synthetic SWE observations improved average SWE biases at maximum snowpack timing in shrub, grass, crop, bare-ground, and wetland land cover types from 14 \%, to within 1 \%. However, forested grid cells contained a disproportionate amount of SWE volume. In forests, SWE mean absolute errors at the time of maximum snow volume were 111 mm and average SWE biases were on the order of 150 \%. Here the data assimilation approach that estimated forest SWE using observations from the nearest canopy-free grid cells substantially improved these SWE biases (18 \%) and the SWE mean absolute error (27 mm). Simulations employing data assimilation also improved estimates of the temporal evolution of both SWE and runoff, even in spring snowmelt periods when melting snow and high snow liquid water content prevented synthetic SWE retrievals. In fact, in the Upper Colorado River region, melt-season SWE biases were improved from 63 \% to within 1 \%, and the Nash–Sutcliffe efficiency of runoff improved from −2.59 to 0.22. These results demonstrate the value of data assimilation and a snow-focused globally relevant remote sensing platform for improving the characterization of SWE and associated water availability.},
	language = {English},
	number = {3},
	urldate = {2024-03-13},
	journal = {Hydrology and Earth System Sciences},
	author = {Pflug, Justin M. and Wrzesien, Melissa L. and Kumar, Sujay V. and Cho, Eunsang and Arsenault, Kristi R. and Houser, Paul R. and Vuyovich, Carrie M.},
	month = feb,
	year = {2024},
	note = {Publisher: Copernicus GmbH},
	keywords = {NALCMS},
	pages = {631--648},
}

Snow is a vital component of the earth system, yet no snow-focused satellite remote sensing platform currently exists. In this study, we investigate how synthetic observations of snow water equivalent (SWE) representative of a synthetic aperture radar remote sensing platform could improve spatiotemporal estimates of snowpack. We use a fraternal twin observing system simulation experiment, specifically investigating how much snow simulated using widely used models and forcing data could be improved by assimilating synthetic observations of SWE. We focus this study across a 24∘×37∘ domain in the western USA and Canada, simulating snow at 250 m resolution and hourly time steps in water year 2019. We perform two data assimilation experiments, including (1) a simulation excluding synthetic observations in forests where canopies obstruct remote sensing retrievals and (2) a simulation inferring snow distribution in forested grid cells using synthetic observations from nearby canopy-free grid cells. Results found that, relative to a nature run, or assumed true simulation of snow evolution, assimilating synthetic SWE observations improved average SWE biases at maximum snowpack timing in shrub, grass, crop, bare-ground, and wetland land cover types from 14 %, to within 1 %. However, forested grid cells contained a disproportionate amount of SWE volume. In forests, SWE mean absolute errors at the time of maximum snow volume were 111 mm and average SWE biases were on the order of 150 %. Here the data assimilation approach that estimated forest SWE using observations from the nearest canopy-free grid cells substantially improved these SWE biases (18 %) and the SWE mean absolute error (27 mm). Simulations employing data assimilation also improved estimates of the temporal evolution of both SWE and runoff, even in spring snowmelt periods when melting snow and high snow liquid water content prevented synthetic SWE retrievals. In fact, in the Upper Colorado River region, melt-season SWE biases were improved from 63 % to within 1 %, and the Nash–Sutcliffe efficiency of runoff improved from −2.59 to 0.22. These results demonstrate the value of data assimilation and a snow-focused globally relevant remote sensing platform for improving the characterization of SWE and associated water availability.

@phdthesis{moore_factors_2024,
	title = {Factors influencing the diversity and abundance of grassland birds in the {Waterton} {Foothills} {Parkland}, {Alberta}, {Canada}},
	url = {http://hdl.handle.net/1993/38628},
	abstract = {Grassland birds are among the most imperilled taxa in North America, with declines being primarily associated with the widespread conversion of grasslands for agriculture. However, alteration of existing vegetation communities and the landscape context in which habitats occur can be important factors affecting the use of remaining grassland habitats by birds. The Waterton Foothills Parkland region in southern Alberta, Canada is characterized by complex topography consisting of native grassland-forest-wetland mosaics. In this thesis, I used naturally occurring landscape heterogeneity and management-relevant habitat metrics to evaluate multi-scale ecological responses of grassland birds. I evaluated how the presence, abundance, and diversity of grassland birds responded to their habitat using Autonomous Recording Units, in-field vegetation surveys, and spatial landscape assessments. I found that the grassland bird community mostly responded to grassland fragmentation and topography within 400 to 800 m extents. Fragmentation increased the total diversity of grassland birds because spillover of facultative grassland birds at edges was greater than decreases in the diversity of a limited pool of obligate species in more fragmented landscapes. Sites with more rugged terrain was autocorrelated with native grasslands, suggesting that landscape-scale responses of grassland birds to terrain ruggedness were associated with the distribution of different grassland types. Local measures of grassland type represented by the percent composition of non-native species and rangeland health were key determinants of the grassland bird community. Healthy, native grasslands supported higher abundances of Vesper and Clay-coloured Sparrows and unhealthy, modified grasslands supported more Savannah Sparrows and Western Meadowlarks. This research supports that sections and quarter-sections of land are informative units for examining the abundance and diversity of grassland birds in the Waterton Foothills Parkland based on responses of the grassland community to grassland fragmentation, topography, non-native vegetation invasion, and range health.},
	language = {eng},
	urldate = {2024-11-20},
	author = {Moore, Zachary},
	month = aug,
	year = {2024},
	keywords = {NALCMS},
}

Grassland birds are among the most imperilled taxa in North America, with declines being primarily associated with the widespread conversion of grasslands for agriculture. However, alteration of existing vegetation communities and the landscape context in which habitats occur can be important factors affecting the use of remaining grassland habitats by birds. The Waterton Foothills Parkland region in southern Alberta, Canada is characterized by complex topography consisting of native grassland-forest-wetland mosaics. In this thesis, I used naturally occurring landscape heterogeneity and management-relevant habitat metrics to evaluate multi-scale ecological responses of grassland birds. I evaluated how the presence, abundance, and diversity of grassland birds responded to their habitat using Autonomous Recording Units, in-field vegetation surveys, and spatial landscape assessments. I found that the grassland bird community mostly responded to grassland fragmentation and topography within 400 to 800 m extents. Fragmentation increased the total diversity of grassland birds because spillover of facultative grassland birds at edges was greater than decreases in the diversity of a limited pool of obligate species in more fragmented landscapes. Sites with more rugged terrain was autocorrelated with native grasslands, suggesting that landscape-scale responses of grassland birds to terrain ruggedness were associated with the distribution of different grassland types. Local measures of grassland type represented by the percent composition of non-native species and rangeland health were key determinants of the grassland bird community. Healthy, native grasslands supported higher abundances of Vesper and Clay-coloured Sparrows and unhealthy, modified grasslands supported more Savannah Sparrows and Western Meadowlarks. This research supports that sections and quarter-sections of land are informative units for examining the abundance and diversity of grassland birds in the Waterton Foothills Parkland based on responses of the grassland community to grassland fragmentation, topography, non-native vegetation invasion, and range health.

@article{duarte_flood_2024,
	title = {Flood prevention benefits provided by {Canadian} natural ecosystems},
	volume = {70},
	issn = {2212-0416},
	url = {https://www.sciencedirect.com/science/article/pii/S2212041624000779},
	doi = {10.1016/j.ecoser.2024.101670},
	abstract = {The escalating impacts of climate change have heightened concerns about the frequency and severity of natural disasters, particularly extreme flooding events. Future projections underscore the necessity for innovative flood prevention strategies, including broad-scale nature-based solutions. Here, we present the first comprehensive assessment of the flood prevention benefits provided by Canadian natural ecosystems and identify key areas crucial for human well-being. Using spatially explicit modeling, we (1) evaluated the potential runoff retention by natural ecosystems and (2) identified downstream urban and agricultural areas critically dependent on these natural benefits, particularly those in floodplains and close proximity to upstream natural ecosystems. The natural ecosystems within the top 5 \% of sub-basins, representing regions with a high priority for conservation practices aimed at flood prevention, play a crucial role in safeguarding approximately 54 \% (∼6,000 km2) of the total built-up area and 74 \% (∼16,900 km2) of the total cropland situated within floodplains. Additionally, they are positioned upstream of floodplain-based urban zones belonging to 358 population centers, directly benefiting 3.7 million people (∼10 \% of the Canadian population) and indirectly benefiting almost 20.1 million people (∼56 \% of the Canadian population). Moreover, among Canada’s 5.2 million km2 of flood-preventing natural ecosystems, we identified a small fraction (10 \%) whose loss or degradation would result in a significant ({\textgreater}50 \%) increase in runoff. Several of these crucial ecosystems are situated in less populated northern regions, where local governments might want to incentivize conservation initiatives to support flood prevention. Our research underscores the imperative to integrate nature-based solutions into national strategies that consider the results of spatial planning analyses. Establishing other effective area-based conservation measures in the priority regions highlighted in this study can contribute towards reaching current ambitious environmental goals and provide critical flood prevention benefits. Additionally, our methods are transferable to other regions worldwide, leveraging globally available datasets and ensuring computational feasibility.},
	urldate = {2025-01-27},
	journal = {Ecosystem Services},
	author = {Duarte, Gabriela T. and Schuster, Richard and Edwards, Marc and Dallaire, Camille O. and Vári, Ágnes and Mitchell, Matthew G. E.},
	month = dec,
	year = {2024},
	keywords = {NALCMS},
	pages = {101670},
}

The escalating impacts of climate change have heightened concerns about the frequency and severity of natural disasters, particularly extreme flooding events. Future projections underscore the necessity for innovative flood prevention strategies, including broad-scale nature-based solutions. Here, we present the first comprehensive assessment of the flood prevention benefits provided by Canadian natural ecosystems and identify key areas crucial for human well-being. Using spatially explicit modeling, we (1) evaluated the potential runoff retention by natural ecosystems and (2) identified downstream urban and agricultural areas critically dependent on these natural benefits, particularly those in floodplains and close proximity to upstream natural ecosystems. The natural ecosystems within the top 5 % of sub-basins, representing regions with a high priority for conservation practices aimed at flood prevention, play a crucial role in safeguarding approximately 54 % (∼6,000 km2) of the total built-up area and 74 % (∼16,900 km2) of the total cropland situated within floodplains. Additionally, they are positioned upstream of floodplain-based urban zones belonging to 358 population centers, directly benefiting 3.7 million people (∼10 % of the Canadian population) and indirectly benefiting almost 20.1 million people (∼56 % of the Canadian population). Moreover, among Canada’s 5.2 million km2 of flood-preventing natural ecosystems, we identified a small fraction (10 %) whose loss or degradation would result in a significant (\textgreater50 %) increase in runoff. Several of these crucial ecosystems are situated in less populated northern regions, where local governments might want to incentivize conservation initiatives to support flood prevention. Our research underscores the imperative to integrate nature-based solutions into national strategies that consider the results of spatial planning analyses. Establishing other effective area-based conservation measures in the priority regions highlighted in this study can contribute towards reaching current ambitious environmental goals and provide critical flood prevention benefits. Additionally, our methods are transferable to other regions worldwide, leveraging globally available datasets and ensuring computational feasibility.

@article{donnelly_flood-irrigated_2024,
	title = {Flood-irrigated agriculture mediates climate-induced wetland scarcity for summering sandhill cranes in western {North} {America}},
	volume = {14},
	copyright = {© 2024 The Authors. Ecology and Evolution published by John Wiley \& Sons Ltd.},
	issn = {2045-7758},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/ece3.10998},
	doi = {10.1002/ece3.10998},
	abstract = {Information about species distributions is lacking in many regions of the world, forcing resource managers to answer complex ecological questions with incomplete data. Information gaps are compounded by climate change, driving ecological bottlenecks that can act as new demographic constraints on fauna. Here, we construct greater sandhill crane (Antigone canadensis tabida) summering range in western North America using movement data from 120 GPS-tagged individuals to determine how landscape composition shaped their distributions. Landscape variables developed from remotely sensed data were combined with bird locations to model distribution probabilities. Additionally, land-use and ownership were summarized within summer range as a measure of general bird use. Wetland variables identified as important predictors of bird distributions were evaluated in a post hoc analysis to measure long-term (1984–2022) effects of climate-driven surface water drying. Wetlands and associated agricultural practices accounted for 1.2\% of summer range but were key predictors of occurrence. Bird distributions were structured by riparian floodplains that concentrated wetlands, and flood-irrigated agriculture in otherwise arid and semi-arid landscapes. Findings highlighted the role of private lands in greater sandhill crane ecology as they accounted for 78\% of predicted distributions. Wetland drying observed in portions of the range from 1984 to 2022 represented an emerging ecological bottleneck that could limit future greater sandhill crane summer range. Study outcomes provide novel insight into the significance of ecosystem services provided by flood-irrigated agriculture that supported nearly 60\% of wetland resources used by birds. Findings suggest greater sandhill cranes function as a surrogate species for agroecology and climate change adaptation strategies seeking to reduce agricultural water use through improved efficiency while also maintaining distinct flood-irrigation practices supporting greater sandhill cranes and other wetland-dependent wildlife. We make our wetland and sandhill crane summering distributions available as interactive web-based mapping tools to inform conservation design.},
	language = {en},
	number = {3},
	urldate = {2026-05-26},
	journal = {Ecology and Evolution},
	author = {Donnelly, J. Patrick and Collins, Daniel P. and Knetter, Jeffrey M. and Gammonley, James H. and Boggie, Matthew A. and Grisham, Blake A. and Nowak, M. Cathy and Naugle, David E.},
	year = {2024},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/ece3.10998},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {e10998},
}

Information about species distributions is lacking in many regions of the world, forcing resource managers to answer complex ecological questions with incomplete data. Information gaps are compounded by climate change, driving ecological bottlenecks that can act as new demographic constraints on fauna. Here, we construct greater sandhill crane (Antigone canadensis tabida) summering range in western North America using movement data from 120 GPS-tagged individuals to determine how landscape composition shaped their distributions. Landscape variables developed from remotely sensed data were combined with bird locations to model distribution probabilities. Additionally, land-use and ownership were summarized within summer range as a measure of general bird use. Wetland variables identified as important predictors of bird distributions were evaluated in a post hoc analysis to measure long-term (1984–2022) effects of climate-driven surface water drying. Wetlands and associated agricultural practices accounted for 1.2% of summer range but were key predictors of occurrence. Bird distributions were structured by riparian floodplains that concentrated wetlands, and flood-irrigated agriculture in otherwise arid and semi-arid landscapes. Findings highlighted the role of private lands in greater sandhill crane ecology as they accounted for 78% of predicted distributions. Wetland drying observed in portions of the range from 1984 to 2022 represented an emerging ecological bottleneck that could limit future greater sandhill crane summer range. Study outcomes provide novel insight into the significance of ecosystem services provided by flood-irrigated agriculture that supported nearly 60% of wetland resources used by birds. Findings suggest greater sandhill cranes function as a surrogate species for agroecology and climate change adaptation strategies seeking to reduce agricultural water use through improved efficiency while also maintaining distinct flood-irrigation practices supporting greater sandhill cranes and other wetland-dependent wildlife. We make our wetland and sandhill crane summering distributions available as interactive web-based mapping tools to inform conservation design.

@phdthesis{main_glacier_2024,
	type = {Thesis},
	title = {Glacier {Velocities} and {Ice} {Dynamics} in the {St}. {Elias} {Mountains}, {Yukon}-{Alaska}},
	url = {http://ruor.uottawa.ca/handle/10393/45826},
	abstract = {Despite their relatively small ice volume, mountain glaciers contributed nearly one third of global sea level rise since 2000, with one of the largest total mass loss rates (73 ± 17 Gt a-1) occurring in the Yukon-Alaska region. However, there is uncertainty surrounding how ice dynamics are being affected by such losses and whether glacier flow instabilities, such as surges, are changing in a warming climate. The St. Elias Mountains contain a major cluster of surge-type glaciers, yet a detailed analysis of their characteristics, including surge frequency, morphology, magnitude, and propensity over time has not been undertaken on a regional basis. This thesis presents a review of surging behaviour and an updated surge event inventory in the St. Elias Mountains, and quantifies the processes influencing both surging and non-surging glacier velocity variability using a variety of remote sensing and field measurements. An updated inventory of surge-type glaciers and observed surge events (1874-2023), compiled from existing inventories, recently published articles, and velocity analysis, is used to analyze the characteristics of surge-type glaciers and velocity patterns during surge events. The modern (1985-2023) trends in annual, winter and summer velocities of selected surge-type glaciers is then used to classify dynamic instability events into 4 categories. While 231 glaciers were classified as surge-type, only 42 were observed to have experienced rapid velocity events over the period 1985-2023, through either direct measurements or remote sensing observations. For glaciers with observed rapid velocity events, these predominantly fall into two categories: Alaskan-style surges with short active and quiescent phases, and glacier pulses, which are velocity accelerations that are limited in both magnitude and extent. An unnamed former tributary to Kluane Glacier underwent a dramatic surge from 2013-18. Using a combination of air photos, remote sensing and field observations, the characteristics and changes of ‘Little Kluane Glacier’ were reconstructed from the 1940s until 2021. While only the single full surge of 2013-18 was identified, it is likely that a partial surge of just the upper north arm occurred between 1963 and 1972. Repeat Digital Elevation Models (DEMs) and velocity profiles show that the recent surge initiated from the upper north arm accumulation area in 2013, which developed into a full surge of the main trunk from 2017-18. Terminus positions show long-term retreat from 1949-2017, followed by rapid advance of {\textgreater}2 km from May to September 2018, with surface velocities reaching a peak of {\textasciitilde}3600 m a-1 in summer 2018 over the lower ablation area. This was likely enhanced by the drainage of supraglacial lakes and streams to the glacier bed through crevassing as the surge progressed. Changes in surface topography caused by initial mass movement, the resulting reorganization of the supraglacial hydrological system, and ponding of surface water, may drive a partial surge into a full surge, and therefore exert a direct control on glacier dynamics. In May 2016, Kaskawulsh Glacier underwent a dramatic proglacial hydrologic reorganization instigated by the rapid drainage of proglacial Slims Lake: as a result, water which previously drained north into Ä’äy Chú, (Slims River) toward Lhú’áán Män (Kluane Lake), was redirected south into Kaskawulsh River, eventually flowing into the Gulf of Alaska. A long-term (up to ∼120 year) record of terminus retreat, thinning and surface velocities from in-situ and remote sensing observations is used to determine the impact of this reorganization on glacier dynamics. After an initial deceleration during the late 1990s, terminus velocities increased at a rate of 3 m a-2 from 2000-12, while the area of proglacial Slims Lake increased simultaneously. The rapid drainage of the lake substantially altered the velocity profile of the adjacent glacier, decreasing annual velocities by 48\% within 3 km of the terminus between 2015 and 2021, at an average rate of ∼12.5 m a-2. A key cause of the rapid drop in glacier motion was a reduction in flotation of the lower part of the terminus after lake drainage. This has important implications for glacier dynamics and provides one of the first assessments of the impacts of a rapid proglacial lake drainage event on local terminus velocities. The results of this study provide an examination of factors controlling glacier dynamics, as well as the characteristics of rapid glacier velocity events, in the St. Elias Mountains. This provides insights into the behaviour of mountain glaciers, how they are changing in a warming climate, controls on glacier surging, and the hazards they may pose for downstream communities, which are particularly vulnerable to disturbances.},
	language = {en},
	urldate = {2024-01-31},
	school = {Université d'Ottawa / University of Ottawa},
	author = {Main, Brittany},
	month = jan,
	year = {2024},
	doi = {10.20381/ruor-30030},
	note = {Accepted: 2024-01-11T20:46:31Z},
	keywords = {Political Boundaries},
}

Despite their relatively small ice volume, mountain glaciers contributed nearly one third of global sea level rise since 2000, with one of the largest total mass loss rates (73 ± 17 Gt a-1) occurring in the Yukon-Alaska region. However, there is uncertainty surrounding how ice dynamics are being affected by such losses and whether glacier flow instabilities, such as surges, are changing in a warming climate. The St. Elias Mountains contain a major cluster of surge-type glaciers, yet a detailed analysis of their characteristics, including surge frequency, morphology, magnitude, and propensity over time has not been undertaken on a regional basis. This thesis presents a review of surging behaviour and an updated surge event inventory in the St. Elias Mountains, and quantifies the processes influencing both surging and non-surging glacier velocity variability using a variety of remote sensing and field measurements. An updated inventory of surge-type glaciers and observed surge events (1874-2023), compiled from existing inventories, recently published articles, and velocity analysis, is used to analyze the characteristics of surge-type glaciers and velocity patterns during surge events. The modern (1985-2023) trends in annual, winter and summer velocities of selected surge-type glaciers is then used to classify dynamic instability events into 4 categories. While 231 glaciers were classified as surge-type, only 42 were observed to have experienced rapid velocity events over the period 1985-2023, through either direct measurements or remote sensing observations. For glaciers with observed rapid velocity events, these predominantly fall into two categories: Alaskan-style surges with short active and quiescent phases, and glacier pulses, which are velocity accelerations that are limited in both magnitude and extent. An unnamed former tributary to Kluane Glacier underwent a dramatic surge from 2013-18. Using a combination of air photos, remote sensing and field observations, the characteristics and changes of ‘Little Kluane Glacier’ were reconstructed from the 1940s until 2021. While only the single full surge of 2013-18 was identified, it is likely that a partial surge of just the upper north arm occurred between 1963 and 1972. Repeat Digital Elevation Models (DEMs) and velocity profiles show that the recent surge initiated from the upper north arm accumulation area in 2013, which developed into a full surge of the main trunk from 2017-18. Terminus positions show long-term retreat from 1949-2017, followed by rapid advance of \textgreater2 km from May to September 2018, with surface velocities reaching a peak of ~3600 m a-1 in summer 2018 over the lower ablation area. This was likely enhanced by the drainage of supraglacial lakes and streams to the glacier bed through crevassing as the surge progressed. Changes in surface topography caused by initial mass movement, the resulting reorganization of the supraglacial hydrological system, and ponding of surface water, may drive a partial surge into a full surge, and therefore exert a direct control on glacier dynamics. In May 2016, Kaskawulsh Glacier underwent a dramatic proglacial hydrologic reorganization instigated by the rapid drainage of proglacial Slims Lake: as a result, water which previously drained north into Ä’äy Chú, (Slims River) toward Lhú’áán Män (Kluane Lake), was redirected south into Kaskawulsh River, eventually flowing into the Gulf of Alaska. A long-term (up to ∼120 year) record of terminus retreat, thinning and surface velocities from in-situ and remote sensing observations is used to determine the impact of this reorganization on glacier dynamics. After an initial deceleration during the late 1990s, terminus velocities increased at a rate of 3 m a-2 from 2000-12, while the area of proglacial Slims Lake increased simultaneously. The rapid drainage of the lake substantially altered the velocity profile of the adjacent glacier, decreasing annual velocities by 48% within 3 km of the terminus between 2015 and 2021, at an average rate of ∼12.5 m a-2. A key cause of the rapid drop in glacier motion was a reduction in flotation of the lower part of the terminus after lake drainage. This has important implications for glacier dynamics and provides one of the first assessments of the impacts of a rapid proglacial lake drainage event on local terminus velocities. The results of this study provide an examination of factors controlling glacier dynamics, as well as the characteristics of rapid glacier velocity events, in the St. Elias Mountains. This provides insights into the behaviour of mountain glaciers, how they are changing in a warming climate, controls on glacier surging, and the hazards they may pose for downstream communities, which are particularly vulnerable to disturbances.

@article{lowitt_governing_2024,
	title = {Governing for transboundary environmental justice: a scientific and policy analysis of fish consumption advisory programs in the {Upper} {St} {Lawrence} {River}},
	volume = {9},
	shorttitle = {Governing for transboundary environmental justice},
	url = {https://www.facetsjournal.com/doi/full/10.1139/facets-2023-0072},
	doi = {10.1139/facets-2023-0072},
	abstract = {This paper examines fish consumption advisories (FCAs) as a site of transboundary governance in the Upper St Lawrence River with the aim of identifying opportunities for enhanced coordination and power sharing to address environmental injustices. The Upper St Lawrence River is part of the Great Lakes watershed of North America and the traditional territory of multiple Indigenous Nations, as well as the present-day jurisdictions of Ontario (Canada), Quebec (Canada), and New York State (USA). Through an analysis of publicly available information on FCA programs, we examine similarities and differences in these programs across jurisdictions. We find an overall lack of coordination in fish monitoring and differences in consumption advice for a waterway in which fish may easily move between transboundary areas. We offer recommendations for improving FCAs in this transboundary waterway from the lens of environmental justice, focusing on (1) a shared and transparent approach to monitoring contaminant levels and fish species; (2) integration of cultural food practices; (3) enhanced outreach to angler populations; and (4) upholding the self-determination of Indigenous communities. We also underscore that FCAs should not be seen as a permanent solution. Preventing and reducing contaminants, including associated harm reduction in communities affected by FCAs, need to be priorities.},
	urldate = {2024-01-31},
	journal = {FACETS},
	author = {Lowitt, K. and Francis, A. and Gunther, L. and Madison, B.N. and McGaughey, L. and Echendu, A. and Kaur, M. and Roussel, K.A. and Pierre, Z. St and Weppler, A.},
	month = jan,
	year = {2024},
	note = {Publisher: Canadian Science Publishing},
	keywords = {Political Boundaries},
	pages = {1--11},
}

This paper examines fish consumption advisories (FCAs) as a site of transboundary governance in the Upper St Lawrence River with the aim of identifying opportunities for enhanced coordination and power sharing to address environmental injustices. The Upper St Lawrence River is part of the Great Lakes watershed of North America and the traditional territory of multiple Indigenous Nations, as well as the present-day jurisdictions of Ontario (Canada), Quebec (Canada), and New York State (USA). Through an analysis of publicly available information on FCA programs, we examine similarities and differences in these programs across jurisdictions. We find an overall lack of coordination in fish monitoring and differences in consumption advice for a waterway in which fish may easily move between transboundary areas. We offer recommendations for improving FCAs in this transboundary waterway from the lens of environmental justice, focusing on (1) a shared and transparent approach to monitoring contaminant levels and fish species; (2) integration of cultural food practices; (3) enhanced outreach to angler populations; and (4) upholding the self-determination of Indigenous communities. We also underscore that FCAs should not be seen as a permanent solution. Preventing and reducing contaminants, including associated harm reduction in communities affected by FCAs, need to be priorities.

@article{sanderfoot_hazardous_2024,
	title = {Hazardous wildfire smoke events can alter dawn soundscapes in dry forests of central and eastern {Washington}, {United} {States}},
	volume = {54},
	issn = {2351-9894},
	url = {https://www.sciencedirect.com/science/article/pii/S2351989424002488},
	doi = {10.1016/j.gecco.2024.e03044},
	abstract = {As global wildfire activity increases, wildlife are facing greater exposure to hazardous smoke pollution – with unknown consequences for biodiversity. Research on the effects of smoke on wild animals is extremely limited, in part due to the inherent logistical challenges of observing how animals respond to smoke in real time. Passive acoustic monitoring may be a powerful tool to safely and effectively monitor biodiversity before, during, and after major smoke events. In this study, we used data collected from a large-scale network of bioacoustic recorders at 92 sites in central and eastern Washington state during August–September, 2019–2020 to investigate the effect of wildfire smoke on dawn soundscapes and, by extension, acoustically active wildlife. We used acoustic indices to document and characterize changes in soundscapes related to smoke exposure, including the Acoustic Complexity Index (ACI), Bioacoustic Index (BI), and Normalized Difference Soundscape Index (NDSI). Higher values of these indices likely indicate higher levels of biodiversity in our study area. We hypothesized that wildfire smoke would reduce bird vocalizations, leading to declines in ACI, BI, and NDSI at dawn, when birds are most active. We used linear and quantile regression models to test for an effect of daily exposure to fine particulate matter (PM2.5), a marker of wildfire smoke, on the mean daily values and the upper 90th percentile of each index at dawn. We also conducted a before-during-after analysis of a particularly hazardous smoke event that impacted our study area on September 12–14, 2020. We did not observe linear effects of daily PM2.5 on average or peak daily values of acoustic indices; however, we did observe a significant reduction in ACI and BI during the three-day smoke event in 2020 and in the two weeks following this air pollution episode. Our results indicate that, on average, ACI and BI were reduced by 2.7 \% and 15.9 \% during and 1.5 \% and 11.0 \% afterward, respectively. These findings add further evidence that wildfire smoke alters soundscapes, likely due to changes in the presence, abundance, or behavior of acoustically active animals. Furthermore, our study demonstrates that wildfire smoke may have delayed and/or cumulative effects on acoustically active wildlife. Our study highlights the potential for passive acoustic monitoring to document wildlife responses to smoke pollution and identify potentially relevant exposure periods.},
	urldate = {2025-01-27},
	journal = {Global Ecology and Conservation},
	author = {Sanderfoot, Olivia V. and Tingley, Morgan W. and Bassing, Sarah B. and Vaughan, Joseph K. and June, Nicole A. and Gardner, Beth},
	month = oct,
	year = {2024},
	keywords = {NALCMS},
	pages = {e03044},
}

As global wildfire activity increases, wildlife are facing greater exposure to hazardous smoke pollution – with unknown consequences for biodiversity. Research on the effects of smoke on wild animals is extremely limited, in part due to the inherent logistical challenges of observing how animals respond to smoke in real time. Passive acoustic monitoring may be a powerful tool to safely and effectively monitor biodiversity before, during, and after major smoke events. In this study, we used data collected from a large-scale network of bioacoustic recorders at 92 sites in central and eastern Washington state during August–September, 2019–2020 to investigate the effect of wildfire smoke on dawn soundscapes and, by extension, acoustically active wildlife. We used acoustic indices to document and characterize changes in soundscapes related to smoke exposure, including the Acoustic Complexity Index (ACI), Bioacoustic Index (BI), and Normalized Difference Soundscape Index (NDSI). Higher values of these indices likely indicate higher levels of biodiversity in our study area. We hypothesized that wildfire smoke would reduce bird vocalizations, leading to declines in ACI, BI, and NDSI at dawn, when birds are most active. We used linear and quantile regression models to test for an effect of daily exposure to fine particulate matter (PM2.5), a marker of wildfire smoke, on the mean daily values and the upper 90th percentile of each index at dawn. We also conducted a before-during-after analysis of a particularly hazardous smoke event that impacted our study area on September 12–14, 2020. We did not observe linear effects of daily PM2.5 on average or peak daily values of acoustic indices; however, we did observe a significant reduction in ACI and BI during the three-day smoke event in 2020 and in the two weeks following this air pollution episode. Our results indicate that, on average, ACI and BI were reduced by 2.7 % and 15.9 % during and 1.5 % and 11.0 % afterward, respectively. These findings add further evidence that wildfire smoke alters soundscapes, likely due to changes in the presence, abundance, or behavior of acoustically active animals. Furthermore, our study demonstrates that wildfire smoke may have delayed and/or cumulative effects on acoustically active wildlife. Our study highlights the potential for passive acoustic monitoring to document wildlife responses to smoke pollution and identify potentially relevant exposure periods.

@article{youngmann_high_2024,
	title = {High {Genetic} {Diversity} and {Low} {Differentiation} in {Colonized} {Coyote} {Populations} {Across} {South} {Carolina}},
	volume = {23},
	issn = {1528-7092, 1938-5412},
	url = {https://bioone.org/journals/southeastern-naturalist/volume-23/issue-3/058.023.0307/High-Genetic-Diversity-and-Low-Differentiation-in-Colonized-Coyote-Populations/10.1656/058.023.0307.full},
	doi = {10.1656/058.023.0307},
	abstract = {Canis latrans (Coyote) is a highly mobile, generalist species that occupies a wide variety of habitats and ecoregions across North and Central America. Assessments of population genetic diversity and structure among the recently colonized populations of Coyotes in the eastern US have been conducted at broad spatial scales, revealing genetic structure concordant with immigration routes and high genetic diversity, or at local spatial scales, usually finding genetic panmixia. However, few studies have assessed eastern Coyote genetics at an intermediate spatial scale (i.e., state-level), which may be commensurate with the population dynamics of this mobile animal. We sampled 10 study areas across South Carolina during summer 2019–2020 using noninvasive genetic sampling and 10 microsatellite loci to identify individuals. We assessed genetic diversity and pairwise relatedness as well as genetic structure across our populations to determine whether there were landscape-level differences in genetic differentiation and the scale of Coyote population structure across the state. We found high levels of observed heterozygosity (0.599–0.872) and allelic richness (3.99–5.12) across our sites but low levels of relatedness. We observed low genetic differentiation (pairwise F ST = 0.010–0.066) and insignificant isolation by distance with limited evidence of genetic structure. Coyote populations seem to be operating at a spatial extent greater than South Carolina, and gene flow is likely maintained by unrelated, transient individuals. Future research and management of Coyotes in the heterogeneous landscapes of the southeastern US should account for the geographic scale that populations encompass.},
	number = {3},
	urldate = {2025-01-27},
	journal = {Southeastern Naturalist},
	author = {Youngmann, Jordan L. and Lance, Stacey L. and Kilgo, John C. and Ruth, Charles and Cantrell, Jay and D'Angelo, Gino J.},
	month = aug,
	year = {2024},
	note = {Publisher: Eagle Hill Institute},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {366--384},
}

Canis latrans (Coyote) is a highly mobile, generalist species that occupies a wide variety of habitats and ecoregions across North and Central America. Assessments of population genetic diversity and structure among the recently colonized populations of Coyotes in the eastern US have been conducted at broad spatial scales, revealing genetic structure concordant with immigration routes and high genetic diversity, or at local spatial scales, usually finding genetic panmixia. However, few studies have assessed eastern Coyote genetics at an intermediate spatial scale (i.e., state-level), which may be commensurate with the population dynamics of this mobile animal. We sampled 10 study areas across South Carolina during summer 2019–2020 using noninvasive genetic sampling and 10 microsatellite loci to identify individuals. We assessed genetic diversity and pairwise relatedness as well as genetic structure across our populations to determine whether there were landscape-level differences in genetic differentiation and the scale of Coyote population structure across the state. We found high levels of observed heterozygosity (0.599–0.872) and allelic richness (3.99–5.12) across our sites but low levels of relatedness. We observed low genetic differentiation (pairwise F ST = 0.010–0.066) and insignificant isolation by distance with limited evidence of genetic structure. Coyote populations seem to be operating at a spatial extent greater than South Carolina, and gene flow is likely maintained by unrelated, transient individuals. Future research and management of Coyotes in the heterogeneous landscapes of the southeastern US should account for the geographic scale that populations encompass.

@article{lauriault_influence_2024,
	title = {Influence of {Grazing} on {Canola} {Grain}, {Canola} {Forage} {Yield}, and {Beef} {Cattle} {Performance}},
	volume = {14},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {2076-2615},
	url = {https://www.mdpi.com/2076-2615/14/3/371},
	doi = {10.3390/ani14030371},
	abstract = {Interest is increasing in grazing winter canola (Brassica napus) as an alternative crop in winter wheat (Triticum aestivum) rotations in the Southern High Plains (SHP) of the USA and similar environments. In this stidy, winter cereal rye (Secale cereale) and winter canola pastures (forage) were compared for two winter growing seasons at New Mexico State University’s Rex E. Kirksey Agricultural Science Center at Tucumcari, NM, USA, to determine the relative effect of pasture type on late-gestation beef cows and growing yearling cattle, along with the effect of grazing on canola grain production. Canola grain yields were reduced by 25\% when canola was grazed until removal approximately one month after grazing was initiated, but before the onset of rapid regrowth after winter (641 vs. 486 kg grain ha−1 for never grazed or grazed canola, respectively, p {\textless} 0.0256). No differences existed for forage mass, nutritive value, or animal performance, although forage mineral composition of canola could be a concern. Grazing winter canola as a dual-purpose crop in the SHP and similar environments is feasible when proper grazing management is applied; producers should anticipate a 20–25\% reduction in grain yield, but expect animal gains to offset that loss.},
	language = {en},
	number = {3},
	urldate = {2024-01-31},
	journal = {Animals},
	author = {Lauriault, Leonard M. and Angadi, Sangu V. and Duff, Glenn C. and Scholljegerdes, Eric J. and Darapuneni, Murali K. and Martinez, Gasper K.},
	month = jan,
	year = {2024},
	note = {Number: 3
Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {Climate Zones},
	pages = {371},
}

Interest is increasing in grazing winter canola (Brassica napus) as an alternative crop in winter wheat (Triticum aestivum) rotations in the Southern High Plains (SHP) of the USA and similar environments. In this stidy, winter cereal rye (Secale cereale) and winter canola pastures (forage) were compared for two winter growing seasons at New Mexico State University’s Rex E. Kirksey Agricultural Science Center at Tucumcari, NM, USA, to determine the relative effect of pasture type on late-gestation beef cows and growing yearling cattle, along with the effect of grazing on canola grain production. Canola grain yields were reduced by 25% when canola was grazed until removal approximately one month after grazing was initiated, but before the onset of rapid regrowth after winter (641 vs. 486 kg grain ha−1 for never grazed or grazed canola, respectively, p \textless 0.0256). No differences existed for forage mass, nutritive value, or animal performance, although forage mineral composition of canola could be a concern. Grazing winter canola as a dual-purpose crop in the SHP and similar environments is feasible when proper grazing management is applied; producers should anticipate a 20–25% reduction in grain yield, but expect animal gains to offset that loss.

@article{shao_invasion_2024,
	title = {Invasion dynamics of the {European} {Collared}-{Dove} in {North} {America} are explained by combined effects of habitat and climate},
	volume = {126},
	issn = {0010-5422},
	url = {https://doi.org/10.1093/ornithapp/duad052},
	doi = {10.1093/ornithapp/duad052},
	abstract = {Global biodiversity is increasingly threatened by the spread of invasive species. Understanding the mechanisms influencing the initial colonization and persistence of invaders is therefore needed if conservation actions are to prevent new invasions or strive to slow their spread. The Eurasian Collared-Dove (Streptopelia decaocto, EUCO) is one of the most successful avian invasive species in North America; however, to our knowledge, no study has simultaneously examined the role that climate-matching, human activity, directional propagation, and local density have in this invasion process. Our research expands upon a cellular-automata-based hierarchical model developed to assess directional invasion dynamics to further quantify the impacts of climate, elevation, and land cover type on the spread of EUCO in North America. Our results suggest that EUCO’s dispersal patterns can largely be explained by the effects of habitat, climate, and environmental conditions at different stages of the invasion process rather than some innate preferred north-westerly spread. Specifically, EUCO initially colonized warm and wet grassland habitats and tended to persist in urban areas. We also found that while EUCO were more likely to spread to the northeast of existing habitats, directional preference did not drive persistence and recolonization events. These findings highlight the importance of incorporating both neighborhood effects and environmental factors in the modelling of range-expanding species, adding to the toolset available to researchers to model invasive species spread. Further, our research demonstrates that historical records of invasive species occurrences can provide the data resources needed to disentangle the characteristics driving species invasion and enable predictions that are of critical importance to resource managers.• The Eurasian Collared-Dove is an invasive species in North America. Starting from the Bahamas in 1974, it has colonized much of the U.S. and Canada.• The Eurasian Collared-Dove tended to spread to the northwest, and previous studies suggested that this was due to an innate preference for this direction. However, these studies did not consider that this might also be explained by habitat selection.• We studied the Eurasian Collared-Dove’s range expansion using data from the Project Feeder Watch citizen science study. Our findings suggest that they prefer grasslands and thrive in areas with higher temperatures, more precipitation, and higher elevations, with little regard for direction.• These results add to our understanding of the invasion process of the Eurasian Collared-Dove in North America, and broadly highlight the importance of historical records to disentangle the characteristics driving species invasion that are important to resource managers. The new methods can also be applied to understand the spread of other invasive species.},
	number = {1},
	urldate = {2024-03-13},
	journal = {Ornithological Applications},
	author = {Shao, Yiran and Ethier, Danielle M and Bonner, Simon J},
	month = feb,
	year = {2024},
	keywords = {NALCMS},
	pages = {duad052},
}

Global biodiversity is increasingly threatened by the spread of invasive species. Understanding the mechanisms influencing the initial colonization and persistence of invaders is therefore needed if conservation actions are to prevent new invasions or strive to slow their spread. The Eurasian Collared-Dove (Streptopelia decaocto, EUCO) is one of the most successful avian invasive species in North America; however, to our knowledge, no study has simultaneously examined the role that climate-matching, human activity, directional propagation, and local density have in this invasion process. Our research expands upon a cellular-automata-based hierarchical model developed to assess directional invasion dynamics to further quantify the impacts of climate, elevation, and land cover type on the spread of EUCO in North America. Our results suggest that EUCO’s dispersal patterns can largely be explained by the effects of habitat, climate, and environmental conditions at different stages of the invasion process rather than some innate preferred north-westerly spread. Specifically, EUCO initially colonized warm and wet grassland habitats and tended to persist in urban areas. We also found that while EUCO were more likely to spread to the northeast of existing habitats, directional preference did not drive persistence and recolonization events. These findings highlight the importance of incorporating both neighborhood effects and environmental factors in the modelling of range-expanding species, adding to the toolset available to researchers to model invasive species spread. Further, our research demonstrates that historical records of invasive species occurrences can provide the data resources needed to disentangle the characteristics driving species invasion and enable predictions that are of critical importance to resource managers.• The Eurasian Collared-Dove is an invasive species in North America. Starting from the Bahamas in 1974, it has colonized much of the U.S. and Canada.• The Eurasian Collared-Dove tended to spread to the northwest, and previous studies suggested that this was due to an innate preference for this direction. However, these studies did not consider that this might also be explained by habitat selection.• We studied the Eurasian Collared-Dove’s range expansion using data from the Project Feeder Watch citizen science study. Our findings suggest that they prefer grasslands and thrive in areas with higher temperatures, more precipitation, and higher elevations, with little regard for direction.• These results add to our understanding of the invasion process of the Eurasian Collared-Dove in North America, and broadly highlight the importance of historical records to disentangle the characteristics driving species invasion that are important to resource managers. The new methods can also be applied to understand the spread of other invasive species.

@article{cole_land_2024,
	title = {Land conversion and lack of protection significantly reduce suitable wolf habitat amount and functional connectivity in the {Adirondack}-to-{Laurentians} ({A2L}) transboundary wildlife linkage},
	volume = {24},
	issn = {1436-378X},
	url = {https://doi.org/10.1007/s10113-024-02288-3},
	doi = {10.1007/s10113-024-02288-3},
	abstract = {The Adirondack-to-Laurentians (A2L) transboundary wildlife linkage connects wilderness areas in the northeastern United States with southeastern Canada. However, land conversion is putting wolf habitat amount and functional connectivity at risk. With the exception of protected areas, hunting and trapping of wolves and coyotes are permitted within the Québec and Ontario portions, while hunting and trapping coyotes are permitted within the New York portion where wolves have been extirpated. Thus, the fear of humans strongly influences wolf habitat selection in this region. We assessed the impact of land conversion on wolf habitat amount, habitat fragmentation, and functional connectivity in the A2L between 2000 and 2015 and identified potential suitable habitat patches and corridors for protection. Suitable habitat patch area decreased by 18,245 km2 (27\%), with losses of 28\% in the Québec portion, 95\% in the Ontario portion, but only 0.3\% in the New York portion. Habitat fragmentation, as measured by the effective mesh size, substantially increased in the Québec and Ontario portions, but only slightly in the New York portion. Functional connectivity significantly decreased, with mean distances and the cost of traveling these distances more than doubling. We propose nine recommendations centered on extensive habitat restoration and protected area expansion in the Québec and Ontario portions of the study area. Wolf recovery within the A2L will require collaborative and coordinated transboundary conservation and the protection of suitable habitat patches and corridors, or the legal protection of both wolves and coyotes within the suitable habitat patches and corridors, to ensure that wolves are not harvested as they disperse and colonize new locations.},
	language = {en},
	number = {3},
	urldate = {2024-08-23},
	journal = {Regional Environmental Change},
	author = {Cole, Jonathan R. and Cheveau, Marianne and Gallo, John A. and Kross, Angela and St-Laurent, Martin-Hugues and Jaeger, Jochen A. G.},
	month = aug,
	year = {2024},
	keywords = {Terrestrial Ecoregions},
	pages = {126},
}

The Adirondack-to-Laurentians (A2L) transboundary wildlife linkage connects wilderness areas in the northeastern United States with southeastern Canada. However, land conversion is putting wolf habitat amount and functional connectivity at risk. With the exception of protected areas, hunting and trapping of wolves and coyotes are permitted within the Québec and Ontario portions, while hunting and trapping coyotes are permitted within the New York portion where wolves have been extirpated. Thus, the fear of humans strongly influences wolf habitat selection in this region. We assessed the impact of land conversion on wolf habitat amount, habitat fragmentation, and functional connectivity in the A2L between 2000 and 2015 and identified potential suitable habitat patches and corridors for protection. Suitable habitat patch area decreased by 18,245 km2 (27%), with losses of 28% in the Québec portion, 95% in the Ontario portion, but only 0.3% in the New York portion. Habitat fragmentation, as measured by the effective mesh size, substantially increased in the Québec and Ontario portions, but only slightly in the New York portion. Functional connectivity significantly decreased, with mean distances and the cost of traveling these distances more than doubling. We propose nine recommendations centered on extensive habitat restoration and protected area expansion in the Québec and Ontario portions of the study area. Wolf recovery within the A2L will require collaborative and coordinated transboundary conservation and the protection of suitable habitat patches and corridors, or the legal protection of both wolves and coyotes within the suitable habitat patches and corridors, to ensure that wolves are not harvested as they disperse and colonize new locations.

@phdthesis{krebs_large-scale_2024,
	title = {Large-{Scale} {GIS}-{Modeling} of {Dog}-{Travois} {Transport} {Suitability} of {Landscapes} in {Western} {North} {America}},
	copyright = {http://rightsstatements.org/vocab/InC/1.0/},
	url = {https://repository.arizona.edu/handle/10150/675317},
	abstract = {This thesis analyzes actual and potential long-distance use of the dog-pulled travois in western North America by developing a Geographic Information Systems (GIS) suitability model. The travois, consisting of a wooden A-frame sled originally pulled by dogs and, later, horses, was widely used across the North American Great Plains to facilitate the transport of supplies and trade goods. However, the absence of archaeological evidence makes it difficult to evaluate imperfect ethnographic data and assess how widespread travois use was, or could have been, in ancient times. Historic and experimental data indicate several shortcomings to travois transport based on the terrain it is being used on and the mass and physiology of the dogs used to pull it. Archaeological, historical, and experimental accounts of travois performance are reviewed to model the topographical and ecological limitations of travois-assisted transport. Limitations include, but are not restricted to, the slope (terrain) over which travois can be hauled, the temperature at which the draft dogs become unproductive and overheat, and the effectiveness of travel over specific types of vegetation. GIS modeling is used to assess the large-scale suitability of terrain for travois travel based on these projected limiting factors, and to calculate least-cost paths between select locations on the Great Plains and Intermountain West. Finally, the models produced by these analyses are compared with existing research on travois use and long-distance exchange in the western US to assess concordance with current evidence, elucidate gaps in ethnographic data, and generate predications for regions of possible dog-facilitated travois use. Beyond the enhancement of the limited available ethnographic accounts, this exploratory thesis provides guidance for future investigations of domestic dog use; especially as a template for detailed site-level analyses of travois and dog use on the local landscape, identifying prospective areas for survey and excavation of further archaeological evidence, and refining the understanding of trade interactions and human-dog relationships within and beyond the Great Plains.},
	language = {en},
	urldate = {2024-11-20},
	author = {Krebs, Talon},
	year = {2024},
	note = {Accepted: 2024-09-22T06:01:32Z
Publisher: The University of Arizona.},
	keywords = {NALCMS},
}

This thesis analyzes actual and potential long-distance use of the dog-pulled travois in western North America by developing a Geographic Information Systems (GIS) suitability model. The travois, consisting of a wooden A-frame sled originally pulled by dogs and, later, horses, was widely used across the North American Great Plains to facilitate the transport of supplies and trade goods. However, the absence of archaeological evidence makes it difficult to evaluate imperfect ethnographic data and assess how widespread travois use was, or could have been, in ancient times. Historic and experimental data indicate several shortcomings to travois transport based on the terrain it is being used on and the mass and physiology of the dogs used to pull it. Archaeological, historical, and experimental accounts of travois performance are reviewed to model the topographical and ecological limitations of travois-assisted transport. Limitations include, but are not restricted to, the slope (terrain) over which travois can be hauled, the temperature at which the draft dogs become unproductive and overheat, and the effectiveness of travel over specific types of vegetation. GIS modeling is used to assess the large-scale suitability of terrain for travois travel based on these projected limiting factors, and to calculate least-cost paths between select locations on the Great Plains and Intermountain West. Finally, the models produced by these analyses are compared with existing research on travois use and long-distance exchange in the western US to assess concordance with current evidence, elucidate gaps in ethnographic data, and generate predications for regions of possible dog-facilitated travois use. Beyond the enhancement of the limited available ethnographic accounts, this exploratory thesis provides guidance for future investigations of domestic dog use; especially as a template for detailed site-level analyses of travois and dog use on the local landscape, identifying prospective areas for survey and excavation of further archaeological evidence, and refining the understanding of trade interactions and human-dog relationships within and beyond the Great Plains.

@misc{manitoba_natural_resources_and_northern_development_forestry_and_peatlands_branch_manitobas_2024,
	title = {Manitoba's {Five} {Year} {Report} on the {Status} of {Forestry}},
	url = {https://storymaps.arcgis.com/stories/217b32789dab4446a84e91b6447e5fc6},
	abstract = {April 2016 - March 2021},
	language = {en},
	urldate = {2024-09-13},
	journal = {ArcGIS StoryMaps},
	author = {{Manitoba Natural Resources and Northern Development; Forestry and Peatlands Branch}},
	month = jul,
	year = {2024},
	keywords = {NALCMS},
}

April 2016 - March 2021

@article{shanley_mapping_2024,
	title = {Mapping forest-based natural climate solutions},
	volume = {5},
	copyright = {2024 The Author(s)},
	issn = {2662-4435},
	url = {https://www.nature.com/articles/s43247-024-01678-z},
	doi = {10.1038/s43247-024-01678-z},
	abstract = {Natural climate solutions are critical actions of ecosystem stewardship to mitigate climate change. However, prioritizing locations and possible actions is challenging. We demonstrate a generalizable approach for identifying potential opportunities for natural climate solutions by creating a spatial hierarchy of land management restrictions. Global forest carbon stocks and flux models were then used to explore forest-based natural climate solutions in the high-carbon density coastal temperate rainforests of western North America. Our results show 13 million hectares are available for action, an area that holds 4,900 ± 640 megatonnes of carbon dioxide equivalent and represents 45\% of regional and 0.5\% of global aboveground forest carbon stocks. Based on historical trends, a 10\% reduction in average annual forest carbon loss through improved forest management and conservation could reduce forest carbon emissions by 9.1 megatonnes of carbon dioxide equivalent per year, corresponding to 5.2\% of the 2030 land-based climate commitments made by the United States and Canada. Large-scale implementation of natural climate solutions will require collaborative planning with forest-dependent communities, industry, governments, and Indigenous peoples.},
	language = {en},
	number = {1},
	urldate = {2024-09-13},
	journal = {Communications Earth \& Environment},
	author = {Shanley, Colin S. and Graves, Rose A. and Drever, C. Ronnie and Schindel, Michael and Robertson, James C. and Case, Michael J. and Biswas, Tanushree},
	month = sep,
	year = {2024},
	note = {Publisher: Nature Publishing Group},
	keywords = {NALCMS},
	pages = {1--12},
}

Natural climate solutions are critical actions of ecosystem stewardship to mitigate climate change. However, prioritizing locations and possible actions is challenging. We demonstrate a generalizable approach for identifying potential opportunities for natural climate solutions by creating a spatial hierarchy of land management restrictions. Global forest carbon stocks and flux models were then used to explore forest-based natural climate solutions in the high-carbon density coastal temperate rainforests of western North America. Our results show 13 million hectares are available for action, an area that holds 4,900 ± 640 megatonnes of carbon dioxide equivalent and represents 45% of regional and 0.5% of global aboveground forest carbon stocks. Based on historical trends, a 10% reduction in average annual forest carbon loss through improved forest management and conservation could reduce forest carbon emissions by 9.1 megatonnes of carbon dioxide equivalent per year, corresponding to 5.2% of the 2030 land-based climate commitments made by the United States and Canada. Large-scale implementation of natural climate solutions will require collaborative planning with forest-dependent communities, industry, governments, and Indigenous peoples.

@article{wang_mapping_2024,
	title = {Mapping the distance between fire hazard and disaster for communities in {Canadian} forests},
	volume = {30},
	copyright = {Global Change Biology© 2024 His Majesty the King in Right of Canada and The Authors. Global Change Biology published by John Wiley \& Sons Ltd.  Reproduced with the permission of the Minister of Natural Resources Canada.},
	issn = {1365-2486},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/gcb.17221},
	doi = {10.1111/gcb.17221},
	abstract = {Communities interspersed throughout the Canadian wildland are threatened by fires that have become bigger and more frequent in some parts of the country in recent decades. Identifying the fireshed (source area) and pathways from which wildland fire may ignite and spread from the landscape to a community is crucial for risk-reduction strategy and planning. We used outputs from a fire simulation model, including fire polygons and rate of spread, to map firesheds, fire pathways and corridors and spread distances for 1980 communities in the forested areas of Canada. We found fireshed sizes are larger in the north, where the mean distances between ecumene and fireshed perimeters were greater than 10 km. The Rayleigh Z test indicated that simulated fires around a large proportion of communities show significant directional trends, and these trends are stronger in the Boreal Plains and Shields than in the Rocky Mountain area. The average distance from which fire, when spreading at the maximum simulated rate, could reach the community perimeter was approximately 5, 12 and 18 km in 1, 2 and 3 days, respectively. The average daily spread distances increased latitudinally, from south to north. Spread distances were the shortest in the Pacific Maritime, Atlantic Maritime and Boreal Plains Ecozones, implying lower rates of spread compared to the rest of the country. The fire corridors generated from random ignitions and from ignitions predicted from local fire history differ, indicating that factors other than fuel (e.g. fire weather, ignition pattern) play a significant role in determining the direction that fires burn into a community.},
	language = {en},
	number = {3},
	urldate = {2024-03-13},
	journal = {Global Change Biology},
	author = {Wang, Xianli and Swystun, Tom and McFayden, Colin B. and Erni, Sandy and Oliver, Jacqueline and Taylor, Stephen W. and Flannigan, Mike D.},
	year = {2024},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/gcb.17221},
	keywords = {NALCMS},
	pages = {e17221},
}

Communities interspersed throughout the Canadian wildland are threatened by fires that have become bigger and more frequent in some parts of the country in recent decades. Identifying the fireshed (source area) and pathways from which wildland fire may ignite and spread from the landscape to a community is crucial for risk-reduction strategy and planning. We used outputs from a fire simulation model, including fire polygons and rate of spread, to map firesheds, fire pathways and corridors and spread distances for 1980 communities in the forested areas of Canada. We found fireshed sizes are larger in the north, where the mean distances between ecumene and fireshed perimeters were greater than 10 km. The Rayleigh Z test indicated that simulated fires around a large proportion of communities show significant directional trends, and these trends are stronger in the Boreal Plains and Shields than in the Rocky Mountain area. The average distance from which fire, when spreading at the maximum simulated rate, could reach the community perimeter was approximately 5, 12 and 18 km in 1, 2 and 3 days, respectively. The average daily spread distances increased latitudinally, from south to north. Spread distances were the shortest in the Pacific Maritime, Atlantic Maritime and Boreal Plains Ecozones, implying lower rates of spread compared to the rest of the country. The fire corridors generated from random ignitions and from ignitions predicted from local fire history differ, indicating that factors other than fuel (e.g. fire weather, ignition pattern) play a significant role in determining the direction that fires burn into a community.

@article{browning_measuring_2024,
	title = {Measuring the 3-30-300 rule to help cities meet nature access thresholds},
	volume = {907},
	issn = {0048-9697},
	url = {https://www.sciencedirect.com/science/article/pii/S0048969723063660},
	doi = {10.1016/j.scitotenv.2023.167739},
	abstract = {The 3-30-300 rule offers benchmarks for cities to promote equitable nature access. It dictates that individuals should see three trees from their dwelling, have 30 \% tree canopy in their neighborhood, and live within 300 m of a high-quality green space. Implementing this demands thorough measurement, monitoring, and evaluation methods, yet little guidance is currently available to pursue these actions. To overcome this gap, we employed an expert-based consensus approach to review the available ways to measure 3-30-300 as well as each measure's strengths and weaknesses. We described seven relevant data and processes: vegetation indices, street level analyses, tree inventories, questionnaires, window view analyses, land cover maps, and green space maps. Based on the reviewed strengths and weaknesses of each measure, we presented a suitability matrix to link recommended measures with each component of the rule. These recommendations included surveys and window-view analyses for the ‘3 component’, high-resolution land cover maps for the ‘30 component’, and green space maps with network analyses for the ‘300 component’. These methods, responsive to local situations and resources, not only implement the 3-30-300 rule but foster broader dialogue on local desires and requirements. Consequently, these techniques can guide strategic investments in urban greening for health, equity, biodiversity, and climate adaptation.},
	urldate = {2023-11-24},
	journal = {Science of The Total Environment},
	author = {Browning, M. H. E. M. and Locke, D. H. and Konijnendijk, C. and Labib, S. M. and Rigolon, A. and Yeager, R. and Bardhan, M. and Berland, A. and Dadvand, P. and Helbich, M. and Li, F. and Li, H. and James, P. and Klompmaker, J. and Reuben, A. and Roman, L. A. and Tsai, W. -L. and Patwary, M. and O'Neil-Dunne, J. and Ossola, A. and Wang, R. and Yang, B. and Yi, L. and Zhang, J. and Nieuwenhuijsen, M.},
	month = jan,
	year = {2024},
	keywords = {NALCMS},
	pages = {167739},
}

The 3-30-300 rule offers benchmarks for cities to promote equitable nature access. It dictates that individuals should see three trees from their dwelling, have 30 % tree canopy in their neighborhood, and live within 300 m of a high-quality green space. Implementing this demands thorough measurement, monitoring, and evaluation methods, yet little guidance is currently available to pursue these actions. To overcome this gap, we employed an expert-based consensus approach to review the available ways to measure 3-30-300 as well as each measure's strengths and weaknesses. We described seven relevant data and processes: vegetation indices, street level analyses, tree inventories, questionnaires, window view analyses, land cover maps, and green space maps. Based on the reviewed strengths and weaknesses of each measure, we presented a suitability matrix to link recommended measures with each component of the rule. These recommendations included surveys and window-view analyses for the ‘3 component’, high-resolution land cover maps for the ‘30 component’, and green space maps with network analyses for the ‘300 component’. These methods, responsive to local situations and resources, not only implement the 3-30-300 rule but foster broader dialogue on local desires and requirements. Consequently, these techniques can guide strategic investments in urban greening for health, equity, biodiversity, and climate adaptation.

@techreport{qiu_mortality_2024,
	type = {Working {Paper}},
	title = {Mortality {Burden} {From} {Wildfire} {Smoke} {Under} {Climate} {Change}},
	url = {https://www.nber.org/papers/w32307},
	abstract = {Wildfire activity has increased in the US and is projected to accelerate under future climate change. However, our understanding of the impacts of climate change on wildfire smoke and health remains highly uncertain. We quantify the past and future mortality burden in the US due to wildfire smoke fine particulate matter (PM2.5). We construct an ensemble of statistical and machine learning models that link variation in climate to wildfire smoke PM2.5, and empirically estimate smoke PM2.5-mortality relationships using georeferenced data on all recorded deaths in the US from 2006 to 2019. We project that climate-driven increases in future smoke PM2.5 could result in 27,800 excess deaths per year by 2050 under a high warming scenario, a 76\% increase relative to estimated 2011-2020 averages. Cumulative excess deaths from wildfire smoke PM2.5 could exceed 700,000 between 2025-2055. When monetized, climate-induced smoke deaths result in annual damages of \$244 billion by mid-century, comparable to the estimated sum of all other damages in the US in prior analyses. Our research suggests that the health cost of climate-driven wildfire smoke could be among the most important and costly consequences of a warming climate in the US.},
	number = {32307},
	urldate = {2024-06-03},
	institution = {National Bureau of Economic Research},
	author = {Qiu, Minghao and Li, Jessica and Gould, Carlos F. and Jing, Renzhi and Kelp, Makoto and Childs, Marissa and Kiang, Mathew and Heft-Neal, Sam and Diffenbaugh, Noah and Burke, Marshall},
	month = apr,
	year = {2024},
	doi = {10.3386/w32307},
	keywords = {NALCMS},
}

Wildfire activity has increased in the US and is projected to accelerate under future climate change. However, our understanding of the impacts of climate change on wildfire smoke and health remains highly uncertain. We quantify the past and future mortality burden in the US due to wildfire smoke fine particulate matter (PM2.5). We construct an ensemble of statistical and machine learning models that link variation in climate to wildfire smoke PM2.5, and empirically estimate smoke PM2.5-mortality relationships using georeferenced data on all recorded deaths in the US from 2006 to 2019. We project that climate-driven increases in future smoke PM2.5 could result in 27,800 excess deaths per year by 2050 under a high warming scenario, a 76% increase relative to estimated 2011-2020 averages. Cumulative excess deaths from wildfire smoke PM2.5 could exceed 700,000 between 2025-2055. When monetized, climate-induced smoke deaths result in annual damages of $244 billion by mid-century, comparable to the estimated sum of all other damages in the US in prior analyses. Our research suggests that the health cost of climate-driven wildfire smoke could be among the most important and costly consequences of a warming climate in the US.

@phdthesis{lee_multi-scale_2024,
	title = {Multi-scale {Patterns} of {Breeding} {Habitat} {Selection} in {Sandhill} {Cranes} {Across} {Canada}’s {Eastern} {Boreal} {Forest}},
	url = {http://hdl.handle.net/10012/20665},
	abstract = {The boreal forest of Canada serves as a critical breeding ground for numerous waterbird species, including sandhill cranes (Antigone canadensis). As sandhill cranes continue to expand their range in the boreal forest, it becomes increasingly important to identify habitat characteristics essential for breeding sandhill cranes for effective conservation and management. Limited research exists regarding the habitat dynamics of breeding sandhill cranes across this vast and remote landscape, necessitating research to understand spatial drivers of territory selection and habitat use in the boreal forest. Using high-resolution satellite telemetry data, we quantified the effects of land cover and land use on breeding habitat selection of sandhill cranes in the boreal forest of Ontario and Quebec, Canada across different scales: the landscape level (i.e., second order selection, which considers the overall landscape within which territories are established) and within the breeding range (i.e., third order selection, which focuses on specific habitat features selected within these territories). At the second order, or landscape level, sandhill cranes established breeding territories containing greater proportions of cropland, recently disturbed areas (e.g., forest cutblocks and burned areas), and wetlands. Sandhill cranes also selected territories with lower proportions of forest, open habitat, and water. At third order, or within their breeding ranges, sandhill cranes selected cropland, wetlands, recently disturbed areas, open habitat, and water, while avoiding forests and urban areas. Our findings suggest that current levels of anthropogenic disturbance do not negatively affect sandhill crane habitat selection, and that wetlands continue to play a crucial role in breeding habitat selection in the boreal forest. However, further research is required to explore the detailed impacts of forestry operations and the selection of recently disturbed areas on breeding behaviour and nest success in sandhill cranes. Our findings highlight the importance of using multi-scale approaches in habitat selection analyses that consider both broad ecological scales and the specific habitat requirements of individuals at the local scale. By comparing habitat use across both landscape and local scales, we demonstrate how sandhill cranes adapt their breeding habitat selection based on the availability and quality of different habitat types, allowing for robust inferences on the mechanisms that drive patterns of habitat selection both within their breeding territories and across the broader landscape. Collectively, this research contributes to the growing body of literature on breeding habitat selection of sandhill cranes, addressing important questions concerning patterns of habitat selection in response to a gradient of land cover and land uses classes in the boreal forest. Findings from this research can be applied to land management practices and assist managers when making inferences about sandhill crane habitat use in the boreal forest. Overall, this empirical approach can also be applied to a variety of species across diverse landscapes to assess how ecological processes differentiate across spatial scales and can support large-scale conservation efforts that ultimately benefits sandhill crane populations and biodiversity conservation in the boreal forest and beyond.},
	language = {en},
	urldate = {2024-08-12},
	author = {Lee, Kiaunna},
	month = jun,
	year = {2024},
	note = {Publisher: University of Waterloo},
	keywords = {NALCMS},
}

The boreal forest of Canada serves as a critical breeding ground for numerous waterbird species, including sandhill cranes (Antigone canadensis). As sandhill cranes continue to expand their range in the boreal forest, it becomes increasingly important to identify habitat characteristics essential for breeding sandhill cranes for effective conservation and management. Limited research exists regarding the habitat dynamics of breeding sandhill cranes across this vast and remote landscape, necessitating research to understand spatial drivers of territory selection and habitat use in the boreal forest. Using high-resolution satellite telemetry data, we quantified the effects of land cover and land use on breeding habitat selection of sandhill cranes in the boreal forest of Ontario and Quebec, Canada across different scales: the landscape level (i.e., second order selection, which considers the overall landscape within which territories are established) and within the breeding range (i.e., third order selection, which focuses on specific habitat features selected within these territories). At the second order, or landscape level, sandhill cranes established breeding territories containing greater proportions of cropland, recently disturbed areas (e.g., forest cutblocks and burned areas), and wetlands. Sandhill cranes also selected territories with lower proportions of forest, open habitat, and water. At third order, or within their breeding ranges, sandhill cranes selected cropland, wetlands, recently disturbed areas, open habitat, and water, while avoiding forests and urban areas. Our findings suggest that current levels of anthropogenic disturbance do not negatively affect sandhill crane habitat selection, and that wetlands continue to play a crucial role in breeding habitat selection in the boreal forest. However, further research is required to explore the detailed impacts of forestry operations and the selection of recently disturbed areas on breeding behaviour and nest success in sandhill cranes. Our findings highlight the importance of using multi-scale approaches in habitat selection analyses that consider both broad ecological scales and the specific habitat requirements of individuals at the local scale. By comparing habitat use across both landscape and local scales, we demonstrate how sandhill cranes adapt their breeding habitat selection based on the availability and quality of different habitat types, allowing for robust inferences on the mechanisms that drive patterns of habitat selection both within their breeding territories and across the broader landscape. Collectively, this research contributes to the growing body of literature on breeding habitat selection of sandhill cranes, addressing important questions concerning patterns of habitat selection in response to a gradient of land cover and land uses classes in the boreal forest. Findings from this research can be applied to land management practices and assist managers when making inferences about sandhill crane habitat use in the boreal forest. Overall, this empirical approach can also be applied to a variety of species across diverse landscapes to assess how ecological processes differentiate across spatial scales and can support large-scale conservation efforts that ultimately benefits sandhill crane populations and biodiversity conservation in the boreal forest and beyond.

@article{prevey_non-native_2024,
	title = {Non-native plant invasion after fire in western {USA} varies by functional type and with climate},
	issn = {1573-1464},
	url = {https://doi.org/10.1007/s10530-023-03235-9},
	doi = {10.1007/s10530-023-03235-9},
	abstract = {Invasions by non-native plant species after fire can negatively affect important ecosystem services and lead to invasion-fire cycles that further degrade ecosystems. The relationship between fire and plant invasion is complex, and the risk of invasion varies greatly between functional types and across geographic scales. Here, we examined patterns and predictors of non-native plant invasion following fire across the western United States. We specifically analyzed how the abundance of non-native plants after fire was related to fire characteristics and environmental conditions, such as climate, soil, and topography, in 26,729 vegetation plots from government networks and individual studies. Non-native plant cover was higher in plots measured after wildfires compared to prescribed burns or unburned plots. The post-fire cover of non-native species varied by plant functional type, and only the cover of short-lived (i.e., annual and biennial) forbs and short-lived C3 grasses was significantly higher in burned plots compared to unburned plots. Cool-season short-lived grasses composed most of the non-native post-fire vegetation, with cheatgrass (Bromus tectorum) being the most recorded species in the dataset. Climate variables were the most influential predictors of the cover of non-native short-lived grasses and forbs after fires, with invasion being more common in areas with drier summers and a higher proportion of yearly precipitation falling in October through March. Models using future projected climate for mid (2041–2070) and end (2071–2100) of century showed a potential for increasing post-fire invasion risk at higher elevations and latitudes. These findings highlight priorities for mitigation, monitoring, and restoration efforts to reduce post-fire plant invasion risk across the western United States.},
	language = {en},
	urldate = {2024-03-11},
	journal = {Biological Invasions},
	author = {Prevéy, Janet S. and Jarnevich, Catherine S. and Pearse, Ian S. and Munson, Seth M. and Stevens, Jens T. and Barrett, Kevin J. and Coop, Jonathan D. and Day, Michelle A. and Firmage, David and Fornwalt, Paula J. and Haynes, Katharine M. and Johnston, James D. and Kerns, Becky K. and Krawchuk, Meg A. and Miller, Becky A. and Nietupski, Ty C. and Roque, Jacquilyn and Springer, Judith D. and Stevens-Rumann, Camille S. and Stoddard, Michael T. and Tortorelli, Claire M.},
	month = feb,
	year = {2024},
	keywords = {NALCMS},
}

Invasions by non-native plant species after fire can negatively affect important ecosystem services and lead to invasion-fire cycles that further degrade ecosystems. The relationship between fire and plant invasion is complex, and the risk of invasion varies greatly between functional types and across geographic scales. Here, we examined patterns and predictors of non-native plant invasion following fire across the western United States. We specifically analyzed how the abundance of non-native plants after fire was related to fire characteristics and environmental conditions, such as climate, soil, and topography, in 26,729 vegetation plots from government networks and individual studies. Non-native plant cover was higher in plots measured after wildfires compared to prescribed burns or unburned plots. The post-fire cover of non-native species varied by plant functional type, and only the cover of short-lived (i.e., annual and biennial) forbs and short-lived C3 grasses was significantly higher in burned plots compared to unburned plots. Cool-season short-lived grasses composed most of the non-native post-fire vegetation, with cheatgrass (Bromus tectorum) being the most recorded species in the dataset. Climate variables were the most influential predictors of the cover of non-native short-lived grasses and forbs after fires, with invasion being more common in areas with drier summers and a higher proportion of yearly precipitation falling in October through March. Models using future projected climate for mid (2041–2070) and end (2071–2100) of century showed a potential for increasing post-fire invasion risk at higher elevations and latitudes. These findings highlight priorities for mitigation, monitoring, and restoration efforts to reduce post-fire plant invasion risk across the western United States.

@article{wi_need_2024,
	title = {On the need for physical constraints in deep learning rainfall–runoff projections under climate change: a sensitivity analysis to warming and shifts in potential evapotranspiration},
	volume = {28},
	issn = {1027-5606},
	shorttitle = {On the need for physical constraints in deep learning rainfall–runoff projections under climate change},
	url = {https://hess.copernicus.org/articles/28/479/2024/},
	doi = {10.5194/hess-28-479-2024},
	abstract = {Deep learning (DL) rainfall–runoff models outperform conceptual, process-based models in a range of applications. However, it remains unclear whether DL models can produce physically plausible projections of streamflow under climate change. We investigate this question through a sensitivity analysis of modeled responses to increases in temperature and potential evapotranspiration (PET), with other meteorological variables left unchanged. Previous research has shown that temperature-based PET methods overestimate evaporative water loss under warming compared with energy budget-based PET methods. We therefore assume that reliable streamflow responses to warming should exhibit less evaporative water loss when forced with smaller, energy-budget-based PET compared with temperature-based PET. We conduct this assessment using three conceptual, process-based rainfall–runoff models and three DL models, trained and tested across 212 watersheds in the Great Lakes basin. The DL models include a Long Short-Term Memory network (LSTM), a mass-conserving LSTM (MC-LSTM), and a novel variant of the MC-LSTM that also respects the relationship between PET and evaporative water loss (MC-LSTM-PET). After validating models against historical streamflow and actual evapotranspiration, we force all models with scenarios of warming, historical precipitation, and both temperature-based (Hamon) and energy-budget-based (Priestley–Taylor) PET, and compare their responses in long-term mean daily flow, low flows, high flows, and seasonal streamflow timing. We also explore similar responses using a national LSTM fit to 531 watersheds across the United States to assess how the inclusion of a larger and more diverse set of basins influences signals of hydrological response under warming. The main results of this study are as follows:

   The three Great Lakes DL models substantially outperform all process-based models in streamflow estimation. The MC-LSTM-PET also matches the best process-based models and outperforms the MC-LSTM in estimating actual evapotranspiration.

   All process-based models show a downward shift in long-term mean daily flows under warming, but median shifts are considerably larger under temperature-based PET (−17 \% to −25 \%) than energy-budget-based PET (−6 \% to −9 \%). The MC-LSTM-PET model exhibits similar differences in water loss across the different PET forcings. Conversely, the LSTM exhibits unrealistically large water losses under warming using Priestley–Taylor PET (−20 \%), while the MC-LSTM is relatively insensitive to the PET method.

   DL models exhibit smaller changes in high flows and seasonal timing of flows as compared with the process-based models, while DL estimates of low flows are within the range estimated by the process-based models.

   Like the Great Lakes LSTM, the national LSTM also shows unrealistically large water losses under warming (−25 \%), but it is more stable when many inputs are changed under warming and better aligns with process-based model responses for seasonal timing of flows.

   Ultimately, the results of this sensitivity analysis suggest that physical considerations regarding model architecture and input variables may be necessary to promote the physical realism of deep-learning-based hydrological projections under climate change.},
	language = {English},
	number = {3},
	urldate = {2024-03-11},
	journal = {Hydrology and Earth System Sciences},
	author = {Wi, Sungwook and Steinschneider, Scott},
	month = feb,
	year = {2024},
	note = {Publisher: Copernicus GmbH},
	keywords = {NALCMS},
	pages = {479--503},
}

Deep learning (DL) rainfall–runoff models outperform conceptual, process-based models in a range of applications. However, it remains unclear whether DL models can produce physically plausible projections of streamflow under climate change. We investigate this question through a sensitivity analysis of modeled responses to increases in temperature and potential evapotranspiration (PET), with other meteorological variables left unchanged. Previous research has shown that temperature-based PET methods overestimate evaporative water loss under warming compared with energy budget-based PET methods. We therefore assume that reliable streamflow responses to warming should exhibit less evaporative water loss when forced with smaller, energy-budget-based PET compared with temperature-based PET. We conduct this assessment using three conceptual, process-based rainfall–runoff models and three DL models, trained and tested across 212 watersheds in the Great Lakes basin. The DL models include a Long Short-Term Memory network (LSTM), a mass-conserving LSTM (MC-LSTM), and a novel variant of the MC-LSTM that also respects the relationship between PET and evaporative water loss (MC-LSTM-PET). After validating models against historical streamflow and actual evapotranspiration, we force all models with scenarios of warming, historical precipitation, and both temperature-based (Hamon) and energy-budget-based (Priestley–Taylor) PET, and compare their responses in long-term mean daily flow, low flows, high flows, and seasonal streamflow timing. We also explore similar responses using a national LSTM fit to 531 watersheds across the United States to assess how the inclusion of a larger and more diverse set of basins influences signals of hydrological response under warming. The main results of this study are as follows: The three Great Lakes DL models substantially outperform all process-based models in streamflow estimation. The MC-LSTM-PET also matches the best process-based models and outperforms the MC-LSTM in estimating actual evapotranspiration. All process-based models show a downward shift in long-term mean daily flows under warming, but median shifts are considerably larger under temperature-based PET (−17 % to −25 %) than energy-budget-based PET (−6 % to −9 %). The MC-LSTM-PET model exhibits similar differences in water loss across the different PET forcings. Conversely, the LSTM exhibits unrealistically large water losses under warming using Priestley–Taylor PET (−20 %), while the MC-LSTM is relatively insensitive to the PET method. DL models exhibit smaller changes in high flows and seasonal timing of flows as compared with the process-based models, while DL estimates of low flows are within the range estimated by the process-based models. Like the Great Lakes LSTM, the national LSTM also shows unrealistically large water losses under warming (−25 %), but it is more stable when many inputs are changed under warming and better aligns with process-based model responses for seasonal timing of flows. Ultimately, the results of this sensitivity analysis suggest that physical considerations regarding model architecture and input variables may be necessary to promote the physical realism of deep-learning-based hydrological projections under climate change.

@article{richter_opportunities_2024,
	title = {Opportunities for {Restoring} {Environmental} {Flows} in the {Rio} {Grande}–{Rio} {Bravo} {Basin} {Spanning} the {US}–{Mexico} {Border}},
	volume = {150},
	copyright = {This work is made available under the terms of the Creative Commons Attribution 4.0 International license, https://creativecommons.org/licenses/by/4.0/.},
	url = {https://ascelibrary.org/doi/10.1061/JWRMD5.WRENG-6278},
	doi = {10.1061/JWRMD5.WRENG-6278},
	abstract = {AbstractThe Rio Grande–Rio Bravo’s flow regime has been highly altered for more than 130\ years,
yet the river ecosystem still supports important biodiversity including numerous endangered
species. More than 80\% of water consumed in the basin goes to ...},
	language = {EN},
	number = {2},
	urldate = {2024-01-10},
	journal = {Journal of Water Resources Planning and Management},
	author = {Richter, Brian D. and Prunes, Enrique and Liu, Ning and Caldwell, Peter and Wei, Dongyang and Davis, Kyle Frankel and Sandoval-Solis, Samuel and Herrera, Gabriela Rendon and Rodriguez, Ramon Saiz and Ao, Yufei and Lamsal, Gambhir and Amaya, Maria and Shahbol, Natalie and Marston, Landon},
	month = feb,
	year = {2024},
	note = {Publisher: American Society of Civil Engineers},
	keywords = {NALCMS},
	pages = {04023079},
}

AbstractThe Rio Grande–Rio Bravo’s flow regime has been highly altered for more than 130 years, yet the river ecosystem still supports important biodiversity including numerous endangered species. More than 80% of water consumed in the basin goes to ...

@article{agboola_optimizing_2024,
	title = {Optimizing landslide susceptibility mapping using machine learning and geospatial techniques},
	volume = {81},
	issn = {1574-9541},
	url = {https://www.sciencedirect.com/science/article/pii/S1574954124001250},
	doi = {10.1016/j.ecoinf.2024.102583},
	abstract = {Landslides present a substantial risk to human lives, the environment, and infrastructure. Consequently, it is crucial to highlight the regions prone to future landslides by examining the correlation between past landslides and various geo-environmental factors. This study aims to investigate the optimal data selection and machine learning model, or ensemble technique, for evaluating the vulnerability of areas to landslides and determining the most accurate approach. To attain our objectives, we considered two different scenarios for selecting landslide-free random points (a slope threshold and a buffer-based approach) and performed a comparative analysis of five machine learning models for landslide susceptibility mapping, namely: Support Vector Machine (SVM), Logistic Regression (LR), Linear Discriminant Analysis (LDA), Random Forest (RF), and Extreme Gradient Boosting (XGBoost). The study area for this research is an area in Polk County in Western North Carolina that has experienced fatal landslides, leading to casualties and significant damage to infrastructure, properties, and road networks. The model construction process involves the utilization of a dataset comprising 1215 historical landslide occurrences and 1215 non-landslide points. We integrated a total of fourteen geospatial data layers, consisting of topographic variables, soil data, geological data, and land cover attributes. We use various metrics to assess the models' performance, including accuracy, F1-score, Kappa score, and AUC-ROC. In addition, we used the seeded-cell area index (SCAI) to evaluate map consistency. The ensemble of the five models using Weighted Average produces outstanding results, with an AUC-ROC of 99.4\% for the slope threshold scenario and 91.8\% for the buffer-based scenario. Our findings emphasize the significant impact of non-landslide random sampling on model performance in landslide susceptibility mapping. Furthermore, by optimally identifying landslide-prone regions and hotspots that need urgent risk management and land use planning, our study demonstrates the effectiveness of machine learning models in analyzing landslide susceptibility and providing valuable insights for informed decision-making and disaster risk reduction initiatives.},
	urldate = {2024-04-24},
	journal = {Ecological Informatics},
	author = {Agboola, Gazali and Beni, Leila Hashemi and Elbayoumi, Tamer and Thompson, Gary},
	month = jul,
	year = {2024},
	keywords = {NALCMS},
	pages = {102583},
}

Landslides present a substantial risk to human lives, the environment, and infrastructure. Consequently, it is crucial to highlight the regions prone to future landslides by examining the correlation between past landslides and various geo-environmental factors. This study aims to investigate the optimal data selection and machine learning model, or ensemble technique, for evaluating the vulnerability of areas to landslides and determining the most accurate approach. To attain our objectives, we considered two different scenarios for selecting landslide-free random points (a slope threshold and a buffer-based approach) and performed a comparative analysis of five machine learning models for landslide susceptibility mapping, namely: Support Vector Machine (SVM), Logistic Regression (LR), Linear Discriminant Analysis (LDA), Random Forest (RF), and Extreme Gradient Boosting (XGBoost). The study area for this research is an area in Polk County in Western North Carolina that has experienced fatal landslides, leading to casualties and significant damage to infrastructure, properties, and road networks. The model construction process involves the utilization of a dataset comprising 1215 historical landslide occurrences and 1215 non-landslide points. We integrated a total of fourteen geospatial data layers, consisting of topographic variables, soil data, geological data, and land cover attributes. We use various metrics to assess the models' performance, including accuracy, F1-score, Kappa score, and AUC-ROC. In addition, we used the seeded-cell area index (SCAI) to evaluate map consistency. The ensemble of the five models using Weighted Average produces outstanding results, with an AUC-ROC of 99.4% for the slope threshold scenario and 91.8% for the buffer-based scenario. Our findings emphasize the significant impact of non-landslide random sampling on model performance in landslide susceptibility mapping. Furthermore, by optimally identifying landslide-prone regions and hotspots that need urgent risk management and land use planning, our study demonstrates the effectiveness of machine learning models in analyzing landslide susceptibility and providing valuable insights for informed decision-making and disaster risk reduction initiatives.

@article{dunmall_pacific_2024,
	title = {Pacific salmon in the {Canadian} {Arctic} highlight a range-expansion pathway for sub-{Arctic} fishes},
	volume = {30},
	copyright = {© 2024 His Majesty the King in Right of Canada and The Author(s). Global Change Biology published by John Wiley \& Sons Ltd. Reproduced with the permission of the Minister of Fisheries and Oceans Canada.},
	issn = {1365-2486},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/gcb.17353},
	doi = {10.1111/gcb.17353},
	abstract = {Rapid climate change is altering Arctic ecosystems at unprecedented rates. These changes in the physical environment may open new corridors for species range expansions, with substantial implications for subsistence-dependent communities and sensitive ecosystems. Over the past 20 years, rising incidental harvest of Pacific salmon by subsistence fishers has been monitored across a widening range spanning multiple land claim jurisdictions in Arctic Canada. In this study, we connect Indigenous and scientific knowledges to explore potential oceanographic mechanisms facilitating this ongoing northward expansion of Pacific salmon into the western Canadian Arctic. A regression analysis was used to reveal and characterize a two-part mechanism related to thermal and sea-ice conditions in the Chukchi and Beaufort seas that explains nearly all of the variation in the relative abundance of salmon observed within this region. The results indicate that warmer late-spring temperatures in a Chukchi Sea watch-zone and persistent, suitable summer thermal conditions in a Beaufort Sea watch-zone together create a range-expansion corridor and are associated with higher salmon occurrences in subsistence harvests. Furthermore, there is a body of knowledge to suggest that these conditions, and consequently the presence and abundance of Pacific salmon, will become more persistent in the coming decades. Our collaborative approach positions us to document, explore, and explain mechanisms driving changes in fish biodiversity that have the potential to, or are already affecting, Indigenous rights-holders in a rapidly warming Arctic.},
	language = {en},
	number = {6},
	urldate = {2024-08-12},
	journal = {Global Change Biology},
	author = {Dunmall, Karen M. and Langan, Joseph A. and Cunningham, Curry J. and Reist, James D. and Melling, Humfrey and {Aklavik Hunters and Trappers Committee} and {Olokhaktomiut Hunters and Trappers Committee} and {Paulatuk Hunters and Trappers Committee} and {Sachs Harbour Hunters and Trappers Committee} and {Tuktoyaktuk Hunters and Trappers Committee} and {Kugluktuk Hunters and Trappers Organization}},
	year = {2024},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/gcb.17353},
	keywords = {Lakes \& Rivers},
	pages = {e17353},
}

Rapid climate change is altering Arctic ecosystems at unprecedented rates. These changes in the physical environment may open new corridors for species range expansions, with substantial implications for subsistence-dependent communities and sensitive ecosystems. Over the past 20 years, rising incidental harvest of Pacific salmon by subsistence fishers has been monitored across a widening range spanning multiple land claim jurisdictions in Arctic Canada. In this study, we connect Indigenous and scientific knowledges to explore potential oceanographic mechanisms facilitating this ongoing northward expansion of Pacific salmon into the western Canadian Arctic. A regression analysis was used to reveal and characterize a two-part mechanism related to thermal and sea-ice conditions in the Chukchi and Beaufort seas that explains nearly all of the variation in the relative abundance of salmon observed within this region. The results indicate that warmer late-spring temperatures in a Chukchi Sea watch-zone and persistent, suitable summer thermal conditions in a Beaufort Sea watch-zone together create a range-expansion corridor and are associated with higher salmon occurrences in subsistence harvests. Furthermore, there is a body of knowledge to suggest that these conditions, and consequently the presence and abundance of Pacific salmon, will become more persistent in the coming decades. Our collaborative approach positions us to document, explore, and explain mechanisms driving changes in fish biodiversity that have the potential to, or are already affecting, Indigenous rights-holders in a rapidly warming Arctic.

@article{mower_parallel_2024,
	title = {Parallel {SnowModel} (v1.0): a parallel implementation of a distributed snow-evolution modeling system ({SnowModel})},
	volume = {17},
	issn = {1991-959X},
	shorttitle = {Parallel {SnowModel} (v1.0)},
	url = {https://gmd.copernicus.org/articles/17/4135/2024/},
	doi = {10.5194/gmd-17-4135-2024},
	abstract = {SnowModel, a spatially distributed snow-evolution modeling system, was parallelized using Coarray Fortran for high-performance computing architectures to allow high-resolution (1 m to hundreds of meters) simulations over large regional- to continental-scale domains. In the parallel algorithm, the model domain was split into smaller rectangular sub-domains that are distributed over multiple processor cores using one-dimensional decomposition. All the memory allocations from the original code were reduced to the size of the local sub-domains, allowing each core to perform fewer computations and requiring less memory for each process. Most of the subroutines in SnowModel were simple to parallelize; however, there were certain physical processes, including blowing snow redistribution and components within the solar radiation and wind models, that required non-trivial parallelization using halo-exchange patterns. To validate the parallel algorithm and assess parallel scaling characteristics, high-resolution (100 m grid) simulations were performed over several western United States domains and over the contiguous United States (CONUS) for a year. The CONUS scaling experiment had approximately 70 \% parallel efficiency; runtime decreased by a factor of 1.9 running on 1800 cores relative to 648 cores (the minimum number of cores that could be used to run such a large domain because of memory and time limitations). CONUS 100 m simulations were performed for 21 years (2000–2021) using 46 238 and 28 260 grid cells in the x and y dimensions, respectively. Each year was simulated using 1800 cores and took approximately 5 h to run.},
	language = {English},
	number = {10},
	urldate = {2024-06-03},
	journal = {Geoscientific Model Development},
	author = {Mower, Ross and Gutmann, Ethan D. and Liston, Glen E. and Lundquist, Jessica and Rasmussen, Soren},
	month = may,
	year = {2024},
	note = {Publisher: Copernicus GmbH},
	keywords = {NALCMS},
	pages = {4135--4154},
}

SnowModel, a spatially distributed snow-evolution modeling system, was parallelized using Coarray Fortran for high-performance computing architectures to allow high-resolution (1 m to hundreds of meters) simulations over large regional- to continental-scale domains. In the parallel algorithm, the model domain was split into smaller rectangular sub-domains that are distributed over multiple processor cores using one-dimensional decomposition. All the memory allocations from the original code were reduced to the size of the local sub-domains, allowing each core to perform fewer computations and requiring less memory for each process. Most of the subroutines in SnowModel were simple to parallelize; however, there were certain physical processes, including blowing snow redistribution and components within the solar radiation and wind models, that required non-trivial parallelization using halo-exchange patterns. To validate the parallel algorithm and assess parallel scaling characteristics, high-resolution (100 m grid) simulations were performed over several western United States domains and over the contiguous United States (CONUS) for a year. The CONUS scaling experiment had approximately 70 % parallel efficiency; runtime decreased by a factor of 1.9 running on 1800 cores relative to 648 cores (the minimum number of cores that could be used to run such a large domain because of memory and time limitations). CONUS 100 m simulations were performed for 21 years (2000–2021) using 46 238 and 28 260 grid cells in the x and y dimensions, respectively. Each year was simulated using 1800 cores and took approximately 5 h to run.

@techreport{avila-garcia_d_planes_2024,
	title = {Planes de {Acción} para el {Manejo} {Integral} de {Cuencas} - {Guía} {Metodológica} ({FMCN})},
	url = {https://agua.org.mx/biblioteca/planes-de-accion-para-el-manejo-integral-de-cuencas-guia-metodologica-fmcn/},
	abstract = {El Instituto Nacional de Ecología y Cambio Climático (INECC) y el Fondo Mexicano para la Conservación de la Naturaleza (FMCN) colaboran con aliados regionales en la implementación del proyecto CONECTA “Conectando la salud de las cuencas con la producción ganadera y agroforestal sostenible” (2021-2026), que es financiado por el Fondo para el Medio Ambiente Mundial (GEF por sus siglas en inglés) a través del Banco Mundial (BM). El objetivo de CONECTA es mejorar el manejo integrado del paisaje y promover prácticas productivas climáticamente inteligentes.},
	urldate = {2024-03-11},
	institution = {Instituto Nacional de Ecología y Cambio Climático (INECC)},
	author = {{Ávila-García, D.} and {Hernández, E.} and {Fernández-Montes de Oca, A.} and {Cicchini, F.} and {Alvarado, J.} and {López S.}},
	month = feb,
	year = {2024},
	keywords = {NALCMS},
	pages = {124},
}

El Instituto Nacional de Ecología y Cambio Climático (INECC) y el Fondo Mexicano para la Conservación de la Naturaleza (FMCN) colaboran con aliados regionales en la implementación del proyecto CONECTA “Conectando la salud de las cuencas con la producción ganadera y agroforestal sostenible” (2021-2026), que es financiado por el Fondo para el Medio Ambiente Mundial (GEF por sus siglas en inglés) a través del Banco Mundial (BM). El objetivo de CONECTA es mejorar el manejo integrado del paisaje y promover prácticas productivas climáticamente inteligentes.

@article{huang_potential_2024,
	title = {Potential for spatial coexistence of a transboundary migratory species and wind energy development},
	volume = {14},
	copyright = {2024 This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply},
	issn = {2045-2322},
	url = {https://www.nature.com/articles/s41598-024-66490-3},
	doi = {10.1038/s41598-024-66490-3},
	abstract = {Global expansion in wind energy development is a notable achievement of the international community’s effort to reduce carbon emissions during energy production. However, the increasing number of wind turbines have unintended consequences for migratory birds and bats. Wind turbine curtailment and other mitigation strategies can reduce fatalities, but improved spatial and temporal data are needed to identify the most effective way for wind energy development and volant migratory species to coexist. Mexican free-tailed bats (Tadarida brasiliensis mexicana) account for a large proportion of known bat fatalities at wind facilities in the southwestern US. We examined the geographic concordance between existing wind energy generation facilities, areas of high wind potential amenable for future deployment of wind facilities, and seasonally suitable habitat for these bats. We used ecological niche modeling to determine species distribution during each of 4 seasons. We used a multi-criteria GIS-based approach to produce a wind turbine siting suitability map. We identified seasonal locations with highest and lowest potential for the species’ probability of occurrence, providing a potential explanation for the higher observed fatalities during fall migration. Thirty percent of 33,606 wind turbines within the southwestern US occurred in highly suitable areas for Mexican free-tailed bats, primarily in west Texas. There is also broad spatial overlap between areas of high wind potential and areas of suitable habitat for Mexican free-tailed bats. Because of this high degree of overlap, our results indicate that post-construction strategies, such as curtailing the timing of operations and deterrents, would be more effective for bat conservation than strategic siting of new wind energy installations.},
	language = {en},
	number = {1},
	urldate = {2024-09-16},
	journal = {Scientific Reports},
	author = {Huang, Ta-Ken and Feng, Xiao and Derbridge, Jonathan J. and Libby, Kaitlin and Diffendorfer, Jay E. and Thogmartin, Wayne E. and McCracken, Gary and Medellin, Rodrigo and López-Hoffman, Laura},
	month = jul,
	year = {2024},
	note = {Publisher: Nature Publishing Group},
	keywords = {NALCMS},
	pages = {17050},
}

Global expansion in wind energy development is a notable achievement of the international community’s effort to reduce carbon emissions during energy production. However, the increasing number of wind turbines have unintended consequences for migratory birds and bats. Wind turbine curtailment and other mitigation strategies can reduce fatalities, but improved spatial and temporal data are needed to identify the most effective way for wind energy development and volant migratory species to coexist. Mexican free-tailed bats (Tadarida brasiliensis mexicana) account for a large proportion of known bat fatalities at wind facilities in the southwestern US. We examined the geographic concordance between existing wind energy generation facilities, areas of high wind potential amenable for future deployment of wind facilities, and seasonally suitable habitat for these bats. We used ecological niche modeling to determine species distribution during each of 4 seasons. We used a multi-criteria GIS-based approach to produce a wind turbine siting suitability map. We identified seasonal locations with highest and lowest potential for the species’ probability of occurrence, providing a potential explanation for the higher observed fatalities during fall migration. Thirty percent of 33,606 wind turbines within the southwestern US occurred in highly suitable areas for Mexican free-tailed bats, primarily in west Texas. There is also broad spatial overlap between areas of high wind potential and areas of suitable habitat for Mexican free-tailed bats. Because of this high degree of overlap, our results indicate that post-construction strategies, such as curtailing the timing of operations and deterrents, would be more effective for bat conservation than strategic siting of new wind energy installations.

@article{kramer_potential_2024,
	title = {Potential landscape connectivity for invasive wild pigs ({Sus} scrofa) across the northern prairies of {North} {America}},
	volume = {26},
	issn = {1573-1464},
	url = {https://doi.org/10.1007/s10530-024-03326-1},
	doi = {10.1007/s10530-024-03326-1},
	abstract = {Understanding landscape scale connectivity is an essential component in the management of invasive species since connectivity facilitates their invasion potential. Invasive wild pigs (Sus scrofa) are among the most prolific invaders on the planet, causing billions of dollars in agricultural and environmental damage annually. Newly introduced to Canada in the 1980s, we examined wild pig invasion potential across the northern prairies from western Canada into the currently wild pig-free northern U.S. states. We used GPS collar data collected in the Canadian prairies to quantify resource selection and incorporated results into an electric circuit theory framework to evaluate potential regional landscape connectivity. While available landcover types in this region were dominated by crops and grasslands, wild pigs were predominately located in deciduous forest, crops, and wetlands. Resource selection modelling indicated wild pigs selected deciduous forest and wetlands over other landcover types. These selection tendencies resulted in areas at greater risk of occupation in an intermixture dominated by crops interspersed with waterbodies and deciduous forest fragments, which facilitated movement. Given the pervasiveness of this intermixture across the northern prairies, there was a high potential for invasive wild pigs to move throughout much of the region with areas in southern Saskatchewan and Manitoba, northeastern Montana, North and South Dakota, and western portions of Minnesota being particularly vulnerable. Our work highlights a need for monitoring and science-based response strategies for likely southward spread of this invasive species to prevent or reduce potential crop damage, risks to native species, and disease transmission to humans, pets, livestock, and wildlife.},
	language = {en},
	number = {8},
	urldate = {2024-08-12},
	journal = {Biological Invasions},
	author = {Kramer, Corey J. and Boudreau, Melanie R. and Powers, Ryan and VerCauteren, Kurt C. and Miller, Ryan S. and Brook, Ryan K.},
	month = aug,
	year = {2024},
	keywords = {NALCMS, Terrestrial Ecoregions},
	pages = {2525--2538},
}

Understanding landscape scale connectivity is an essential component in the management of invasive species since connectivity facilitates their invasion potential. Invasive wild pigs (Sus scrofa) are among the most prolific invaders on the planet, causing billions of dollars in agricultural and environmental damage annually. Newly introduced to Canada in the 1980s, we examined wild pig invasion potential across the northern prairies from western Canada into the currently wild pig-free northern U.S. states. We used GPS collar data collected in the Canadian prairies to quantify resource selection and incorporated results into an electric circuit theory framework to evaluate potential regional landscape connectivity. While available landcover types in this region were dominated by crops and grasslands, wild pigs were predominately located in deciduous forest, crops, and wetlands. Resource selection modelling indicated wild pigs selected deciduous forest and wetlands over other landcover types. These selection tendencies resulted in areas at greater risk of occupation in an intermixture dominated by crops interspersed with waterbodies and deciduous forest fragments, which facilitated movement. Given the pervasiveness of this intermixture across the northern prairies, there was a high potential for invasive wild pigs to move throughout much of the region with areas in southern Saskatchewan and Manitoba, northeastern Montana, North and South Dakota, and western portions of Minnesota being particularly vulnerable. Our work highlights a need for monitoring and science-based response strategies for likely southward spread of this invasive species to prevent or reduce potential crop damage, risks to native species, and disease transmission to humans, pets, livestock, and wildlife.

@inproceedings{boschee_predicting_2024,
	title = {Predicting {Flood} {Damages} using {Machine} {Learning} and {National} {Flood} {Insurance} {Program} {Data}},
	url = {https://ams.confex.com/ams/104ANNUAL/mediafile/Handout/Paper440366/AMSPoster_Boschee.pdf},
	publisher = {AMS},
	author = {Boschee, Azara and Corringham, Tom and Hu, Weiming},
	year = {2024},
	keywords = {NALCMS},
}

@article{wallace_predicting_2024,
	title = {Predicting the spatial distribution of wintering golden eagles to inform full annual cycle conservation in western {North} {America}},
	volume = {19},
	issn = {1932-6203},
	url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0297345},
	doi = {10.1371/journal.pone.0297345},
	abstract = {Wildlife conservation strategies focused on one season or population segment may fail to adequately protect populations, especially when a species’ habitat preferences vary among seasons, age-classes, geographic regions, or other factors. Conservation of golden eagles (Aquila chrysaetos) is an example of such a complex scenario, in which the distribution, habitat use, and migratory strategies of this species of conservation concern vary by age-class, reproductive status, region, and season. Nonetheless, research aimed at mapping priority use areas to inform management of golden eagles in western North America has typically focused on territory-holding adults during the breeding period, largely to the exclusion of other seasons and life-history groups. To support population-wide conservation planning across the full annual cycle for golden eagles, we developed a distribution model for individuals in a season not typically evaluated–winter–and in an area of the interior western U.S. that is a high priority for conservation of the species. We used a large GPS-telemetry dataset and library of environmental variables to develop a machine-learning model to predict spatial variation in the relative intensity of use by golden eagles during winter in Wyoming, USA, and surrounding ecoregions. Based on a rigorous series of evaluations including cross-validation, withheld and independent data, our winter-season model accurately predicted spatial variation in intensity of use by multiple age- and life-history groups of eagles not associated with nesting territories (i.e., all age classes of long-distance migrants, and resident non-adults and adult “floaters”, and movements of adult territory holders and their offspring outside their breeding territories). Important predictors in the model were wind and uplift (40.2\% contribution), vegetation and landcover (27.9\%), topography (14\%), climate and weather (9.4\%), and ecoregion (8.7\%). Predicted areas of high-use winter habitat had relatively low spatial overlap with nesting habitat, suggesting a conservation strategy targeting high-use areas for one season would capture as much as half and as little as one quarter of high-use areas for the other season. The majority of predicted high-use habitat (top 10\% quantile) occurred on private lands (55\%); lands managed by states and the Bureau of Land Management (BLM) had a lower amount (33\%), but higher concentration of high-use habitat than expected for their area (1.5–1.6x). These results will enable those involved in conservation and management of golden eagles in our study region to incorporate spatial prioritization of wintering habitat into their existing regulatory processes, land-use planning tasks, and conservation actions.},
	language = {en},
	number = {1},
	urldate = {2026-05-29},
	journal = {PLOS ONE},
	author = {Wallace, Zachary P. and Bedrosian, Bryan E. and Dunk, Jeffrey R. and LaPlante, David W. and Woodbridge, Brian and Smith, Brian W. and Brown, Jessi L. and Lickfett, Todd M. and Gura, Katherine and Bittner, Dave and Crandall, Ross H. and Domenech, Rob and Katzner, Todd E. and Kritz, Kevin J. and Lewis, Stephen B. and Lockhart, Michael J. and Miller, Tricia A. and Quint, Katie and Shreading, Adam and Slater, Steve J. and Stahlecker, Dale W.},
	month = jan,
	year = {2024},
	note = {Publisher: Public Library of Science},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {e0297345},
}

Wildlife conservation strategies focused on one season or population segment may fail to adequately protect populations, especially when a species’ habitat preferences vary among seasons, age-classes, geographic regions, or other factors. Conservation of golden eagles (Aquila chrysaetos) is an example of such a complex scenario, in which the distribution, habitat use, and migratory strategies of this species of conservation concern vary by age-class, reproductive status, region, and season. Nonetheless, research aimed at mapping priority use areas to inform management of golden eagles in western North America has typically focused on territory-holding adults during the breeding period, largely to the exclusion of other seasons and life-history groups. To support population-wide conservation planning across the full annual cycle for golden eagles, we developed a distribution model for individuals in a season not typically evaluated–winter–and in an area of the interior western U.S. that is a high priority for conservation of the species. We used a large GPS-telemetry dataset and library of environmental variables to develop a machine-learning model to predict spatial variation in the relative intensity of use by golden eagles during winter in Wyoming, USA, and surrounding ecoregions. Based on a rigorous series of evaluations including cross-validation, withheld and independent data, our winter-season model accurately predicted spatial variation in intensity of use by multiple age- and life-history groups of eagles not associated with nesting territories (i.e., all age classes of long-distance migrants, and resident non-adults and adult “floaters”, and movements of adult territory holders and their offspring outside their breeding territories). Important predictors in the model were wind and uplift (40.2% contribution), vegetation and landcover (27.9%), topography (14%), climate and weather (9.4%), and ecoregion (8.7%). Predicted areas of high-use winter habitat had relatively low spatial overlap with nesting habitat, suggesting a conservation strategy targeting high-use areas for one season would capture as much as half and as little as one quarter of high-use areas for the other season. The majority of predicted high-use habitat (top 10% quantile) occurred on private lands (55%); lands managed by states and the Bureau of Land Management (BLM) had a lower amount (33%), but higher concentration of high-use habitat than expected for their area (1.5–1.6x). These results will enable those involved in conservation and management of golden eagles in our study region to incorporate spatial prioritization of wintering habitat into their existing regulatory processes, land-use planning tasks, and conservation actions.

@article{seydi_predictive_2024,
	title = {Predictive {Understanding} of {Links} {Between} {Vegetation} and {Soil} {Burn} {Severities} {Using} {Physics}-{Informed} {Machine} {Learning}},
	volume = {12},
	copyright = {© 2024. The Author(s).},
	issn = {2328-4277},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2024EF004873},
	doi = {10.1029/2024EF004873},
	abstract = {Burn severity is fundamental to post-fire impact assessment and emergency response. Vegetation Burn Severity (VBS) can be derived from satellite observations. However, Soil Burn Severity (SBS) assessment—critical for mitigating hydrologic and geologic hazards—requires costly and laborious field recalibration of VBS maps. Here, we develop a physics-informed Machine Learning model capable of accurately estimating SBS while revealing the intricate relationships between soil and vegetation burn severities. Our SBS classification model uses VBS, as well as climatological, meteorological, ecological, geological, and topographical wildfire covariates. This model demonstrated an overall accuracy of 89\% for out-of-sample test data. The model exhibited scalability with additional data, and was able to extract universal functional relationships between vegetation and soil burn severities across the western US. VBS had the largest control on SBS, followed by weather (e.g., wind, fire danger, temperature), climate (e.g., annual precipitation), topography (e.g., elevation), and soil characteristics (e.g., soil organic carbon content). The relative control of processes on SBS changes across regions. Our model revealed nuanced relationships between VBS and SBS; for example, a similar VBS with lower wind speeds—that is, higher fire residence time—translates to a higher SBS. This transferrable model develops reliable and timely SBS maps using satellite and publicly accessible data, providing science-based insights for managers and diverse stakeholders.},
	language = {en},
	number = {8},
	urldate = {2025-01-27},
	journal = {Earth's Future},
	author = {Seydi, Seyd Teymoor and Abatzoglou, John T. and AghaKouchak, Amir and Pourmohamad, Yavar and Mishra, Ashok and Sadegh, Mojtaba},
	year = {2024},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1029/2024EF004873},
	keywords = {NALCMS},
	pages = {e2024EF004873},
}

Burn severity is fundamental to post-fire impact assessment and emergency response. Vegetation Burn Severity (VBS) can be derived from satellite observations. However, Soil Burn Severity (SBS) assessment—critical for mitigating hydrologic and geologic hazards—requires costly and laborious field recalibration of VBS maps. Here, we develop a physics-informed Machine Learning model capable of accurately estimating SBS while revealing the intricate relationships between soil and vegetation burn severities. Our SBS classification model uses VBS, as well as climatological, meteorological, ecological, geological, and topographical wildfire covariates. This model demonstrated an overall accuracy of 89% for out-of-sample test data. The model exhibited scalability with additional data, and was able to extract universal functional relationships between vegetation and soil burn severities across the western US. VBS had the largest control on SBS, followed by weather (e.g., wind, fire danger, temperature), climate (e.g., annual precipitation), topography (e.g., elevation), and soil characteristics (e.g., soil organic carbon content). The relative control of processes on SBS changes across regions. Our model revealed nuanced relationships between VBS and SBS; for example, a similar VBS with lower wind speeds—that is, higher fire residence time—translates to a higher SBS. This transferrable model develops reliable and timely SBS maps using satellite and publicly accessible data, providing science-based insights for managers and diverse stakeholders.

@article{pio-leon_priority_2024,
	title = {Priority areas for conservation based on endemic vascular plant species and their biocultural attributes: a case study in {Sinaloa}, {Mexico}},
	volume = {95},
	copyright = {Derechos de autor 2024 Revista Mexicana de Biodiversidad},
	issn = {2007-8706},
	shorttitle = {Priority areas for conservation based on endemic vascular plant species and their biocultural attributes},
	url = {https://revista.ib.unam.mx/index.php/bio/article/view/5446},
	doi = {10.22201/ib.20078706e.2024.95.5446},
	abstract = {Endemic vascular plants are one of the main biodiversity indicators used to propose priority conservation areas. The richness of endemic species and corrected and weighted endemism are the most frequently used criteria, while anthropogenic or biocultural factors such as ethnobotanical value or ecological vulnerability are seldom considered. This work proposes priority conservation areas for Sinaloa, Mexico, considering the richness of its endemic species, corrected and weighted endemism, as well as ethnobotanical value, protection status, and the Priority Conservation Index (PCI). The analysis was performed in a 19 × 19 km grid and included 247 records of 78 species. The areas proposed when considering only the richness of endemic species and the weighted endemism coincided with previously known areas of high biodiversity in the state, which are areas of high collection effort and low anthropogenic impact. When considering the ethnobotanical value and protection status, the areas identified included those with greater anthropogenic impact, which contained species of biocultural and economic importance. When the PCI was used, both of these types of regions were identified. We therefore recommend this index as a better indicator to select priority areas.},
	language = {en},
	urldate = {2026-05-28},
	journal = {Revista Mexicana de Biodiversidad},
	author = {Pío-León, Juan Fernando and Munguía-Lino, Guadalupe and González-Gallegos, Jesús Guadalupe and González-Elizondo, Martha},
	month = nov,
	year = {2024},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {e955446--e955446},
}

Endemic vascular plants are one of the main biodiversity indicators used to propose priority conservation areas. The richness of endemic species and corrected and weighted endemism are the most frequently used criteria, while anthropogenic or biocultural factors such as ethnobotanical value or ecological vulnerability are seldom considered. This work proposes priority conservation areas for Sinaloa, Mexico, considering the richness of its endemic species, corrected and weighted endemism, as well as ethnobotanical value, protection status, and the Priority Conservation Index (PCI). The analysis was performed in a 19 × 19 km grid and included 247 records of 78 species. The areas proposed when considering only the richness of endemic species and the weighted endemism coincided with previously known areas of high biodiversity in the state, which are areas of high collection effort and low anthropogenic impact. When considering the ethnobotanical value and protection status, the areas identified included those with greater anthropogenic impact, which contained species of biocultural and economic importance. When the PCI was used, both of these types of regions were identified. We therefore recommend this index as a better indicator to select priority areas.

@article{saffer_reconstructing_2024,
	title = {Reconstructing historic and modern potato late blight outbreaks using text analytics},
	volume = {14},
	copyright = {2024 The Author(s)},
	issn = {2045-2322},
	url = {https://www.nature.com/articles/s41598-024-52870-2},
	doi = {10.1038/s41598-024-52870-2},
	abstract = {In 1843, a hitherto unknown plant pathogen entered the US and spread to potato fields in the northeast. By 1845, the pathogen had reached Ireland leading to devastating famine. Questions arose immediately about the source of the outbreaks and how the disease should be managed. The pathogen, now known as Phytophthora infestans, still continues to threaten food security globally. A wealth of untapped knowledge exists in both archival and modern documents, but is not readily available because the details are hidden in descriptive text. In this work, we (1) used text analytics of unstructured historical reports (1843–1845) to map US late blight outbreaks; (2) characterized theories on the source of the pathogen and remedies for control; and (3) created modern late blight intensity maps using Twitter feeds. The disease spread from 5 to 17 states and provinces in the US and Canada between 1843 and 1845. Crop losses, Andean sources of the pathogen, possible causes and potential treatments were discussed. Modern disease discussion on Twitter included near-global coverage and local disease observations. Topic modeling revealed general disease information, published research, and outbreak locations. The tools described will help researchers explore and map unstructured text to track and visualize pandemics.},
	language = {en},
	number = {1},
	urldate = {2024-03-11},
	journal = {Scientific Reports},
	author = {Saffer, Ariel and Tateosian, Laura and Saville, Amanda C. and Yang, Yi-Peng and Ristaino, Jean B.},
	month = feb,
	year = {2024},
	note = {Publisher: Nature Publishing Group},
	keywords = {Political Boundaries},
	pages = {2523},
}

In 1843, a hitherto unknown plant pathogen entered the US and spread to potato fields in the northeast. By 1845, the pathogen had reached Ireland leading to devastating famine. Questions arose immediately about the source of the outbreaks and how the disease should be managed. The pathogen, now known as Phytophthora infestans, still continues to threaten food security globally. A wealth of untapped knowledge exists in both archival and modern documents, but is not readily available because the details are hidden in descriptive text. In this work, we (1) used text analytics of unstructured historical reports (1843–1845) to map US late blight outbreaks; (2) characterized theories on the source of the pathogen and remedies for control; and (3) created modern late blight intensity maps using Twitter feeds. The disease spread from 5 to 17 states and provinces in the US and Canada between 1843 and 1845. Crop losses, Andean sources of the pathogen, possible causes and potential treatments were discussed. Modern disease discussion on Twitter included near-global coverage and local disease observations. Topic modeling revealed general disease information, published research, and outbreak locations. The tools described will help researchers explore and map unstructured text to track and visualize pandemics.

@misc{braden_satellite-derived_2024,
	title = {Satellite-{Derived} {Forest} {Extent} {Likelihood} {Map} for {Mexico}},
	url = {https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=2320},
	doi = {10.3334/ORNLDAAC/2320},
	abstract = {This dataset provides a comparison of forest extent agreement from seven remote sensing-based products across Mexico. These satellite-derived products include European Space Agency 2020 Land Cover Map for Mexico (ESA), Globeland30 2020 (Globeland30), Commission for Environmental Cooperation 2015 Land Cover Map (CEC), Impact Observatory 2020 Land Cover Map (IO), NAIP Trained Mean Percent Cover Map (NEX-TC), Global Land Analysis and Discovery Global 2010 Tree Cover (Hansen-TC), and Global Forest Cover Change Tree Cover 30 m Global (GFCC-TC). All products included data at 10-30 m resolution and represented the state of forest or tree cover from 2010 to 2020. These seven products were chosen based on: a) feedback from end-users in Mexico; b) availability and FAIR (findable, accessible, interoperable, and replicable) data principles; and c) products representing different methodological approaches from global to regional scales. The combined agreement map documents forest cover for each satellite-derived product at 30-m resolution across Mexico. The data are in cloud optimized GeoTIFF format and cover the period 2010-2020. A shapefile is included that outlines Mexico mainland areas.},
	language = {en},
	urldate = {2024-04-24},
	author = {Braden, D. and Mondal, P. and Park, T. and De la rosa, J.A.A. and Leal, M.I.A. and Lara, R.A.C. and Saucedo, R.M. and Salas-Aguilar, V.M. and Soriano-Luna, M.A. and Vargas, R.},
	collaborator = {{ORNL DAAC}},
	year = {2024},
	note = {Artwork Size: 0 MB
Medium: COG, ESRI Shapefile
Publisher: [object Object]},
	keywords = {NALCMS},
}

This dataset provides a comparison of forest extent agreement from seven remote sensing-based products across Mexico. These satellite-derived products include European Space Agency 2020 Land Cover Map for Mexico (ESA), Globeland30 2020 (Globeland30), Commission for Environmental Cooperation 2015 Land Cover Map (CEC), Impact Observatory 2020 Land Cover Map (IO), NAIP Trained Mean Percent Cover Map (NEX-TC), Global Land Analysis and Discovery Global 2010 Tree Cover (Hansen-TC), and Global Forest Cover Change Tree Cover 30 m Global (GFCC-TC). All products included data at 10-30 m resolution and represented the state of forest or tree cover from 2010 to 2020. These seven products were chosen based on: a) feedback from end-users in Mexico; b) availability and FAIR (findable, accessible, interoperable, and replicable) data principles; and c) products representing different methodological approaches from global to regional scales. The combined agreement map documents forest cover for each satellite-derived product at 30-m resolution across Mexico. The data are in cloud optimized GeoTIFF format and cover the period 2010-2020. A shapefile is included that outlines Mexico mainland areas.

@article{bowser_self-reported_2024,
	title = {Self-reported tick exposure as an indicator of {Lyme} disease risk in an endemic region of {Quebec}, {Canada}},
	volume = {15},
	issn = {1877-959X},
	url = {https://www.sciencedirect.com/science/article/pii/S1877959X23001528},
	doi = {10.1016/j.ttbdis.2023.102271},
	abstract = {Background
Lyme disease (LD) and other tick-borne diseases are emerging across Canada. Spatial and temporal LD risk is typically estimated using acarological surveillance and reported human cases, the former not considering human behavior leading to tick exposure and the latter occurring after infection.
Objectives
The primary objective was to explore, at the census subdivision level (CSD), the associations of self-reported tick exposure, alternative risk indicators (predicted tick density, eTick submissions, public health risk level), and ecological variables (Ixodes scapularis habitat suitability index and cumulative degree days {\textgreater} 0 °C) with incidence proportion of LD. A secondary objective was to explore which of these predictor variables were associated with self-reported tick exposure at the CSD level.
Methods
Self-reported tick exposure was measured in a cross-sectional populational health survey conducted in 2018, among 10,790 respondents living in 116 CSDs of the Estrie region, Quebec, Canada. The number of reported LD cases per CSD in 2018 was obtained from the public health department. Generalized linear mixed-effets models accounting for spatial autocorrelation were built to fulfill the objectives.
Results
Self-reported tick exposure ranged from 0.0 \% to 61.5 \% (median 8.9 \%) and reported LD incidence rates ranged from 0 to 324 cases per 100,000 person-years, per CSD. A positive association was found between self-reported tick exposure and LD incidence proportion (ß = 0.08, CI = 0.04,0.11, p {\textless} 0.0001). The best-fit model included public health risk level (AIC: 144.2), followed by predicted tick density, ecological variables, self-reported tick exposure and eTick submissions (AIC: 158.4, 158.4, 160.4 and 170.1 respectively). Predicted tick density was the only significant predictor of self-reported tick exposure (ß = 0.83, CI = 0.16,1.50, p = 0.02).
Discussion
This proof-of-concept study explores self-reported tick exposure as a potential indicator of LD risk using populational survey data. This approach may offer a low-cost and simple tool for evaluating LD risk and deserves further evaluation.},
	number = {1},
	urldate = {2024-01-10},
	journal = {Ticks and Tick-borne Diseases},
	author = {Bowser, Natasha and Bouchard, Catherine and Sautié Castellanos, Miguel and Baron, Geneviève and Carabin, Hélène and Chuard, Pierre and Leighton, Patrick and Milord, François and Richard, Lucie and Savage, Jade and Tardy, Olivia and Aenishaenslin, Cécile},
	month = jan,
	year = {2024},
	keywords = {NALCMS},
	pages = {102271},
}

Background Lyme disease (LD) and other tick-borne diseases are emerging across Canada. Spatial and temporal LD risk is typically estimated using acarological surveillance and reported human cases, the former not considering human behavior leading to tick exposure and the latter occurring after infection. Objectives The primary objective was to explore, at the census subdivision level (CSD), the associations of self-reported tick exposure, alternative risk indicators (predicted tick density, eTick submissions, public health risk level), and ecological variables (Ixodes scapularis habitat suitability index and cumulative degree days \textgreater 0 °C) with incidence proportion of LD. A secondary objective was to explore which of these predictor variables were associated with self-reported tick exposure at the CSD level. Methods Self-reported tick exposure was measured in a cross-sectional populational health survey conducted in 2018, among 10,790 respondents living in 116 CSDs of the Estrie region, Quebec, Canada. The number of reported LD cases per CSD in 2018 was obtained from the public health department. Generalized linear mixed-effets models accounting for spatial autocorrelation were built to fulfill the objectives. Results Self-reported tick exposure ranged from 0.0 % to 61.5 % (median 8.9 %) and reported LD incidence rates ranged from 0 to 324 cases per 100,000 person-years, per CSD. A positive association was found between self-reported tick exposure and LD incidence proportion (ß = 0.08, CI = 0.04,0.11, p \textless 0.0001). The best-fit model included public health risk level (AIC: 144.2), followed by predicted tick density, ecological variables, self-reported tick exposure and eTick submissions (AIC: 158.4, 158.4, 160.4 and 170.1 respectively). Predicted tick density was the only significant predictor of self-reported tick exposure (ß = 0.83, CI = 0.16,1.50, p = 0.02). Discussion This proof-of-concept study explores self-reported tick exposure as a potential indicator of LD risk using populational survey data. This approach may offer a low-cost and simple tool for evaluating LD risk and deserves further evaluation.

@article{roy_sharp-tailed_2024,
	title = {Sharp-tailed {Grouse} increase site use after prescribed fire but not mechanical treatments during the fall},
	volume = {19},
	copyright = {© 2024 by the author(s)},
	issn = {1712-6568},
	url = {https://ace-eco.org/vol19/iss1/art1/},
	doi = {10.5751/ACE-02574-190101},
	abstract = {In the Great Lakes Region, Sharp-tailed Grouse (Tympanuchus phasianellus) use open habitats of grass and brush that require frequent management. Wildlife managers expressed concern that Sharp-tailed Grouse were not responding to management throughout the year, so we examined responses to prescribed fire and mechanical treatment (mowing or shearing) conducted during the fall. We surveyed Sharp-tailed Grouse use and vegetation at 15 mechanical treatments, 10 prescribed burns, and 25 control sites in a before-after-control-impact-paired design. We surveyed Sharp-tailed Grouse use before management, and one week, one month, one year, and three years after management by conducting fecal pellet surveys along transects at each site. Sharp-tailed Grouse responses, as indicated by differences between fecal pellet counts at treatments and paired controls during each survey, increased following prescribed fire, but did not change after mechanical treatments. However, increased Sharp-tailed Grouse use following prescribed fire was temporary, thus management should be conducted at least once every three years at each site. Changes in vegetation metrics at managed sites were also temporary and most metrics returned to pre-treatment levels after one year, although shrub height at sites that received mechanical treatments and the forb response following prescribed fire persisted for {\textgreater} 3 years. We suggest that fall prescribed fire is more effective at increasing Sharp-tailed Grouse use of sites than fall mechanical treatment, which could be due to differences in vegetation responses, site size, landscape context, or cues produced by fire that attract Sharp-tailed Grouse. However, mechanical treatments maintain Sharp-tailed Grouse habitat, and without management, unchecked woody encroachment reduces habitat. Targeting mowing and shearing at sites known to be used by Sharp-tailed Grouse may prioritize management activities to sites that will have the most impact. Prescribed fire and mechanical treatments produced different Sharp-tailed Grouse and vegetation responses in the fall and should be used to address different management objectives.},
	language = {en},
	number = {1},
	urldate = {2024-03-13},
	journal = {Avian Conservation and Ecology},
	author = {Roy, Charlotte L. and Giudice, John and Shartell, Lindsey M.},
	month = jan,
	year = {2024},
	note = {Publisher: The Resilience Alliance},
	keywords = {NALCMS},
}

In the Great Lakes Region, Sharp-tailed Grouse (Tympanuchus phasianellus) use open habitats of grass and brush that require frequent management. Wildlife managers expressed concern that Sharp-tailed Grouse were not responding to management throughout the year, so we examined responses to prescribed fire and mechanical treatment (mowing or shearing) conducted during the fall. We surveyed Sharp-tailed Grouse use and vegetation at 15 mechanical treatments, 10 prescribed burns, and 25 control sites in a before-after-control-impact-paired design. We surveyed Sharp-tailed Grouse use before management, and one week, one month, one year, and three years after management by conducting fecal pellet surveys along transects at each site. Sharp-tailed Grouse responses, as indicated by differences between fecal pellet counts at treatments and paired controls during each survey, increased following prescribed fire, but did not change after mechanical treatments. However, increased Sharp-tailed Grouse use following prescribed fire was temporary, thus management should be conducted at least once every three years at each site. Changes in vegetation metrics at managed sites were also temporary and most metrics returned to pre-treatment levels after one year, although shrub height at sites that received mechanical treatments and the forb response following prescribed fire persisted for \textgreater 3 years. We suggest that fall prescribed fire is more effective at increasing Sharp-tailed Grouse use of sites than fall mechanical treatment, which could be due to differences in vegetation responses, site size, landscape context, or cues produced by fire that attract Sharp-tailed Grouse. However, mechanical treatments maintain Sharp-tailed Grouse habitat, and without management, unchecked woody encroachment reduces habitat. Targeting mowing and shearing at sites known to be used by Sharp-tailed Grouse may prioritize management activities to sites that will have the most impact. Prescribed fire and mechanical treatments produced different Sharp-tailed Grouse and vegetation responses in the fall and should be used to address different management objectives.

@article{felfelani_simulation_2024,
	title = {Simulation of groundwater-flow dynamics in the {U}.{S}. {Northern} {High} {Plains} driven by multi-model estimates of surficial aquifer recharge},
	issn = {0022-1694},
	url = {https://www.sciencedirect.com/science/article/pii/S0022169424000970},
	doi = {10.1016/j.jhydrol.2024.130703},
	abstract = {There is growing interest in incorporating higher-resolution groundwater modeling within the framework of large-scale land surface models (LSMs), including processes such as three-dimensional flow, variable soil saturation, and surface water/groundwater interactions. Conversely, complex groundwater models (e.g., the U.S. Geological Survey Groundwater-Flow Model, MODFLOW) often use simpler representations of land surface dynamics (e.g., surface vegetation, evapotranspiration, recharge) and may benefit from higher process fidelity and temporal resolutions in these inputs. This study investigates the potential of improving groundwater representation in LSMs and land surface dynamics in MODFLOW through forcing MODFLOW with recharge from LSMs. Groundwater simulations build on an existing and well-calibrated MODFLOW model of the U.S. Northern High Plains aquifer, a hydrologically complex basin under the dual impacts of conversion of native vegetation to intense irrigated agricultural fields and climate change. Simulated groundwater recharge from four different land models are used to drive MODFLOW groundwater simulations. Results show relatively large discrepancies between recharge estimates among simulations. Forcing MODFLOW using recharge simulated by some of the LSMs in place of a simple water balance model marginally improves MODFLOW groundwater simulation. Further, our results support the efficacy of coupling LSMs to a sophisticated groundwater model such as MODFLOW. The coupling results in notable improvements in matching the historical groundwater levels through reduction of the skewness coefficient in percentage bias histogram (from 1.50 and 1.41 in original LSMs to 0.44 and 0.27, respectively, when MODFLOW is forced by groundwater recharge from LSMs) and reduction of bias. This modeling effort seeks to identify the best compromise between comprehensive land surface processes from global LSMs and advanced representation of groundwater from regional models.},
	urldate = {2024-01-31},
	journal = {Journal of Hydrology},
	author = {Felfelani, Farshid and Hughes, Joseph and Chen, Fei and Dugger, Aubrey and Schneider, Tim and Gochis, David and Traylor, Jonathan and Essaid, Hedeff},
	month = jan,
	year = {2024},
	keywords = {NALCMS},
	pages = {130703},
}

There is growing interest in incorporating higher-resolution groundwater modeling within the framework of large-scale land surface models (LSMs), including processes such as three-dimensional flow, variable soil saturation, and surface water/groundwater interactions. Conversely, complex groundwater models (e.g., the U.S. Geological Survey Groundwater-Flow Model, MODFLOW) often use simpler representations of land surface dynamics (e.g., surface vegetation, evapotranspiration, recharge) and may benefit from higher process fidelity and temporal resolutions in these inputs. This study investigates the potential of improving groundwater representation in LSMs and land surface dynamics in MODFLOW through forcing MODFLOW with recharge from LSMs. Groundwater simulations build on an existing and well-calibrated MODFLOW model of the U.S. Northern High Plains aquifer, a hydrologically complex basin under the dual impacts of conversion of native vegetation to intense irrigated agricultural fields and climate change. Simulated groundwater recharge from four different land models are used to drive MODFLOW groundwater simulations. Results show relatively large discrepancies between recharge estimates among simulations. Forcing MODFLOW using recharge simulated by some of the LSMs in place of a simple water balance model marginally improves MODFLOW groundwater simulation. Further, our results support the efficacy of coupling LSMs to a sophisticated groundwater model such as MODFLOW. The coupling results in notable improvements in matching the historical groundwater levels through reduction of the skewness coefficient in percentage bias histogram (from 1.50 and 1.41 in original LSMs to 0.44 and 0.27, respectively, when MODFLOW is forced by groundwater recharge from LSMs) and reduction of bias. This modeling effort seeks to identify the best compromise between comprehensive land surface processes from global LSMs and advanced representation of groundwater from regional models.

@article{marsh_snowdrift-permitting_2024,
	title = {Snowdrift-{Permitting} {Simulations} of {Seasonal} {Snowpack} {Processes} {Over} {Large} {Mountain} {Extents}},
	volume = {60},
	copyright = {© 2024. The Author(s).},
	issn = {1944-7973},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2023WR036948},
	doi = {10.1029/2023WR036948},
	abstract = {The melt of seasonal snowpack in mountain regions provides downstream river basins with a critical supply of freshwater. Snowdrift-permitting models have been proposed as a way to accurately simulate snowpack heterogeneity that stems from differences in energy inputs, over winter redistribution, sublimation, melt, and variations in precipitation. However, these spatial scales can be computationally intractable for large extents. In this work, the multiscale Canadian Hydrological Model (CHM) was applied to simulate snowpacks at snowdrift-permitting scales (≈50 m) across the Canadian Cordillera and adjacent regions (1.37 million km2) forced by downscaled atmospheric data. The use of a multiscale land surface representation resulted in a reduction of computational elements of 98\% while preserving land-surface heterogeneity. CHM includes complex terrain windflow and radiative transfer calculations, lapses temperature, humidity, and precipitation with elevation, redistributes snow by avalanching, wind transport and forest canopy interception and calculates the energetics of canopy and surface snowpacks. Model outputs were compared to a set of multiscale observations including snow-covered area (SCA) from Sentinel and Landsat imagery, snow depth from uncrewed aerial system lidar, and point surface observations of depth and density. Including snow redistribution and sublimation processes improved the summer SCA r2 from 0.7 to 0.9. At larger scales, inclusion of snow redistribution processes delayed full snowpack ablation by an average of 33 days, demonstrating process emergence with scale. These simulations show how multiscale modeling can improve snowpack predictions to support prediction of water supply, droughts, and floods.},
	language = {en},
	number = {8},
	urldate = {2025-01-27},
	journal = {Water Resources Research},
	author = {Marsh, Christopher B. and Lv, Zhibang and Vionnet, Vincent and Harder, Phillip and Spiteri, Raymond J. and Pomeroy, John W.},
	year = {2024},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1029/2023WR036948},
	keywords = {NALCMS},
	pages = {e2023WR036948},
}

The melt of seasonal snowpack in mountain regions provides downstream river basins with a critical supply of freshwater. Snowdrift-permitting models have been proposed as a way to accurately simulate snowpack heterogeneity that stems from differences in energy inputs, over winter redistribution, sublimation, melt, and variations in precipitation. However, these spatial scales can be computationally intractable for large extents. In this work, the multiscale Canadian Hydrological Model (CHM) was applied to simulate snowpacks at snowdrift-permitting scales (≈50 m) across the Canadian Cordillera and adjacent regions (1.37 million km2) forced by downscaled atmospheric data. The use of a multiscale land surface representation resulted in a reduction of computational elements of 98% while preserving land-surface heterogeneity. CHM includes complex terrain windflow and radiative transfer calculations, lapses temperature, humidity, and precipitation with elevation, redistributes snow by avalanching, wind transport and forest canopy interception and calculates the energetics of canopy and surface snowpacks. Model outputs were compared to a set of multiscale observations including snow-covered area (SCA) from Sentinel and Landsat imagery, snow depth from uncrewed aerial system lidar, and point surface observations of depth and density. Including snow redistribution and sublimation processes improved the summer SCA r2 from 0.7 to 0.9. At larger scales, inclusion of snow redistribution processes delayed full snowpack ablation by an average of 33 days, demonstrating process emergence with scale. These simulations show how multiscale modeling can improve snowpack predictions to support prediction of water supply, droughts, and floods.

@article{schmidt_spatial_2024,
	title = {Spatial distribution of wildfire threat in the far north: exposure assessment in boreal communities},
	issn = {1573-0840},
	shorttitle = {Spatial distribution of wildfire threat in the far north},
	url = {https://doi.org/10.1007/s11069-023-06365-4},
	doi = {10.1007/s11069-023-06365-4},
	abstract = {Increased wildfire activity has raised concerns among communities about how to assess and prepare for this threat. There is a need for wildfire hazard assessment approaches that capture local variability to inform decisions, produce results understood by the public, and are updatable in a timely manner. We modified an existing approach to assess decadal wildfire hazards based primarily on ember dispersal and wildfire proximity, referencing landscape changes from 1984 through 2014. Our modifications created a categorical flammability hazard scheme, rather than dichotomous, and integrated wildfire exposure results across spatial scales. We used remote sensed land cover from four historical decadal points to create flammability hazard and wildfire exposure maps for three arctic communities (Anchorage and Fairbanks, Alaska and Whitehorse, Yukon). Within the Fairbanks study area, we compared 2014 flammability hazard, wildfire exposure, and FlamMap burn probabilities among burned (2014–2023) and unburned areas. Unlike burn probabilities, there were significantly higher in exposure values among burned and unburned locations (Wilcoxon; p {\textless} 0.001) and exposure rose as flammability hazard classes increased (Kruskal–Wallis; p {\textless} 0.001). Very high flammability hazard class supported 75\% of burned areas and burns tended to occur in areas with 60\% exposure or greater. Areas with high exposure values are more prone to burn and thus desirable for mitigation actions. By working with wildfire practitioners and communities, we created a tool that rapidly assesses wildfire hazards and is easily modified to help identify and prioritize mitigation activities.},
	language = {en},
	urldate = {2024-03-13},
	journal = {Natural Hazards},
	author = {Schmidt, Jennifer I. and Ziel, Robert H. and Calef, Monika P. and Varvak, Anna},
	month = jan,
	year = {2024},
	keywords = {NALCMS},
}

Increased wildfire activity has raised concerns among communities about how to assess and prepare for this threat. There is a need for wildfire hazard assessment approaches that capture local variability to inform decisions, produce results understood by the public, and are updatable in a timely manner. We modified an existing approach to assess decadal wildfire hazards based primarily on ember dispersal and wildfire proximity, referencing landscape changes from 1984 through 2014. Our modifications created a categorical flammability hazard scheme, rather than dichotomous, and integrated wildfire exposure results across spatial scales. We used remote sensed land cover from four historical decadal points to create flammability hazard and wildfire exposure maps for three arctic communities (Anchorage and Fairbanks, Alaska and Whitehorse, Yukon). Within the Fairbanks study area, we compared 2014 flammability hazard, wildfire exposure, and FlamMap burn probabilities among burned (2014–2023) and unburned areas. Unlike burn probabilities, there were significantly higher in exposure values among burned and unburned locations (Wilcoxon; p \textless 0.001) and exposure rose as flammability hazard classes increased (Kruskal–Wallis; p \textless 0.001). Very high flammability hazard class supported 75% of burned areas and burns tended to occur in areas with 60% exposure or greater. Areas with high exposure values are more prone to burn and thus desirable for mitigation actions. By working with wildfire practitioners and communities, we created a tool that rapidly assesses wildfire hazards and is easily modified to help identify and prioritize mitigation activities.

@article{ali_spatiotemporal_2024,
	title = {Spatiotemporal variability of runoff events in response to rainfall, snowmelt, and rain-on-snow in the {Lake} {Erie} {Basin}},
	volume = {53},
	issn = {2214-5818},
	url = {https://www.sciencedirect.com/science/article/pii/S2214581824001228},
	doi = {10.1016/j.ejrh.2024.101774},
	abstract = {Study Region
The Lake Erie Basin spanning Canada and the United States.
Study Focus
Countless studies have performed event-based hyetograph-hydrograph analyses. However, most studies focused on experimental forested catchments and rainfall-runoff analyses, thereby neglecting larger, mid-latitude, heterogenous watersheds where snowmelt and rain-on-snow events can generate significant runoff. The goal of the present study was, therefore, to examine runoff generation in contrasted watersheds, by: (1) quantifying the spatiotemporal variability of event-specific runoff response across the Lake Erie Basin; 2) assessing the difference in runoff response characteristics based on precipitation type; and 3) identifying the influence of event precipitation and watershed characteristics on runoff response. Daily gridded climate and gauged streamflow data spanning 2000–2019 were used for 99 watersheds, resulting in the analysis of 28,123 rainfall, snowmelt, rain-on-snow and mixed events and their associated runoff responses.
New Hydrological Insights for the Region
Rainfall events were rarely identified as the triggers of the largest runoff responses. Conversely, snowmelt and rain-on-snow events led to high-magnitude and flashy runoff responses for 70 out of 99 watersheds. Watershed characteristics pertaining to topography, soil, and land use were good predictors of the temporal variability of runoff response metrics. Given the link between runoff-driven nutrient mobilization and recurrent algal blooms in Lake Erie, this study offers a comprehensive assessment of the variability of runoff responses and triggering precipitation events across the large transboundary basin.},
	urldate = {2024-08-12},
	journal = {Journal of Hydrology: Regional Studies},
	author = {Ali, Geneviève and Siebert, Krystal and Mizero, Steven Mugisha},
	month = jun,
	year = {2024},
	keywords = {NALCMS},
	pages = {101774},
}

Study Region The Lake Erie Basin spanning Canada and the United States. Study Focus Countless studies have performed event-based hyetograph-hydrograph analyses. However, most studies focused on experimental forested catchments and rainfall-runoff analyses, thereby neglecting larger, mid-latitude, heterogenous watersheds where snowmelt and rain-on-snow events can generate significant runoff. The goal of the present study was, therefore, to examine runoff generation in contrasted watersheds, by: (1) quantifying the spatiotemporal variability of event-specific runoff response across the Lake Erie Basin; 2) assessing the difference in runoff response characteristics based on precipitation type; and 3) identifying the influence of event precipitation and watershed characteristics on runoff response. Daily gridded climate and gauged streamflow data spanning 2000–2019 were used for 99 watersheds, resulting in the analysis of 28,123 rainfall, snowmelt, rain-on-snow and mixed events and their associated runoff responses. New Hydrological Insights for the Region Rainfall events were rarely identified as the triggers of the largest runoff responses. Conversely, snowmelt and rain-on-snow events led to high-magnitude and flashy runoff responses for 70 out of 99 watersheds. Watershed characteristics pertaining to topography, soil, and land use were good predictors of the temporal variability of runoff response metrics. Given the link between runoff-driven nutrient mobilization and recurrent algal blooms in Lake Erie, this study offers a comprehensive assessment of the variability of runoff responses and triggering precipitation events across the large transboundary basin.

@article{costley_summer_2024,
	title = {Summer cave use by tricolored bats declined in response to white-nose syndrome despite persistence in winter hibernacula in the southeastern {United} {States}},
	volume = {105},
	issn = {0022-2372},
	url = {https://doi.org/10.1093/jmammal/gyae064},
	doi = {10.1093/jmammal/gyae064},
	abstract = {Several bat species have experienced rapid population declines in the northern United States and Canada in response to the white-nose syndrome (WNS) epizootic. The pathogen has since spread across the United States, including the Southeast, where relatively warm temperatures may change host–pathogen interactions. In the cave-rich Tennessee–Alabama–Georgia (TAG) region, we examined the impacts of WNS and forest cover on the Tricolored Bat (Perimyotis subflavus) metapopulation using a long-term data set of 832 cave surveys conducted in summer and winter from 2004 to 2022. Most bat colonies were small (\<30 individuals), and bats were more likely to be present and abundant in caves surrounded by high percent forest cover, reiterating the importance of forest management for bat conservation. When comparing the years before and after the pathogen arrived in 2010 to 2012, bat presence and abundance during winter hibernation did not change. This stability contrasts with significant declines in other studies, suggesting that Tricolored Bat populations respond differently to WNS in small colonies in the TAG region. Fewer tricolored bats used caves in the summer than during hibernation, but across all years, we observed 1,021 tricolored bats in 121 caves during summer surveys. Unlike stable winter trends, bat presence and abundance declined in the post-WNS period in summer, when cave use is optional. This first broad geographical analysis of summer cave use highlights a potentially important change in bat behavior. Disease surveillance and conservation efforts that target caves with relatively small Tricolored Bat colonies in winter and/or summer may be important for regional population persistence of this threatened species.},
	number = {5},
	urldate = {2026-05-22},
	journal = {Journal of Mammalogy},
	author = {Costley, Tessa and Hopkins, Skylar R and Meng, Sophie and Gajewski, Zachary and Niemiller, Matthew L},
	month = oct,
	year = {2024},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {1032--1043},
}

Several bat species have experienced rapid population declines in the northern United States and Canada in response to the white-nose syndrome (WNS) epizootic. The pathogen has since spread across the United States, including the Southeast, where relatively warm temperatures may change host–pathogen interactions. In the cave-rich Tennessee–Alabama–Georgia (TAG) region, we examined the impacts of WNS and forest cover on the Tricolored Bat (Perimyotis subflavus) metapopulation using a long-term data set of 832 cave surveys conducted in summer and winter from 2004 to 2022. Most bat colonies were small (<30 individuals), and bats were more likely to be present and abundant in caves surrounded by high percent forest cover, reiterating the importance of forest management for bat conservation. When comparing the years before and after the pathogen arrived in 2010 to 2012, bat presence and abundance during winter hibernation did not change. This stability contrasts with significant declines in other studies, suggesting that Tricolored Bat populations respond differently to WNS in small colonies in the TAG region. Fewer tricolored bats used caves in the summer than during hibernation, but across all years, we observed 1,021 tricolored bats in 121 caves during summer surveys. Unlike stable winter trends, bat presence and abundance declined in the post-WNS period in summer, when cave use is optional. This first broad geographical analysis of summer cave use highlights a potentially important change in bat behavior. Disease surveillance and conservation efforts that target caves with relatively small Tricolored Bat colonies in winter and/or summer may be important for regional population persistence of this threatened species.

@article{hanson_systematic_2024,
	title = {Systematic conservation prioritization with the prioritizr {R} package},
	volume = {n/a},
	copyright = {© 2024 The Author(s). Conservation Biology published by Wiley Periodicals LLC on behalf of Society for Conservation Biology.},
	issn = {1523-1739},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/cobi.14376},
	doi = {10.1111/cobi.14376},
	abstract = {Plans for expanding protected area systems (prioritizations) need to fulfill conservation objectives. They also need to account for other factors, such as economic feasibility and anthropogenic land-use requirements. Although prioritizations are often generated with decision support tools, most tools have limitations that hinder their use for decision-making. We outlined how the prioritizr R package (https://prioritizr.net) can be used for systematic conservation prioritization. This decision support tool provides a flexible interface to build conservation planning problems. It can leverage a variety of commercial (e.g., Gurobi) and open-source (e.g., CBC and SYMPHONY) exact algorithm solvers to identify optimal solutions in a short period. It is also compatible with a variety of spatially explicit (e.g., ESRI Shapefile, GeoTIFF) and nonspatial tabular (e.g., Microsoft Excel Spreadsheet) data formats. Additionally, it provides functionality for evaluating prioritizations, such as assessing the relative importance of different places selected by a prioritization. To showcase the prioritizr R package, we applied it to a case study based in Washington state (United States) for which we developed a prioritization to improve protected area coverage of native avifauna. We accounted for land acquisition costs, existing protected areas, places that might not be suitable for protected area establishment, and spatial fragmentation. We also conducted a benchmark analysis to examine the performance of different solvers. The prioritization identified 12,400 km2 of priority areas for increasing the percentage of species’ distributions covered by protected areas. Although open source and commercial solvers were able to quickly solve large-scale conservation planning problems, commercial solvers were required for complex, large-scale problems.. The prioritizr R package is available on the Comprehensive R Archive Network (CRAN). In addition to reserve selection, it can inform habitat restoration, connectivity enhancement, and ecosystem service provisioning. It has been used in numerous conservation planning exercises to inform best practices and aid real-world decision-making.},
	language = {en},
	number = {n/a},
	urldate = {2025-01-27},
	journal = {Conservation Biology},
	author = {Hanson, Jeffrey O. and Schuster, Richard and Strimas-Mackey, Matthew and Morrell, Nina and Edwards, Brandon P. M. and Arcese, Peter and Bennett, Joseph R. and Possingham, Hugh P.},
	month = sep,
	year = {2024},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/cobi.14376},
	keywords = {NALCMS},
	pages = {e14376},
}

Plans for expanding protected area systems (prioritizations) need to fulfill conservation objectives. They also need to account for other factors, such as economic feasibility and anthropogenic land-use requirements. Although prioritizations are often generated with decision support tools, most tools have limitations that hinder their use for decision-making. We outlined how the prioritizr R package (https://prioritizr.net) can be used for systematic conservation prioritization. This decision support tool provides a flexible interface to build conservation planning problems. It can leverage a variety of commercial (e.g., Gurobi) and open-source (e.g., CBC and SYMPHONY) exact algorithm solvers to identify optimal solutions in a short period. It is also compatible with a variety of spatially explicit (e.g., ESRI Shapefile, GeoTIFF) and nonspatial tabular (e.g., Microsoft Excel Spreadsheet) data formats. Additionally, it provides functionality for evaluating prioritizations, such as assessing the relative importance of different places selected by a prioritization. To showcase the prioritizr R package, we applied it to a case study based in Washington state (United States) for which we developed a prioritization to improve protected area coverage of native avifauna. We accounted for land acquisition costs, existing protected areas, places that might not be suitable for protected area establishment, and spatial fragmentation. We also conducted a benchmark analysis to examine the performance of different solvers. The prioritization identified 12,400 km2 of priority areas for increasing the percentage of species’ distributions covered by protected areas. Although open source and commercial solvers were able to quickly solve large-scale conservation planning problems, commercial solvers were required for complex, large-scale problems.. The prioritizr R package is available on the Comprehensive R Archive Network (CRAN). In addition to reserve selection, it can inform habitat restoration, connectivity enhancement, and ecosystem service provisioning. It has been used in numerous conservation planning exercises to inform best practices and aid real-world decision-making.

@article{saenz-ceja_temporal_2024,
	title = {Temporal and spatial patterns of fire regime disruption in conifer forests of western {North} {America}},
	volume = {0},
	issn = {0272-3646},
	url = {https://doi.org/10.1080/02723646.2024.2331292},
	doi = {10.1080/02723646.2024.2331292},
	abstract = {Temporal and spatial patterns of fire regime disruption were reconstructed in conifer forests of western North America from information on pre-disruption and disrupted mean fire intervals (MFIs) of 498 dendrochronology-based fire chronologies. We identified the conifer forest types most affected by MFI shift and the influence of land category designation on MFI change. We also mapped the years of the MFI shift, the last fire recorded, and disrupted/pre-disruption MFI ratios. Fire cessation and longer MFIs predominated in most fire chronologies and conifer forest types. MFI was significantly higher in most conifer forest types, with most differences in dry conifer forests. MFI shift occurred mainly before the designation of protected, federal, social-property, and private areas. MFI shift began in 1829 in the United States of America Southwest, a region subjected to prolonged fire exclusion and with the highest disrupted/pre-disruption MFI ratios. Fire regime disruption moved gradually into the Pacific Northwest and the Sierra Nevada until reaching the northern conifer forests of Canada and Alaska. In contrast, one-third of fire chronologies in Mexican conifer forests retained pre-disruption MFIs. Our findings allowed us to identify areas with MFIs outside of their natural variability, with prolonged fire exclusion, or with intact fire regimes.},
	number = {0},
	urldate = {2024-04-24},
	journal = {Physical Geography},
	author = {Sáenz-Ceja, Jesús E. and Mendoza, Manuel E.},
	year = {2024},
	note = {Publisher: Taylor \& Francis
\_eprint: https://doi.org/10.1080/02723646.2024.2331292},
	keywords = {NALCMS, Protected Areas},
	pages = {1--33},
}

Temporal and spatial patterns of fire regime disruption were reconstructed in conifer forests of western North America from information on pre-disruption and disrupted mean fire intervals (MFIs) of 498 dendrochronology-based fire chronologies. We identified the conifer forest types most affected by MFI shift and the influence of land category designation on MFI change. We also mapped the years of the MFI shift, the last fire recorded, and disrupted/pre-disruption MFI ratios. Fire cessation and longer MFIs predominated in most fire chronologies and conifer forest types. MFI was significantly higher in most conifer forest types, with most differences in dry conifer forests. MFI shift occurred mainly before the designation of protected, federal, social-property, and private areas. MFI shift began in 1829 in the United States of America Southwest, a region subjected to prolonged fire exclusion and with the highest disrupted/pre-disruption MFI ratios. Fire regime disruption moved gradually into the Pacific Northwest and the Sierra Nevada until reaching the northern conifer forests of Canada and Alaska. In contrast, one-third of fire chronologies in Mexican conifer forests retained pre-disruption MFIs. Our findings allowed us to identify areas with MFIs outside of their natural variability, with prolonged fire exclusion, or with intact fire regimes.

@article{fernandez-figueroa_green_2024,
	title = {The green convergence: {United} {States} lakes are collectively moving toward a eutrophic state},
	volume = {139},
	issn = {1568-9883},
	shorttitle = {The green convergence},
	url = {https://www.sciencedirect.com/science/article/pii/S1568988324001549},
	doi = {10.1016/j.hal.2024.102721},
	abstract = {Nutrient enrichment and climate change promote algal blooms, leading to many lakes being characterized as eutrophic (i.e., green) worldwide. We examined recent eutrophication trends of freshwater lakes at a national scale by collating 32 years (1990–2021) of growing season (July-September) in situ chlorophyll-a, nutrient, transparency, and climate data for 1,082 lakes across 32 freshwater ecoregions in the United States. Based on chlorophyll-a, 78.2 \% (427/546) of lakes initially exhibited eutrophic conditions and have remained eutrophic. Moreover, non-eutrophic lakes converged toward a eutrophic state, with oligotrophic (i.e., clear) or mesotrophic (i.e., moderately clear) lakes becoming greener, and hypereutrophic (i.e., very green) becoming less green. Optimized Hot Spot Analysis suggests lakes in the Appalachian Piedmont and Apalachicola freshwater ecoregions eutrophied more rapidly than other locations. Results suggest nutrient management targeting eutrophic lakes has hindered further degradation, but poor preventative management of clear lakes has led to their eutrophication.},
	urldate = {2025-01-27},
	journal = {Harmful Algae},
	author = {Fernandez-Figueroa, Edna G. and Rogers, Stephanie R. and Waters, Matthew N. and Wilson, Alan E.},
	month = nov,
	year = {2024},
	keywords = {NALCMS},
	pages = {102721},
}

Nutrient enrichment and climate change promote algal blooms, leading to many lakes being characterized as eutrophic (i.e., green) worldwide. We examined recent eutrophication trends of freshwater lakes at a national scale by collating 32 years (1990–2021) of growing season (July-September) in situ chlorophyll-a, nutrient, transparency, and climate data for 1,082 lakes across 32 freshwater ecoregions in the United States. Based on chlorophyll-a, 78.2 % (427/546) of lakes initially exhibited eutrophic conditions and have remained eutrophic. Moreover, non-eutrophic lakes converged toward a eutrophic state, with oligotrophic (i.e., clear) or mesotrophic (i.e., moderately clear) lakes becoming greener, and hypereutrophic (i.e., very green) becoming less green. Optimized Hot Spot Analysis suggests lakes in the Appalachian Piedmont and Apalachicola freshwater ecoregions eutrophied more rapidly than other locations. Results suggest nutrient management targeting eutrophic lakes has hindered further degradation, but poor preventative management of clear lakes has led to their eutrophication.

@article{hethcoat_unrecorded_2024,
	title = {Unrecorded {Tundra} {Fires} in {Canada}, 1986–2022},
	volume = {16},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {2072-4292},
	url = {https://www.mdpi.com/2072-4292/16/2/230},
	doi = {10.3390/rs16020230},
	abstract = {Climate-driven changes in fire regimes are expected across the pan-Arctic region. Trends in arctic fires are thought to be generally increasing; however, fire mapping across the region is far from comprehensive or systematic. We developed a new detection workflow and built a dataset of unrecorded tundra fires in Canada using Landsat data. We built a reference dataset of spectral indices from previously mapped fires in northern Canada to train a Random Forest model for detecting new fires between 1986 and 2022. In addition, we used time series information for each pixel to reduce false positives and narrow the large search space down to a finite set of regions that had experienced changes. We found 209 previously undetected fires in the Arctic and sub-Arctic regions, increasing the mapped burned area by approximately 30\%. The median fire size was small, with roughly 3/4 of the fires being {\textless}100 ha in size. The majority of newly detected fires (69\%) did not have satellite-derived hotspots associated with them. The dataset presented here is commission error-free and can be viewed as a reference dataset for future analyses. Moreover, future improvements and updates will leverage these data to improve the detection workflow outlined here, particularly for small and low-severity fires. These data can facilitate broader analyses that examine trends and environmental drivers of fire across the Arctic region. Such analyses could begin to untangle the mechanisms driving heterogeneous fire responses to climate observed across regions of the Circumpolar North.},
	language = {en},
	number = {2},
	urldate = {2024-03-20},
	journal = {Remote Sensing},
	author = {Hethcoat, Matthew G. and Jain, Piyush and Parisien, Marc-André and Skakun, Rob and Rogic, Luka and Whitman, Ellen},
	month = jan,
	year = {2024},
	note = {Number: 2
Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {NALCMS},
	pages = {230},
}

Climate-driven changes in fire regimes are expected across the pan-Arctic region. Trends in arctic fires are thought to be generally increasing; however, fire mapping across the region is far from comprehensive or systematic. We developed a new detection workflow and built a dataset of unrecorded tundra fires in Canada using Landsat data. We built a reference dataset of spectral indices from previously mapped fires in northern Canada to train a Random Forest model for detecting new fires between 1986 and 2022. In addition, we used time series information for each pixel to reduce false positives and narrow the large search space down to a finite set of regions that had experienced changes. We found 209 previously undetected fires in the Arctic and sub-Arctic regions, increasing the mapped burned area by approximately 30%. The median fire size was small, with roughly 3/4 of the fires being \textless100 ha in size. The majority of newly detected fires (69%) did not have satellite-derived hotspots associated with them. The dataset presented here is commission error-free and can be viewed as a reference dataset for future analyses. Moreover, future improvements and updates will leverage these data to improve the detection workflow outlined here, particularly for small and low-severity fires. These data can facilitate broader analyses that examine trends and environmental drivers of fire across the Arctic region. Such analyses could begin to untangle the mechanisms driving heterogeneous fire responses to climate observed across regions of the Circumpolar North.

@article{udell_using_2024,
	title = {Using mobile acoustic monitoring and false-positive {N}-mixture models to estimate bat abundance and population trends},
	volume = {94},
	copyright = {Published 2024. This article is a U.S. Government work and is in the public domain in the USA. Ecological Monographs published by Wiley Periodicals LLC on behalf of The Ecological Society of America.},
	issn = {1557-7015},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/ecm.1617},
	doi = {10.1002/ecm.1617},
	abstract = {Estimating the abundance of unmarked animal populations from acoustic data is challenging due to the inability to identify individuals and the need to adjust for observation biases including detectability (false negatives), species misclassification (false positives), and sampling exposure. Acoustic surveys conducted along mobile transects were designed to avoid counting individuals more than once, where raw counts are commonly treated as an index of abundance. More recently, false-positive abundance models have been developed to estimate abundance while accounting for imperfect detection and misclassification. We adapted these methods to model summertime abundance and trends of three species of bats at multiple spatial scales using acoustic recordings collected along mobile transects by partners of the North American Bat Monitoring Program (NABat) from 2012 to 2020. This multiscale modeling spanned individual transect routes, larger NABat grid cells (10 km × 10 km), and across the entire extent of modeled species ranges. We estimated relationships between species abundances and a suite of abiotic and biotic predictors (landcover types, climatological variables, physiographic diversity, building density, and the impacts of white-nose syndrome [WNS]) and found varying levels of support between species. We present clear evidence of substantial declines in populations of tricolored bats (Perimyotis subflavus) and little brown bats (Myotis lucifugus), declines that corresponded in space and time with the progression of WNS, a devastating disease of hibernating bats. In contrast, our analysis revealed that similar population-wide declines probably have not occurred in big brown bats (Eptesicus fuscus), a species known to be less affected by WNS. This study provides the first abundance-based species distribution predictions and population trends for bats in their summer ranges in North America. These models will probably be applicable to assessing wildlife populations in other monitoring programs where acoustic data are used or where false-negative and false-positive detections are present. Finally, our abundance framework (as a spatial point pattern process) can serve as a foundation from which more sophisticated integrated species distribution models that incorporate additional streams of monitoring data (e.g., stationary acoustics, captures) can be developed for North American bats.},
	language = {en},
	number = {4},
	urldate = {2025-01-27},
	journal = {Ecological Monographs},
	author = {Udell, Bradley J. and Straw, Bethany Rose and Loeb, Susan C. and Irvine, Kathryn M. and Thogmartin, Wayne E. and Lausen, Cori L. and Reichard, Jonathan D. and Coleman, Jeremy T. H. and Cryan, Paul M. and Frick, Winifred F. and Reichert, Brian E.},
	year = {2024},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/ecm.1617},
	keywords = {NALCMS},
	pages = {e1617},
}

Estimating the abundance of unmarked animal populations from acoustic data is challenging due to the inability to identify individuals and the need to adjust for observation biases including detectability (false negatives), species misclassification (false positives), and sampling exposure. Acoustic surveys conducted along mobile transects were designed to avoid counting individuals more than once, where raw counts are commonly treated as an index of abundance. More recently, false-positive abundance models have been developed to estimate abundance while accounting for imperfect detection and misclassification. We adapted these methods to model summertime abundance and trends of three species of bats at multiple spatial scales using acoustic recordings collected along mobile transects by partners of the North American Bat Monitoring Program (NABat) from 2012 to 2020. This multiscale modeling spanned individual transect routes, larger NABat grid cells (10 km × 10 km), and across the entire extent of modeled species ranges. We estimated relationships between species abundances and a suite of abiotic and biotic predictors (landcover types, climatological variables, physiographic diversity, building density, and the impacts of white-nose syndrome [WNS]) and found varying levels of support between species. We present clear evidence of substantial declines in populations of tricolored bats (Perimyotis subflavus) and little brown bats (Myotis lucifugus), declines that corresponded in space and time with the progression of WNS, a devastating disease of hibernating bats. In contrast, our analysis revealed that similar population-wide declines probably have not occurred in big brown bats (Eptesicus fuscus), a species known to be less affected by WNS. This study provides the first abundance-based species distribution predictions and population trends for bats in their summer ranges in North America. These models will probably be applicable to assessing wildlife populations in other monitoring programs where acoustic data are used or where false-negative and false-positive detections are present. Finally, our abundance framework (as a spatial point pattern process) can serve as a foundation from which more sophisticated integrated species distribution models that incorporate additional streams of monitoring data (e.g., stationary acoustics, captures) can be developed for North American bats.

@article{li_validation_2024,
	title = {Validation of the vertical canopy cover profile products derived from {GEDI} over selected forest sites},
	volume = {10},
	issn = {2666-0172},
	url = {https://www.sciencedirect.com/science/article/pii/S2666017224000427},
	doi = {10.1016/j.srs.2024.100158},
	abstract = {Canopy cover (CC) quantifies the proportion of canopy materials projected vertically onto the ground surface. CC is a crucial canopy structural variable and is commonly used in many ecological and climatic models. The vertical CC profile product is currently available from the Global Ecosystem Dynamics Investigation (GEDI). However, detailed information about the accuracy and uncertainty of the GEDI vertical CC profile product remains limited. The objective of this study is to validate the GEDI CC product over selected forest sites using reference values derived from digital hemispherical photography (DHP), airborne laser scanning (ALS) point clouds, and simulated waveforms. The accuracy of CC was quantified and analyzed regarding GEDI observation conditions, waveform processing, and estimation methods. The results show that the GEDI total CC correlates well with those estimated from DHP, ALS, and simulated waveform data (r2 = 0.65, 0.71, and 0.71, respectively) but is systematically underestimated (bias = −0.05, −0.11, and −0.07, respectively) based on reference data. Compared with the ALS-estimated CC, needleleaf forest shows the highest correlation for vertical CC (r2 ≥ 0.65) and shrubland shows the lowest bias for total CC (bias = −0.13). The mean absolute error (MAE) of the GEDI CC decreases from 0.15 to 0.09 as the estimation height increases from ground to 35 m. The GEDI total CCs derived from the waveform interpretation algorithms A2 and A6 display the highest r2 (≥ 0.6) and smallest RMSE (≤ 0.23) compared to those of the other algorithms. The CC accuracy increases with beam sensitivity and decreases with increasing canopy cover. The GEDI CC was improved at moderate CC values using a canopy-to-ground backscattering coefficient ratio (ρv/ρg) determined with the regression method. The partial difference between GEDI CC and ALS CC is attributed to definitional discrepancies. Further improvement of the CC algorithm can be made by using vegetation-specific waveform processing algorithms and realistic ρv/ρg values.},
	urldate = {2025-01-17},
	journal = {Science of Remote Sensing},
	author = {Li, Yu and Fang, Hongliang and Wang, Yao and Li, Sijia and Ma, Tian and Wu, Yunjia and Tang, Hao},
	month = dec,
	year = {2024},
	keywords = {NALCMS},
	pages = {100158},
}

Canopy cover (CC) quantifies the proportion of canopy materials projected vertically onto the ground surface. CC is a crucial canopy structural variable and is commonly used in many ecological and climatic models. The vertical CC profile product is currently available from the Global Ecosystem Dynamics Investigation (GEDI). However, detailed information about the accuracy and uncertainty of the GEDI vertical CC profile product remains limited. The objective of this study is to validate the GEDI CC product over selected forest sites using reference values derived from digital hemispherical photography (DHP), airborne laser scanning (ALS) point clouds, and simulated waveforms. The accuracy of CC was quantified and analyzed regarding GEDI observation conditions, waveform processing, and estimation methods. The results show that the GEDI total CC correlates well with those estimated from DHP, ALS, and simulated waveform data (r2 = 0.65, 0.71, and 0.71, respectively) but is systematically underestimated (bias = −0.05, −0.11, and −0.07, respectively) based on reference data. Compared with the ALS-estimated CC, needleleaf forest shows the highest correlation for vertical CC (r2 ≥ 0.65) and shrubland shows the lowest bias for total CC (bias = −0.13). The mean absolute error (MAE) of the GEDI CC decreases from 0.15 to 0.09 as the estimation height increases from ground to 35 m. The GEDI total CCs derived from the waveform interpretation algorithms A2 and A6 display the highest r2 (≥ 0.6) and smallest RMSE (≤ 0.23) compared to those of the other algorithms. The CC accuracy increases with beam sensitivity and decreases with increasing canopy cover. The GEDI CC was improved at moderate CC values using a canopy-to-ground backscattering coefficient ratio (ρv/ρg) determined with the regression method. The partial difference between GEDI CC and ALS CC is attributed to definitional discrepancies. Further improvement of the CC algorithm can be made by using vegetation-specific waveform processing algorithms and realistic ρv/ρg values.

@article{dagher_variation_2024,
	title = {Variation in white-tailed and mule deer dental metrics is associated with precipitation gradients in the {Americas}},
	volume = {324},
	copyright = {© 2024 The Author(s). Journal of Zoology published by John Wiley \& Sons Ltd on behalf of Zoological Society of London.},
	issn = {1469-7998},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/jzo.13220},
	doi = {10.1111/jzo.13220},
	abstract = {Investigating the relationship between the physical environment and organismal adaptation is crucial to understanding the selective pressures that drive mammalian evolution. Of the varied approaches to exploring this relationship, macroscopic tooth wear analyses have become widely used due to their economic and simple methodologies. However, more work is needed to understand how assessments of wear patterns operate within finer levels of dietary and environmental contexts. It is specifically unclear if and how tooth wear differs inter- and intraspecifically between geographically widespread, large-bodied mammalian populations. This project characterizes molar hypsodonty indices and mesowear scores of white-tailed deer (Odocoileus virginianus) and mule deer (Odocoileus hemionus) populations across North and Central America, investigating if and how molar wear and morphology vary over the deer's large and ecologically variable geographic distribution. While mesowear scores generally do not strongly track environmental signals within and between Odocoileus species, hypsodonty indices reveal a strong correlation between crown height and aridity, which likely represents an adaptive response to abrasive diets in areas with low precipitation.},
	language = {en},
	number = {4},
	urldate = {2026-05-22},
	journal = {Journal of Zoology},
	author = {Dagher, J. and Greiner, E.},
	year = {2024},
	note = {\_eprint: https://zslpublications.onlinelibrary.wiley.com/doi/pdf/10.1111/jzo.13220},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {325--338},
}

Investigating the relationship between the physical environment and organismal adaptation is crucial to understanding the selective pressures that drive mammalian evolution. Of the varied approaches to exploring this relationship, macroscopic tooth wear analyses have become widely used due to their economic and simple methodologies. However, more work is needed to understand how assessments of wear patterns operate within finer levels of dietary and environmental contexts. It is specifically unclear if and how tooth wear differs inter- and intraspecifically between geographically widespread, large-bodied mammalian populations. This project characterizes molar hypsodonty indices and mesowear scores of white-tailed deer (Odocoileus virginianus) and mule deer (Odocoileus hemionus) populations across North and Central America, investigating if and how molar wear and morphology vary over the deer's large and ecologically variable geographic distribution. While mesowear scores generally do not strongly track environmental signals within and between Odocoileus species, hypsodonty indices reveal a strong correlation between crown height and aridity, which likely represents an adaptive response to abrasive diets in areas with low precipitation.

@article{leon-pesqueira_vascular_2024,
	title = {Vascular plants of the {Médanos} de {Samalayuca} natural protected area, {Chihuahua}, {Mexico}},
	volume = {102},
	copyright = {Copyright (c) 2023 Botanical Sciences},
	issn = {2007-4476},
	url = {https://botanicalsciences.com.mx/index.php/botanicalSciences/article/view/3369},
	doi = {10.17129/botsci.3369},
	abstract = {Background: Inland sand dunes are expanding and increasing mobility. Knowledge on the plants growing on them is keystone for their management. One of the largest inland dune systems in Mexico is the Médanos de Samalayuca area.
Questions: How many and which species of vascular plants are in Samalayuca? Which is the distribution pattern of that flora? Are there endemisms? Are there species of conservation concern?
Studied species: Vascular plants.
Study site and dates: Médanos de Samalayuca protected area, northern Chihuahua, Mexico; 2017-2022.
Methods: A database was generated based on literature, electronic sources, herbarium specimens, photographing, and collection and identification of materials. Distribution, endemism level and conservation status were recorded.
Results: The updated checklist of vascular plants for Samalayuca includes 400 species of 246 genera and 65 families. Most species grow in Mixed desert scrub and in Sand dune vegetation. Almost a half are restricted to the Megamexico 1 region, followed by the North American element. One species is Threatened according to the Mexican Official Norm NOM-059, while two are Vulnerable and one is Almost threatened according to the IUCN. Ribes fontinale appears to be extinct.
Conclusions: Considering the arid, extreme climate and the low stability of the psammophilous vegetation, the flora of Samalayuca is richer than expected. The area is home to regional and local endemics. The data and information generated here is baseline for further management programs and action planning to protect these fragile ecosystems and the adjacent communities.},
	language = {en},
	number = {1},
	urldate = {2024-08-12},
	journal = {Botanical Sciences},
	author = {León-Pesqueira, Laura De and Gatica-Colima, Ana Bertha and González-Elizondo, M. Socorro},
	year = {2024},
	note = {Number: 1},
	keywords = {Terrestrial Ecoregions},
	pages = {256--272},
}

Background: Inland sand dunes are expanding and increasing mobility. Knowledge on the plants growing on them is keystone for their management. One of the largest inland dune systems in Mexico is the Médanos de Samalayuca area. Questions: How many and which species of vascular plants are in Samalayuca? Which is the distribution pattern of that flora? Are there endemisms? Are there species of conservation concern? Studied species: Vascular plants. Study site and dates: Médanos de Samalayuca protected area, northern Chihuahua, Mexico; 2017-2022. Methods: A database was generated based on literature, electronic sources, herbarium specimens, photographing, and collection and identification of materials. Distribution, endemism level and conservation status were recorded. Results: The updated checklist of vascular plants for Samalayuca includes 400 species of 246 genera and 65 families. Most species grow in Mixed desert scrub and in Sand dune vegetation. Almost a half are restricted to the Megamexico 1 region, followed by the North American element. One species is Threatened according to the Mexican Official Norm NOM-059, while two are Vulnerable and one is Almost threatened according to the IUCN. Ribes fontinale appears to be extinct. Conclusions: Considering the arid, extreme climate and the low stability of the psammophilous vegetation, the flora of Samalayuca is richer than expected. The area is home to regional and local endemics. The data and information generated here is baseline for further management programs and action planning to protect these fragile ecosystems and the adjacent communities.

@incollection{schlafke_waters_2024,
	address = {Cham},
	title = {Waters and {Geology} of the {Dakotas}},
	isbn = {978-3-031-38040-2},
	url = {https://doi.org/10.1007/978-3-031-38040-2_1},
	abstract = {This chapter describes the historical and geological foundations relevant to the current fish populations of North Dakota (ND) and South Dakota (SD). It starts with a brief description of the political and geological history of the area that eventually became the states of North Dakota and South Dakota in the United States of America. Historical fish assemblages are then described, followed by an in-depth review of the eight level III ecoregions. This chapter then concludes with a review of each of the major river systems in each state.},
	language = {en},
	urldate = {2024-11-20},
	booktitle = {Fishes of the {Dakotas}},
	publisher = {Springer International Publishing},
	author = {Schlafke, Kathryn E. and Wagner, Matthew D. and Pasbrig, Chelsey A.},
	editor = {Schlafke, Kathryn E. and Wagner, Matthew D. and Pasbrig, Chelsey A. and Barnes, Michael},
	year = {2024},
	doi = {10.1007/978-3-031-38040-2_1},
	keywords = {Terrestrial Ecoregions (Griffith 2010)},
	pages = {1--17},
}

This chapter describes the historical and geological foundations relevant to the current fish populations of North Dakota (ND) and South Dakota (SD). It starts with a brief description of the political and geological history of the area that eventually became the states of North Dakota and South Dakota in the United States of America. Historical fish assemblages are then described, followed by an in-depth review of the eight level III ecoregions. This chapter then concludes with a review of each of the major river systems in each state.

@article{christianson_wildland_2024,
	title = {Wildland fire evacuations in {Canada} from 1980 to 2021},
	volume = {33},
	issn = {1049-8001},
	url = {https://doi.org/10.1071/WF23097},
	doi = {10.1071/WF23097},
	abstract = {Every year, people in Canada are evacuated due to wildland fires to avoid death, injury, and illness from fire and smoke events.In this paper, we provide an overview of evacuations recorded in the Canadian Wildland Fire Evacuation Database between 1980 and 2021.Our analysis covers evacuations in Canada from 1980 to 2021. We provide summary statistics including number of evacuations and evacuees, evacuation duration, seasonality, evacuation causes, community types, structure losses, and fatalities. We also investigate temporal and spatial patterns.Between 1980 and 2021, there were 1393 wildland fire evacuation events with 576,747 people evacuated. During this period, there was an overall increase in frequency of evacuations, number of evacuees, and duration of events. Structure loss occurred during 194 evacuation events, with 4105 homes burned. We estimate wildland fire evacuations cost at least CAD3.7 billion (excluding structural losses), jumping to CAD4.6 billion if we include productivity losses. Indigenous peoples are disproportionately impacted in wildfire evacuations compared to the general Canadian population.Wildland fire evacuations continue to occur across Canada and are increasing.The findings from this study give us a better understanding of the characteristics of wildland fire evacuations, which can help guide emergency management.},
	number = {7},
	urldate = {2026-05-22},
	journal = {International Journal of Wildland Fire},
	author = {Christianson, Amy Cardinal and Johnston, Lynn M. and Oliver, Jacqueline A. and Watson, David and Young, David and MacDonald, Heather and Little, John and Macnab, Bruce and Gonzalez Bautista, Noemie},
	month = jun,
	year = {2024},
	keywords = {Populated Places},
	pages = {WF23097},
}

Every year, people in Canada are evacuated due to wildland fires to avoid death, injury, and illness from fire and smoke events.In this paper, we provide an overview of evacuations recorded in the Canadian Wildland Fire Evacuation Database between 1980 and 2021.Our analysis covers evacuations in Canada from 1980 to 2021. We provide summary statistics including number of evacuations and evacuees, evacuation duration, seasonality, evacuation causes, community types, structure losses, and fatalities. We also investigate temporal and spatial patterns.Between 1980 and 2021, there were 1393 wildland fire evacuation events with 576,747 people evacuated. During this period, there was an overall increase in frequency of evacuations, number of evacuees, and duration of events. Structure loss occurred during 194 evacuation events, with 4105 homes burned. We estimate wildland fire evacuations cost at least CAD3.7 billion (excluding structural losses), jumping to CAD4.6 billion if we include productivity losses. Indigenous peoples are disproportionately impacted in wildfire evacuations compared to the general Canadian population.Wildland fire evacuations continue to occur across Canada and are increasing.The findings from this study give us a better understanding of the characteristics of wildland fire evacuations, which can help guide emergency management.

@article{iverson_winter_2024,
	title = {Winter {GPS} tagging reveals home ranges during the breeding season for a boreal-nesting migrant songbird, the {Golden}-crowned {Sparrow}},
	volume = {19},
	issn = {1932-6203},
	url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0305369},
	doi = {10.1371/journal.pone.0305369},
	abstract = {Determining space use for species is fundamental to understanding their ecology, and tracking animals can reveal insights into their spatial ecology on home ranges and territories. Recent technological advances have led to GPS-tracking devices light enough for birds as small as {\textasciitilde}30 g, creating novel opportunities to remotely monitor fine-scale movements and space use for these smaller species. We tested whether miniaturized GPS tags can allow us to understand space use of migratory birds away from their capture sites and sought to understand both pre-breeding space use as well as territory and habitat use on the breeding grounds. We used GPS tags to characterize home ranges on the breeding grounds for a migratory songbird with limited available breeding information, the Golden-crowned Sparrow (Zonotrichia atricapilla). Using GPS points from 23 individuals across 26 tags (three birds tagged twice), we found home ranges in Alaska and British Columbia were on average 44.1 ha (95\% kernel density estimate). In addition, estimates of territory sizes based on field observations (mean 2.1 ha, 95\% minimum convex polygon [MCP]) were three times smaller than 95\% MCPs created using GPS tags (mean 6.5 ha). Home ranges included a variety of land cover classes, with shrubland particularly dominant (64–100\% of home range cover for all but one bird). Three birds tracked twice returned to the same breeding area each year, supporting high breeding site fidelity for this species. We found reverse spring migration for five birds that flew up to 154 km past breeding destinations before returning. GPS-tracking technology allowed for critical ecological insights into this migratory species that breeds in very remote locations.},
	language = {en},
	number = {6},
	urldate = {2024-08-12},
	journal = {PLOS ONE},
	author = {Iverson, Autumn R. and Humple, Diana L. and Cormier, Renée L. and Hahn, Thomas P. and Block, Theadora A. and Shizuka, Daizaburo and Lyon, Bruce E. and Chaine, Alexis S. and Hudson, Emily J. and Hull, Elisha M.},
	month = jun,
	year = {2024},
	note = {Publisher: Public Library of Science},
	keywords = {NALCMS},
	pages = {e0305369},
}

Determining space use for species is fundamental to understanding their ecology, and tracking animals can reveal insights into their spatial ecology on home ranges and territories. Recent technological advances have led to GPS-tracking devices light enough for birds as small as ~30 g, creating novel opportunities to remotely monitor fine-scale movements and space use for these smaller species. We tested whether miniaturized GPS tags can allow us to understand space use of migratory birds away from their capture sites and sought to understand both pre-breeding space use as well as territory and habitat use on the breeding grounds. We used GPS tags to characterize home ranges on the breeding grounds for a migratory songbird with limited available breeding information, the Golden-crowned Sparrow (Zonotrichia atricapilla). Using GPS points from 23 individuals across 26 tags (three birds tagged twice), we found home ranges in Alaska and British Columbia were on average 44.1 ha (95% kernel density estimate). In addition, estimates of territory sizes based on field observations (mean 2.1 ha, 95% minimum convex polygon [MCP]) were three times smaller than 95% MCPs created using GPS tags (mean 6.5 ha). Home ranges included a variety of land cover classes, with shrubland particularly dominant (64–100% of home range cover for all but one bird). Three birds tracked twice returned to the same breeding area each year, supporting high breeding site fidelity for this species. We found reverse spring migration for five birds that flew up to 154 km past breeding destinations before returning. GPS-tracking technology allowed for critical ecological insights into this migratory species that breeds in very remote locations.

@article{pruitt_winter_2024,
	title = {Winter occurrence and roosting behavior of the secretive {Northern} {Saw}-whet {Owl} ({Aegolius} acadicus) at the southern edge of its range},
	volume = {136},
	issn = {1559-4491},
	url = {https://doi.org/10.1676/23-00074},
	doi = {10.1676/23-00074},
	abstract = {Understanding a species’ distribution is vital for making sound conservation and management decisions. Secretive behaviors and complicated seasonal movement patterns have made range delimitation surprisingly elusive for some North American birds, including the Northern Saw-whet Owl (Aegolius acadicus). Despite being among the most common of North American forest owls, only the species’ breeding range is well demarcated. This has resulted in the species historically being considered a “northern” bird, with eastern migratory and nonbreeding ranges extending only as far south as central Missouri and eastern Tennessee. Recent banding efforts have shown that saw-whet owls are fall migrants much farther south. We extend this work by investigating stopover duration and nonbreeding habitat selection during 2 winters at the edge of the species’ southern distribution in the Ozark Highlands of northwest Arkansas. We used radio telemetry to track 27 owls, with 17 individuals detected at least once post-release (n = 54 surveys and 131 total detections). Length of stay in the study area was most influenced by year—birds remained an average of 3.6 weeks longer during an irruption year—and our data suggest that the species uses the Ozark Highlands for both nonbreeding residency and brief stopover periods. During the 2 year study, 37\% of marked owls were winter residents, 26\% remained in the area temporarily, and 37\% were not redetected. Winter habitat preferences of saw-whet owls in the southeast are consistent with what is known about the species in its more northernly range, with birds selecting conifers on south-facing slopes in areas with an open understory. Overall, our results suggest that saw-whet owls are not rare fall migrants and winter residents in Arkansas as was previously assumed, and more generally, are likely underappreciated winter predators in southern pine ecosystems.},
	number = {3},
	urldate = {2026-05-29},
	journal = {The Wilson Journal of Ornithology},
	author = {Pruitt, Mitchell L. and Smith, Kimberly G. and Mortensen, Jennifer L.},
	month = sep,
	year = {2024},
	note = {Publisher: Taylor \& Francis
\_eprint: https://doi.org/10.1676/23-00074},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {293--306},
}

Understanding a species’ distribution is vital for making sound conservation and management decisions. Secretive behaviors and complicated seasonal movement patterns have made range delimitation surprisingly elusive for some North American birds, including the Northern Saw-whet Owl (Aegolius acadicus). Despite being among the most common of North American forest owls, only the species’ breeding range is well demarcated. This has resulted in the species historically being considered a “northern” bird, with eastern migratory and nonbreeding ranges extending only as far south as central Missouri and eastern Tennessee. Recent banding efforts have shown that saw-whet owls are fall migrants much farther south. We extend this work by investigating stopover duration and nonbreeding habitat selection during 2 winters at the edge of the species’ southern distribution in the Ozark Highlands of northwest Arkansas. We used radio telemetry to track 27 owls, with 17 individuals detected at least once post-release (n = 54 surveys and 131 total detections). Length of stay in the study area was most influenced by year—birds remained an average of 3.6 weeks longer during an irruption year—and our data suggest that the species uses the Ozark Highlands for both nonbreeding residency and brief stopover periods. During the 2 year study, 37% of marked owls were winter residents, 26% remained in the area temporarily, and 37% were not redetected. Winter habitat preferences of saw-whet owls in the southeast are consistent with what is known about the species in its more northernly range, with birds selecting conifers on south-facing slopes in areas with an open understory. Overall, our results suggest that saw-whet owls are not rare fall migrants and winter residents in Arkansas as was previously assumed, and more generally, are likely underappreciated winter predators in southern pine ecosystems.

@article{yeardley_comparison_2023,
	title = {A {Comparison} of {Two} {Macroinvertebrate} {Multi}-{Plate} {Sampling} {Methods} to {Inform} {Great} {Lakes} {Monitoring} and {Remediation} {Efforts}},
	volume = {14},
	copyright = {http://creativecommons.org/licenses/by/4.0/},
	url = {https://www.scirp.org/journal/paperinformation.aspx?paperid=129647},
	doi = {10.4236/jep.2023.1412052},
	abstract = {Hester-Dendy (HD) multi-plate samplers have been widely used by state and federal government agencies for bioassessment of water quality through use of macroinvertebrate community data. To help guide remediation and restoration efforts at the Niagara River Great Lakes Area of Concern site, a multi-agency study was conducted in 2014 to assess the contribution of seven major urban tributaries on the US side of the river toward the impairment of the Niagara River. As part of this study, macroinvertebrate communities were sampled using two co-located versions of HD samplers: one version used by the New York State Department of Environmental Conservation (NYSDEC) and another by the US Environmental Protection Agency Office of Research and Development. Samplers were deployed in tributaries in highly developed watersheds with high percent impervious surface. The two sampling methods varied in terms of number and size of plates, between-plate spacing, and deployment method. Comparison of the similarity/grouping of communities with multivariate ordination techniques, Nonmetric Multidimensional Scaling and Multi-Response Permutation Procedure, showed that both methods were able to detect differences in communities at stations, despite some grouping by month and method. The indices and metrics derived from the two HD methods were found to give comparable but not identical assessments of water quality. Despite their differences, the methods were robust with respect to water quality categories derived from indices used nationally (HBI) and by NY state (BAP). For the common richness metrics, total taxa and EPT richness, there was no statistical difference between means from 3 samplings. Some metrics, especially percent tolerant collector-gatherer individuals, did show significant differences at certain stations. Indicator Species Analysis showed some taxa associated with each method. The observed community differences were thought mostly due to the difference in sampler deployment position.},
	language = {en},
	number = {12},
	urldate = {2024-03-11},
	journal = {Journal of Environmental Protection},
	author = {Yeardley, Roger and Duffy, Brian and Kimbrough, Kimani and Lazorchak, Jim and Mills, Marc A. and Johnson, Ed},
	month = dec,
	year = {2023},
	note = {Number: 12
Publisher: Scientific Research Publishing},
	keywords = {NALCMS},
	pages = {933--953},
}

Hester-Dendy (HD) multi-plate samplers have been widely used by state and federal government agencies for bioassessment of water quality through use of macroinvertebrate community data. To help guide remediation and restoration efforts at the Niagara River Great Lakes Area of Concern site, a multi-agency study was conducted in 2014 to assess the contribution of seven major urban tributaries on the US side of the river toward the impairment of the Niagara River. As part of this study, macroinvertebrate communities were sampled using two co-located versions of HD samplers: one version used by the New York State Department of Environmental Conservation (NYSDEC) and another by the US Environmental Protection Agency Office of Research and Development. Samplers were deployed in tributaries in highly developed watersheds with high percent impervious surface. The two sampling methods varied in terms of number and size of plates, between-plate spacing, and deployment method. Comparison of the similarity/grouping of communities with multivariate ordination techniques, Nonmetric Multidimensional Scaling and Multi-Response Permutation Procedure, showed that both methods were able to detect differences in communities at stations, despite some grouping by month and method. The indices and metrics derived from the two HD methods were found to give comparable but not identical assessments of water quality. Despite their differences, the methods were robust with respect to water quality categories derived from indices used nationally (HBI) and by NY state (BAP). For the common richness metrics, total taxa and EPT richness, there was no statistical difference between means from 3 samplings. Some metrics, especially percent tolerant collector-gatherer individuals, did show significant differences at certain stations. Indicator Species Analysis showed some taxa associated with each method. The observed community differences were thought mostly due to the difference in sampler deployment position.

@phdthesis{moalemi_machine_2023,
	type = {Master of {Science} ({MSc})},
	title = {A {Machine} {Learning} {Approach} to {Classify} {Open} {Water} and {Ice} {Cover} on {Slave} {River} {Delta}},
	url = {https://scholars.wlu.ca/etd/2598},
	school = {Wilfrid Laurier University},
	author = {Moalemi, Ida},
	month = jan,
	year = {2023},
	keywords = {Precipitation, Temperature},
}

@article{heim_review_2023,
	title = {A {Review} of {User} {Perceptions} of {Drought} {Indices} and {Indicators} {Used} in the {Diverse} {Climates} of {North} {America}},
	volume = {14},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {2073-4433},
	url = {https://www.mdpi.com/2073-4433/14/12/1794},
	doi = {10.3390/atmos14121794},
	abstract = {Drought monitoring and early detection have improved greatly in recent decades through the development and refinement of numerous indices and indicators. However, a lack of guidance, based on user experience, exists as to which drought-monitoring tools are most appropriate in a given location. This review paper summarizes the results of targeted user engagement and the published literature to improve the understanding of drought across North America and to enhance the utility of drought-monitoring tools. Workshops and surveys were used to assess and make general conclusions about the perceived performance of drought indicators, indices and impact information used for monitoring drought in the five main Köppen climate types (Tropical, Temperate, Continental, Polar Tundra, Dry) found across Canada, Mexico, and the United States. In Tropical, humid Temperate, and southerly Continental climates, droughts are perceived to be more short-term (less than 6 months) in duration rather than long-term (more than 6 months). In Polar Tundra climates, Dry climates, Temperate climates with dry warm seasons, and northerly Continental climates, droughts are perceived to be more long-term than short-term. In general, agricultural and hydrological droughts were considered to be the most important drought types. Drought impacts related to agriculture, water supply, ecosystem, and human health were rated to be of greatest importance. Users identified the most effective indices and indicators for monitoring drought across North America to be the U.S. Drought Monitor (USDM) and Standardized Precipitation Index (SPI) (or another measure of precipitation anomaly), followed by the Normalized Difference Vegetation Index (NDVI) (or another satellite-observed vegetation index), temperature anomalies, crop status, soil moisture, streamflow, reservoir storage, water use (demand), and reported drought impacts. Users also noted the importance of indices that measure evapotranspiration, evaporative demand, and snow water content. Drought indices and indicators were generally thought to perform equally well across seasons in Tropical and colder Continental climates, but their performance was perceived to vary seasonally in Dry, Temperate, Polar Tundra, and warmer Continental climates, with improved performance during warm and wet times of the year. The drought indices and indicators, in general, were not perceived to perform equally well across geographies. This review paper provides guidance on when (time of year) and where (climate zone) the more popular drought indices and indicators should be used. The paper concludes by noting the importance of understanding how drought, its impacts, and its indicators are changing over time as the climate warms and by recommending ways to strengthen the use of indices and indicators in drought decision making.},
	language = {en},
	number = {12},
	urldate = {2023-12-19},
	journal = {Atmosphere},
	author = {Heim, Richard R. and Bathke, Deborah and Bonsal, Barrie and Cooper, Ernest W. T. and Hadwen, Trevor and Kodama, Kevin and McEvoy, Dan and Muth, Meredith and Nielsen-Gammon, John W. and Prendeville, Holly R. and Ramirez, Reynaldo Pascual and Rippey, Brad and Simeral, David B. and Thoman, Richard L. and Timlin, Michael S. and Weight, Elizabeth},
	month = dec,
	year = {2023},
	note = {Number: 12
Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {Climate Zones},
	pages = {1794},
}

Drought monitoring and early detection have improved greatly in recent decades through the development and refinement of numerous indices and indicators. However, a lack of guidance, based on user experience, exists as to which drought-monitoring tools are most appropriate in a given location. This review paper summarizes the results of targeted user engagement and the published literature to improve the understanding of drought across North America and to enhance the utility of drought-monitoring tools. Workshops and surveys were used to assess and make general conclusions about the perceived performance of drought indicators, indices and impact information used for monitoring drought in the five main Köppen climate types (Tropical, Temperate, Continental, Polar Tundra, Dry) found across Canada, Mexico, and the United States. In Tropical, humid Temperate, and southerly Continental climates, droughts are perceived to be more short-term (less than 6 months) in duration rather than long-term (more than 6 months). In Polar Tundra climates, Dry climates, Temperate climates with dry warm seasons, and northerly Continental climates, droughts are perceived to be more long-term than short-term. In general, agricultural and hydrological droughts were considered to be the most important drought types. Drought impacts related to agriculture, water supply, ecosystem, and human health were rated to be of greatest importance. Users identified the most effective indices and indicators for monitoring drought across North America to be the U.S. Drought Monitor (USDM) and Standardized Precipitation Index (SPI) (or another measure of precipitation anomaly), followed by the Normalized Difference Vegetation Index (NDVI) (or another satellite-observed vegetation index), temperature anomalies, crop status, soil moisture, streamflow, reservoir storage, water use (demand), and reported drought impacts. Users also noted the importance of indices that measure evapotranspiration, evaporative demand, and snow water content. Drought indices and indicators were generally thought to perform equally well across seasons in Tropical and colder Continental climates, but their performance was perceived to vary seasonally in Dry, Temperate, Polar Tundra, and warmer Continental climates, with improved performance during warm and wet times of the year. The drought indices and indicators, in general, were not perceived to perform equally well across geographies. This review paper provides guidance on when (time of year) and where (climate zone) the more popular drought indices and indicators should be used. The paper concludes by noting the importance of understanding how drought, its impacts, and its indicators are changing over time as the climate warms and by recommending ways to strengthen the use of indices and indicators in drought decision making.

@techreport{dupont_social-ecological_2023,
	type = {preprint},
	title = {A social-ecological geography of southern {Canadian} {Lakes}},
	url = {http://biorxiv.org/lookup/doi/10.1101/2023.03.09.531893},
	abstract = {Abstract
          Anthropogenic pressures, including urban and agricultural expansion, can negatively influence a lake’s capacity to provide aquatic ecosystem services (ES). However, identifying lakes most at risk of losing their ES requires integrating information on lake ecological state, global change threats, and ES demand. Here, we provide a social-ecological framework that combines these features within a regional context based on an ecological evaluation of the state of 659 lakes across Canada. From deviation of impacted lakes to reference ones, we identified much higher concentrations of total nitrogen and chloride as the main indicators of altered lake ecological state in all regions identified. Lake ecological state was mapped using an additive colour model along with regional scores of threat levels and recreational ES demand. Population density and agriculture were linked to high lake vulnerability. Lakes in Southern Ontario were most concerning, being highly altered, under threat, and heavily used. Lakes near urban centers along coasts were altered and used, but less threatened, whereas those in the Prairies were altered and threatened, but less used. Our novel framework provides the first social-ecological geography of Canadian lakes, and, is a promising tool to assess lake state and vulnerability at scales relevant for management.
          
            Plan language summary
            Plain language title: Assessing overall lake health across Canada to identify sites for restoration and conservation
            Canadians love to swim, fish, and navigate in and on the countless lakes across the country. But Canadian lakes are under a considerable amount of pressure from human activities in their watershed. The expansion of cities, intensive farming, wetland loss, and industrial development all results in the transfer of pollutants to aquatic habitats, threatening the health of lakes and the ecosystem services they provide. Where are lakes being used across Canada? What condition are they in and is their use under threat from different pressures? To answer these questions, we combined information from many different sources, including a national scale lake assessment, through the NSERC Strategic Network Cluster Lake Pulse to create the first social-ecological geography of southern Canadian lakes. Regionally specific baseline conditions were established from lakes considered healthy due to limited human activities in their watershed. When lakes with impacted watershed were compared to healthy ones within their specific region, two early warning signals of human pressure, pollution from nitrogen found in fertilizers and sewage, and chloride found in road salt, determined whether a lake was altered. We combined these two health indicators, with information on future potential lake threats and use by the population for recreational purposes. Using a colour-coded mapping technique, we were able to identify regions where lakes were altered, threatened, and used. These regions occurred primarily around dense urban areas, of southern Ontario and Quebec, and major cities on the east and west coast. Lakes were altered and threatened, but seemingly less used in the Prairie Provinces. The novel approach is very adaptable, easy to understand, and can be used at more regional levels for management to determine priority sites for conservation and restoration, as well as in science communication to describe overall lake health.},
	language = {en},
	urldate = {2023-06-02},
	institution = {Ecology},
	author = {Dupont, Andréanne and Botrel, Morgan and St-Gelais, Nicolas Fortin and Poisot, Timothée and Maranger, Roxane},
	month = mar,
	year = {2023},
	doi = {10.1101/2023.03.09.531893},
	keywords = {NALCMS},
}

Abstract Anthropogenic pressures, including urban and agricultural expansion, can negatively influence a lake’s capacity to provide aquatic ecosystem services (ES). However, identifying lakes most at risk of losing their ES requires integrating information on lake ecological state, global change threats, and ES demand. Here, we provide a social-ecological framework that combines these features within a regional context based on an ecological evaluation of the state of 659 lakes across Canada. From deviation of impacted lakes to reference ones, we identified much higher concentrations of total nitrogen and chloride as the main indicators of altered lake ecological state in all regions identified. Lake ecological state was mapped using an additive colour model along with regional scores of threat levels and recreational ES demand. Population density and agriculture were linked to high lake vulnerability. Lakes in Southern Ontario were most concerning, being highly altered, under threat, and heavily used. Lakes near urban centers along coasts were altered and used, but less threatened, whereas those in the Prairies were altered and threatened, but less used. Our novel framework provides the first social-ecological geography of Canadian lakes, and, is a promising tool to assess lake state and vulnerability at scales relevant for management. Plan language summary Plain language title: Assessing overall lake health across Canada to identify sites for restoration and conservation Canadians love to swim, fish, and navigate in and on the countless lakes across the country. But Canadian lakes are under a considerable amount of pressure from human activities in their watershed. The expansion of cities, intensive farming, wetland loss, and industrial development all results in the transfer of pollutants to aquatic habitats, threatening the health of lakes and the ecosystem services they provide. Where are lakes being used across Canada? What condition are they in and is their use under threat from different pressures? To answer these questions, we combined information from many different sources, including a national scale lake assessment, through the NSERC Strategic Network Cluster Lake Pulse to create the first social-ecological geography of southern Canadian lakes. Regionally specific baseline conditions were established from lakes considered healthy due to limited human activities in their watershed. When lakes with impacted watershed were compared to healthy ones within their specific region, two early warning signals of human pressure, pollution from nitrogen found in fertilizers and sewage, and chloride found in road salt, determined whether a lake was altered. We combined these two health indicators, with information on future potential lake threats and use by the population for recreational purposes. Using a colour-coded mapping technique, we were able to identify regions where lakes were altered, threatened, and used. These regions occurred primarily around dense urban areas, of southern Ontario and Quebec, and major cities on the east and west coast. Lakes were altered and threatened, but seemingly less used in the Prairie Provinces. The novel approach is very adaptable, easy to understand, and can be used at more regional levels for management to determine priority sites for conservation and restoration, as well as in science communication to describe overall lake health.

@incollection{pilliod_amphibians_2023,
	address = {Cham},
	title = {Amphibians and {Reptiles}},
	isbn = {978-3-031-34037-6},
	url = {https://doi.org/10.1007/978-3-031-34037-6_25},
	abstract = {Amphibians and reptiles are a diverse group of ectothermic vertebrates that occupy a variety of habitats in rangelands of North America, from wetlands to the driest deserts. These two classes of vertebrates are often referred to as herpetofauna and are studied under the field of herpetology. In U.S. rangelands, there are approximately 66 species of frogs and toads, 58 salamanders, 98 lizards, 111 snakes, and 27 turtles and tortoises. Herpetofauna tend to be poorly studied compared with other vertebrates, which creates a challenge for biologists and landowners who are trying to manage rangeland activities for this diverse group of animals and their habitats. Degradation of habitats from human land use and alteration of natural processes, like wildfire, are primary threats to herpetofauna populations. Disease, non-native predators, collection for the pet trade, and persecution are also conservation concerns for some species. Properly managed livestock grazing is generally compatible with herpetofauna conservation, and private and public rangelands provide crucial habitat for many species. Climate change also poses a threat to herpetofauna, but we have an incomplete understanding of the potential effects on species. Dispersal and adaptation could provide some capacity for species to persist on rangelands as climates, disturbance regimes, and habitats change. However, inadequate information and considerable uncertainty will make climate mitigation planning difficult for the foreseeable future. Planning for and mitigating effects of climate change, and interactions with other stressors, is an urgent area for research. Maintaining large, heterogeneous land areas as rangelands will certainly be an important part of the conservation strategy for herpetofauna in North America.},
	language = {en},
	urldate = {2023-10-04},
	booktitle = {Rangeland {Wildlife} {Ecology} and {Conservation}},
	publisher = {Springer International Publishing},
	author = {Pilliod, David S. and Esque, Todd C.},
	editor = {McNew, Lance B. and Dahlgren, David K. and Beck, Jeffrey L.},
	year = {2023},
	doi = {10.1007/978-3-031-34037-6_25},
	keywords = {NALCMS},
	pages = {861--895},
}

Amphibians and reptiles are a diverse group of ectothermic vertebrates that occupy a variety of habitats in rangelands of North America, from wetlands to the driest deserts. These two classes of vertebrates are often referred to as herpetofauna and are studied under the field of herpetology. In U.S. rangelands, there are approximately 66 species of frogs and toads, 58 salamanders, 98 lizards, 111 snakes, and 27 turtles and tortoises. Herpetofauna tend to be poorly studied compared with other vertebrates, which creates a challenge for biologists and landowners who are trying to manage rangeland activities for this diverse group of animals and their habitats. Degradation of habitats from human land use and alteration of natural processes, like wildfire, are primary threats to herpetofauna populations. Disease, non-native predators, collection for the pet trade, and persecution are also conservation concerns for some species. Properly managed livestock grazing is generally compatible with herpetofauna conservation, and private and public rangelands provide crucial habitat for many species. Climate change also poses a threat to herpetofauna, but we have an incomplete understanding of the potential effects on species. Dispersal and adaptation could provide some capacity for species to persist on rangelands as climates, disturbance regimes, and habitats change. However, inadequate information and considerable uncertainty will make climate mitigation planning difficult for the foreseeable future. Planning for and mitigating effects of climate change, and interactions with other stressors, is an urgent area for research. Maintaining large, heterogeneous land areas as rangelands will certainly be an important part of the conservation strategy for herpetofauna in North America.

@article{lopez_gonzalez_ecoregionalization_2023,
	title = {An ecoregionalization of the {Sierra} {Madre} {Occidental}, {México}, based on non-volant, small mammal distributions},
	volume = {30},
	issn = {1195-6860},
	url = {https://www.tandfonline.com/doi/full/10.1080/11956860.2023.2207947},
	doi = {10.1080/11956860.2023.2207947},
	number = {1},
	urldate = {2023-07-04},
	journal = {Écoscience},
	author = {López González, Celia and Sandoval, Sarahi and Escobar Flores, Jonathan G.},
	month = jan,
	year = {2023},
	note = {Publisher: Taylor \& Francis},
	keywords = {Terrestrial Ecoregions (CEC 1997)},
	pages = {65--81},
}

@phdthesis{haight_anthropogenic_2023,
	title = {Anthropogenic {Environments} {Shape} {Wildlife} {Communities} and {Human}-{Wildlife} {Coexistence} {Across} {Urbanizing} {Landscapes}},
	url = {https://keep.lib.asu.edu/items/189248},
	abstract = {With a growing majority of humans living within cities and towns, urbanization is one of the most persistent drivers of change in global land use and challenges to sustainability and biodiversity conservation. The development of cities and towns can substantially shape local and regional environments in which wildlife communities persist. Although urbanization can negatively affect wildlife communities – through processes such as habitat fragmentation and non-native species introduction – cities can also provide resources to wildlife, such as through food, water, and space, creating potential opportunities for conservation. However, managing wildlife communities persisting in urbanizing landscapes requires better understanding of how urbanized landscapes influence the ability of wildlife to coexist with one another and with people at local and regional scales. In this dissertation, I addressed these research needs by evaluating the environmental and human factors driving dynamic wildlife community distributions and people’s attitudes towards wildlife. In my first two chapters,I used wildlife camera data collected from across the Phoenix Metropolitan Area, AZ to examine seasonal patterns of wildlife space use, species richness, and interspecific interactions across levels of urbanization with varying landscape characteristics, including plant productivity and spatial land use heterogeneity. Here I found that urbanization was a primary driver of wildlife community characteristics within the region, but that seasonal resource availability and landscape heterogeneity could have mediating influences that require further exploration. In my third chapter, I partnered with wildlife researchers across North America to examine how relationships between urbanization and community composition vary among cities with distinct social-ecological characteristics, finding that effects of local urbanization were more negative in warmer, less vegetated, and more urbanized cities. In my fourth and final chapter, I explored the potential for human-wildlife coexistence by examining how various ideological, environmental, and sociodemographic factors influenced Phoenix area residents’ level of comfort living near different wildlife groups. Although I found that residents’ attitudes were primarily shaped by their relatively static wildlife values, comfort living near wildlife also depended on the characteristics of the neighboring environment, of the residents, and of the wildlife involved, indicating the potential for facilitating conditions for human-wildlife coexistence. Altogether, the findings of this dissertation suggest that the management of wildlife and their interactions with people within cities would benefit from more proactive and holistic consideration of the interacting environmental, wildlife, and human characteristics that influence the persistence of biodiversity within an increasingly urbanized world.},
	language = {en},
	urldate = {2024-01-09},
	school = {Arizona State University},
	author = {Haight, Jeffrey Douglas},
	year = {2023},
	keywords = {NALCMS},
}

With a growing majority of humans living within cities and towns, urbanization is one of the most persistent drivers of change in global land use and challenges to sustainability and biodiversity conservation. The development of cities and towns can substantially shape local and regional environments in which wildlife communities persist. Although urbanization can negatively affect wildlife communities – through processes such as habitat fragmentation and non-native species introduction – cities can also provide resources to wildlife, such as through food, water, and space, creating potential opportunities for conservation. However, managing wildlife communities persisting in urbanizing landscapes requires better understanding of how urbanized landscapes influence the ability of wildlife to coexist with one another and with people at local and regional scales. In this dissertation, I addressed these research needs by evaluating the environmental and human factors driving dynamic wildlife community distributions and people’s attitudes towards wildlife. In my first two chapters,I used wildlife camera data collected from across the Phoenix Metropolitan Area, AZ to examine seasonal patterns of wildlife space use, species richness, and interspecific interactions across levels of urbanization with varying landscape characteristics, including plant productivity and spatial land use heterogeneity. Here I found that urbanization was a primary driver of wildlife community characteristics within the region, but that seasonal resource availability and landscape heterogeneity could have mediating influences that require further exploration. In my third chapter, I partnered with wildlife researchers across North America to examine how relationships between urbanization and community composition vary among cities with distinct social-ecological characteristics, finding that effects of local urbanization were more negative in warmer, less vegetated, and more urbanized cities. In my fourth and final chapter, I explored the potential for human-wildlife coexistence by examining how various ideological, environmental, and sociodemographic factors influenced Phoenix area residents’ level of comfort living near different wildlife groups. Although I found that residents’ attitudes were primarily shaped by their relatively static wildlife values, comfort living near wildlife also depended on the characteristics of the neighboring environment, of the residents, and of the wildlife involved, indicating the potential for facilitating conditions for human-wildlife coexistence. Altogether, the findings of this dissertation suggest that the management of wildlife and their interactions with people within cities would benefit from more proactive and holistic consideration of the interacting environmental, wildlife, and human characteristics that influence the persistence of biodiversity within an increasingly urbanized world.

@article{elliott_application_2023,
	title = {Application of habitat association models across regions: {Useful} explanatory power retained in wetland bird case study},
	volume = {14},
	issn = {2150-8925, 2150-8925},
	shorttitle = {Application of habitat association models across regions},
	url = {https://esajournals.onlinelibrary.wiley.com/doi/10.1002/ecs2.4499},
	doi = {10.1002/ecs2.4499},
	language = {en},
	number = {5},
	urldate = {2023-06-02},
	journal = {Ecosphere},
	author = {Elliott, Lisa H. and Bracey, Annie M. and Niemi, Gerald J. and Johnson, Douglas H. and Gehring, Thomas M. and Gnass Giese, Erin E. and Fiorino, Giuseppe E. and Howe, Robert W. and Lawrence, Gregory J. and Norment, Christopher J. and Tozer, Douglas C. and Igl, Lawrence D.},
	month = may,
	year = {2023},
	keywords = {NALCMS},
	pages = {e4499},
}

@misc{flower_arcgis_2023,
	title = {{ArcGIS} {StoryMaps} - {Salish} {Sea} {Atlas}, {Land} {Cover} and {Land} {Use}},
	url = {https://storymaps.arcgis.com/stories/43e8f7863cc548638f4545dd39b7bf69},
	abstract = {Land Cover and Land Use in the Salish Sea Bioregion. Part of the Salish Sea Atlas.},
	language = {en},
	urldate = {2023-11-27},
	journal = {ArcGIS StoryMaps - Salish Sea Atlas},
	author = {Flower, Aquila},
	month = feb,
	year = {2023},
	keywords = {NALCMS},
}

Land Cover and Land Use in the Salish Sea Bioregion. Part of the Salish Sea Atlas.

@article{youngmann_assessing_2023,
	title = {Assessing springtime vertebrate prey of sympatric mesopredators in the southeastern {United} {States} using metabarcoding analysis},
	volume = {18},
	issn = {1932-6203},
	url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0293270},
	doi = {10.1371/journal.pone.0293270},
	abstract = {Coyotes (Canis latrans) colonized the eastern United States over the last century and formed a 3-species predator guild with bobcats (Lynx rufus) and gray foxes (Urocyon cinereoargenteus) across much of the southeastern United States. Diets among the three species vary along with respective impacts on game species such as white-tailed deer (Odocoileus virginianus) and wild turkeys (Meleagris gallopavo). To determine predation impacts on vertebrate prey and dietary overlap in consumption of prey items, we assessed diets of coyote, bobcat, and gray fox during spring, coinciding with white-tailed deer fawning and wild turkey nesting and brood rearing. We sampled across three sites along the Savannah River in South Carolina from mid-May through mid-June of 2020–2021. We collected 180 scat samples along 295.9 kilometers (71.1–122.4 km/site) of unpaved secondary roads and used DNA metabarcoding to determine vertebrate diet items. We identified predator species of scat using DNA metabarcoding and species-specific mtDNA fragment analysis (153 were coyote, 20 bobcat, and seven gray fox). Overall, we found evidence that two species, coyote and bobcat, consumed deer while all three consumed turkeys. Frequency of deer in the diet varied across sites for coyotes from 62–86\% and wild turkey was present with a frequency of occurrence of 9\% for coyotes, 5\% for bobcats, and 14\% for gray fox. Vertebrate diet specialization was evident across predator species with high frequency of deer in coyote diets, rabbits and small mammals in bobcat diets, and herpetofauna in gray fox diets. During deer fawning and wild turkey nesting and brood rearing, dietary overlap appears to be mediated by disparate selection of prey items, which reduced competition among coyotes, bobcats, and gray foxes. Use of DNA metabarcoding may augment our understanding of dietary preferences within this predator guild by providing increased resolution of diet composition among important game species.},
	language = {en},
	number = {10},
	urldate = {2024-01-10},
	journal = {PLOS ONE},
	author = {Youngmann, Jordan L. and Lance, Stacey L. and Kilgo, John C. and Ruth, Charles and Cantrell, Jay and D’Angelo, Gino J.},
	month = oct,
	year = {2023},
	note = {Publisher: Public Library of Science},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {e0293270},
}

Coyotes (Canis latrans) colonized the eastern United States over the last century and formed a 3-species predator guild with bobcats (Lynx rufus) and gray foxes (Urocyon cinereoargenteus) across much of the southeastern United States. Diets among the three species vary along with respective impacts on game species such as white-tailed deer (Odocoileus virginianus) and wild turkeys (Meleagris gallopavo). To determine predation impacts on vertebrate prey and dietary overlap in consumption of prey items, we assessed diets of coyote, bobcat, and gray fox during spring, coinciding with white-tailed deer fawning and wild turkey nesting and brood rearing. We sampled across three sites along the Savannah River in South Carolina from mid-May through mid-June of 2020–2021. We collected 180 scat samples along 295.9 kilometers (71.1–122.4 km/site) of unpaved secondary roads and used DNA metabarcoding to determine vertebrate diet items. We identified predator species of scat using DNA metabarcoding and species-specific mtDNA fragment analysis (153 were coyote, 20 bobcat, and seven gray fox). Overall, we found evidence that two species, coyote and bobcat, consumed deer while all three consumed turkeys. Frequency of deer in the diet varied across sites for coyotes from 62–86% and wild turkey was present with a frequency of occurrence of 9% for coyotes, 5% for bobcats, and 14% for gray fox. Vertebrate diet specialization was evident across predator species with high frequency of deer in coyote diets, rabbits and small mammals in bobcat diets, and herpetofauna in gray fox diets. During deer fawning and wild turkey nesting and brood rearing, dietary overlap appears to be mediated by disparate selection of prey items, which reduced competition among coyotes, bobcats, and gray foxes. Use of DNA metabarcoding may augment our understanding of dietary preferences within this predator guild by providing increased resolution of diet composition among important game species.

@article{jones_biology_2023,
	title = {Biology of {Yucatán} {Box} {Turtles} ({Terrapene} yucatana) in {Northern} {Yucatán}},
	volume = {57},
	issn = {0022-1511, 1937-2418},
	url = {https://bioone.org/journals/journal-of-herpetology/volume-57/issue-3/20-107/Biology-of-Yucat%c3%a1n-Box-Turtles-Terrapene-yucatana-in-Northern-Yucat%c3%a1n/10.1670/20-107.full},
	doi = {10.1670/20-107},
	abstract = {La tortuga de caja de Yucatán (Terrapene yucatana) es el único linaje completamente tropical de tortugas de caja (Terrapene spp.). Realizamos un estudio de la ecología, movimientos, comportamiento y asociaciones de hábitat de T. yucatana en el norte de Yucatán, México, durante 218 días de campo entre 2014 y 2019. Estimamos el tamaño de dos poblaciones comprendidas en 36,6 y 3,0 tortugas, respectivamente, con densidades correspondientes a 2,29 y 0,39 tortugas / ha. Obtuvimos 2,808 radiolocalizaciones de 20 tortugas adultas. Estimamos una tasa de supervivencia anual superior a 0,989 basado en el marcado y recaptura de 37 individuos. Para ambos sexos, el tamaño medio anual del área de distribución (95\% del MCP) fue de 0,684 ha, y la distancia entre los centroides del área de distribución anual consecutivos fue de 22,5 m. Los machos exhibieron rangos de distribución significativamente mayores que las hembras en 2 de los 5 años. Observamos alimentación, cortejo y peleas en su estado natural entre junio y diciembre. Las hembras se movieron más que los machos en julio, cuando también se observaron tortugas grávidas. Encontramos que T. yucatana se asoció positivamente con Mimosa sp. y Bromelia spp. El uso de hábitats acuáticos fue infrecuente (0,17\%). Terrapene yucatana, un linaje alopátrico y completamente tropical de las tortugas de caja de América del Norte, es una especie de bosque interior y matorrales espinosos que ocurre en densidades bajas. En ambientes no perturbados, T. yucatana puede exhibir altas tasas de supervivencia, un ámbito hogareño pequeño y una notable fidelidad a su ámbito doméstico, lo que acentúa la importancia de los esfuerzos de conservación de bosques a gran escala junto con la protección específica de poblaciones documentadas de tortugas de caja.},
	language = {en},
	number = {3},
	urldate = {2026-05-27},
	journal = {Journal of Herpetology},
	author = {Jones, Michael T. and Willey, Lisabeth L. and Akre, Thomas S. B. and Gonzalez-Akre, Erika and Nahuat-Jiménez, Eddie Gabriel and Gamboa, Luis Díaz and Macip-Ríos, Rodrigo},
	month = oct,
	year = {2023},
	note = {Publisher: Society for the Study of Amphibians and Reptiles},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {325--333},
}

La tortuga de caja de Yucatán (Terrapene yucatana) es el único linaje completamente tropical de tortugas de caja (Terrapene spp.). Realizamos un estudio de la ecología, movimientos, comportamiento y asociaciones de hábitat de T. yucatana en el norte de Yucatán, México, durante 218 días de campo entre 2014 y 2019. Estimamos el tamaño de dos poblaciones comprendidas en 36,6 y 3,0 tortugas, respectivamente, con densidades correspondientes a 2,29 y 0,39 tortugas / ha. Obtuvimos 2,808 radiolocalizaciones de 20 tortugas adultas. Estimamos una tasa de supervivencia anual superior a 0,989 basado en el marcado y recaptura de 37 individuos. Para ambos sexos, el tamaño medio anual del área de distribución (95% del MCP) fue de 0,684 ha, y la distancia entre los centroides del área de distribución anual consecutivos fue de 22,5 m. Los machos exhibieron rangos de distribución significativamente mayores que las hembras en 2 de los 5 años. Observamos alimentación, cortejo y peleas en su estado natural entre junio y diciembre. Las hembras se movieron más que los machos en julio, cuando también se observaron tortugas grávidas. Encontramos que T. yucatana se asoció positivamente con Mimosa sp. y Bromelia spp. El uso de hábitats acuáticos fue infrecuente (0,17%). Terrapene yucatana, un linaje alopátrico y completamente tropical de las tortugas de caja de América del Norte, es una especie de bosque interior y matorrales espinosos que ocurre en densidades bajas. En ambientes no perturbados, T. yucatana puede exhibir altas tasas de supervivencia, un ámbito hogareño pequeño y una notable fidelidad a su ámbito doméstico, lo que acentúa la importancia de los esfuerzos de conservación de bosques a gran escala junto con la protección específica de poblaciones documentadas de tortugas de caja.

@article{mei_can_2023,
	title = {Can {Hydrological} {Models} {Benefit} {From} {Using} {Global} {Soil} {Moisture}, {Evapotranspiration}, and {Runoff} {Products} as {Calibration} {Targets}?},
	volume = {59},
	copyright = {© 2023. The Authors.},
	issn = {1944-7973},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2022WR032064},
	doi = {10.1029/2022WR032064},
	abstract = {Hydrological models are usually calibrated to in-situ streamflow observations with reasonably long and uninterrupted records. This is challenging for poorly gage or ungaged basins where such information is not available. Even for gaged basins, the single-objective calibration to gaged streamflow cannot guarantee reliable forecasts because, as has been documented elsewhere, the inverse problem is mathematically ill-posed. Therefore, the inclusion of other observations, and the reproduction of other hydrological variables beyond streamflow, become critical components of accurate hydrological forecasting. In this study, six single- and multi-objective model calibration schemes based on different combinations of gaged streamflow, global-scale gridded soil moisture, actual evapotranspiration (ET), and runoff products are used for the calibration of a process-based hydrological model for 20 catchments located within the Lake Michigan watershed, of the Laurentian Great Lakes. Results show that the addition of gridded soil moisture to gaged streamflow in model calibration improves the ET simulation performance for most of the catchments, leading to the overall best-performing models. The monthly streamflow simulation performance for the experiments using gridded runoff products to inform the model is outperformed by those using the gaged streamflow, but the discrepancy is mitigated with increasing catchment scale. A new visualization method that effectively synthesizes model performance for the simulations of streamflow, soil moisture, and ET was also proposed. Based on the method, it is revealed that the streamflow simulation performance is relatively weak for baseflow-dominated catchments; overall, the 20 catchment models simulate streamflow and ET better than soil moisture.},
	language = {en},
	number = {2},
	urldate = {2023-06-23},
	journal = {Water Resources Research},
	author = {Mei, Yiwen and Mai, Juliane and Do, Hong Xuan and Gronewold, Andrew and Reeves, Howard and Eberts, Sandra and Niswonger, Richard and Regan, R. Steven and Hunt, Randall J.},
	year = {2023},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1029/2022WR032064},
	keywords = {NALCMS},
	pages = {e2022WR032064},
}

Hydrological models are usually calibrated to in-situ streamflow observations with reasonably long and uninterrupted records. This is challenging for poorly gage or ungaged basins where such information is not available. Even for gaged basins, the single-objective calibration to gaged streamflow cannot guarantee reliable forecasts because, as has been documented elsewhere, the inverse problem is mathematically ill-posed. Therefore, the inclusion of other observations, and the reproduction of other hydrological variables beyond streamflow, become critical components of accurate hydrological forecasting. In this study, six single- and multi-objective model calibration schemes based on different combinations of gaged streamflow, global-scale gridded soil moisture, actual evapotranspiration (ET), and runoff products are used for the calibration of a process-based hydrological model for 20 catchments located within the Lake Michigan watershed, of the Laurentian Great Lakes. Results show that the addition of gridded soil moisture to gaged streamflow in model calibration improves the ET simulation performance for most of the catchments, leading to the overall best-performing models. The monthly streamflow simulation performance for the experiments using gridded runoff products to inform the model is outperformed by those using the gaged streamflow, but the discrepancy is mitigated with increasing catchment scale. A new visualization method that effectively synthesizes model performance for the simulations of streamflow, soil moisture, and ET was also proposed. Based on the method, it is revealed that the streamflow simulation performance is relatively weak for baseflow-dominated catchments; overall, the 20 catchment models simulate streamflow and ET better than soil moisture.

@article{scheick_change_2023,
	title = {Change in black bear range and distribution in {Florida} using two decadal datasets from 2001–2020},
	volume = {87},
	copyright = {© 2023 The Wildlife Society},
	issn = {1937-2817},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/jwmg.22394},
	doi = {10.1002/jwmg.22394},
	abstract = {American black bears (Ursus americanus) in Florida have increased in abundance from historically low numbers and currently number {\textgreater}4,000 across 7 subpopulations. Biologists monitor the range of black bears to track their recovery for conservation and management efforts. We estimated geographic range of black bears in Florida for historical (2001–2010) and contemporary (2011–2020) periods using 12 sources of occurrence data collected from wildlife professionals and the public. We reduced data sets by subsampling protocols to account for localized spatiotemporal biases and for possible differences in sampling effort from increases in the human population between modeling periods. We developed models at 2 levels: a generalized boundary (range extent) and a more detailed delineation (occupied range). We developed range extent using a concave hull model and occupied range using kernel density estimation with a corresponding 97.5\% isopleth. Between modeling periods, range extent increased by 13.4\% and occupied range increased by 11.3\%, with both range levels expanding and contracting in certain areas. The ranges indicated improved connectivity among bear subpopulations. We also produced a range map for research, management, and public use built upon contemporary data that partitioned the state into 4 levels representing the relative frequency of bear use (frequent, common, occasional, and rare). Range map levels at the occupied range, and especially frequent use areas, help focus bear research efforts (e.g., placement of hair corrals), management efforts (e.g., assess varying levels of risk to the public of bear conflicts), and conservation efforts (e.g., focusing habitat protection in areas with high use by bears).},
	language = {en},
	number = {4},
	urldate = {2023-06-27},
	journal = {The Journal of Wildlife Management},
	author = {Scheick, Brian K. and Barrett, Mark A. and Doran-Myers, Darcy},
	year = {2023},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/jwmg.22394},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {e22394},
}

American black bears (Ursus americanus) in Florida have increased in abundance from historically low numbers and currently number \textgreater4,000 across 7 subpopulations. Biologists monitor the range of black bears to track their recovery for conservation and management efforts. We estimated geographic range of black bears in Florida for historical (2001–2010) and contemporary (2011–2020) periods using 12 sources of occurrence data collected from wildlife professionals and the public. We reduced data sets by subsampling protocols to account for localized spatiotemporal biases and for possible differences in sampling effort from increases in the human population between modeling periods. We developed models at 2 levels: a generalized boundary (range extent) and a more detailed delineation (occupied range). We developed range extent using a concave hull model and occupied range using kernel density estimation with a corresponding 97.5% isopleth. Between modeling periods, range extent increased by 13.4% and occupied range increased by 11.3%, with both range levels expanding and contracting in certain areas. The ranges indicated improved connectivity among bear subpopulations. We also produced a range map for research, management, and public use built upon contemporary data that partitioned the state into 4 levels representing the relative frequency of bear use (frequent, common, occasional, and rare). Range map levels at the occupied range, and especially frequent use areas, help focus bear research efforts (e.g., placement of hair corrals), management efforts (e.g., assess varying levels of risk to the public of bear conflicts), and conservation efforts (e.g., focusing habitat protection in areas with high use by bears).

@article{morineau_climate_2023,
	title = {Climate change alone cannot explain boreal caribou range recession in {Quebec} since 1850},
	volume = {29},
	copyright = {© 2023 The Authors. Global Change Biology published by John Wiley \& Sons Ltd.},
	issn = {1365-2486},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/gcb.16949},
	doi = {10.1111/gcb.16949},
	abstract = {The contraction of species range is one of the most significant symptoms of biodiversity loss worldwide. While anthropogenic activities and habitat alteration are major threats for several species, climate change should also be considered. For species at risk, differentiating the effects of human disturbances and climate change on past and current range transformations is an important step towards improved conservation strategies. We paired historical range maps with global atmospheric reanalyses from different sources to assess the potential effects of recent climate change on the observed northward contraction of the range of boreal populations of woodland caribou (Rangifer tarandus caribou) in Quebec (Canada) since 1850. We quantified these effects by highlighting the discrepancies between different southern limits of the caribou's range (used as references) observed in the past and reconstitutions obtained through the hindcasting of the climate conditions within which caribou are currently found. Hindcasted southern limits moved 105 km north over time under all reanalysis datasets, a trend drastically different from the 620 km reported for observed southern limits since 1850. The differences in latitudinal shift through time between the observed and hindcasted southern limits of distribution suggest that caribou range recession should have been only 17\% of what has been observed since 1850 if recent climate change had been the only disturbance driver. This relatively limited impact of climate reinforces the scientific consensus stating that caribou range recession in Quebec is mainly caused by anthropogenic drivers (i.e. logging, development of the road network, agriculture, urbanization) that have modified the structure and composition of the forest over the past 160 years, paving the way for habitat-mediated apparent competition and overharvesting. Our results also call for a reconsideration of past ranges in models aiming at projecting future distributions, especially for endangered species.},
	language = {en},
	number = {23},
	urldate = {2024-01-10},
	journal = {Global Change Biology},
	author = {Morineau, Chloé and Boulanger, Yan and Gachon, Philippe and Plante, Sabrina and St-Laurent, Martin-Hugues},
	year = {2023},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/gcb.16949},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {6661--6678},
}

The contraction of species range is one of the most significant symptoms of biodiversity loss worldwide. While anthropogenic activities and habitat alteration are major threats for several species, climate change should also be considered. For species at risk, differentiating the effects of human disturbances and climate change on past and current range transformations is an important step towards improved conservation strategies. We paired historical range maps with global atmospheric reanalyses from different sources to assess the potential effects of recent climate change on the observed northward contraction of the range of boreal populations of woodland caribou (Rangifer tarandus caribou) in Quebec (Canada) since 1850. We quantified these effects by highlighting the discrepancies between different southern limits of the caribou's range (used as references) observed in the past and reconstitutions obtained through the hindcasting of the climate conditions within which caribou are currently found. Hindcasted southern limits moved 105 km north over time under all reanalysis datasets, a trend drastically different from the 620 km reported for observed southern limits since 1850. The differences in latitudinal shift through time between the observed and hindcasted southern limits of distribution suggest that caribou range recession should have been only 17% of what has been observed since 1850 if recent climate change had been the only disturbance driver. This relatively limited impact of climate reinforces the scientific consensus stating that caribou range recession in Quebec is mainly caused by anthropogenic drivers (i.e. logging, development of the road network, agriculture, urbanization) that have modified the structure and composition of the forest over the past 160 years, paving the way for habitat-mediated apparent competition and overharvesting. Our results also call for a reconsideration of past ranges in models aiming at projecting future distributions, especially for endangered species.

@article{aubry_climatic_2023,
	title = {Climatic conditions limit wolverine distribution in the {Cascade} {Range} of southwestern {North} {America}},
	volume = {101},
	issn = {0008-4301, 1480-3283},
	url = {https://cdnsciencepub.com/doi/10.1139/cjz-2022-0005},
	doi = {10.1139/cjz-2022-0005},
	abstract = {Recolonization of the Cascade Range in southern British Columbia, Canada, and Washington, USA, by wolverines ( Gulo gulo (L., 1758)) is an ongoing process whose ultimate outcome is unknown. A reliable species distribution model for the wolverine in the Cascades (i.e., their first-order habitat selection) is urgently needed to help inform management and conservation strategies. Using Argos location data obtained on 10 resident adult wolverines (six females, four males) from 2008 to 2016, we generated a multi-covariate species distribution model for the wolverine in the Cascades. Our final model included three climatic covariates and their quadratic terms: Proximity to the Transitional Zone Near Alpine Tree Line, Number of Frost-free Days per Year, and Annual Precipitation as Snow. Model validations indicated that our model was robust and could identify areas of potential wolverine distribution in the Cascades reliably. Our model provides evidence that wolverine distribution in the Cascades is constrained by climatic conditions and that snowy and cold environments define the geographic areas that are overwhelmingly associated with resident wolverines. In addition, our model provides a reliable basis for monitoring the direct effects of climate change on wolverines in the Cascade Range and for predicting the extent to which climate change may impact their populations under various scenarios.},
	language = {en},
	number = {2},
	urldate = {2023-06-01},
	journal = {Canadian Journal of Zoology},
	author = {Aubry, Keith B. and Raley, Catherine M. and Shirk, Andrew J. and McKelvey, Kevin S. and Copeland, Jeffrey P.},
	month = feb,
	year = {2023},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {95--113},
}

Recolonization of the Cascade Range in southern British Columbia, Canada, and Washington, USA, by wolverines ( Gulo gulo (L., 1758)) is an ongoing process whose ultimate outcome is unknown. A reliable species distribution model for the wolverine in the Cascades (i.e., their first-order habitat selection) is urgently needed to help inform management and conservation strategies. Using Argos location data obtained on 10 resident adult wolverines (six females, four males) from 2008 to 2016, we generated a multi-covariate species distribution model for the wolverine in the Cascades. Our final model included three climatic covariates and their quadratic terms: Proximity to the Transitional Zone Near Alpine Tree Line, Number of Frost-free Days per Year, and Annual Precipitation as Snow. Model validations indicated that our model was robust and could identify areas of potential wolverine distribution in the Cascades reliably. Our model provides evidence that wolverine distribution in the Cascades is constrained by climatic conditions and that snowy and cold environments define the geographic areas that are overwhelmingly associated with resident wolverines. In addition, our model provides a reliable basis for monitoring the direct effects of climate change on wolverines in the Cascade Range and for predicting the extent to which climate change may impact their populations under various scenarios.

@article{langlois_collocating_2023,
	title = {Collocating pipelines to minimize fragmentation: evaluating ecological costs of a shale gas mitigation practice},
	volume = {n/a},
	copyright = {© 2023 The Authors. The Journal of Wildlife Management published by Wiley Periodicals LLC on behalf of The Wildlife Society.},
	issn = {1937-2817},
	shorttitle = {Collocating pipelines to minimize fragmentation},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/jwmg.22468},
	doi = {10.1002/jwmg.22468},
	abstract = {Shale gas development occurs in forests of the Appalachian Basin within breeding habitat for forest songbirds. Development requires linear infrastructure (e.g., pipelines, gas access roads) that fragments habitat and reduces core forest. Collocation is a mitigation practice that sites new pipelines adjacent to existing surface disturbance such as forest roads; it reduces core forest loss but may have associated ecological costs, defined as negative effects on native species and ecosystems. We conducted a paired sampling design between forest roads and collocated pipelines (expanded gas access roads collocated with pipelines) to evaluate ecological costs to forest songbirds in 2013 in Pennsylvania, USA. We surveyed 4 focal songbird species: 3 territorial species that varied in habitat requirements and the non-territorial brown-headed cowbird (Molothrus ater), an obligate brood parasite. We used spot mapping to survey focal species within linear corridors and the adjacent mature forest. Territory density of forest interior ovenbirds (Seiurus aurocapilla) was significantly lower on collocated pipelines (5.1 fewer territories per 10 ha) compared to forest road sites. We found no effect of collocation on territory density for the early successional species, eastern towhee (Pipilo erythrophthalmus) and chestnut-sided warbler (Setophaga pensylvanica). Territories of all 3 territorial focal species crossed collocated pipeline sites less frequently than forest roads (ovenbird: 16\%, eastern towhee: 14\%, chestnut-sided warbler: 31\%) and the barrier effect increased with increasing corridor width. In contrast, brown-headed cowbird abundance was 15 times greater at collocated pipelines compared to forest roads, suggesting that wider gas corridors provide enhanced access routes for cowbirds. Our study indicates the expansion of forest roads to collocated pipelines exacerbates the negative ecological effects already present with the existing road including increased edge avoidance by a forest interior species, greater barrier effects for all 3 territorial forest songbirds, and increased access for brown-headed cowbirds into core forest. We support collocation as a mitigation strategy but emphasize restricting overall corridor width to reduce the additional ecological costs associated with this practice.},
	language = {en},
	number = {n/a},
	urldate = {2023-08-11},
	journal = {The Journal of Wildlife Management},
	author = {Langlois, Lillie A. and Brenner, Stephen J. and Brittingham, Margaret C.},
	month = aug,
	year = {2023},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/jwmg.22468},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {e22468},
}

Shale gas development occurs in forests of the Appalachian Basin within breeding habitat for forest songbirds. Development requires linear infrastructure (e.g., pipelines, gas access roads) that fragments habitat and reduces core forest. Collocation is a mitigation practice that sites new pipelines adjacent to existing surface disturbance such as forest roads; it reduces core forest loss but may have associated ecological costs, defined as negative effects on native species and ecosystems. We conducted a paired sampling design between forest roads and collocated pipelines (expanded gas access roads collocated with pipelines) to evaluate ecological costs to forest songbirds in 2013 in Pennsylvania, USA. We surveyed 4 focal songbird species: 3 territorial species that varied in habitat requirements and the non-territorial brown-headed cowbird (Molothrus ater), an obligate brood parasite. We used spot mapping to survey focal species within linear corridors and the adjacent mature forest. Territory density of forest interior ovenbirds (Seiurus aurocapilla) was significantly lower on collocated pipelines (5.1 fewer territories per 10 ha) compared to forest road sites. We found no effect of collocation on territory density for the early successional species, eastern towhee (Pipilo erythrophthalmus) and chestnut-sided warbler (Setophaga pensylvanica). Territories of all 3 territorial focal species crossed collocated pipeline sites less frequently than forest roads (ovenbird: 16%, eastern towhee: 14%, chestnut-sided warbler: 31%) and the barrier effect increased with increasing corridor width. In contrast, brown-headed cowbird abundance was 15 times greater at collocated pipelines compared to forest roads, suggesting that wider gas corridors provide enhanced access routes for cowbirds. Our study indicates the expansion of forest roads to collocated pipelines exacerbates the negative ecological effects already present with the existing road including increased edge avoidance by a forest interior species, greater barrier effects for all 3 territorial forest songbirds, and increased access for brown-headed cowbirds into core forest. We support collocation as a mitigation strategy but emphasize restricting overall corridor width to reduce the additional ecological costs associated with this practice.

@article{rincon_combining_2023,
	title = {Combining {Landsat} {TIR}-imagery data and {ERA5} reanalysis information with different calibration strategies to improve simulations of streamflow and river temperature in the {Canadian} {Subarctic}},
	volume = {37},
	copyright = {© 2023 The Authors. Hydrological Processes published by John Wiley \& Sons Ltd.},
	issn = {1099-1085},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/hyp.15008},
	doi = {10.1002/hyp.15008},
	abstract = {Arctic and Subarctic environments are among the most vulnerable regions to climate change. Increases in liquid precipitation and changes in snowmelt onset are cited as the main drivers of change in streamflow and water temperature patterns in some of the largest rivers of the Canadian Arctic. However, in spite of this evidence, there is still a lack of research on water temperature, particularly in the eastern Canadian Arctic. In this paper, we use the CEQUEAU hydrological-water temperature model to derive consistent long-term daily flow and stream temperature time series in Aux Mélèzes River, a non-regulated basin (41 297 km2) in the eastern Canadian subarctic. The model was forced using reanalysis data from the fifth-generation ECMWF atmospheric reanalyses (ERA5) from 1979 to 2020. We used water temperature derived from thermal infrared (TIR) images as reference data to calibrate CEQUEAU's water temperature model, with calibration performed using single-site, multi-site, and upscaling factors approaches. Our results indicate that the CEQUEAU model can simulate streamflow patterns in the river and shows excellent spatiotemporal performance with Kling-Gupta Efficiency (KGE) metric {\textgreater}0.8. Using the best-performing flow simulation as one of the inputs allowed us to produce synthetic daily water temperature time series throughout the basin, with the multi-site calibration approach being the most accurate with root mean square errors (RMSE) {\textless}2.0°C. The validation of the water temperature simulations with a three-year in situ data logger dataset yielded an RMSE = 1.38°C for the summer temperatures, highlighting the robustness of the calibrated parameters and the chosen calibration strategy. This research demonstrates the reliability of TIR imagery and ERA5 as sources of model calibration data in data-sparse environments and underlines the CEQUEAU model as an assessment tool, opening the door to its use to assess climate change impact on the arctic regions of Canada.},
	language = {en},
	number = {10},
	urldate = {2023-11-24},
	journal = {Hydrological Processes},
	author = {Rincón, Eisinhower and St-hilaire, André and Bergeron, Normand E. and Dugdale, Stephen J.},
	year = {2023},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/hyp.15008},
	keywords = {NALCMS},
	pages = {e15008},
}

Arctic and Subarctic environments are among the most vulnerable regions to climate change. Increases in liquid precipitation and changes in snowmelt onset are cited as the main drivers of change in streamflow and water temperature patterns in some of the largest rivers of the Canadian Arctic. However, in spite of this evidence, there is still a lack of research on water temperature, particularly in the eastern Canadian Arctic. In this paper, we use the CEQUEAU hydrological-water temperature model to derive consistent long-term daily flow and stream temperature time series in Aux Mélèzes River, a non-regulated basin (41 297 km2) in the eastern Canadian subarctic. The model was forced using reanalysis data from the fifth-generation ECMWF atmospheric reanalyses (ERA5) from 1979 to 2020. We used water temperature derived from thermal infrared (TIR) images as reference data to calibrate CEQUEAU's water temperature model, with calibration performed using single-site, multi-site, and upscaling factors approaches. Our results indicate that the CEQUEAU model can simulate streamflow patterns in the river and shows excellent spatiotemporal performance with Kling-Gupta Efficiency (KGE) metric \textgreater0.8. Using the best-performing flow simulation as one of the inputs allowed us to produce synthetic daily water temperature time series throughout the basin, with the multi-site calibration approach being the most accurate with root mean square errors (RMSE) \textless2.0°C. The validation of the water temperature simulations with a three-year in situ data logger dataset yielded an RMSE = 1.38°C for the summer temperatures, highlighting the robustness of the calibrated parameters and the chosen calibration strategy. This research demonstrates the reliability of TIR imagery and ERA5 as sources of model calibration data in data-sparse environments and underlines the CEQUEAU model as an assessment tool, opening the door to its use to assess climate change impact on the arctic regions of Canada.

@article{fortin_combining_2023,
	title = {Combining forest growth models and remotely sensed data through a hierarchical model-based inferential framework},
	volume = {53},
	issn = {0045-5067, 1208-6037},
	url = {https://cdnsciencepub.com/doi/10.1139/cjfr-2022-0168},
	doi = {10.1139/cjfr-2022-0168},
	abstract = {Large-area growth estimates can be obtained by coupling growth model predictions with wall-to-wall remotely sensed auxiliary variables through a generalized hierarchical model-based (GHMB) inferential framework. So far, most GHMB variance estimators do not account for the residual errors of the submodels and their spatial correlations. This likely induces an underestimation of the true variance of the point estimator. In this study, we provide an example of large-area growth estimation obtained through the GHMB framework. To do this, we developed a new variance estimator that accounts for residual errors as well as potential spatial correlations among them. We tested this variance estimator through a simulation study and then used it to estimate the annual volume increment for a forest management unit in Quebec, Canada. Our results show that, contrary to our expectation, neglecting the residual errors of the different submodels leads to overestimating the true variance of the point estimator. We observed increases in the overestimation with small populations and spatially correlated residual errors. Our developed variance estimator corrected this overestimation and made it possible to derive reliable confidence intervals for annual volume increments at the population level.},
	language = {en},
	number = {2},
	urldate = {2023-06-01},
	journal = {Canadian Journal of Forest Research},
	author = {Fortin, Mathieu and van Lier, Olivier and Côté, Jean-François},
	month = feb,
	year = {2023},
	keywords = {Political Boundaries},
	pages = {90--102},
}

Large-area growth estimates can be obtained by coupling growth model predictions with wall-to-wall remotely sensed auxiliary variables through a generalized hierarchical model-based (GHMB) inferential framework. So far, most GHMB variance estimators do not account for the residual errors of the submodels and their spatial correlations. This likely induces an underestimation of the true variance of the point estimator. In this study, we provide an example of large-area growth estimation obtained through the GHMB framework. To do this, we developed a new variance estimator that accounts for residual errors as well as potential spatial correlations among them. We tested this variance estimator through a simulation study and then used it to estimate the annual volume increment for a forest management unit in Quebec, Canada. Our results show that, contrary to our expectation, neglecting the residual errors of the different submodels leads to overestimating the true variance of the point estimator. We observed increases in the overestimation with small populations and spatially correlated residual errors. Our developed variance estimator corrected this overestimation and made it possible to derive reliable confidence intervals for annual volume increments at the population level.

@article{chambers_combining_2023,
	title = {Combining resilience and resistance with threat-based approaches for prioritizing management actions in sagebrush ecosystems},
	volume = {5},
	issn = {2578-4854},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/csp2.13021},
	doi = {10.1111/csp2.13021},
	abstract = {The sagebrush biome is a dryland region in the western United States experiencing rapid transformations to novel ecological states. Threat-based approaches for managing anthropogenic and ecosystem threats have recently become prominent, but successfully mitigating threats depends on the ecological resilience of ecosystems. We used a spatially explicit approach for prioritizing management actions that combined a threat-based model with models of resilience to disturbance and resistance to annual grass invasion. The threat-based model assessed geographic patterns in sagebrush ecological integrity (SEI) to identify core sagebrush, growth opportunity, and other rangeland areas. The resilience and resistance model identified ecologically relevant climate and soil water availability indicators from process-based ecohydrological models. The SEI areas and resilience and resistance indicators were consistent—the resilience and resistance indicators showed generally positive relationships with the SEI areas. They also were complementary—SEI areas provided information on intact sagebrush areas and threats, while resilience and resistance provided information on responses to disturbances and management actions. The SEI index and resilience and resistance indicators provide the basis for prioritizing conservation and restoration actions and determining appropriate strategies. The difficulty and time required to conserve or restore SEI areas increase as threats increases and resilience and resistance decrease.},
	language = {en},
	number = {11},
	urldate = {2026-05-22},
	journal = {Conservation Science and Practice},
	author = {Chambers, Jeanne C. and Brown, Jessi L. and Bradford, John B. and Doherty, Kevin E. and Crist, Michele R. and Schlaepfer, Daniel R. and Urza, Alexandra K. and Short, Karen C.},
	year = {2023},
	note = {\_eprint: https://conbio.onlinelibrary.wiley.com/doi/pdf/10.1111/csp2.13021},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {e13021},
}

The sagebrush biome is a dryland region in the western United States experiencing rapid transformations to novel ecological states. Threat-based approaches for managing anthropogenic and ecosystem threats have recently become prominent, but successfully mitigating threats depends on the ecological resilience of ecosystems. We used a spatially explicit approach for prioritizing management actions that combined a threat-based model with models of resilience to disturbance and resistance to annual grass invasion. The threat-based model assessed geographic patterns in sagebrush ecological integrity (SEI) to identify core sagebrush, growth opportunity, and other rangeland areas. The resilience and resistance model identified ecologically relevant climate and soil water availability indicators from process-based ecohydrological models. The SEI areas and resilience and resistance indicators were consistent—the resilience and resistance indicators showed generally positive relationships with the SEI areas. They also were complementary—SEI areas provided information on intact sagebrush areas and threats, while resilience and resistance provided information on responses to disturbances and management actions. The SEI index and resilience and resistance indicators provide the basis for prioritizing conservation and restoration actions and determining appropriate strategies. The difficulty and time required to conserve or restore SEI areas increase as threats increases and resilience and resistance decrease.

@article{de_pedro_congruence_2023,
	title = {Congruence between species richness and phylogenetic diversity in {North} {America} for the bee genus {Diadasia} ({Hymenoptera}: {Apidae})},
	issn = {1572-9710},
	shorttitle = {Congruence between species richness and phylogenetic diversity in {North} {America} for the bee genus {Diadasia} ({Hymenoptera}},
	url = {https://doi.org/10.1007/s10531-023-02706-8},
	doi = {10.1007/s10531-023-02706-8},
	abstract = {The current ecological crisis stemming from the loss of biodiversity and associated ecosystem services, highlights the urgency of documenting diversity and distribution. Bees are a classical example of an ecologically and economically important group, due to their high diversity and varied ecosystem services, especially pollination. Here, two common biodiversity indices, namely species richness and phylogenetic diversity, are evaluated geographically to determine the best approach for selecting areas of conservation priority. The model organisms used in this study are the North American species belonging to the bee genus Diadasia (Apidae). Based on the results obtained by analyzing distributional records and a molecular phylogeny, we can see that species richness and phylogenetic diversity are closely linked, although phylogenetic diversity provides a more detailed assessment of the spatial distribution of diversity. Therefore, while either one of these commonly used indices are valid as far as selecting areas of conservation priority, we recommend, if possible, to include genetic information in biodiversity and conservation studies.},
	language = {en},
	urldate = {2023-10-05},
	journal = {Biodiversity and Conservation},
	author = {de Pedro, Diego and Ceccarelli, Fadia Sara and Vandame, Rémy and Mérida, Jorge and Sagot, Philippe},
	month = sep,
	year = {2023},
	keywords = {Terrestrial Ecoregions},
}

The current ecological crisis stemming from the loss of biodiversity and associated ecosystem services, highlights the urgency of documenting diversity and distribution. Bees are a classical example of an ecologically and economically important group, due to their high diversity and varied ecosystem services, especially pollination. Here, two common biodiversity indices, namely species richness and phylogenetic diversity, are evaluated geographically to determine the best approach for selecting areas of conservation priority. The model organisms used in this study are the North American species belonging to the bee genus Diadasia (Apidae). Based on the results obtained by analyzing distributional records and a molecular phylogeny, we can see that species richness and phylogenetic diversity are closely linked, although phylogenetic diversity provides a more detailed assessment of the spatial distribution of diversity. Therefore, while either one of these commonly used indices are valid as far as selecting areas of conservation priority, we recommend, if possible, to include genetic information in biodiversity and conservation studies.

@article{arsenault_continuous_2023,
	title = {Continuous streamflow prediction in ungauged basins: long short-term memory neural networks clearly outperform traditional hydrological models},
	volume = {27},
	issn = {1607-7938},
	url = {https://hess.copernicus.org/articles/27/139/2023/},
	doi = {10.5194/hess-27-139-2023},
	abstract = {Abstract. This study investigates the ability of long short-term memory (LSTM) neural networks to perform streamflow prediction at ungauged basins. A set of state-of-the-art, hydrological model-dependent regionalization methods are applied to 148 catchments in northeast North America and compared to an LSTM model that uses the exact same available data as the hydrological models. While conceptual model-based methods attempt to derive parameterizations at ungauged sites from other similar or nearby catchments, the LSTM model uses all available data in the region to maximize the information content and increase its robustness. Furthermore, by design, the LSTM does not require explicit definition of hydrological processes and derives its own structure from the provided data. The LSTM networks were able to clearly outperform the hydrological models in a leave-one-out cross-validation regionalization setting on most catchments in the study area, with the LSTM model outperforming the hydrological models in 93 \% to 97 \% of catchments depending on the hydrological model. Furthermore, for up to 78 \% of the catchments, the LSTM model was able to predict streamflow more accurately on pseudo-ungauged catchments than hydrological models calibrated on the target data, showing that the LSTM model's structure was better suited to convert the meteorological data and geophysical descriptors into streamflow than the hydrological models even calibrated to those sites in these cases. Furthermore, the LSTM model robustness was tested by varying its hyperparameters, and still outperformed hydrological models in regionalization in almost all cases. Overall, LSTM networks have the potential to change the regionalization research landscape by providing clear improvement pathways over traditional methods in the field of streamflow prediction in ungauged catchments.},
	number = {1},
	journal = {Hydrology and Earth System Sciences},
	author = {Arsenault, Richard and Martel, Jean-Luc and Brunet, Frédéric and Brissette, François and Mai, Juliane},
	month = jan,
	year = {2023},
	keywords = {NALCMS},
	pages = {139--157},
}

Abstract. This study investigates the ability of long short-term memory (LSTM) neural networks to perform streamflow prediction at ungauged basins. A set of state-of-the-art, hydrological model-dependent regionalization methods are applied to 148 catchments in northeast North America and compared to an LSTM model that uses the exact same available data as the hydrological models. While conceptual model-based methods attempt to derive parameterizations at ungauged sites from other similar or nearby catchments, the LSTM model uses all available data in the region to maximize the information content and increase its robustness. Furthermore, by design, the LSTM does not require explicit definition of hydrological processes and derives its own structure from the provided data. The LSTM networks were able to clearly outperform the hydrological models in a leave-one-out cross-validation regionalization setting on most catchments in the study area, with the LSTM model outperforming the hydrological models in 93 % to 97 % of catchments depending on the hydrological model. Furthermore, for up to 78 % of the catchments, the LSTM model was able to predict streamflow more accurately on pseudo-ungauged catchments than hydrological models calibrated on the target data, showing that the LSTM model's structure was better suited to convert the meteorological data and geophysical descriptors into streamflow than the hydrological models even calibrated to those sites in these cases. Furthermore, the LSTM model robustness was tested by varying its hyperparameters, and still outperformed hydrological models in regionalization in almost all cases. Overall, LSTM networks have the potential to change the regionalization research landscape by providing clear improvement pathways over traditional methods in the field of streamflow prediction in ungauged catchments.

@article{palm_corridor-based_2023,
	title = {Corridor-based approach with spatial cross-validation reveals scale-dependent effects of geographic distance, human footprint and canopy cover on grizzly bear genetic connectivity},
	volume = {32},
	copyright = {© 2023 His Majesty the King in Right of Canada. Molecular Ecology © 2023 John Wiley \& Sons Ltd. Reproduced with the permission of the Minister of Environment and Climate Change Canada. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.},
	issn = {1365-294X},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/mec.17098},
	doi = {10.1111/mec.17098},
	abstract = {Understanding how human infrastructure and other landscape attributes affect genetic differentiation in animals is an important step for identifying and maintaining dispersal corridors for these species. We built upon recent advances in the field of landscape genetics by using an individual-based and multiscale approach to predict landscape-level genetic connectivity for grizzly bears (Ursus arctos) across 100,000 km2 in Canada's southern Rocky Mountains. We used a genetic dataset with 1156 unique individuals genotyped at nine microsatellite loci to identify landscape characteristics that influence grizzly bear gene flow at multiple spatial scales and map predicted genetic connectivity through a matrix of rugged terrain, large protected areas, highways and a growing human footprint. Our corridor-based modelling approach used a machine learning algorithm that objectively parameterized landscape resistance, incorporated spatial cross validation and variable selection and explicitly accounted for isolation by distance. This approach avoided overfitting, discarded variables that did not improve model performance across withheld test datasets and spatial predictive capacity compared to random cross-validation. We found that across all spatial scales, geographic distance explained more variation in genetic differentiation in grizzly bears than landscape variables. Human footprint inhibited connectivity across all spatial scales, while open canopies inhibited connectivity at the broadest spatial scale. Our results highlight the negative effect of human footprint on genetic connectivity, provide strong evidence for using spatial cross-validation in landscape genetics analyses and show that multiscale analyses provide additional information on how landscape variables affect genetic differentiation.},
	language = {en},
	number = {19},
	urldate = {2024-01-31},
	journal = {Molecular Ecology},
	author = {Palm, Eric C. and Landguth, Erin L. and Holden, Zachary A. and Day, Casey C. and Lamb, Clayton T. and Frame, Paul F. and Morehouse, Andrea T. and Mowat, Garth and Proctor, Michael F. and Sawaya, Michael A. and Stenhouse, Gordon and Whittington, Jesse and Zeller, Katherine A.},
	year = {2023},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/mec.17098},
	keywords = {NALCMS},
	pages = {5211--5227},
}

Understanding how human infrastructure and other landscape attributes affect genetic differentiation in animals is an important step for identifying and maintaining dispersal corridors for these species. We built upon recent advances in the field of landscape genetics by using an individual-based and multiscale approach to predict landscape-level genetic connectivity for grizzly bears (Ursus arctos) across 100,000 km2 in Canada's southern Rocky Mountains. We used a genetic dataset with 1156 unique individuals genotyped at nine microsatellite loci to identify landscape characteristics that influence grizzly bear gene flow at multiple spatial scales and map predicted genetic connectivity through a matrix of rugged terrain, large protected areas, highways and a growing human footprint. Our corridor-based modelling approach used a machine learning algorithm that objectively parameterized landscape resistance, incorporated spatial cross validation and variable selection and explicitly accounted for isolation by distance. This approach avoided overfitting, discarded variables that did not improve model performance across withheld test datasets and spatial predictive capacity compared to random cross-validation. We found that across all spatial scales, geographic distance explained more variation in genetic differentiation in grizzly bears than landscape variables. Human footprint inhibited connectivity across all spatial scales, while open canopies inhibited connectivity at the broadest spatial scale. Our results highlight the negative effect of human footprint on genetic connectivity, provide strong evidence for using spatial cross-validation in landscape genetics analyses and show that multiscale analyses provide additional information on how landscape variables affect genetic differentiation.

@techreport{gebhardt_creation_2023,
	address = {Germany},
	title = {Creation of a harmonized land cover map as an example for the entire region of the {Geneva} {Air} {Pollution} {Convention}},
	url = {https://www.umweltbundesamt.de/en/publikationen/creation-of-a-harmonized-land-cover-map-as-an},
	abstract = {A new map product for calculating the critical loads for eutrophication and acidification of terrestrial ecosystems and for modelling air quality was created in this project. The spatial extent of the map covers a large number of countries in Europe, the Caucasus and Central Asia. The results of this project are map products representing the land cover in 217 EUNIS classes and 13 RCG classes. In addition to the individual, national application of the data set, a broader use of the data is planned within the framework of the Convention on Long-Range Transboundary Air Pollution.},
	language = {en},
	urldate = {2024-09-18},
	institution = {German Environment Agency},
	author = {Gebhardt, Steffen},
	year = {2023},
	keywords = {NALCMS},
	pages = {122},
}

A new map product for calculating the critical loads for eutrophication and acidification of terrestrial ecosystems and for modelling air quality was created in this project. The spatial extent of the map covers a large number of countries in Europe, the Caucasus and Central Asia. The results of this project are map products representing the land cover in 217 EUNIS classes and 13 RCG classes. In addition to the individual, national application of the data set, a broader use of the data is planned within the framework of the Convention on Long-Range Transboundary Air Pollution.

@article{griffith_development_2023,
	title = {Development of national stressor-specific genus sensitivity values},
	volume = {895},
	issn = {0048-9697},
	url = {https://www.sciencedirect.com/science/article/pii/S0048969723037440},
	doi = {10.1016/j.scitotenv.2023.165121},
	abstract = {Effective water quality management is based on associations between at least two pieces of information: a stressor and a response. However, assessments are hindered by the lack of pre-developed stressor-response associations. To remedy this, I developed genus stressor-specific sensitivity values (SVs) for up to 704 genera to estimate a sensitive genera ratio (SGR) metric for as many as 34 common stream stressors. The SVs were estimated from a large, paired macroinvertebrate and environmental data set for the contiguous United States. Environmental variables measuring potential stressors were selected that were generally uncorrelated and usually had several thousand station observations. I calculated relative abundance weighted averages (WA) for each genus and environmental variable meeting data requirements in a calibration data set. Each environmental variable was split into 10 intervals along each stressor gradient. Genera were assigned an SV from 1 to 10 based on the interval consistent with the WA for each environmental parameter. Using the calibration derived SVs, SGRs were calculated for the calibration and a validation subsets. SGRs are the number of genera with SV ≤ 5 divided by the total number of genera in a sample. In general, as stress increased, the SGR (range: 0–1) decreased for many environmental variables, but for five environmental variables, the decrease was not consistent. The 95 \% confidence intervals of the mean of the SGRs were greater for least disturbed stations compared to all other stations for 23 of the remaining 29 environmental variables. Regional performance of SGRs was evaluated by subdividing the calibration data set into West, Central, and East subsets and recalculating SVs. SGR mean absolute errors were smallest in the East and Central regions. These stressor-specific SVs expand the available tools for assessing stream biological impairments from commonly encountered environmental stressors.},
	urldate = {2026-05-27},
	journal = {Science of The Total Environment},
	author = {Griffith, Michael B.},
	month = oct,
	year = {2023},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {165121},
}

Effective water quality management is based on associations between at least two pieces of information: a stressor and a response. However, assessments are hindered by the lack of pre-developed stressor-response associations. To remedy this, I developed genus stressor-specific sensitivity values (SVs) for up to 704 genera to estimate a sensitive genera ratio (SGR) metric for as many as 34 common stream stressors. The SVs were estimated from a large, paired macroinvertebrate and environmental data set for the contiguous United States. Environmental variables measuring potential stressors were selected that were generally uncorrelated and usually had several thousand station observations. I calculated relative abundance weighted averages (WA) for each genus and environmental variable meeting data requirements in a calibration data set. Each environmental variable was split into 10 intervals along each stressor gradient. Genera were assigned an SV from 1 to 10 based on the interval consistent with the WA for each environmental parameter. Using the calibration derived SVs, SGRs were calculated for the calibration and a validation subsets. SGRs are the number of genera with SV ≤ 5 divided by the total number of genera in a sample. In general, as stress increased, the SGR (range: 0–1) decreased for many environmental variables, but for five environmental variables, the decrease was not consistent. The 95 % confidence intervals of the mean of the SGRs were greater for least disturbed stations compared to all other stations for 23 of the remaining 29 environmental variables. Regional performance of SGRs was evaluated by subdividing the calibration data set into West, Central, and East subsets and recalculating SVs. SGR mean absolute errors were smallest in the East and Central regions. These stressor-specific SVs expand the available tools for assessing stream biological impairments from commonly encountered environmental stressors.

@article{peraza_diet_2023,
	title = {Diet and landscape characteristics drive spatial patterns of mercury accumulation in a high-latitude terrestrial carnivore},
	volume = {18},
	issn = {1932-6203},
	url = {https://dx.plos.org/10.1371/journal.pone.0285826},
	doi = {10.1371/journal.pone.0285826},
	abstract = {Limited information exists on mercury concentrations and environmental drivers of mercury bioaccumulation in high latitude terrestrial carnivores. Spatial patterns of mercury concentrations in wolverine (
              Gulo gulo
              , n = 419) were assessed across a 1,600,000 km
              2
              study area in relation to landscape, climate, diet and biological factors in Arctic and boreal biomes of western Canada. Hydrogen stable isotope ratios were measured in wolverine hair from a subset of 80 animals to assess the spatial scale for characterizing environmental conditions of their habitat. Habitat characteristics were determined using GIS methods and raster datasets at two scales, the collection location point and a 150 km radius buffer, which was selected based on results of a correlation analysis between hydrogen stable isotopes in precipitation and wolverine hair. Total mercury concentrations in wolverine muscle ranged {\textgreater}2 orders of magnitude from 0.01 to 5.72 μg/g dry weight and varied geographically, with the highest concentrations in the Northwest Territories followed by Nunavut and Yukon. Regression models at both spatial scales indicated diet (based on nitrogen stable isotope ratios) was the strongest explanatory variable of mercury concentrations in wolverine, with smaller though statistically significant contributions from landscape variables (soil organic carbon, percent cover of wet area, percent cover of perennial snow-ice) and distance to the Arctic Ocean coast. The carbon and nitrogen stable isotope ratios of wolverine muscle suggested greater mercury bioaccumulation could be associated with feeding on marine biota in coastal habitats. Landscape variables identified in the modelling may reflect habitat conditions which support enhanced methylmercury transfer to terrestrial biota. Spatially-explicit estimates of wet atmospheric deposition were positively correlated with wolverine mercury concentrations but this variable was not selected in the final regression models. These landscape patterns provide a basis for further research on underlying processes enhancing methylmercury uptake in high latitude terrestrial food webs.},
	language = {en},
	number = {5},
	urldate = {2023-06-02},
	journal = {PLOS ONE},
	author = {Peraza, Inés and Chételat, John and Richardson, Murray and Jung, Thomas S. and Awan, Malik and Baryluk, Steve and Dastoor, Ashu and Harrower, William and Kukka, Piia M. and McClelland, Christine and Mowat, Garth and Pelletier, Nicolas and Rodford, Christine and Ryjkov, Andrei},
	editor = {Qureshi, Asif},
	month = may,
	year = {2023},
	keywords = {Terrestrial Ecoregions},
	pages = {e0285826},
}

Limited information exists on mercury concentrations and environmental drivers of mercury bioaccumulation in high latitude terrestrial carnivores. Spatial patterns of mercury concentrations in wolverine ( Gulo gulo , n = 419) were assessed across a 1,600,000 km 2 study area in relation to landscape, climate, diet and biological factors in Arctic and boreal biomes of western Canada. Hydrogen stable isotope ratios were measured in wolverine hair from a subset of 80 animals to assess the spatial scale for characterizing environmental conditions of their habitat. Habitat characteristics were determined using GIS methods and raster datasets at two scales, the collection location point and a 150 km radius buffer, which was selected based on results of a correlation analysis between hydrogen stable isotopes in precipitation and wolverine hair. Total mercury concentrations in wolverine muscle ranged \textgreater2 orders of magnitude from 0.01 to 5.72 μg/g dry weight and varied geographically, with the highest concentrations in the Northwest Territories followed by Nunavut and Yukon. Regression models at both spatial scales indicated diet (based on nitrogen stable isotope ratios) was the strongest explanatory variable of mercury concentrations in wolverine, with smaller though statistically significant contributions from landscape variables (soil organic carbon, percent cover of wet area, percent cover of perennial snow-ice) and distance to the Arctic Ocean coast. The carbon and nitrogen stable isotope ratios of wolverine muscle suggested greater mercury bioaccumulation could be associated with feeding on marine biota in coastal habitats. Landscape variables identified in the modelling may reflect habitat conditions which support enhanced methylmercury transfer to terrestrial biota. Spatially-explicit estimates of wet atmospheric deposition were positively correlated with wolverine mercury concentrations but this variable was not selected in the final regression models. These landscape patterns provide a basis for further research on underlying processes enhancing methylmercury uptake in high latitude terrestrial food webs.

@article{hayward_diet_2023,
	title = {Diet selection in the {Coyote} {Canis} latrans},
	volume = {104},
	issn = {0022-2372},
	url = {https://doi.org/10.1093/jmammal/gyad094},
	doi = {10.1093/jmammal/gyad094},
	abstract = {The Coyote (Canis latrans) is one of the most studied species in North America with at least 445 papers on its diet alone. While this research has yielded excellent reviews of what coyotes eat, it has been inadequate to draw deeper conclusions because no synthesis to date has considered prey availability. We accounted for prey availability by investigating the prey selection of coyotes across its distribution using the traditional Jacobs’ index method, as well as the new iterative preference averaging (IPA) method on scats and biomass. We found that coyotes selected for Dall’s Sheep (Ovis dalli), White-tailed Deer (Odocoileus virginianus), Eastern Cottontail Rabbit (Sylvilagus floridanus), and California Vole (Microtus californicus), which yielded a predator-to-preferred prey mass ratio of 1:2. We also found that coyotes avoided preying on other small mammals, including carnivorans and arboreal species. There was strong concordance between the traditional and IPA method on scats, but this pattern was weakened when biomass was considered. General linear models revealed that coyotes preferred to prey upon larger species that were riskier to hunt, reflecting their ability to hunt in groups, and were least likely to hunt solitary species. Coyotes increasingly selected Mule Deer (O. hemionus) and Snowshoe Hare (Lepus americanus) at higher latitudes, whereas Black-tailed Jackrabbit (L. californicus) were increasingly selected toward the tropics. Mule Deer were increasingly selected at higher coyote densities, while Black-tailed Jackrabbit were increasingly avoided at higher coyote densities. Coyote predation could constrain the realized niche of prey species at the distributional limits of the predator through their increased efficiency of predation reflected in increased prey selection values. These results are integral to improved understandings of Coyote ecology and can inform predictive analyses allowing for spatial variation, which ultimately will lead to better understandings about the ecological role of the coyote across different ecosystems.},
	number = {6},
	urldate = {2024-01-10},
	journal = {Journal of Mammalogy},
	author = {Hayward, Matt W and Mitchell, Carl D and Kamler, Jan F and Rippon, Paul and Heit, David R and Nams, Vilis and Montgomery, Robert A},
	month = dec,
	year = {2023},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {1338--1352},
}

The Coyote (Canis latrans) is one of the most studied species in North America with at least 445 papers on its diet alone. While this research has yielded excellent reviews of what coyotes eat, it has been inadequate to draw deeper conclusions because no synthesis to date has considered prey availability. We accounted for prey availability by investigating the prey selection of coyotes across its distribution using the traditional Jacobs’ index method, as well as the new iterative preference averaging (IPA) method on scats and biomass. We found that coyotes selected for Dall’s Sheep (Ovis dalli), White-tailed Deer (Odocoileus virginianus), Eastern Cottontail Rabbit (Sylvilagus floridanus), and California Vole (Microtus californicus), which yielded a predator-to-preferred prey mass ratio of 1:2. We also found that coyotes avoided preying on other small mammals, including carnivorans and arboreal species. There was strong concordance between the traditional and IPA method on scats, but this pattern was weakened when biomass was considered. General linear models revealed that coyotes preferred to prey upon larger species that were riskier to hunt, reflecting their ability to hunt in groups, and were least likely to hunt solitary species. Coyotes increasingly selected Mule Deer (O. hemionus) and Snowshoe Hare (Lepus americanus) at higher latitudes, whereas Black-tailed Jackrabbit (L. californicus) were increasingly selected toward the tropics. Mule Deer were increasingly selected at higher coyote densities, while Black-tailed Jackrabbit were increasingly avoided at higher coyote densities. Coyote predation could constrain the realized niche of prey species at the distributional limits of the predator through their increased efficiency of predation reflected in increased prey selection values. These results are integral to improved understandings of Coyote ecology and can inform predictive analyses allowing for spatial variation, which ultimately will lead to better understandings about the ecological role of the coyote across different ecosystems.

@article{ceccarelli_diversidad_2023,
	title = {Diversidad genética e historias poblacionales de dos especies de {Phidippus} ({Araneae}: {Salticidae}) del noroeste de {México}},
	volume = {94},
	copyright = {Derechos de autor 2023 Revista Mexicana de Biodiversidad},
	issn = {2007-8706},
	shorttitle = {Genetic diversity and population histories of two species of {Phidippus} ({Araneae}},
	url = {https://revista.ib.unam.mx/index.php/bio/article/view/5052},
	doi = {10.22201/ib.20078706e.2023.94.5052},
	abstract = {The northwestern Mexican Baja California state is an ecologically unique area being the only part of the country with a Mediterranean ecosystem and a high species diversity and endemism for many groups. Studies on the biodiversity of the region are scarce, especially regarding ecologically important groups such as terrestrial arthropods. Even scarcer are studies on another important aspect of diversity, namely genetic diversity. Due to the paucity of information, the genetic diversity and population histories of the 2 most abundant species of Phidippus (Araneae: Salticidae) of the region are presented, based on nuclear and mitochondrial DNA data. Phidippus johnsoni, the more widespread of the 2, belonged to 1 large, panmictic population in Baja California, while P. phoenix was divided into 2 populations. Both species have high genetic diversity and estimated large population sizes, which increased during the last 150,000 years for P. johnsoni, and the last 30,000 years, after the Last Glacial Maximum for P. phoenix. This study, therefore, reinforces the importance of this area, not only for its species diversity but also for the genetic diversity found within the populations, which reflects ecological stability during the Pleistocene, allowing for the accumulation of genetic diversity through time.},
	language = {en},
	urldate = {2023-06-23},
	journal = {Revista Mexicana de Biodiversidad},
	author = {Ceccarelli, Fadia Sara and Garduño-Villaseñor, Luz Abril and Hernández-Salgado, Luis Carlos},
	month = feb,
	year = {2023},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {e945052--e945052},
}

The northwestern Mexican Baja California state is an ecologically unique area being the only part of the country with a Mediterranean ecosystem and a high species diversity and endemism for many groups. Studies on the biodiversity of the region are scarce, especially regarding ecologically important groups such as terrestrial arthropods. Even scarcer are studies on another important aspect of diversity, namely genetic diversity. Due to the paucity of information, the genetic diversity and population histories of the 2 most abundant species of Phidippus (Araneae: Salticidae) of the region are presented, based on nuclear and mitochondrial DNA data. Phidippus johnsoni, the more widespread of the 2, belonged to 1 large, panmictic population in Baja California, while P. phoenix was divided into 2 populations. Both species have high genetic diversity and estimated large population sizes, which increased during the last 150,000 years for P. johnsoni, and the last 30,000 years, after the Last Glacial Maximum for P. phoenix. This study, therefore, reinforces the importance of this area, not only for its species diversity but also for the genetic diversity found within the populations, which reflects ecological stability during the Pleistocene, allowing for the accumulation of genetic diversity through time.

@phdthesis{reynolds_does_2023,
	title = {Does {It} {Matter} {Where} {Stocker} {Steers} {Originate} {From}? {An} {Evaluation} of {Originating} {Environment} on {Performance} and the {Rumen} {Microbiome}},
	shorttitle = {Does {It} {Matter} {Where} {Stocker} {Steers} {Originate} {From}?},
	url = {https://uwyo.primo.exlibrisgroup.com/discovery/fulldisplay?docid=cdi_proquest_journals_2817927109&context=PC&vid=01UOW_INST:quicksearch&lang=en&search_scope=MyInst_and_CI&adaptor=Primo%20Central&tab=Everything&query=any,contains,Does%20It%20Matter%20Where%20Stocker%20Steers%20Originate%20From%3F%20An%20Evaluation%20of%20Originating%20Environment%20on%20Performance%20and%20the%20Rumen%20Microbiome},
	abstract = {Growing stocker cattle on native rangelands is a viable agricultural enterprise for many ranchers as yearlings offer producers flexibility in management and marketing of the cattle. Grazing studies evaluating livestock performance across different rangeland ecosystems are extensive, and differences in weight gains across these studies can be attributed to genetics, environment, climate, management. However, the origin of cattle and its implications for producers is understudied. We compared performance of yearling steers originating from a local ranch in northeastern Colorado to yearlings originating from a high-elevation mountain ranch in southeastern Wyoming and a mixed-grass prairie ecosystem in south-central Nebraska. Forty steers of each origin grazed on the shortgrass steppe from mid-May to October with individual animal weights obtained at the beginning and end of each three grazing seasons (2019-2021). Weather patterns in 2019 and 2021 were similar, with spring precipitation followed by a dry late summer. In these years with normal precipitation, we observed consistent ordering of yearling steer weight gains by origin. In 2019 and 2021, local steers gained 1.08 and 0.96 kg/head/day, respectively. Weight gains of steers from the high-elevation ranch were 12 – 23\% lower at 0.83 and 0.84 kg/head/day in 2019 and 2021, respectively. Yearlings from the mixed-grass prairie had 20 – 31\% lower gains than local cattle at 0.75 and 0.76 kg/head/day in 2019 and 2021, respectively. Average daily gain of yearling steers was reduced 15 – 25\% by drought in 2020, where forage quantity and quality were greatly impacted. Local cattle gains were 0.81 kg/head/day, which is 11\% greater than gains observed in yearlings from the mixed-grass prairie. Diet quality, including measures of crude protein and digestible organic matter, did not differ among yearlings of different originating environments across the full grazing season in any year of the study. These data suggest that differences in weight gain of yearling steers could be attributed to physiological acclimation to a new grazing environment, lack of knowledge influencing grazing behavior, differences in digestive efficiency based on rumen microbial populations, or genetics that are not matched to grazing on the shortgrass steppe. To better understand the influence of origin on yearling steer ruminal microbial community structure and composition, rumen fluid was collected from 18 steers (n = 6 per origin) in each of the two non-drought years. Microbial DNA was extracted from the rumen fluid and 16S rRNA sequencing was completed on the Illumina MiSeq platform. QIIME2 was used to process reads, assign taxonomy, and compare samples utilizing alpha and beta diversity metrics as well as Analysis of Compositions of Microbiomes (ANCOM) to detect differences between originating environment, rangeland plant community, and sample period in each year. Differences in alpha diversity were observed within yearling steer origin and sampling date in richness and evenness Rangeland plant community did not influence differences in alpha or beta diversity measures. Ruminal microbial composition varied between origin in 2019 and differences in composition occurred between the early and late grazing season. In 2021, differences between originating environment were minimal, though compositional differences between early and late grazing were detected. Further investigation into the mechanisms by which originating environment influences performance of yearling steers could provide producers means to improve efficiency, as well as mitigate impacts of drought through optimally matching livestock to their grazing environment.},
	language = {eng},
	urldate = {2023-08-11},
	school = {ProQuest Dissertations Publishing},
	author = {Reynolds, Averi Q.},
	year = {2023},
	note = {Book Title: Does It Matter Where Stocker Steers Originate From? An Evaluation of Originating Environment on Performance and the Rumen Microbiome
ISBN: 9798379562151},
	keywords = {Terrestrial Ecoregions},
}

Growing stocker cattle on native rangelands is a viable agricultural enterprise for many ranchers as yearlings offer producers flexibility in management and marketing of the cattle. Grazing studies evaluating livestock performance across different rangeland ecosystems are extensive, and differences in weight gains across these studies can be attributed to genetics, environment, climate, management. However, the origin of cattle and its implications for producers is understudied. We compared performance of yearling steers originating from a local ranch in northeastern Colorado to yearlings originating from a high-elevation mountain ranch in southeastern Wyoming and a mixed-grass prairie ecosystem in south-central Nebraska. Forty steers of each origin grazed on the shortgrass steppe from mid-May to October with individual animal weights obtained at the beginning and end of each three grazing seasons (2019-2021). Weather patterns in 2019 and 2021 were similar, with spring precipitation followed by a dry late summer. In these years with normal precipitation, we observed consistent ordering of yearling steer weight gains by origin. In 2019 and 2021, local steers gained 1.08 and 0.96 kg/head/day, respectively. Weight gains of steers from the high-elevation ranch were 12 – 23% lower at 0.83 and 0.84 kg/head/day in 2019 and 2021, respectively. Yearlings from the mixed-grass prairie had 20 – 31% lower gains than local cattle at 0.75 and 0.76 kg/head/day in 2019 and 2021, respectively. Average daily gain of yearling steers was reduced 15 – 25% by drought in 2020, where forage quantity and quality were greatly impacted. Local cattle gains were 0.81 kg/head/day, which is 11% greater than gains observed in yearlings from the mixed-grass prairie. Diet quality, including measures of crude protein and digestible organic matter, did not differ among yearlings of different originating environments across the full grazing season in any year of the study. These data suggest that differences in weight gain of yearling steers could be attributed to physiological acclimation to a new grazing environment, lack of knowledge influencing grazing behavior, differences in digestive efficiency based on rumen microbial populations, or genetics that are not matched to grazing on the shortgrass steppe. To better understand the influence of origin on yearling steer ruminal microbial community structure and composition, rumen fluid was collected from 18 steers (n = 6 per origin) in each of the two non-drought years. Microbial DNA was extracted from the rumen fluid and 16S rRNA sequencing was completed on the Illumina MiSeq platform. QIIME2 was used to process reads, assign taxonomy, and compare samples utilizing alpha and beta diversity metrics as well as Analysis of Compositions of Microbiomes (ANCOM) to detect differences between originating environment, rangeland plant community, and sample period in each year. Differences in alpha diversity were observed within yearling steer origin and sampling date in richness and evenness Rangeland plant community did not influence differences in alpha or beta diversity measures. Ruminal microbial composition varied between origin in 2019 and differences in composition occurred between the early and late grazing season. In 2021, differences between originating environment were minimal, though compositional differences between early and late grazing were detected. Further investigation into the mechanisms by which originating environment influences performance of yearling steers could provide producers means to improve efficiency, as well as mitigate impacts of drought through optimally matching livestock to their grazing environment.

@techreport{buonanduci_does_2023,
	type = {{JFSP} {PROJECT} {ID}: 21-1-01-26},
	title = {Does high-severity patch structure scale consistently with fire size across the {Northwest} {US}? {\textbar} {Northern} {Rockies} {Fire} {Science} {Network}},
	url = {https://www.nrfirescience.org/resource/25504},
	urldate = {2023-06-30},
	institution = {School of Environmental and Forest Sciences, University of Washington},
	author = {Buonanduci, Michele S. and Harvey, Brian J},
	month = mar,
	year = {2023},
	keywords = {Terrestrial Ecoregions (CEC 1997)},
}

@article{chaudhary_east_2023,
	title = {East {Texas} forests show strong resilience to exceptional drought},
	volume = {96},
	issn = {0015-752X},
	url = {https://doi.org/10.1093/forestry/cpac050},
	doi = {10.1093/forestry/cpac050},
	abstract = {Drought-induced tree mortality has increased in many parts of the world because of climate change, and in some regions, has altered forest structure, species composition and ecosystem functions. These developments have the potential to reduce forest resilience and push forests over a tipping point to an alternate state (i.e. a different forest type or a non-forest ecosystem). Texas experienced an exceptional drought in 2011, which killed an estimated 65.5 million trees in the heavily forested areas of the East Texas region. The objective of this study was to understand the effects of the 2011 drought on mortality, biomass and growth in this region and explore forest stability at species, forest and ecoregion levels. We categorized 19 years’ time-series data of 1455 Forest Inventory and Analysis plots into four periods, base (2001–2003), pre-drought (2004–2010), drought (2011–2016) and post-drought (2017–2019), and used repeated-measures analysis of variance to analyse annual mortality, biomass loss, growth rates and the Forest Stability Index to understand forest stability. Our results show that tree mortality and biomass loss increased significantly during the drought period and annual growth rates declined. During the post-drought period, mortality and biomass loss rates returned to the pre-drought level and growth partially recovered. During the drought period, FSI dropped at species, forest type and ecoregion levels but recovered during the post-drought period, except for the Oak Woods and Prairies ecoregion and for forests dominated by southern red oak. Our results indicate that East Texas forests are undergoing a reorganization and recovery stage (in terms of species composition and stand structure) but have yet to reach a tipping point. Given the increased frequency and severity of climate change-induced weather events, East Texas forests could approach a tipping point in the future if there is insufficient time between events for reorganization and recovery. Further analyses are needed to understand the fate of tree species and forests in East Texas under global climate change.},
	number = {3},
	urldate = {2023-08-11},
	journal = {Forestry: An International Journal of Forest Research},
	author = {Chaudhary, Tilak and Xi, Weimin and Subedi, Mukti and Rideout-Hanzak, Sandra and Su, Haibin and Dewez, Nicholas P and Clarke, Stephen},
	month = jul,
	year = {2023},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {326--339},
}

Drought-induced tree mortality has increased in many parts of the world because of climate change, and in some regions, has altered forest structure, species composition and ecosystem functions. These developments have the potential to reduce forest resilience and push forests over a tipping point to an alternate state (i.e. a different forest type or a non-forest ecosystem). Texas experienced an exceptional drought in 2011, which killed an estimated 65.5 million trees in the heavily forested areas of the East Texas region. The objective of this study was to understand the effects of the 2011 drought on mortality, biomass and growth in this region and explore forest stability at species, forest and ecoregion levels. We categorized 19 years’ time-series data of 1455 Forest Inventory and Analysis plots into four periods, base (2001–2003), pre-drought (2004–2010), drought (2011–2016) and post-drought (2017–2019), and used repeated-measures analysis of variance to analyse annual mortality, biomass loss, growth rates and the Forest Stability Index to understand forest stability. Our results show that tree mortality and biomass loss increased significantly during the drought period and annual growth rates declined. During the post-drought period, mortality and biomass loss rates returned to the pre-drought level and growth partially recovered. During the drought period, FSI dropped at species, forest type and ecoregion levels but recovered during the post-drought period, except for the Oak Woods and Prairies ecoregion and for forests dominated by southern red oak. Our results indicate that East Texas forests are undergoing a reorganization and recovery stage (in terms of species composition and stand structure) but have yet to reach a tipping point. Given the increased frequency and severity of climate change-induced weather events, East Texas forests could approach a tipping point in the future if there is insufficient time between events for reorganization and recovery. Further analyses are needed to understand the fate of tree species and forests in East Texas under global climate change.

@article{brunell_effects_2023,
	title = {Effects of translocation on {American} crocodile movements and habitat use in {South} {Florida}},
	volume = {87},
	copyright = {© 2023 The Authors. The Journal of Wildlife Management published by Wiley Periodicals LLC on behalf of The Wildlife Society.},
	issn = {1937-2817},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/jwmg.22427},
	doi = {10.1002/jwmg.22427},
	abstract = {The range of the threatened American crocodile (Crocodylus acutus) in the United States is limited to the southernmost parts of Florida. As this species has recovered concurrently with an increasing human population, human–crocodile conflicts have also increased. Resolving conflicts can involve translocating crocodiles; however, they often return to the site from which they were removed. We examined the effects of translocation on crocodile movements, habitat use, body condition, and survival in Florida, USA, in 2018–2019 to refine recommendations for managers considering translocation to resolve human–crocodile conflict. We captured and attached global positioning system (GPS) units to 17 crocodiles, 10 of which served as a reference group (free-ranging crocodiles released at their capture site) and 7 served as a treatment group (crocodiles that were translocated 14–158 km from their capture site). We collected location data from individual crocodiles for 34–661 days (x ¯ {\textbackslash}mathopx{\textbackslash}limits{\textasciicircum}̅{\textbackslash} 250 days for each group). Body condition was similar for both groups. Corticosterone levels measured periodically during handling indicated that crocodiles experienced increasing stress levels during handling. Three crocodiles translocated ≤45 km from their original capture site returned to that location within 13 days. Three crocodiles translocated ≥110 km did not return. One female translocated 152 km was recaptured 0.42 km from its original capture site 965 days after its release. We identified 2 states of characteristic movement patterns: state 1 indicated individuals moving slowly and somewhat randomly, and state 2 indicated individuals exhibiting fast, active directional movement. Translocated individuals were more likely than reference individuals to switch to, and stay in, state 2. Because of concerns regarding return rates and heightened stress as a result of capture and translocation, we suggest crocodile translocations have limited conservation value and may only be worth considering once all other reasonable options are exhausted.},
	language = {en},
	number = {6},
	urldate = {2023-08-11},
	journal = {The Journal of Wildlife Management},
	author = {Brunell, Arnold M. and Deem, Vincent and Bankovich, Brittany and Bled, Florent and Mazzotti, Frank J.},
	year = {2023},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/jwmg.22427},
	keywords = {Terrestrial Ecoregions (Griffith 2010)},
	pages = {e22427},
}

The range of the threatened American crocodile (Crocodylus acutus) in the United States is limited to the southernmost parts of Florida. As this species has recovered concurrently with an increasing human population, human–crocodile conflicts have also increased. Resolving conflicts can involve translocating crocodiles; however, they often return to the site from which they were removed. We examined the effects of translocation on crocodile movements, habitat use, body condition, and survival in Florida, USA, in 2018–2019 to refine recommendations for managers considering translocation to resolve human–crocodile conflict. We captured and attached global positioning system (GPS) units to 17 crocodiles, 10 of which served as a reference group (free-ranging crocodiles released at their capture site) and 7 served as a treatment group (crocodiles that were translocated 14–158 km from their capture site). We collected location data from individual crocodiles for 34–661 days (x ¯ \mathopx\limits\textasciicircum̅\ 250 days for each group). Body condition was similar for both groups. Corticosterone levels measured periodically during handling indicated that crocodiles experienced increasing stress levels during handling. Three crocodiles translocated ≤45 km from their original capture site returned to that location within 13 days. Three crocodiles translocated ≥110 km did not return. One female translocated 152 km was recaptured 0.42 km from its original capture site 965 days after its release. We identified 2 states of characteristic movement patterns: state 1 indicated individuals moving slowly and somewhat randomly, and state 2 indicated individuals exhibiting fast, active directional movement. Translocated individuals were more likely than reference individuals to switch to, and stay in, state 2. Because of concerns regarding return rates and heightened stress as a result of capture and translocation, we suggest crocodile translocations have limited conservation value and may only be worth considering once all other reasonable options are exhausted.

@article{reitz_ensemble_2023,
	title = {Ensemble {Estimation} of {Historical} {Evapotranspiration} for the {Conterminous} {U}.{S}.},
	volume = {59},
	copyright = {Published 2023. This article is a U.S. Government work and is in the public domain in the USA.},
	issn = {1944-7973},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2022WR034012},
	doi = {10.1029/2022WR034012},
	abstract = {Evapotranspiration (ET) is the largest component of the water budget, accounting for the majority of the water available from precipitation. ET is challenging to quantify because of the uncertainties associated with the many ET equations currently in use, and because observations of ET are uncertain and sparse. In this study, we combine information provided by available ET data and equations to produce a new monthly data set for ET for the conterminous U.S. (CONUS). These maps are produced from 1895 to 2018 at an 800 m spatial scale, marking a finer resolution than currently available products over this time period. In our approach, the relative performance of a suite of ET equations is assessed using water balance, flux tower, and remotely sensed ET estimates. At the observation locations, we use error distributions to quantify relative weights for the equations and use these in a modified Bayesian model averaging weighted ensemble approach. The relative weights are spatially generalized using a random forest regression, which is applied to wall-to-wall explanatory variable maps to generate CONUS-wide relative weight maps and ensemble estimates. We assess the performance of the ensemble using a reserved subset of the observations and compare this performance against other national-scale map products for historical to modern ET. The ensemble ET maps are shown to provide an improved accuracy over the alternative comparison products. These ET maps could be useful for a variety of hydrologic modeling and assessment applications that benefit from a long record, such as the study of periods of water scarcity through time.},
	language = {en},
	number = {6},
	urldate = {2023-08-11},
	journal = {Water Resources Research},
	author = {Reitz, M. and Sanford, W. E. and Saxe, S.},
	year = {2023},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1029/2022WR034012},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {e2022WR034012},
}

Evapotranspiration (ET) is the largest component of the water budget, accounting for the majority of the water available from precipitation. ET is challenging to quantify because of the uncertainties associated with the many ET equations currently in use, and because observations of ET are uncertain and sparse. In this study, we combine information provided by available ET data and equations to produce a new monthly data set for ET for the conterminous U.S. (CONUS). These maps are produced from 1895 to 2018 at an 800 m spatial scale, marking a finer resolution than currently available products over this time period. In our approach, the relative performance of a suite of ET equations is assessed using water balance, flux tower, and remotely sensed ET estimates. At the observation locations, we use error distributions to quantify relative weights for the equations and use these in a modified Bayesian model averaging weighted ensemble approach. The relative weights are spatially generalized using a random forest regression, which is applied to wall-to-wall explanatory variable maps to generate CONUS-wide relative weight maps and ensemble estimates. We assess the performance of the ensemble using a reserved subset of the observations and compare this performance against other national-scale map products for historical to modern ET. The ensemble ET maps are shown to provide an improved accuracy over the alternative comparison products. These ET maps could be useful for a variety of hydrologic modeling and assessment applications that benefit from a long record, such as the study of periods of water scarcity through time.

@phdthesis{christensen_estimating_2023,
	title = {Estimating blue carbon storage capacity of {Canada}’s eelgrass beds},
	url = {https://open.library.ubc.ca/soa/cIRcle/collections/ubctheses/24/items/1.0427399},
	abstract = {Despite the importance of coastal ecosystems for the global carbon (carbon) budgets including obligations to the United Nations (UN) and growing policy frameworks for natural climate solutions, knowledge of coastal carbon storage capacity and the factors driving variability in st},
	language = {eng},
	urldate = {2023-06-02},
	school = {University of British Columbia},
	author = {Christensen, Matthew Shane},
	year = {2023},
	doi = {10.14288/1.0427399},
	keywords = {Blue Carbon},
}

Despite the importance of coastal ecosystems for the global carbon (carbon) budgets including obligations to the United Nations (UN) and growing policy frameworks for natural climate solutions, knowledge of coastal carbon storage capacity and the factors driving variability in st

@article{curasi_evaluating_2023,
	title = {Evaluating the {Performance} of the {Canadian} {Land} {Surface} {Scheme} {Including} {Biogeochemical} {Cycles} ({CLASSIC}) {Tailored} to the {Pan}-{Canadian} {Domain}},
	volume = {15},
	copyright = {© 2023 His Majesty the King in Right of Canada and The Authors. Reproduced with the permission of the Minister of Environment and Climate Change.},
	issn = {1942-2466},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2022MS003480},
	doi = {10.1029/2022MS003480},
	abstract = {Canada's boreal forests and tundra ecosystems are responding to unprecedented climate change with implications for the global carbon (C) cycle and global climate. However, our ability to model the response of Canada's terrestrial ecosystems to climate change is limited and there has been no comprehensive, process-based assessment of Canada's terrestrial C cycle. We tailor the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) to Canada and evaluate its C cycling performance against independent reference data. We utilize skill scores to assess model performance against reference data alongside benchmark scores that quantify the level of agreement between the reference data sets to aid in interpretation. Our results demonstrate CLASSIC's sensitivity to prescribed vegetation cover. They also show that the addition of five region-specific Plant functional types (PFTs) improves CLASSIC's skill at simulating the Canadian C cycle. CLASSIC performs well when tailored to Canada, falls within the range of the reference data sets, and meets or exceeds the benchmark scores for most C cycling processes. New region-specific land cover products, well-informed PFT parameterizations, and more detailed reference data sets will facilitate improvements to the representation of the terrestrial C cycle in regional and global land surface models. Incorporating a parameterization for boreal disturbance processes and explicitly representing peatlands and permafrost soils will improve CLASSIC's future performance in Canada and other boreal regions. This is an important step toward a comprehensive process-based assessment of Canada's terrestrial C cycle and evaluating Canada's net C balance under climate change.},
	language = {en},
	number = {4},
	urldate = {2023-06-23},
	journal = {Journal of Advances in Modeling Earth Systems},
	author = {Curasi, Salvatore R. and Melton, Joe R. and Humphreys, Elyn R. and Wang, Libo and Seiler, Christian and Cannon, Alex J. and Chan, Ed and Qu, Bo},
	year = {2023},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1029/2022MS003480},
	keywords = {NALCMS},
	pages = {e2022MS003480},
}

Canada's boreal forests and tundra ecosystems are responding to unprecedented climate change with implications for the global carbon (C) cycle and global climate. However, our ability to model the response of Canada's terrestrial ecosystems to climate change is limited and there has been no comprehensive, process-based assessment of Canada's terrestrial C cycle. We tailor the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) to Canada and evaluate its C cycling performance against independent reference data. We utilize skill scores to assess model performance against reference data alongside benchmark scores that quantify the level of agreement between the reference data sets to aid in interpretation. Our results demonstrate CLASSIC's sensitivity to prescribed vegetation cover. They also show that the addition of five region-specific Plant functional types (PFTs) improves CLASSIC's skill at simulating the Canadian C cycle. CLASSIC performs well when tailored to Canada, falls within the range of the reference data sets, and meets or exceeds the benchmark scores for most C cycling processes. New region-specific land cover products, well-informed PFT parameterizations, and more detailed reference data sets will facilitate improvements to the representation of the terrestrial C cycle in regional and global land surface models. Incorporating a parameterization for boreal disturbance processes and explicitly representing peatlands and permafrost soils will improve CLASSIC's future performance in Canada and other boreal regions. This is an important step toward a comprehensive process-based assessment of Canada's terrestrial C cycle and evaluating Canada's net C balance under climate change.

@article{shu_evolution_2023,
	title = {Evolution of the local climate in {Montreal} and {Ottawa} before, during and after a heatwave and the effects on urban heat islands},
	issn = {00489697},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0048969723031182},
	doi = {10.1016/j.scitotenv.2023.164497},
	language = {en},
	urldate = {2023-06-02},
	journal = {Science of The Total Environment},
	author = {Shu, Chang and Gaur, Abhishek and Wang, Liangzhu and Lacasse, Michael A.},
	month = may,
	year = {2023},
	keywords = {NALCMS},
	pages = {164497},
}

@article{tsenov_exploration_2023,
	title = {Exploration of convolutional neural network architectures for large region map automation},
	volume = {17},
	issn = {1931-3195, 1931-3195},
	url = {https://www.spiedigitallibrary.org/journals/journal-of-applied-remote-sensing/volume-17/issue-1/018505/Exploration-of-convolutional-neural-network-architectures-for-large-region-map/10.1117/1.JRS.17.018505.full},
	doi = {10.1117/1.JRS.17.018505},
	abstract = {Deep learning semantic segmentation algorithms have provided improved frameworks for the automated production of land use and land cover (LULC) maps, which significantly increases the frequency of map generation as well as consistency of production quality. In this research, a total of 28 different model variations were examined to improve the accuracy of LULC maps. The experiments were carried out using Landsat 5/7 or Landsat 8 satellite images with the North American land change monitoring system (NALCMS) labels. The performance of various convolutional neural networks and extension combinations were assessed, where Visual Geometry Group Network with an output stride of 4, and modified U-Net architecture, provided the best results. Additional expanded analysis of the generated LULC maps was also provided. Using a deep neural network, this work achieved 92.4\% accuracy for 13 LULC classes within southern Manitoba representing a 15.8\% improvement over published results for the NALCMS. Based on the large regions of interest, higher radiometric resolution of Landsat 8 data resulted in better overall accuracies (88.04\%) compare to Landsat 5/7 (80.66\%) for 16 LULC classes. This represents an 11.44\% and 4.06\% increase in overall accuracy compared to previously published NALCMS results, including larger land area and higher number of LULC classes incorporated into the models compared to other published LULC map automation methods.},
	number = {1},
	urldate = {2023-06-27},
	journal = {Journal of Applied Remote Sensing},
	author = {Tsenov, Rostyslav-Mykola and Henry, Christopher J. and Storie, Joni L. and Storie, Christopher D. and Murray, Brent and Sokolov, Mikhail},
	month = feb,
	year = {2023},
	note = {Publisher: SPIE},
	keywords = {NALCMS},
	pages = {018505},
}

Deep learning semantic segmentation algorithms have provided improved frameworks for the automated production of land use and land cover (LULC) maps, which significantly increases the frequency of map generation as well as consistency of production quality. In this research, a total of 28 different model variations were examined to improve the accuracy of LULC maps. The experiments were carried out using Landsat 5/7 or Landsat 8 satellite images with the North American land change monitoring system (NALCMS) labels. The performance of various convolutional neural networks and extension combinations were assessed, where Visual Geometry Group Network with an output stride of 4, and modified U-Net architecture, provided the best results. Additional expanded analysis of the generated LULC maps was also provided. Using a deep neural network, this work achieved 92.4% accuracy for 13 LULC classes within southern Manitoba representing a 15.8% improvement over published results for the NALCMS. Based on the large regions of interest, higher radiometric resolution of Landsat 8 data resulted in better overall accuracies (88.04%) compare to Landsat 5/7 (80.66%) for 16 LULC classes. This represents an 11.44% and 4.06% increase in overall accuracy compared to previously published NALCMS results, including larger land area and higher number of LULC classes incorporated into the models compared to other published LULC map automation methods.

@phdthesis{hock-reid_exploring_2023,
	title = {Exploring the {Relationships} {Between} {Mammalian} {Functional} {Trait} {Distributions} and {Regional} {Biomes}, {With} {Application} to {Miocene} {Paleoecology}},
	url = {https://unl.primo.exlibrisgroup.com/discovery/fulldisplay?context=PC&vid=01UON_LINC:UNL&search_scope=MyInst_and_CI&tab=Everything&docid=cdi_proquest_journals_2842753557},
	abstract = {Paleoecology relies on understanding relationships between modern animals and their environment. Animals are adapted to niches in their environments, and those physical adaptations, or functional traits, are utilized as proxies to interpret aspects of paleo-ecosystems. Much is known about individual functional traits in extant mammals and their relationship to the environment. Less is known about how multiple functional traits across a community can be utilized for paleoecological interpretations. I develop models utilizing traits in mammalian communities at the biome level. For Chapter 1, I build a model for North American regional biomes using mammalian trait frequencies. I quantify changes in trait frequency distributions from historical (1832-1899) to modern (2008-2020) times across twelve regional biomes. Results indicate broad species loss across all taxonomic levels and decreased trait frequencies in all biomes due to widespread range contractions. For Chapter 2, I develop models of North American and African mammalian trait distributions. Additionally, I use the models to make paleoecological interpretations of a middle Miocene (late Barstovian; Ba2) Great Plains fauna. Many established paleoecological proxies use African data, even for North American environments. I compare and evaluate these models to determine which is most appropriate for North American paleoecological interpretations. North American and African trait distributions of similar biomes are distinctly different. The African model provides a paleoecological interpretation of the Ba2 Great Plains fauna consistent with past interpretations. For Chapter 3, I apply trait distributions from three Miocene Nebraskan mammalian assemblages to the paleoecological North American and African models developed in Chapter 2. Miocene assemblages are more similar to each other than to modern communities, representing fundamental underlying differences in trait distributions. Both models appear unsuited to make interpretations of local assemblages. Species richness and geographic scale contribute to differences in trait distributions of local assemblages, as does sampling and taphonomic biases against small mammals. However, the African model is the best option for making paleoecological interpretations of Miocene assemblages, though differences still remain.},
	language = {eng},
	urldate = {2023-08-11},
	school = {ProQuest Dissertations Publishing},
	author = {Hock-Reid, Devra G.},
	year = {2023},
	note = {Book Title: Exploring the Relationships Between Mammalian Functional Trait Distributions and Regional Biomes, With Application to Miocene Paleoecology
ISBN: 9798379955939},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
}

Paleoecology relies on understanding relationships between modern animals and their environment. Animals are adapted to niches in their environments, and those physical adaptations, or functional traits, are utilized as proxies to interpret aspects of paleo-ecosystems. Much is known about individual functional traits in extant mammals and their relationship to the environment. Less is known about how multiple functional traits across a community can be utilized for paleoecological interpretations. I develop models utilizing traits in mammalian communities at the biome level. For Chapter 1, I build a model for North American regional biomes using mammalian trait frequencies. I quantify changes in trait frequency distributions from historical (1832-1899) to modern (2008-2020) times across twelve regional biomes. Results indicate broad species loss across all taxonomic levels and decreased trait frequencies in all biomes due to widespread range contractions. For Chapter 2, I develop models of North American and African mammalian trait distributions. Additionally, I use the models to make paleoecological interpretations of a middle Miocene (late Barstovian; Ba2) Great Plains fauna. Many established paleoecological proxies use African data, even for North American environments. I compare and evaluate these models to determine which is most appropriate for North American paleoecological interpretations. North American and African trait distributions of similar biomes are distinctly different. The African model provides a paleoecological interpretation of the Ba2 Great Plains fauna consistent with past interpretations. For Chapter 3, I apply trait distributions from three Miocene Nebraskan mammalian assemblages to the paleoecological North American and African models developed in Chapter 2. Miocene assemblages are more similar to each other than to modern communities, representing fundamental underlying differences in trait distributions. Both models appear unsuited to make interpretations of local assemblages. Species richness and geographic scale contribute to differences in trait distributions of local assemblages, as does sampling and taphonomic biases against small mammals. However, the African model is the best option for making paleoecological interpretations of Miocene assemblages, though differences still remain.

@article{gregory_exploring_2023,
	title = {Exploring within-ecodistrict lake organic matter variability and identifying possible environmental contaminant biomarkers using sedimentomics},
	volume = {871},
	issn = {0048-9697},
	url = {https://www.sciencedirect.com/science/article/pii/S004896972300596X},
	doi = {10.1016/j.scitotenv.2023.161981},
	abstract = {Sedimentomics methods offer insight into the physiological parameters that influence freshwater sediment organic matter (sedOM). To date, most sedimentomics studies characterized variations across large spatial and environmental gradients; here we examine whether sedimentomics methods capture subtle sedOM variations within a relatively homogeneous study area in southwestern Nova Scotia, Canada. Additionally, we explore the lake sedimentome for candidate biomarkers related to ongoing carnivorous animal farming in the region. Sediment cores were recovered from seven lakes across a trophic (oligo- to eu- trophic) and anthropogenic land use gradient (carnivorous animal farming in catchment, downstream of farming, no farming nearby). Subsamples that dated prior to 1910 (pre-carnivorous animal farming) and later than 2010 (during carnivorous animal farming) were analyzed using UHPLC-HRMS in both negative (ESI−) and positive (ESI+) electrospray ionization modes. Cluster analysis (k-means) showed replicate samples from a given lake clustered distinctly from one another in both ESI modes, indicating sedOM captured subtle variations between lake systems. PCA combined with multiple linear regression indicated carnivorous animal farming and OM source explained most of the observed variation in lake sedOM. Principal component analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) of ESI− and ESI+ data sets identified 103 unique candidate biomarkers. Ten strong candidate biomarkers were identified using graphical methods; more research is required for biomarker verification and molecular characterization. Our results indicate sedimentomics could be used in environmentally homogeneous areas, offering insight into the controls of sedOM cycling. Additionally, we identified prospective biomarkers related to carnivorous animal farming that could be used to understand relative contributions of farming to ongoing eutrophication issues in southwestern Nova Scotia.},
	language = {en},
	urldate = {2023-06-23},
	journal = {Science of The Total Environment},
	author = {Gregory, B. R. B. and Bell, M. A. and Sproule, A. and Shields, S. W. and Overy, D. P. and Blais, J. M.},
	month = may,
	year = {2023},
	keywords = {NALCMS},
	pages = {161981},
}

Sedimentomics methods offer insight into the physiological parameters that influence freshwater sediment organic matter (sedOM). To date, most sedimentomics studies characterized variations across large spatial and environmental gradients; here we examine whether sedimentomics methods capture subtle sedOM variations within a relatively homogeneous study area in southwestern Nova Scotia, Canada. Additionally, we explore the lake sedimentome for candidate biomarkers related to ongoing carnivorous animal farming in the region. Sediment cores were recovered from seven lakes across a trophic (oligo- to eu- trophic) and anthropogenic land use gradient (carnivorous animal farming in catchment, downstream of farming, no farming nearby). Subsamples that dated prior to 1910 (pre-carnivorous animal farming) and later than 2010 (during carnivorous animal farming) were analyzed using UHPLC-HRMS in both negative (ESI−) and positive (ESI+) electrospray ionization modes. Cluster analysis (k-means) showed replicate samples from a given lake clustered distinctly from one another in both ESI modes, indicating sedOM captured subtle variations between lake systems. PCA combined with multiple linear regression indicated carnivorous animal farming and OM source explained most of the observed variation in lake sedOM. Principal component analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) of ESI− and ESI+ data sets identified 103 unique candidate biomarkers. Ten strong candidate biomarkers were identified using graphical methods; more research is required for biomarker verification and molecular characterization. Our results indicate sedimentomics could be used in environmentally homogeneous areas, offering insight into the controls of sedOM cycling. Additionally, we identified prospective biomarkers related to carnivorous animal farming that could be used to understand relative contributions of farming to ongoing eutrophication issues in southwestern Nova Scotia.

@article{benedict_extracting_2023,
	title = {Extracting exotic annual grass phenology and climate relations in western {U}.{S}. rangeland ecoregions},
	volume = {25},
	issn = {1573-1464},
	url = {https://doi.org/10.1007/s10530-023-03021-7},
	doi = {10.1007/s10530-023-03021-7},
	abstract = {This research builds upon the extensive body of work to model exotic annual grass (EAG) characteristics and invasion. EAGs increase wildland fire risk and intensifies wildland fire behavior in western U.S. rangelands. Therefore, understanding characteristics of EAG growth increases understanding of its dynamics and can inform rangeland management decisions. To better understand EAG phenology and spatial distribution, monthly weather (precipitation, minimum and maximum temperature) variables were analyzed for 24 level III ecoregions. This research characterizes EAGs’ phenology identified by a normalized difference vegetation index (NDVI) threshold-based interpolation technique. An EAG phenology metric model was used to estimate a growing season dynamic for the years 2017–2021 for shrub and herbaceous land cover types in the western conterminous United States (66\% of the area). The EAG phenology metrics include six growing season metrics such as start of season time, end of season time, and time of maximum NDVI during the growing season. The models’ cross validation results for Pearson’s r ranged from 0.88 to 0.95. Increased understanding of the effects that weather conditions have on EAG growth and spatial distribution can help land managers develop time-sensitive plans to protect entities deemed valuable to society like native habitat, wildlife, recreational areas, and air quality.},
	language = {en},
	number = {6},
	urldate = {2023-06-23},
	journal = {Biological Invasions},
	author = {Benedict, Trenton D. and Boyte, Stephen P. and Dahal, Devendra and Shrestha, Dinesh and Parajuli, Sujan and Megard, Logan J.},
	month = jun,
	year = {2023},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {2023--2041},
}

This research builds upon the extensive body of work to model exotic annual grass (EAG) characteristics and invasion. EAGs increase wildland fire risk and intensifies wildland fire behavior in western U.S. rangelands. Therefore, understanding characteristics of EAG growth increases understanding of its dynamics and can inform rangeland management decisions. To better understand EAG phenology and spatial distribution, monthly weather (precipitation, minimum and maximum temperature) variables were analyzed for 24 level III ecoregions. This research characterizes EAGs’ phenology identified by a normalized difference vegetation index (NDVI) threshold-based interpolation technique. An EAG phenology metric model was used to estimate a growing season dynamic for the years 2017–2021 for shrub and herbaceous land cover types in the western conterminous United States (66% of the area). The EAG phenology metrics include six growing season metrics such as start of season time, end of season time, and time of maximum NDVI during the growing season. The models’ cross validation results for Pearson’s r ranged from 0.88 to 0.95. Increased understanding of the effects that weather conditions have on EAG growth and spatial distribution can help land managers develop time-sensitive plans to protect entities deemed valuable to society like native habitat, wildlife, recreational areas, and air quality.

@article{isted_ferruginous_2023,
	title = {Ferruginous {Hawk} movements respond predictably to intra‐annual variation but unexpectedly to anthropogenic habitats},
	issn = {0019-1019, 1474-919X},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/ibi.13200},
	doi = {10.1111/ibi.13200},
	language = {en},
	urldate = {2023-06-02},
	journal = {Ibis},
	author = {Isted, Georgia H. and Thomas, Robert J. and Warner, Kevin S. and Stuber, Matthew J. and Ellsworth, Ethan and Katzner, Todd E.},
	month = apr,
	year = {2023},
	keywords = {NALCMS},
	pages = {ibi.13200},
}

@article{uhelski_fire_2023,
	title = {Fire {History} and {Long}-{Term} {Carbon} {Accumulation} in {Hemi}-boreal {Peatlands}},
	issn = {1435-0629},
	url = {https://doi.org/10.1007/s10021-023-00851-3},
	doi = {10.1007/s10021-023-00851-3},
	abstract = {Fire can play an important role in peatlands by modifying plant communities and carbon (C) stocks. However, baseline disturbance data on peatland fire history are lacking in the hemi-boreal region. We sampled 29 peatlands in northern Michigan, Wisconsin, and Minnesota and used peat core records, radiocarbon dating, and infrared spectrometry to identify and date past fire events in 4 major hemi-boreal peatland ecotypes including open poor fens, treed poor fens, forested poor fens, and forested rich fens. In this region all types of poor fens had widely variable fire frequencies between sites. The poor fens experienced 2.1 fires per thousand years, or once every 476 years, on average, while the rich fens experienced almost no fire. Overall C stocks ranged from 10.1 to 263.3 kg C m−2 with a mean of 94.6 and median of 90.5 kg C m−2. The long-term apparent rate of carbon accumulation (LARCA) varied between 10–45 g m−2 y−1 with an average of 28 g m−2 y−1. We found a significant negative relationship between fire frequency and LARCA. Our research indicates that fire frequency is not consistent across peatland types and increases in fire frequency will likely diminish peat C stocks. These findings provide a historical context for management decisions concerning wildland fires and their consequences for ecosystem C storage in hemi-boreal peatlands.},
	language = {en},
	urldate = {2023-08-11},
	journal = {Ecosystems},
	author = {Uhelski, Dominic M. and Kane, Evan S. and Heckman, Katherine A. and Chimner, Rodney A.},
	month = may,
	year = {2023},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
}

Fire can play an important role in peatlands by modifying plant communities and carbon (C) stocks. However, baseline disturbance data on peatland fire history are lacking in the hemi-boreal region. We sampled 29 peatlands in northern Michigan, Wisconsin, and Minnesota and used peat core records, radiocarbon dating, and infrared spectrometry to identify and date past fire events in 4 major hemi-boreal peatland ecotypes including open poor fens, treed poor fens, forested poor fens, and forested rich fens. In this region all types of poor fens had widely variable fire frequencies between sites. The poor fens experienced 2.1 fires per thousand years, or once every 476 years, on average, while the rich fens experienced almost no fire. Overall C stocks ranged from 10.1 to 263.3 kg C m−2 with a mean of 94.6 and median of 90.5 kg C m−2. The long-term apparent rate of carbon accumulation (LARCA) varied between 10–45 g m−2 y−1 with an average of 28 g m−2 y−1. We found a significant negative relationship between fire frequency and LARCA. Our research indicates that fire frequency is not consistent across peatland types and increases in fire frequency will likely diminish peat C stocks. These findings provide a historical context for management decisions concerning wildland fires and their consequences for ecosystem C storage in hemi-boreal peatlands.

@article{nicoletta_firelossrate_2023,
	title = {{FireLossRate}: {An} {R} package to estimate the loss rate of residential structures affected by wildfires at the {Wildland} {Urban} {Interface}},
	volume = {10},
	issn = {2215-0161},
	shorttitle = {{FireLossRate}},
	url = {https://www.sciencedirect.com/science/article/pii/S2215016123002352},
	doi = {10.1016/j.mex.2023.102238},
	abstract = {To inform proactive management actions supporting community resilience to wildfires, we developed a new software package called FireLossRate. This package in R helps the user to compute wildfire impacts on residential structures at the Wildland Urban Interface (WUI). The package integrates spatial information about exposed structures, empirical equations that estimate the loss rate of structures affected by wildfires as a function of fireline intensity and distance from fire edge with fire growth modeling outputs from fire simulation software and burn probability models. FireLossRate helps to quantify and produce spatially explicit data on structural exposure and loss for single and multiple fires. The package automates post hoc analyses on simulations that include single or multiple wildfires and enables result mapping when combined with other packages available in R. In this paper, we describe the functionality of the FireLossRate package and introduce users to the interpretation of impact indicators of wildfires at the WUI. FireLossRate is available for download at https://github.com/LFCFireLab/FireLossRate.•FireLossRate allows the computation of wildfire impacts indicators on residential structures at the Wildland Urban Interface in support of community fire risk management.},
	language = {en},
	urldate = {2023-08-11},
	journal = {MethodsX},
	author = {Nicoletta, Vittorio and D． Chavardès, Raphaël and Abo El Ezz, Ahmad and Cotton-Gagnon, Anne and Bélanger, Valérie and Boucher, Jonathan},
	month = jan,
	year = {2023},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {102238},
}

To inform proactive management actions supporting community resilience to wildfires, we developed a new software package called FireLossRate. This package in R helps the user to compute wildfire impacts on residential structures at the Wildland Urban Interface (WUI). The package integrates spatial information about exposed structures, empirical equations that estimate the loss rate of structures affected by wildfires as a function of fireline intensity and distance from fire edge with fire growth modeling outputs from fire simulation software and burn probability models. FireLossRate helps to quantify and produce spatially explicit data on structural exposure and loss for single and multiple fires. The package automates post hoc analyses on simulations that include single or multiple wildfires and enables result mapping when combined with other packages available in R. In this paper, we describe the functionality of the FireLossRate package and introduce users to the interpretation of impact indicators of wildfires at the WUI. FireLossRate is available for download at https://github.com/LFCFireLab/FireLossRate.•FireLossRate allows the computation of wildfire impacts indicators on residential structures at the Wildland Urban Interface in support of community fire risk management.

@article{mckellar_first-ever_2023,
	title = {First-ever satellite tracking of {Black} {Terns} ({Chlidonias} niger): {Insights} into home range and habitat selection},
	volume = {13},
	copyright = {© 2023 The Authors. Ecology and Evolution published by John Wiley \& Sons Ltd.},
	issn = {2045-7758},
	shorttitle = {First-ever satellite tracking of {Black} {Terns} ({Chlidonias} niger)},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/ece3.10716},
	doi = {10.1002/ece3.10716},
	abstract = {Understanding animal movement across the annual cycle is critical for developing appropriate conservation plans, but the large size and high cost of tracking devices can limit the spatial and temporal resolution at which movement data can be collected, especially for small avian species. Furthermore, for species with low breeding site fidelity, the ability to obtain tracking data from small, archival tags is hindered by low recapture rates. We deployed satellite tracking devices on four adult Black Terns (Chlidonias niger), a declining waterbird with low site fidelity, to examine space use and selection of resources within individual breeding home ranges. We also provide a preliminary assessment of habitat use during fall stopover. We found that home ranges were extensive (mean 283.7 km2) and distances travelled from the nest substantially larger (up to 35 km) than previously thought ( 2.5 km). Terns showed selection for wetlands and open water on the breeding grounds, but also showed selection for developed areas. This may reflect humans selecting similar landscape features for recreation and development as terns, and suggests that terns can tolerate the light degree of development (e.g. cottages, boat launches, etc.) within our study area. Despite a small sample size, this is the first study to track individual Black Terns at a high resolution with implications for conservation and wetland management practices relevant to the spatial scales at which habitat is used by the species.},
	language = {en},
	number = {11},
	urldate = {2024-01-10},
	journal = {Ecology and Evolution},
	author = {McKellar, Ann E. and Clements, Sarah J.},
	year = {2023},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/ece3.10716},
	keywords = {NALCMS},
	pages = {e10716},
}

Understanding animal movement across the annual cycle is critical for developing appropriate conservation plans, but the large size and high cost of tracking devices can limit the spatial and temporal resolution at which movement data can be collected, especially for small avian species. Furthermore, for species with low breeding site fidelity, the ability to obtain tracking data from small, archival tags is hindered by low recapture rates. We deployed satellite tracking devices on four adult Black Terns (Chlidonias niger), a declining waterbird with low site fidelity, to examine space use and selection of resources within individual breeding home ranges. We also provide a preliminary assessment of habitat use during fall stopover. We found that home ranges were extensive (mean 283.7 km2) and distances travelled from the nest substantially larger (up to 35 km) than previously thought ( 2.5 km). Terns showed selection for wetlands and open water on the breeding grounds, but also showed selection for developed areas. This may reflect humans selecting similar landscape features for recreation and development as terns, and suggests that terns can tolerate the light degree of development (e.g. cottages, boat launches, etc.) within our study area. Despite a small sample size, this is the first study to track individual Black Terns at a high resolution with implications for conservation and wetland management practices relevant to the spatial scales at which habitat is used by the species.

@article{massey_forest_2023,
	title = {Forest composition change and biophysical climate feedbacks across boreal {North} {America}},
	volume = {13},
	copyright = {2023 The Author(s)},
	issn = {1758-6798},
	url = {https://www.nature.com/articles/s41558-023-01851-w},
	doi = {10.1038/s41558-023-01851-w},
	abstract = {Deciduous tree cover is expected to increase in North American boreal forests with climate warming and wildfire. This shift in composition has the potential to generate biophysical cooling via increased land surface albedo. Here we use Landsat-derived maps of continuous tree canopy cover and deciduous fractional composition to assess albedo change over recent decades. We find, on average, a small net decrease in deciduous fraction from 2000 to 2015 across boreal North America and from 1992 to 2015 across Canada, despite extensive fire disturbance that locally increased deciduous vegetation. We further find near-neutral net biophysical change in radiative forcing associated with albedo when aggregated across the domain. Thus, while there have been widespread changes in forest composition over the past several decades, the net changes in composition and associated post-fire radiative forcing have not induced systematic negative feedbacks to climate warming over the spatial and temporal scope of our study.},
	language = {en},
	number = {12},
	urldate = {2024-01-10},
	journal = {Nature Climate Change},
	author = {Massey, Richard and Rogers, Brendan M. and Berner, Logan T. and Cooperdock, Sol and Mack, Michelle C. and Walker, Xanthe J. and Goetz, Scott J.},
	month = dec,
	year = {2023},
	note = {Number: 12
Publisher: Nature Publishing Group},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {1368--1375},
}

Deciduous tree cover is expected to increase in North American boreal forests with climate warming and wildfire. This shift in composition has the potential to generate biophysical cooling via increased land surface albedo. Here we use Landsat-derived maps of continuous tree canopy cover and deciduous fractional composition to assess albedo change over recent decades. We find, on average, a small net decrease in deciduous fraction from 2000 to 2015 across boreal North America and from 1992 to 2015 across Canada, despite extensive fire disturbance that locally increased deciduous vegetation. We further find near-neutral net biophysical change in radiative forcing associated with albedo when aggregated across the domain. Thus, while there have been widespread changes in forest composition over the past several decades, the net changes in composition and associated post-fire radiative forcing have not induced systematic negative feedbacks to climate warming over the spatial and temporal scope of our study.

@article{hansen_formation_2023,
	title = {Formation of the {Holarctic} {Fauna}: {Dated} molecular phylogenetic and biogeographic insights from the {Quedius}-lineage of {Ground}-{Dwelling} {Rove} {Beetles} ({Coleoptera}, {Staphylinidae})},
	volume = {182},
	issn = {1055-7903},
	shorttitle = {Formation of the {Holarctic} {Fauna}},
	url = {https://www.sciencedirect.com/science/article/pii/S1055790323000490},
	doi = {10.1016/j.ympev.2023.107749},
	abstract = {Although the Holarctic fauna has been explored for centuries, many questions on its formation are still unanswered. For example, i) what was the impact of the uplift of the Himalaya and Tibetan Plateau?, ii) what were the timings and climate of the faunal bridges connecting the Nearctic and Palearctic regions?, and iii) how did insect lineages respond to the late Paleogene global cooling and regional aridification? To answer these, we developed a phylogenetic dataset of 1229 nuclear loci for a total of 222 species of rove beetles (Staphylinidae) with emphasis in the tribe Quediini, especially Quedius-lineage and its subclade Quedius sensu stricto. Using eight fossils for calibrating molecular clock, we estimated divergence times and then analysed in BioGeoBEARS paleodistributions of the most recent common ancestor for each target lineage. For each species we generated climatic envelopes of the temperature and precipitation and mapped them across the phylogeny to explore evolutionary shifts. Our results suggest that the warm and humid Himalaya and Tibetan Plateau acted as an evolutionary cradle for the Quedius-lineage originating during the Oligocene from where, in the Early Miocene, the ancestor of the Quedius s. str. dispersed into the West Palearctic. With the climate cooling from the Mid Miocene onwards, new lineages within Quedius s. str. emerged and gradually expanded distributions across the Palearctic. In Late Miocene, a member of the group dispersed to the Nearctic region via Beringia before the closure of this land bridge 5.3 Ma. Paleogene global cooling and regional aridification largely shaped the current biogeographic pattern for Quedius s. str. species, many of them originating during the Pliocene and shifting or contracting their ranges during Pleistocene.},
	language = {en},
	urldate = {2023-07-04},
	journal = {Molecular Phylogenetics and Evolution},
	author = {Hansen, Aslak Kappel and Brunke, Adam J. and Thomsen, Philip Francis and Simonsen, Thomas J. and Solodovnikov, Alexey},
	month = may,
	year = {2023},
	keywords = {Terrestrial Ecoregions (CEC 1997)},
	pages = {107749},
}

Although the Holarctic fauna has been explored for centuries, many questions on its formation are still unanswered. For example, i) what was the impact of the uplift of the Himalaya and Tibetan Plateau?, ii) what were the timings and climate of the faunal bridges connecting the Nearctic and Palearctic regions?, and iii) how did insect lineages respond to the late Paleogene global cooling and regional aridification? To answer these, we developed a phylogenetic dataset of 1229 nuclear loci for a total of 222 species of rove beetles (Staphylinidae) with emphasis in the tribe Quediini, especially Quedius-lineage and its subclade Quedius sensu stricto. Using eight fossils for calibrating molecular clock, we estimated divergence times and then analysed in BioGeoBEARS paleodistributions of the most recent common ancestor for each target lineage. For each species we generated climatic envelopes of the temperature and precipitation and mapped them across the phylogeny to explore evolutionary shifts. Our results suggest that the warm and humid Himalaya and Tibetan Plateau acted as an evolutionary cradle for the Quedius-lineage originating during the Oligocene from where, in the Early Miocene, the ancestor of the Quedius s. str. dispersed into the West Palearctic. With the climate cooling from the Mid Miocene onwards, new lineages within Quedius s. str. emerged and gradually expanded distributions across the Palearctic. In Late Miocene, a member of the group dispersed to the Nearctic region via Beringia before the closure of this land bridge 5.3 Ma. Paleogene global cooling and regional aridification largely shaped the current biogeographic pattern for Quedius s. str. species, many of them originating during the Pliocene and shifting or contracting their ranges during Pleistocene.

@article{chambers_fuel_2023,
	title = {Fuel treatment response groups for fire-prone sagebrush landscapes},
	volume = {19},
	copyright = {2023 This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply},
	issn = {1933-9747},
	url = {https://link.springer.com/article/10.1186/s42408-023-00230-2},
	doi = {10.1186/s42408-023-00230-2},
	abstract = {Background Sagebrush shrublands in the Great Basin, USA, are experiencing widespread increases in wildfire size and area burned resulting in new policies and funding to implement fuel treatments. However, we lack the spatial data needed to optimize the types and locations of fuel treatments across large landscapes and mitigate fire risk. To address this, we developed treatment response groups (TRGs)—sagebrush and pinyon-juniper vegetation associations that differ in resilience to fire and resistance to annual grass invasion (R\&R) and thus responses to fuel treatments. Results We developed spatial layers of the dominant sagebrush associations by overlaying LANDFIRE Existing Vegetation Type, Biophysical Setting, and Mapping Zone, extracting vegetation plot data from the LANDFIRE 2016 LF Reference Database for each combination, and identifying associated sagebrush, grass, shrub, and tree species. We derived spatial layers of pinyon-juniper (PJ) cover and expansion phase within the sagebrush associations from the Rangeland Analysis Platform and identified persistent PJ woodlands from the LANDFIRE Biophysical Setting. TRGs were created by overlaying dominant sagebrush associations, with and without PJ expansion, and new indicators of resilience and resistance. We assigned appropriate woody fuel treatments to the TRGs based on prior research on treatment responses. The potential area to receive woody fuel treatments was constrained to 52,940 km2 (18.4\%) of the dominant sagebrush associations (272,501 km2) largely because of extensive areas of low R\&R (68.9\%), which respond poorly and were not assigned treatments. Prescribed fire was assigned to big sagebrush associations with moderate or higher resilience and moderately low or higher resistance (14.2\%) due to higher productivity, fuels, and recovery potential. Mechanical treatments were assigned to big sagebrush associations with moderately low resilience and to low, black, and mixed low sagebrush associations with moderately low or higher R\&R (4.2\%) due to lower productivity, fuels, and recovery potential. Persistent PJ woodlands represent high value resources and were not assigned treatments (9\%). Conclusions Mapped TRGs can help identify the dominant sagebrush associations and determine appropriate fuel treatments at intermediate scales and provide the basis for quantitative wildfire risk assessments and outcome-based scenario planning to prioritize fuel treatment investments at large landscape scales.},
	language = {en},
	number = {1},
	urldate = {2026-05-22},
	journal = {Fire Ecology},
	author = {Chambers, Jeanne C. and Brown, Jessi L. and Reeves, Matthew C. and Strand, Eva K. and Ellsworth, Lisa M. and Tortorelli, Claire M. and Urza, Alexandra K. and Short, Karen C.},
	month = dec,
	year = {2023},
	note = {Company: SpringerOpen
Distributor: SpringerOpen
Institution: SpringerOpen
Label: SpringerOpen
Publisher: Springer International Publishing},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {70},
}

Background Sagebrush shrublands in the Great Basin, USA, are experiencing widespread increases in wildfire size and area burned resulting in new policies and funding to implement fuel treatments. However, we lack the spatial data needed to optimize the types and locations of fuel treatments across large landscapes and mitigate fire risk. To address this, we developed treatment response groups (TRGs)—sagebrush and pinyon-juniper vegetation associations that differ in resilience to fire and resistance to annual grass invasion (R&R) and thus responses to fuel treatments. Results We developed spatial layers of the dominant sagebrush associations by overlaying LANDFIRE Existing Vegetation Type, Biophysical Setting, and Mapping Zone, extracting vegetation plot data from the LANDFIRE 2016 LF Reference Database for each combination, and identifying associated sagebrush, grass, shrub, and tree species. We derived spatial layers of pinyon-juniper (PJ) cover and expansion phase within the sagebrush associations from the Rangeland Analysis Platform and identified persistent PJ woodlands from the LANDFIRE Biophysical Setting. TRGs were created by overlaying dominant sagebrush associations, with and without PJ expansion, and new indicators of resilience and resistance. We assigned appropriate woody fuel treatments to the TRGs based on prior research on treatment responses. The potential area to receive woody fuel treatments was constrained to 52,940 km2 (18.4%) of the dominant sagebrush associations (272,501 km2) largely because of extensive areas of low R&R (68.9%), which respond poorly and were not assigned treatments. Prescribed fire was assigned to big sagebrush associations with moderate or higher resilience and moderately low or higher resistance (14.2%) due to higher productivity, fuels, and recovery potential. Mechanical treatments were assigned to big sagebrush associations with moderately low resilience and to low, black, and mixed low sagebrush associations with moderately low or higher R&R (4.2%) due to lower productivity, fuels, and recovery potential. Persistent PJ woodlands represent high value resources and were not assigned treatments (9%). Conclusions Mapped TRGs can help identify the dominant sagebrush associations and determine appropriate fuel treatments at intermediate scales and provide the basis for quantitative wildfire risk assessments and outcome-based scenario planning to prioritize fuel treatment investments at large landscape scales.

@techreport{schnorbus_future_2023,
	title = {Future {Design} {Flood} {Values} in the {Fraser} and {Peace} {River} {Basins} {Using} the {CanESM2}-{LE}},
	url = {https://www2.gov.bc.ca/assets/gov/driving-and-transportation/environment/climate-action/moti_streamflow_design_values.pdf},
	language = {en},
	institution = {Pacific Climate Impacts Consortium},
	author = {Schnorbus, Markus A. and Alaya, Mohamed Ali Ben},
	month = mar,
	year = {2023},
	keywords = {NALCMS},
	pages = {38},
}

@article{van_den_bosch_habitat_2023,
	title = {Habitat selection of resident and non-resident gray wolves: implications for habitat connectivity},
	volume = {13},
	copyright = {2023 The Author(s)},
	issn = {2045-2322},
	shorttitle = {Habitat selection of resident and non-resident gray wolves},
	url = {https://www.nature.com/articles/s41598-023-47815-0},
	doi = {10.1038/s41598-023-47815-0},
	abstract = {Habitat selection studies facilitate assessing and predicting species distributions and habitat connectivity, but habitat selection can vary temporally and among individuals, which is often ignored. We used GPS telemetry data from 96 Gray wolves (Canis lupus) in the western Great Lakes region of the USA to assess differences in habitat selection while wolves exhibited resident (territorial) or non-resident (dispersing or floating) movements and discuss implications for habitat connectivity. We used a step-selection function (SSF) to assess habitat selection by wolves exhibiting resident or non-resident movements, and modeled circuit connectivity throughout the western Great Lakes region. Wolves selected for natural land cover and against areas with high road densities, with no differences in selection among wolves when resident, dispersing, or floating. Similar habitat selection between resident and non-resident wolves may be due to similarity in environmental conditions, when non-resident movements occur largely within established wolf range rather than near the periphery or beyond the species range. Alternatively, non-resident wolves may travel through occupied territories because higher food availability or lower human disturbance outweighs risks posed by conspecifics. Finally, an absence of differences in habitat selection between resident and non-resident wolf movements may be due to other unknown reasons. We recommend considering context-dependency when evaluating differences in movements and habitat use between resident and non-resident individuals. Our results also provide independent validation of a previous species distribution model and connectivity analysis suggesting most potential wolf habitat in the western Great Lakes region is occupied, with limited connectivity to unoccupied habitat.},
	language = {en},
	number = {1},
	urldate = {2024-01-10},
	journal = {Scientific Reports},
	author = {van den Bosch, M. and Kellner, K. F. and Gantchoff, M. G. and Patterson, B. R. and Barber-Meyer, S. M. and Beyer, D. E. and Erb, J. D. and Isaac, E. J. and MacFarland, D. M. and Moore, S. A. and Norton, D. C. and Petroelje, T. R. and Price Tack, J. L. and Roell, B. J. and Schrage, M. and Belant, J. L.},
	month = nov,
	year = {2023},
	note = {Number: 1
Publisher: Nature Publishing Group},
	keywords = {NALCMS},
	pages = {20415},
}

Habitat selection studies facilitate assessing and predicting species distributions and habitat connectivity, but habitat selection can vary temporally and among individuals, which is often ignored. We used GPS telemetry data from 96 Gray wolves (Canis lupus) in the western Great Lakes region of the USA to assess differences in habitat selection while wolves exhibited resident (territorial) or non-resident (dispersing or floating) movements and discuss implications for habitat connectivity. We used a step-selection function (SSF) to assess habitat selection by wolves exhibiting resident or non-resident movements, and modeled circuit connectivity throughout the western Great Lakes region. Wolves selected for natural land cover and against areas with high road densities, with no differences in selection among wolves when resident, dispersing, or floating. Similar habitat selection between resident and non-resident wolves may be due to similarity in environmental conditions, when non-resident movements occur largely within established wolf range rather than near the periphery or beyond the species range. Alternatively, non-resident wolves may travel through occupied territories because higher food availability or lower human disturbance outweighs risks posed by conspecifics. Finally, an absence of differences in habitat selection between resident and non-resident wolf movements may be due to other unknown reasons. We recommend considering context-dependency when evaluating differences in movements and habitat use between resident and non-resident individuals. Our results also provide independent validation of a previous species distribution model and connectivity analysis suggesting most potential wolf habitat in the western Great Lakes region is occupied, with limited connectivity to unoccupied habitat.

@article{hammond_high_2023,
	title = {High {Resolution} {SnowModel} {Simulations} {Reveal} {Future} {Elevation}-{Dependent} {Snow} {Loss} and {Earlier}, {Flashier} {Surface} {Water} {Input} for the {Upper} {Colorado} {River} {Basin}},
	volume = {11},
	copyright = {© 2023 The Authors. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.},
	issn = {2328-4277},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2022EF003092},
	doi = {10.1029/2022EF003092},
	abstract = {Continued climate warming is reducing seasonal snowpacks in the western United States, where {\textgreater}50\% of historical water supplies were snowmelt-derived. In the Upper Colorado River Basin, declining snow water equivalent (SWE) and altered surface water input (SWI, rainfall and snowmelt available to enter the soil) timing and magnitude affect streamflow generation and water availability. To adapt effectively to future conditions, we need to understand current spatiotemporal distributions of SWE and SWI and how they may change in future decades. We developed 100-m SnowModel simulations for water years 2001–2013 and two scenarios: control (CTL) and pseudo-global-warming (PGW). The PGW fraction of precipitation falling as snow was lower relative to CTL, except for November–April at high elevations. PGW peak SWE was lower for low (−45\%) and mid elevations (−14\%), while the date of peak SWE was uniformly earlier in the year for all elevations (17–23 days). Currently unmonitored high elevation snow represented a greater fraction of total PGW SWE. PGW peak daily SWI was higher for all elevations (30\%–42\%), while the dates of SWI peaks and centroids were earlier in the year for all elevations under PGW. PGW displayed elevated winter SWI, lower summer SWI, and changes in spring SWI timing were elevation-dependent. Although PGW peak SWI was elevated and earlier compared to CTL, SWI was more evenly distributed throughout the year for PGW. These simulated shifts in the timing and magnitude of SWE and SWI have broad implications for water management in dry, snow-dominated regions.},
	language = {en},
	number = {2},
	urldate = {2023-06-23},
	journal = {Earth's Future},
	author = {Hammond, John C. and Sexstone, Graham A. and Putman, Annie L. and Barnhart, Theodore B. and Rey, David M. and Driscoll, Jessica M. and Liston, Glen E. and Rasmussen, Kristen L. and McGrath, Daniel and Fassnacht, Steven R. and Kampf, Stephanie K.},
	year = {2023},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1029/2022EF003092},
	keywords = {NALCMS},
	pages = {e2022EF003092},
}

Continued climate warming is reducing seasonal snowpacks in the western United States, where \textgreater50% of historical water supplies were snowmelt-derived. In the Upper Colorado River Basin, declining snow water equivalent (SWE) and altered surface water input (SWI, rainfall and snowmelt available to enter the soil) timing and magnitude affect streamflow generation and water availability. To adapt effectively to future conditions, we need to understand current spatiotemporal distributions of SWE and SWI and how they may change in future decades. We developed 100-m SnowModel simulations for water years 2001–2013 and two scenarios: control (CTL) and pseudo-global-warming (PGW). The PGW fraction of precipitation falling as snow was lower relative to CTL, except for November–April at high elevations. PGW peak SWE was lower for low (−45%) and mid elevations (−14%), while the date of peak SWE was uniformly earlier in the year for all elevations (17–23 days). Currently unmonitored high elevation snow represented a greater fraction of total PGW SWE. PGW peak daily SWI was higher for all elevations (30%–42%), while the dates of SWI peaks and centroids were earlier in the year for all elevations under PGW. PGW displayed elevated winter SWI, lower summer SWI, and changes in spring SWI timing were elevation-dependent. Although PGW peak SWI was elevated and earlier compared to CTL, SWI was more evenly distributed throughout the year for PGW. These simulated shifts in the timing and magnitude of SWE and SWI have broad implications for water management in dry, snow-dominated regions.

@misc{lidd_how_2023,
	title = {How {Geography} {Shapes} {Logistics} {Across} {North} {America} - {It}'s the {End} of the {Week}!},
	url = {https://www.youtube.com/watch?v=zxdz17r4C9s},
	abstract = {\#ItsTheEndOfTheWeek and in this episode, hosts Germán and Jorge dive deep into the intricacies of supply chain networks across North America. With a focus on Canada, the United States, and Mexico, Germán and Jorge explore the unique geographical and infrastructural challenges these countries face and how they influence the design of supply chain networks.

1️⃣ Geography Matters: The geography of North America plays a pivotal role in determining the supply chain strategies employed by businesses. Whether it's the vast expanse of Canada, the diverse terrains of the United States, or the rugged landscapes of Mexico, geography influences many aspects of a supply chain network.

2️⃣ The Balancing Act Between Canada and the United States: Due to extensive road networks and relatively flat terrain between the countries, Canada and the United States can often manage supply chain logistics with one or two strategically located centers, efficiently serving a vast majority of the population. However, with the United States having a larger population spread across the east and west, some businesses opt for two, three, or even four distribution centers to balance transportation costs and maintain service levels.

3️⃣ Mexico's Need for Many Distribution Centers: Given the rugged nature of Mexico's geography, companies frequently require numerous distribution centers in their supply chain network to ensure timely product delivery while keeping transportation costs in check. Moreover, Mexico's labor cost advantage allows for the establishment of many smaller distribution centers where third party logistics companies play a pivotal role in warehouse management and last-mile delivery.

Sources: 
- https://www.statista.com/statistics/2...
- https://data.worldbank.org/indicator/...
- http://www.cec.org/north-american-env...
- https://en.wikipedia.org/wiki/List\_of...},
	urldate = {2023-09-28},
	author = {{LIDD}},
	month = sep,
	year = {2023},
	note = {Directors: \_:n8888},
	keywords = {Population Density},
}

#ItsTheEndOfTheWeek and in this episode, hosts Germán and Jorge dive deep into the intricacies of supply chain networks across North America. With a focus on Canada, the United States, and Mexico, Germán and Jorge explore the unique geographical and infrastructural challenges these countries face and how they influence the design of supply chain networks. 1️⃣ Geography Matters: The geography of North America plays a pivotal role in determining the supply chain strategies employed by businesses. Whether it's the vast expanse of Canada, the diverse terrains of the United States, or the rugged landscapes of Mexico, geography influences many aspects of a supply chain network. 2️⃣ The Balancing Act Between Canada and the United States: Due to extensive road networks and relatively flat terrain between the countries, Canada and the United States can often manage supply chain logistics with one or two strategically located centers, efficiently serving a vast majority of the population. However, with the United States having a larger population spread across the east and west, some businesses opt for two, three, or even four distribution centers to balance transportation costs and maintain service levels. 3️⃣ Mexico's Need for Many Distribution Centers: Given the rugged nature of Mexico's geography, companies frequently require numerous distribution centers in their supply chain network to ensure timely product delivery while keeping transportation costs in check. Moreover, Mexico's labor cost advantage allows for the establishment of many smaller distribution centers where third party logistics companies play a pivotal role in warehouse management and last-mile delivery. Sources: - https://www.statista.com/statistics/2... - https://data.worldbank.org/indicator/... - http://www.cec.org/north-american-env... - https://en.wikipedia.org/wiki/List_of...

@article{visscher_human_2023,
	title = {Human impact on deer use is greater than predators and competitors in a multiuse recreation area},
	volume = {197},
	issn = {00033472},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0003347223000039},
	doi = {10.1016/j.anbehav.2023.01.003},
	language = {en},
	urldate = {2023-06-02},
	journal = {Animal Behaviour},
	author = {Visscher, Darcy R. and Walker, Philip D. and Flowers, Mitchell and Kemna, Colborne and Pattison, Jesse and Kushnerick, Brandon},
	month = mar,
	year = {2023},
	keywords = {NALCMS},
	pages = {61--69},
}

@article{cole_impacts_2023,
	title = {Impacts of anthropogenic land transformation on species-specific habitat amount, fragmentation, and connectivity in the {Adirondack}-to-{Laurentians} ({A2L}) transboundary wildlife linkage between 2000 and 2015: {Implications} for conservation and ecological restoration},
	issn = {1572-9761},
	shorttitle = {Impacts of anthropogenic land transformation on species-specific habitat amount, fragmentation, and connectivity in the {Adirondack}-to-{Laurentians} ({A2L}) transboundary wildlife linkage between 2000 and 2015},
	url = {https://doi.org/10.1007/s10980-023-01727-6},
	doi = {10.1007/s10980-023-01727-6},
	abstract = {The Adirondack-to-Laurentians (A2L) transboundary wildlife linkage is one of three north–south movement linkages that connect natural areas in northeastern USA and southeastern Canada. This region still retains habitats of high ecological integrity and biodiversity; however, anthropogenic land transformation may be putting transboundary connectivity at risk.},
	language = {en},
	urldate = {2023-08-11},
	journal = {Landscape Ecology},
	author = {Cole, Jonathan R. and Koen, Erin L. and Pedersen, Eric J. and Gallo, John A. and Kross, Angela and Jaeger, Jochen A. G.},
	month = jul,
	year = {2023},
	note = {https://link.springer.com/epdf/10.1007/s10980-023-01727-6?sharing\_token=rtYflGjejO3ksBrEB3GqOve4RwlQNchNByi7wbcMAY4zVbh61XAiP-\_6l6-lPj7beqFG5tOJmYOahRFKXPE2kZtrpXtLqsEFPJsJavUNQlNGduQ-sE4Bhvbb3w3v5HxrlRTXCarVsZsYmg5dzXUtqPZtf-WlBuchWwtcox9HJ4g\%3D},
	keywords = {Terrestrial Ecoregions},
}

The Adirondack-to-Laurentians (A2L) transboundary wildlife linkage is one of three north–south movement linkages that connect natural areas in northeastern USA and southeastern Canada. This region still retains habitats of high ecological integrity and biodiversity; however, anthropogenic land transformation may be putting transboundary connectivity at risk.

@article{ahmed_implementing_2023,
	title = {Implementing a parsimonious variable contributing area algorithm for the prairie pothole region in the {HYPE} modelling framework},
	volume = {167},
	issn = {1364-8152},
	url = {https://www.sciencedirect.com/science/article/pii/S136481522300155X},
	doi = {10.1016/j.envsoft.2023.105769},
	abstract = {The North American prairie region is known for its poorly defined drainage system with numerous surface depressions that lead to variable contributing areas for streamflow generation. Current approaches of representing surface depressions are either simplistic or computationally demanding. In this study, a variable contributing area algorithm is implemented in the HYdrological Predictions for the Environment (HYPE) model and evaluated in the Canadian prairies. HYPE's local lake module is replaced with a Hysteretic Depressional Storage (HDS) algorithm to estimate the variable contributing fractions of subbasins. The modified model shows significant improvements in simulating the streamflows of two prairie basins in Saskatchewan, Canada. The modified model can replicate the hysteretic relationships between the water volume and contributing area of the basins. With the inclusion of the HDS algorithm in HYPE, the global HYPE modelling community can now simulate an important hydrological phenomenon, previously unavailable in the model.},
	language = {en},
	urldate = {2023-08-11},
	journal = {Environmental Modelling \& Software},
	author = {Ahmed, Mohamed Ismaiel and Shook, Kevin and Pietroniro, Alain and Stadnyk, Tricia and Pomeroy, John W. and Pers, Charlotta and Gustafsson, David},
	month = sep,
	year = {2023},
	keywords = {NALCMS},
	pages = {105769},
}

The North American prairie region is known for its poorly defined drainage system with numerous surface depressions that lead to variable contributing areas for streamflow generation. Current approaches of representing surface depressions are either simplistic or computationally demanding. In this study, a variable contributing area algorithm is implemented in the HYdrological Predictions for the Environment (HYPE) model and evaluated in the Canadian prairies. HYPE's local lake module is replaced with a Hysteretic Depressional Storage (HDS) algorithm to estimate the variable contributing fractions of subbasins. The modified model shows significant improvements in simulating the streamflows of two prairie basins in Saskatchewan, Canada. The modified model can replicate the hysteretic relationships between the water volume and contributing area of the basins. With the inclusion of the HDS algorithm in HYPE, the global HYPE modelling community can now simulate an important hydrological phenomenon, previously unavailable in the model.

@article{widurska_influence_2023,
	title = {Influence of landscape position and climatic seasonality on soil water and gas conductivity properties in agricultural soils},
	issn = {0008-4271},
	url = {https://cdnsciencepub.com/doi/10.1139/cjss-2022-0107},
	doi = {10.1139/cjss-2022-0107},
	abstract = {Agricultural landscape management and climate seasonality can influence soil structure, hydraulic conductivity, and air permeability within the context of soil water and soil gas mobility. To investigate this, in situ and laboratory-based data were collected from three agricultural landscape positions within a watershed in eastern Ontario, Canada during a growing season. Macropore classification, water infiltration tests, and air permeability measurements were conducted in situ and standard soil characterizations were carried out on soil samples. Hydraulic conductivity of the soil matrix, based on grain size data, indicated that the highest values were consistently measured in the B horizon at each landscape setting. Macropores were found to be more abundant within uncultivated drainage ditch bank soils, compared to the adjacent cropped fields. Macropores in the ditch bank soils were exclusively consisted of circular biopores, while both circular and linear macropores were observed in the cultivated field soils. Air permeability, vertical hydraulic conductivity, and horizontal hydraulic conductivity were also greater in the uncultivated soils, relative to the cultivated soils. Field saturated hydraulic conductivity measurements offered evidence of anisotropy, likely due to the vertical nature of the macropore features. Macropore disposition and extent varied over the growing season, especially in the cultivated field soils where tillage and field trafficking are physically disruptive. Seasonality of macropore development will influence temporal changes in advection-based mass exchange of gas and water in the vadose zone. Modeling of mass exchange in agricultural soils should consider time variability in macroporosity to more realistically characterize infiltration and soil gas emissions.},
	urldate = {2024-01-10},
	journal = {Canadian Journal of Soil Science},
	author = {Widurska, I. and Frey, S.K. and Lapen, D.R. and Rudolph, D.L.},
	month = oct,
	year = {2023},
	note = {Publisher: NRC Research Press},
	keywords = {Political Boundaries},
}

Agricultural landscape management and climate seasonality can influence soil structure, hydraulic conductivity, and air permeability within the context of soil water and soil gas mobility. To investigate this, in situ and laboratory-based data were collected from three agricultural landscape positions within a watershed in eastern Ontario, Canada during a growing season. Macropore classification, water infiltration tests, and air permeability measurements were conducted in situ and standard soil characterizations were carried out on soil samples. Hydraulic conductivity of the soil matrix, based on grain size data, indicated that the highest values were consistently measured in the B horizon at each landscape setting. Macropores were found to be more abundant within uncultivated drainage ditch bank soils, compared to the adjacent cropped fields. Macropores in the ditch bank soils were exclusively consisted of circular biopores, while both circular and linear macropores were observed in the cultivated field soils. Air permeability, vertical hydraulic conductivity, and horizontal hydraulic conductivity were also greater in the uncultivated soils, relative to the cultivated soils. Field saturated hydraulic conductivity measurements offered evidence of anisotropy, likely due to the vertical nature of the macropore features. Macropore disposition and extent varied over the growing season, especially in the cultivated field soils where tillage and field trafficking are physically disruptive. Seasonality of macropore development will influence temporal changes in advection-based mass exchange of gas and water in the vadose zone. Modeling of mass exchange in agricultural soils should consider time variability in macroporosity to more realistically characterize infiltration and soil gas emissions.

@article{leach_informational_2023,
	title = {Informational analysis of the {Canadian} {National} {Hydrometric} program monitoring network},
	volume = {0},
	issn = {0701-1784},
	url = {https://doi.org/10.1080/07011784.2023.2242815},
	doi = {10.1080/07011784.2023.2242815},
	abstract = {An information theory-based analysis was used to evaluate the Canadian National Hydrometric Network. The information theory approach used a mutual information based metric known as information quality ratio (IQR) to evaluate the reproducible information available in the network. The analysis was based on available data from 1 January 2009 to 31 December 2018, and compared using average daily discharge and average daily stage data from all months, summer months, and winter months to calculate the IQR. This evaluation showed that 63–77\% of hydrometric stations providing discharge data and 87–90\% of hydrometric stations providing stage data, depending on the season, have an IQR equal to or greater than 0.4. These results indicate that the majority of hydrometric stations provide an average or higher level of information during the analysis period. Based on the information theory analysis, the existing hydrometric network has been shown to be average in the gauged regions of Canada, excluding the Great Plains region. These results suggest that if new stations were to be added, greater effort should be focused in the ungauged areas of Northern Canada or to bolster information content of the Great Plains.},
	number = {0},
	urldate = {2023-08-30},
	journal = {Canadian Water Resources Journal / Revue canadienne des ressources hydriques},
	author = {Leach, James M. and Keum, Jongho and Karn, Jeffrey and Garner, Megan and Coulibaly, Paulin},
	month = aug,
	year = {2023},
	note = {Publisher: Taylor \& Francis
\_eprint: https://doi.org/10.1080/07011784.2023.2242815},
	keywords = {Terrestrial Ecoregions},
	pages = {1--14},
}

An information theory-based analysis was used to evaluate the Canadian National Hydrometric Network. The information theory approach used a mutual information based metric known as information quality ratio (IQR) to evaluate the reproducible information available in the network. The analysis was based on available data from 1 January 2009 to 31 December 2018, and compared using average daily discharge and average daily stage data from all months, summer months, and winter months to calculate the IQR. This evaluation showed that 63–77% of hydrometric stations providing discharge data and 87–90% of hydrometric stations providing stage data, depending on the season, have an IQR equal to or greater than 0.4. These results indicate that the majority of hydrometric stations provide an average or higher level of information during the analysis period. Based on the information theory analysis, the existing hydrometric network has been shown to be average in the gauged regions of Canada, excluding the Great Plains region. These results suggest that if new stations were to be added, greater effort should be focused in the ungauged areas of Northern Canada or to bolster information content of the Great Plains.

@article{miguel-vazquez_insights_2023,
	title = {Insights on the {Distribution} of {Struthanthus} palmeri {Kuijt} ({Loranthaceae}), the {Northernmost} {Species} of the {Genus}},
	volume = {83},
	issn = {1527-0904, 1944-8341},
	url = {https://bioone.org/journals/western-north-american-naturalist/volume-83/issue-2/064.083.0215/Insights-on-the-Distribution-of-Struthanthus-palmeri-Kuijt-Loranthaceae-the/10.3398/064.083.0215.full},
	doi = {10.3398/064.083.0215},
	abstract = {Struthanthus (Loranthaceae) es nativo de América y varias de sus especies se encuentran en México, algunas de las cuales son endémicas, por ejemplo S. palmeri. Dentro del género, S. palmeri tiene la distribución más septentrional, habitando en los ambientes áridos del noroeste de México, cerca de la frontera con Estados Unidos. En este estudio, se actualizó la distribución conocida de la especie. Se compiló la elevación, hospederos y tipos de vegetación donde S. palmeri se encuentra, para inferir su distribución potencial, usando modelado de nicho ecológico. Con base en los resultados, se reforzó el estatus de endemismo de S. palmeri. Este taxón se presenta en varios tipos de vegetación, desde cerca del nivel del mar hasta los 1300 m y parasitando taxa de 12 familias. Hay registros de la especie para una de las 21 Áreas Naturales Protegidas federales incluidas en el área M empleada en el análisis. Su distribución potencial muestra probabilidades altas de presencia, principalmente en las Ecorregiones Terrestres de Norteamérica que incluyen las áreas costeras de Sonora y Sinaloa. Este estudio expande el conocimiento de muérdagos de regiones áridas de América y de las especies endémicas de México, proporcionando información adicional sobre hábitat y hospederos, para el manejo y conservación de este grupo.},
	number = {2},
	urldate = {2024-01-10},
	journal = {Western North American Naturalist},
	author = {Miguel-Vázquez, Mónica I. and Olmos-Reyes, Yasser S. López de and Maldonado-Borja, Maria Guadalupe and Cerros-Tlatilpa, Rosa},
	month = aug,
	year = {2023},
	note = {Publisher: Monte L. Bean Life Science Museum, Brigham Young University},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {289--295},
}

Struthanthus (Loranthaceae) es nativo de América y varias de sus especies se encuentran en México, algunas de las cuales son endémicas, por ejemplo S. palmeri. Dentro del género, S. palmeri tiene la distribución más septentrional, habitando en los ambientes áridos del noroeste de México, cerca de la frontera con Estados Unidos. En este estudio, se actualizó la distribución conocida de la especie. Se compiló la elevación, hospederos y tipos de vegetación donde S. palmeri se encuentra, para inferir su distribución potencial, usando modelado de nicho ecológico. Con base en los resultados, se reforzó el estatus de endemismo de S. palmeri. Este taxón se presenta en varios tipos de vegetación, desde cerca del nivel del mar hasta los 1300 m y parasitando taxa de 12 familias. Hay registros de la especie para una de las 21 Áreas Naturales Protegidas federales incluidas en el área M empleada en el análisis. Su distribución potencial muestra probabilidades altas de presencia, principalmente en las Ecorregiones Terrestres de Norteamérica que incluyen las áreas costeras de Sonora y Sinaloa. Este estudio expande el conocimiento de muérdagos de regiones áridas de América y de las especies endémicas de México, proporcionando información adicional sobre hábitat y hospederos, para el manejo y conservación de este grupo.

@phdthesis{katz_integrating_2023,
	title = {Integrating {Environmental} {DNA}, {Traditional} {Fisheries} {Techniques}, and {Species} {Distribution} {Modeling} to {Assess} {Bridle} {Shiner} {Status} in {Maine}},
	url = {https://digitalcommons.library.umaine.edu/etd/3855},
	abstract = {The bridle shiner (Notropis bifrenatus) is a small minnow species native to the eastern United States and southeastern Canada. The species is declining dramatically throughout most of its native range and has legal protection or concern status in thirteen states and two Canadian provinces. In Maine, the bridle shiner is listed as a Species of Special Concern and considered a Species of Greatest Conservation Need, partially because we lack a basic understanding of their status and distribution within the state. Bridle shiners have historically been found in southern and western Maine in densely vegetated, shallow habitats along the shorelines of streams and ponds. Surveys performed at sites where the shiners were once abundant have yielded very few or none of these fish. This project informed the Maine Department of Inland Fisheries \& Wildlife on the status of the species in Maine and provides a foundation for future long-term monitoring of bridle shiner populations in the State. We used a combination of both direct capture techniques and environmental DNA (eDNA) to locate bridle shiners. eDNA is increasingly being used to detect rare aquatic species such as bridle shiners because it is both highly sensitive and less invasive than direct capture. We designed a single-species primer-probe assay to detect bridle shiner DNA, then surveyed 32 sites with a record of historic bridle shiner occurrence. In addition to collecting eDNA samples (2021-2022), we surveyed 29 sites using traditional seine netting techniques in 2021. In 2022, we used a preliminary habitat suitability model to select 46 locations with unknown bridle shiner presence to survey with eDNA. To refine eDNA methodology, we assessed trends in eDNA detection probability across seasons and compared DNA detection between three filter pore sizes. We rediscovered bridle shiner populations at 11 of 32 historically occupied sites and documented bridle shiners in four additional waterbodies. We determined that eDNA surveys were most effective in early or midsummer, and that larger filter pore sizes are a viable option for surveying bridle shiners. Species distribution modeling (SDM) statistically associates species occurrence data with environmental variables to evaluate habitat suitability. We used an ensemble species distribution modeling (SDM) approach to identify both the current and historic range of the bridle shiner within Maine and New Hampshire. We also investigated how local habitat characteristics influenced bridle shiner presence using generalized linear models. Both historic site surveys and ensemble SDMs suggest that there has been a},
	language = {en},
	urldate = {2024-01-09},
	school = {The University of Maine},
	author = {Katz, Lara S.},
	year = {2023},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
}

The bridle shiner (Notropis bifrenatus) is a small minnow species native to the eastern United States and southeastern Canada. The species is declining dramatically throughout most of its native range and has legal protection or concern status in thirteen states and two Canadian provinces. In Maine, the bridle shiner is listed as a Species of Special Concern and considered a Species of Greatest Conservation Need, partially because we lack a basic understanding of their status and distribution within the state. Bridle shiners have historically been found in southern and western Maine in densely vegetated, shallow habitats along the shorelines of streams and ponds. Surveys performed at sites where the shiners were once abundant have yielded very few or none of these fish. This project informed the Maine Department of Inland Fisheries & Wildlife on the status of the species in Maine and provides a foundation for future long-term monitoring of bridle shiner populations in the State. We used a combination of both direct capture techniques and environmental DNA (eDNA) to locate bridle shiners. eDNA is increasingly being used to detect rare aquatic species such as bridle shiners because it is both highly sensitive and less invasive than direct capture. We designed a single-species primer-probe assay to detect bridle shiner DNA, then surveyed 32 sites with a record of historic bridle shiner occurrence. In addition to collecting eDNA samples (2021-2022), we surveyed 29 sites using traditional seine netting techniques in 2021. In 2022, we used a preliminary habitat suitability model to select 46 locations with unknown bridle shiner presence to survey with eDNA. To refine eDNA methodology, we assessed trends in eDNA detection probability across seasons and compared DNA detection between three filter pore sizes. We rediscovered bridle shiner populations at 11 of 32 historically occupied sites and documented bridle shiners in four additional waterbodies. We determined that eDNA surveys were most effective in early or midsummer, and that larger filter pore sizes are a viable option for surveying bridle shiners. Species distribution modeling (SDM) statistically associates species occurrence data with environmental variables to evaluate habitat suitability. We used an ensemble species distribution modeling (SDM) approach to identify both the current and historic range of the bridle shiner within Maine and New Hampshire. We also investigated how local habitat characteristics influenced bridle shiner presence using generalized linear models. Both historic site surveys and ensemble SDMs suggest that there has been a

@article{rodriguez_gonzalez_integration_2023,
	title = {Integration of the {Livelihood} and {Ecosystem} {Services} {Frameworks}—{A} {Case} {Study} on {Urban} {Agriculture} in {Mexico} {City}},
	volume = {27},
	url = {https://journals.ametsoc.org/view/journals/eint/27/1/EI-D-22-0010.1.xml},
	doi = {10.1175/EI-D-22-0010.1},
	abstract = {Abstract Strategies that demonstrate renewed potential to enhance both social and ecological systems are crucial in today’s era of rapid urbanization. However, the approaches used to understand the impacts of such strategies sometimes favor social over environmental theory, or the opposite, but do not always consider both equally. Our study addresses this disconnect by exploring the role of urban agriculture (UA) as an alleviation and land management strategy in Mexico City (MC), Mexico. Our integrated design combined the ecosystem services framework, which was primarily used to assess material and nonmaterial benefits MC residents obtain from UA spaces and its associated vegetation, and the livelihoods framework, which was used to evaluate the relationship between UA and societal impacts. We used a mixed-method approach to quantify the amount of food produced, assess crop diversity, assess six distinct ecological processes linked to UA, identify cultural benefits, and conduct an evaluation of contributions to livelihood capitals. Our study documented the role of UA in supporting ecological processes, connecting humans to nature, and providing a supplemental source of income. However, a multitude of unintended outcomes are identified, such as trade-offs between different ecological processes, constraints in promoting formal education beyond agroecological knowledge, and an inability to fully elevate families out of poverty. Our integrated approach demonstrated how the ecosystem services and livelihoods frameworks can be used simultaneously to provide thorough assessments of socioecological systems, identifying outcomes that could go unnoticed without an interdisciplinary lens.},
	language = {EN},
	number = {1},
	urldate = {2023-06-27},
	journal = {Earth Interactions},
	author = {Rodríguez González, Mayra I. and Scott, Christian Kelly and Marquina, Tatiana and Mewa, Demeke B. and Polo, Jorge García and Peng, Binbin},
	month = may,
	year = {2023},
	note = {Publisher: American Meteorological Society
Section: Earth Interactions},
	keywords = {NALCMS},
}

Abstract Strategies that demonstrate renewed potential to enhance both social and ecological systems are crucial in today’s era of rapid urbanization. However, the approaches used to understand the impacts of such strategies sometimes favor social over environmental theory, or the opposite, but do not always consider both equally. Our study addresses this disconnect by exploring the role of urban agriculture (UA) as an alleviation and land management strategy in Mexico City (MC), Mexico. Our integrated design combined the ecosystem services framework, which was primarily used to assess material and nonmaterial benefits MC residents obtain from UA spaces and its associated vegetation, and the livelihoods framework, which was used to evaluate the relationship between UA and societal impacts. We used a mixed-method approach to quantify the amount of food produced, assess crop diversity, assess six distinct ecological processes linked to UA, identify cultural benefits, and conduct an evaluation of contributions to livelihood capitals. Our study documented the role of UA in supporting ecological processes, connecting humans to nature, and providing a supplemental source of income. However, a multitude of unintended outcomes are identified, such as trade-offs between different ecological processes, constraints in promoting formal education beyond agroecological knowledge, and an inability to fully elevate families out of poverty. Our integrated approach demonstrated how the ecosystem services and livelihoods frameworks can be used simultaneously to provide thorough assessments of socioecological systems, identifying outcomes that could go unnoticed without an interdisciplinary lens.

@article{wehr_island_2023,
	title = {Island characteristics and species traits predict mammal diversity across islands of the great lakes of {North} {America}},
	issn = {1572-9710},
	url = {https://doi.org/10.1007/s10531-023-02675-y},
	doi = {10.1007/s10531-023-02675-y},
	abstract = {Island biogeography theory states biodiversity increases with island size and decreases with distance from mainland source populations; however, the influence of other island characteristics (e.g., presence of neighboring islands) and species traits (e.g., body size) could alter expected patterns. We assessed the influence of island characteristics and species traits on island biodiversity using presence data for 20 mammal species on 70 islands across the Great Lakes of North America. We collated presence data from public databases of species distributions, a literature review, and personal communications with resource managers and researchers. As predicted, islands closer to mainland source populations as well as islands and archipelagoes with larger areas supported greater mammalian species richness. Winter dormant species (e.g., American black bear [Ursus americanus]) occurred less on islands while semiaquatic species (e.g., American beaver [Castor canadensis]) occurred more. Our results broadly support island biogeography theory and highlight the importance of considering archipelago characteristics and species traits for describing island biodiversity. Specifically, we found support for the existence of archipelagic meta-communities whereby archipelago area was a better predictor of mammalian species richness than the area of individual islands and further support for the effects of winter dormancy and semiaquatic lifestyles as species traits predictive of mammal occurrence on islands. Our results may aid restoration and conservation planning including consideration of assisted colonization and invasive species precautions. Further, our dataset provides an important baseline for mammal diversity and distributions in the Great Lakes region.},
	language = {en},
	urldate = {2023-07-04},
	journal = {Biodiversity and Conservation},
	author = {Wehr, Nathaniel H. and Boone, Hailey M. and Wehr, Samuel R. and Belant, Jerrold L.},
	month = jun,
	year = {2023},
	keywords = {Terrestrial Ecoregions (CEC 1997)},
}

Island biogeography theory states biodiversity increases with island size and decreases with distance from mainland source populations; however, the influence of other island characteristics (e.g., presence of neighboring islands) and species traits (e.g., body size) could alter expected patterns. We assessed the influence of island characteristics and species traits on island biodiversity using presence data for 20 mammal species on 70 islands across the Great Lakes of North America. We collated presence data from public databases of species distributions, a literature review, and personal communications with resource managers and researchers. As predicted, islands closer to mainland source populations as well as islands and archipelagoes with larger areas supported greater mammalian species richness. Winter dormant species (e.g., American black bear [Ursus americanus]) occurred less on islands while semiaquatic species (e.g., American beaver [Castor canadensis]) occurred more. Our results broadly support island biogeography theory and highlight the importance of considering archipelago characteristics and species traits for describing island biodiversity. Specifically, we found support for the existence of archipelagic meta-communities whereby archipelago area was a better predictor of mammalian species richness than the area of individual islands and further support for the effects of winter dormancy and semiaquatic lifestyles as species traits predictive of mammal occurrence on islands. Our results may aid restoration and conservation planning including consideration of assisted colonization and invasive species precautions. Further, our dataset provides an important baseline for mammal diversity and distributions in the Great Lakes region.

@article{iverson_land_2023,
	title = {Land cover and {NDVI} are important predictors in habitat selection along migration for the {Golden}-crowned {Sparrow}, a temperate-zone migrating songbird},
	volume = {11},
	issn = {2051-3933},
	url = {https://movementecologyjournal.biomedcentral.com/articles/10.1186/s40462-022-00353-2},
	doi = {10.1186/s40462-022-00353-2},
	abstract = {Background: Migrating passerines in North America have shown sharp declines. Understanding habitat selection and threats along migration paths are critical research needs, but details about migrations have been limited due to the difficulty of tracking small birds. Recent technological advances of tiny GPS-tags provide new opportunities to delineate fine-scale movements in small passerines during a life stage that has previously been inherently difficult to study. Methods: We investigated habitat selection along migration routes for a temperate-zone migratory passerine, the Golden-crowned Sparrow (Zonotrichia atricapilla), given GPS tags on California wintering grounds. We used a resource selection function combined with conditional logistic regression to compare matched sets of known stopover locations and available but unused locations to determine how land cover class, vegetation greenness and climate variables influence habitat selection during migration. We also provide general migration descriptions for this understudied species including migration distance, duration, and elevation, and repeated use of stopover areas. Results: We acquired 22 tracks across 19 individuals, with a total of 541 valid spring and fall migration locations. Birds traveled to breeding grounds in Alaska and British Columbia along coastal routes, selecting for shrubland and higher vegetation greenness in both migration seasons as well as grasslands during fall migration. However, model interactions showed they selected sites with lower levels of greenness when in forest (both seasons) and shrubland (fall only), which may reflect their preference for more open habitats or represent a trade-off in selection between habitat type and productivity. Birds also selected for locations with higher daily maximum temperature during spring migration. Routes during spring migration were lower in elevation on average, shorter in duration, and had fewer long stopovers than in fall migration. For two birds, we found repeated use of the same stopover areas in spring and fall migration. Conclusions: Using miniaturized GPS, this study provides new insight into habitat selection along migration routes for a common temperate-zone migrating songbird, contributing to a better understanding of full annual cycle models, and informing conservation efforts. Golden-crowned Sparrows selected for specific habitats along migration routes, and we found previously unknown behaviors such as repeated use of the same stopover areas by individuals across different migratory seasons.},
	number = {1},
	journal = {Movement Ecology},
	author = {Iverson, Autumn R. and Humple, Diana L. and Cormier, Renée L. and Hull, Josh},
	month = jan,
	year = {2023},
	note = {Publisher: BioMed Central Ltd},
	keywords = {NALCMS},
	pages = {2},
}

Background: Migrating passerines in North America have shown sharp declines. Understanding habitat selection and threats along migration paths are critical research needs, but details about migrations have been limited due to the difficulty of tracking small birds. Recent technological advances of tiny GPS-tags provide new opportunities to delineate fine-scale movements in small passerines during a life stage that has previously been inherently difficult to study. Methods: We investigated habitat selection along migration routes for a temperate-zone migratory passerine, the Golden-crowned Sparrow (Zonotrichia atricapilla), given GPS tags on California wintering grounds. We used a resource selection function combined with conditional logistic regression to compare matched sets of known stopover locations and available but unused locations to determine how land cover class, vegetation greenness and climate variables influence habitat selection during migration. We also provide general migration descriptions for this understudied species including migration distance, duration, and elevation, and repeated use of stopover areas. Results: We acquired 22 tracks across 19 individuals, with a total of 541 valid spring and fall migration locations. Birds traveled to breeding grounds in Alaska and British Columbia along coastal routes, selecting for shrubland and higher vegetation greenness in both migration seasons as well as grasslands during fall migration. However, model interactions showed they selected sites with lower levels of greenness when in forest (both seasons) and shrubland (fall only), which may reflect their preference for more open habitats or represent a trade-off in selection between habitat type and productivity. Birds also selected for locations with higher daily maximum temperature during spring migration. Routes during spring migration were lower in elevation on average, shorter in duration, and had fewer long stopovers than in fall migration. For two birds, we found repeated use of the same stopover areas in spring and fall migration. Conclusions: Using miniaturized GPS, this study provides new insight into habitat selection along migration routes for a common temperate-zone migrating songbird, contributing to a better understanding of full annual cycle models, and informing conservation efforts. Golden-crowned Sparrows selected for specific habitats along migration routes, and we found previously unknown behaviors such as repeated use of the same stopover areas by individuals across different migratory seasons.

@article{bansal_large_2023,
	title = {Large increases in methane emissions expected from {North} {America}’s largest wetland complex},
	volume = {9},
	issn = {2375-2548},
	url = {https://www.science.org/doi/10.1126/sciadv.ade1112},
	doi = {10.1126/sciadv.ade1112},
	abstract = {Natural methane (CH
              4
              ) emissions from aquatic ecosystems may rise because of human-induced climate warming, although the magnitude of increase is highly uncertain. Using an exceptionally large CH
              4
              flux dataset ({\textasciitilde}19,000 chamber measurements) and remotely sensed information, we modeled plot- and landscape-scale wetland CH
              4
              emissions from the Prairie Pothole Region (PPR), North America’s largest wetland complex. Plot-scale CH
              4
              emissions were driven by hydrology, temperature, vegetation, and wetland size. Historically, landscape-scale PPR wetland CH
              4
              emissions were largely dependent on total wetland extent. However, regardless of future wetland extent, PPR CH
              4
              emissions are predicted to increase by two- or threefold by 2100 under moderate or severe warming scenarios, respectively. Our findings suggest that international efforts to decrease atmospheric CH
              4
              concentrations should jointly account for anthropogenic and natural emissions to maintain climate mitigation targets to the end of the century.
            
          , 
            
              Future increases in wetland CH
              4
              emissions due to climate warming may offset anthropogenic CH
              4
              -reduction actions.},
	language = {en},
	number = {9},
	urldate = {2023-06-02},
	journal = {Science Advances},
	author = {Bansal, Sheel and Post Van Der Burg, Max and Fern, Rachel R. and Jones, John W. and Lo, Rachel and McKenna, Owen P. and Tangen, Brian A. and Zhang, Zhen and Gleason, Robert A.},
	month = mar,
	year = {2023},
	keywords = {NALCMS},
	pages = {eade1112},
}

Natural methane (CH 4 ) emissions from aquatic ecosystems may rise because of human-induced climate warming, although the magnitude of increase is highly uncertain. Using an exceptionally large CH 4 flux dataset (~19,000 chamber measurements) and remotely sensed information, we modeled plot- and landscape-scale wetland CH 4 emissions from the Prairie Pothole Region (PPR), North America’s largest wetland complex. Plot-scale CH 4 emissions were driven by hydrology, temperature, vegetation, and wetland size. Historically, landscape-scale PPR wetland CH 4 emissions were largely dependent on total wetland extent. However, regardless of future wetland extent, PPR CH 4 emissions are predicted to increase by two- or threefold by 2100 under moderate or severe warming scenarios, respectively. Our findings suggest that international efforts to decrease atmospheric CH 4 concentrations should jointly account for anthropogenic and natural emissions to maintain climate mitigation targets to the end of the century. , Future increases in wetland CH 4 emissions due to climate warming may offset anthropogenic CH 4 -reduction actions.

@article{pio-leon_plantas_2023,
	title = {Las plantas vasculares endémicas del estado de {Sinaloa}, {México}},
	volume = {101},
	issn = {2007-4298},
	url = {http://www.scielo.org.mx/scielo.php?script=sci_abstract&pid=S2007-42982023000100243&lng=es&nrm=iso&tlng=es},
	doi = {10.17129/botsci.3076},
	language = {es},
	number = {1},
	urldate = {2023-08-11},
	journal = {Botanical Sciences},
	author = {Pío-León, Juan Fernando and González-Elizondo, Martha and Vega-Aviña, Rito and González-Elizondo, M. Socorro and González-Gallegos, Jesús Guadalupe and Salomón-Montijo, Bladimir and Millán-Otero, Manuel Guillermo and Lim-Vega, Carlos A.},
	month = mar,
	year = {2023},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {243--269},
}

@article{ahmed_learning_2023,
	title = {Learning from hydrological models’ challenges: {A} case study from the {Nelson} basin model intercomparison project},
	volume = {623},
	issn = {0022-1694},
	shorttitle = {Learning from hydrological models’ challenges},
	url = {https://www.sciencedirect.com/science/article/pii/S002216942300762X},
	doi = {10.1016/j.jhydrol.2023.129820},
	abstract = {Intercomparison studies play an important, but limited role in understanding the usefulness and limitations of currently available hydrological models. Comparison studies are often limited to well-behaved hydrological regimes, where rainfall-runoff processes dominate the hydrological response. These efforts have not covered western Canada due to the difficulty in simulating that region’s complex cold region hydrology with varying spatiotemporal contributing areas. This intercomparison study is the first of a series of studies under the intercomparison project of the international and interprovincial transboundary Nelson-Churchill River Basin (NCRB) in North America (Nelson-MIP), which encompasses different ecozones with major areas of the non-contributing Prairie potholes, forests, glaciers, mountains, and permafrost. The performance of eight hydrological and land surface models is compared at different unregulated watersheds within the NCRB. This is done to assess the models’ streamflow performance and overall fidelity without and with calibration, to capture the underlying physics of the region and to better understand why models struggle to accurately simulate its hydrology. Results show that some of the participating models have difficulties in simulating streamflow and/or internal hydrological variables (e.g., evapotranspiration) over Prairie watersheds but most models performed well elsewhere. This stems from model structural deficiencies, despite the various models being well calibrated to observed streamflow. Some model structural changes are identified for the participating models for future improvement. The outcomes of this study offer guidance for practitioners for the accurate prediction of NCRB streamflow, and for increasing confidence in future projections of water resources supply and management.},
	language = {en},
	urldate = {2023-08-11},
	journal = {Journal of Hydrology},
	author = {Ahmed, Mohamed Ismaiel and Stadnyk, Tricia and Pietroniro, Alain and Awoye, Hervé and Bajracharya, Ajay and Mai, Juliane and Tolson, Bryan A. and Shen, Hongren and Craig, James R. and Gervais, Mark and Sagan, Kevin and Wruth, Shane and Koenig, Kristina and Lilhare, Rajtantra and Déry, Stephen J. and Pokorny, Scott and Venema, Hank and Muhammad, Ameer and Taheri, Mahkameh},
	month = aug,
	year = {2023},
	keywords = {NALCMS},
	pages = {129820},
}

Intercomparison studies play an important, but limited role in understanding the usefulness and limitations of currently available hydrological models. Comparison studies are often limited to well-behaved hydrological regimes, where rainfall-runoff processes dominate the hydrological response. These efforts have not covered western Canada due to the difficulty in simulating that region’s complex cold region hydrology with varying spatiotemporal contributing areas. This intercomparison study is the first of a series of studies under the intercomparison project of the international and interprovincial transboundary Nelson-Churchill River Basin (NCRB) in North America (Nelson-MIP), which encompasses different ecozones with major areas of the non-contributing Prairie potholes, forests, glaciers, mountains, and permafrost. The performance of eight hydrological and land surface models is compared at different unregulated watersheds within the NCRB. This is done to assess the models’ streamflow performance and overall fidelity without and with calibration, to capture the underlying physics of the region and to better understand why models struggle to accurately simulate its hydrology. Results show that some of the participating models have difficulties in simulating streamflow and/or internal hydrological variables (e.g., evapotranspiration) over Prairie watersheds but most models performed well elsewhere. This stems from model structural deficiencies, despite the various models being well calibrated to observed streamflow. Some model structural changes are identified for the participating models for future improvement. The outcomes of this study offer guidance for practitioners for the accurate prediction of NCRB streamflow, and for increasing confidence in future projections of water resources supply and management.

@article{lundell_lets_2023,
	title = {Let’s talk about the weather: a cluster-based approach to weather forecast accuracy},
	issn = {1613-9658},
	shorttitle = {Let’s talk about the weather},
	url = {https://doi.org/10.1007/s00180-023-01339-3},
	doi = {10.1007/s00180-023-01339-3},
	abstract = {Improved understanding of characteristics related to weather forecast accuracy in the United States may help meteorologists develop more accurate predictions and may help Americans better interpret their daily weather forecasts. This article examines how spatio-temporal characteristics across the United States relate to forecast accuracy. We cluster the United States into six weather regions based on weather and geographic characteristics and analyze the patterns in forecast accuracy within each weather region. We then explore the relationship between climate characteristics and forecast accuracy within these weather regions. We conclude that patterns in forecast errors are closely related to the unique climates that characterize each region.},
	language = {en},
	urldate = {2023-06-30},
	journal = {Computational Statistics},
	author = {Lundell, Jill F. and Bean, Brennan and Symanzik, Jürgen},
	month = mar,
	year = {2023},
	keywords = {Terrestrial Ecoregions (CEC 1997)},
}

Improved understanding of characteristics related to weather forecast accuracy in the United States may help meteorologists develop more accurate predictions and may help Americans better interpret their daily weather forecasts. This article examines how spatio-temporal characteristics across the United States relate to forecast accuracy. We cluster the United States into six weather regions based on weather and geographic characteristics and analyze the patterns in forecast accuracy within each weather region. We then explore the relationship between climate characteristics and forecast accuracy within these weather regions. We conclude that patterns in forecast errors are closely related to the unique climates that characterize each region.

@article{kalashnikov_lightning-ignited_2023,
	title = {Lightning-{Ignited} {Wildfires} in the {Western} {United} {States}: {Ignition} {Precipitation} and {Associated} {Environmental} {Conditions}},
	volume = {50},
	copyright = {© 2023. The Authors. Geophysical Research Letters published by Wiley Periodicals LLC on behalf of American Geophysical Union.},
	issn = {1944-8007},
	shorttitle = {Lightning-{Ignited} {Wildfires} in the {Western} {United} {States}},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2023GL103785},
	doi = {10.1029/2023GL103785},
	abstract = {Cloud-to-ground lightning with minimal rainfall (“dry” lightning) is a major wildfire ignition source in the western United States (WUS). Although dry lightning is commonly defined as occurring with {\textless}2.5 mm of daily-accumulated precipitation, a rigorous quantification of precipitation amounts concurrent with lightning-ignited wildfires (LIWs) is lacking. We combine wildfire, lightning and precipitation data sets to quantify these ignition precipitation amounts across ecoprovinces of the WUS. The median precipitation for all LIWs is 2.8 mm but varies with vegetation and fire characteristics. “Holdover” fires not detected until 2–5 days following ignition occur with significantly higher precipitation (5.1 mm) compared to fires detected promptly after ignition (2.5 mm), and with cooler and wetter environmental conditions. Further, there is substantial variation in precipitation associated with promptly-detected (1.7–4.6 mm) and holdover (3.0–7.7 mm) fires across ecoprovinces. Consequently, the widely-used 2.5 mm threshold does not fully capture lightning ignition risk and incorporating ecoprovince-specific precipitation amounts would better inform WUS wildfire prediction and management.},
	language = {en},
	number = {16},
	urldate = {2023-08-30},
	journal = {Geophysical Research Letters},
	author = {Kalashnikov, Dmitri A. and Abatzoglou, John T. and Loikith, Paul C. and Nauslar, Nicholas J. and Bekris, Yianna and Singh, Deepti},
	year = {2023},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1029/2023GL103785},
	keywords = {NALCMS},
	pages = {e2023GL103785},
}

Cloud-to-ground lightning with minimal rainfall (“dry” lightning) is a major wildfire ignition source in the western United States (WUS). Although dry lightning is commonly defined as occurring with \textless2.5 mm of daily-accumulated precipitation, a rigorous quantification of precipitation amounts concurrent with lightning-ignited wildfires (LIWs) is lacking. We combine wildfire, lightning and precipitation data sets to quantify these ignition precipitation amounts across ecoprovinces of the WUS. The median precipitation for all LIWs is 2.8 mm but varies with vegetation and fire characteristics. “Holdover” fires not detected until 2–5 days following ignition occur with significantly higher precipitation (5.1 mm) compared to fires detected promptly after ignition (2.5 mm), and with cooler and wetter environmental conditions. Further, there is substantial variation in precipitation associated with promptly-detected (1.7–4.6 mm) and holdover (3.0–7.7 mm) fires across ecoprovinces. Consequently, the widely-used 2.5 mm threshold does not fully capture lightning ignition risk and incorporating ecoprovince-specific precipitation amounts would better inform WUS wildfire prediction and management.

@phdthesis{mclellan_linking_2023,
	address = {Peterborough, Ontario, Canada},
	type = {Master of {Science}},
	title = {Linking large scale monitoring and spatially explicit capture–recapture models to identify factors shaping large carnivore densities: case study of the {American} black bear in {Ontario}, {Canada}},
	url = {https://digitalcollections.trentu.ca/objects/etd-1057},
	school = {Trent University},
	author = {McLellan, Brynn},
	month = jan,
	year = {2023},
	keywords = {NALCMS},
}

@article{du_mapping_2023,
	title = {Mapping {Annual} {Global} {Forest} {Gain} {From} 1983 to 2021 {With} {Landsat} {Imagery}},
	volume = {16},
	issn = {1939-1404, 2151-1535},
	url = {https://ieeexplore.ieee.org/document/10103610/},
	doi = {10.1109/JSTARS.2023.3267796},
	urldate = {2023-06-02},
	journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
	author = {Du, Zhenrong and Yu, Le and Yang, Jianyu and Coomes, David and Kanniah, Kasturi and Fu, Haohuan and Gong, Peng},
	year = {2023},
	keywords = {NALCMS},
	pages = {4195--4204},
}

@article{wang_mapping_2023,
	title = {Mapping of {ESA}'s {Climate} {Change} {Initiative} land cover data to plant functional types for use in the {CLASSIC} land model},
	volume = {20},
	issn = {1726-4170},
	url = {https://bg.copernicus.org/articles/20/2265/2023/},
	doi = {10.5194/bg-20-2265-2023},
	abstract = {Plant functional types (PFTs) are used to represent vegetation distribution in land surface models (LSMs). Previous studies have shown large differences in the geographical distribution of PFTs currently used in various LSMs, which may arise from the differences in the underlying land cover products but also the methods used to map or reclassify land cover data to the PFTs that a given LSM represents. There are large uncertainties associated with existing PFT mapping methods since they are largely based on expert judgement and therefore are subjective. In this study, we propose a new approach to inform the mapping or the cross-walking process using analyses from sub-pixel fractional error matrices, which allows for a quantitative assessment of the fractional composition of the land cover categories in a dataset. We use the Climate Change Initiative (CCI) land cover product produced by the European Space Agency (ESA). Previous work has shown that compared to fine-resolution maps over Canada, the ESA-CCI product provides an improved land cover distribution compared to that from the GLC2000 dataset currently used in the CLASSIC (Canadian Land Surface Scheme Including Biogeochemical Cycles) model. A tree cover fraction dataset and a fine-resolution land cover map over Canada are used to compute the sub-pixel fractional composition of the land cover classes in ESA-CCI, which is then used to create a cross-walking table for mapping the ESA-CCI land cover categories to nine PFTs represented in the CLASSIC model. There are large differences between the new PFT distributions and those currently used in the model. Offline simulations performed with the CLASSIC model using the ESA-CCI-based PFTs show improved winter albedo compared to that based on the GLC2000 dataset. This emphasizes the importance of accurate representation of vegetation distribution for realistic simulation of surface albedo in LSMs. Results in this study suggest that the sub-pixel fractional composition analyses are an effective way to reduce uncertainties in the PFT mapping process and therefore, to some extent, objectify the otherwise subjective process.},
	language = {English},
	number = {12},
	urldate = {2023-08-11},
	journal = {Biogeosciences},
	author = {Wang, Libo and Arora, Vivek K. and Bartlett, Paul and Chan, Ed and Curasi, Salvatore R.},
	month = jun,
	year = {2023},
	note = {Publisher: Copernicus GmbH},
	keywords = {NALCMS},
	pages = {2265--2282},
}

Plant functional types (PFTs) are used to represent vegetation distribution in land surface models (LSMs). Previous studies have shown large differences in the geographical distribution of PFTs currently used in various LSMs, which may arise from the differences in the underlying land cover products but also the methods used to map or reclassify land cover data to the PFTs that a given LSM represents. There are large uncertainties associated with existing PFT mapping methods since they are largely based on expert judgement and therefore are subjective. In this study, we propose a new approach to inform the mapping or the cross-walking process using analyses from sub-pixel fractional error matrices, which allows for a quantitative assessment of the fractional composition of the land cover categories in a dataset. We use the Climate Change Initiative (CCI) land cover product produced by the European Space Agency (ESA). Previous work has shown that compared to fine-resolution maps over Canada, the ESA-CCI product provides an improved land cover distribution compared to that from the GLC2000 dataset currently used in the CLASSIC (Canadian Land Surface Scheme Including Biogeochemical Cycles) model. A tree cover fraction dataset and a fine-resolution land cover map over Canada are used to compute the sub-pixel fractional composition of the land cover classes in ESA-CCI, which is then used to create a cross-walking table for mapping the ESA-CCI land cover categories to nine PFTs represented in the CLASSIC model. There are large differences between the new PFT distributions and those currently used in the model. Offline simulations performed with the CLASSIC model using the ESA-CCI-based PFTs show improved winter albedo compared to that based on the GLC2000 dataset. This emphasizes the importance of accurate representation of vegetation distribution for realistic simulation of surface albedo in LSMs. Results in this study suggest that the sub-pixel fractional composition analyses are an effective way to reduce uncertainties in the PFT mapping process and therefore, to some extent, objectify the otherwise subjective process.

@article{pouw_mapping_2023,
	title = {Mapping snow depth on {Canadian} sub-arctic lakes using ground-penetrating radar},
	volume = {17},
	issn = {1994-0416},
	url = {https://tc.copernicus.org/articles/17/2367/2023/},
	doi = {10.5194/tc-17-2367-2023},
	abstract = {Ice thickness across lake ice is mainly influenced by the presence of snow and its distribution, which affects the rate of lake ice growth. The distribution of snow depth over lake ice varies due to wind redistribution and snowpack metamorphism, affecting the variability of lake ice thickness. Accurate and consistent snow depth data on lake ice are sparse and challenging to obtain. However, high spatial resolution lake snow depth observations are necessary for the next generation of thermodynamic lake ice models to improve the understanding of how the varying distribution of snow depth influences lake ice formation and growth. This study was conducted using ground-penetrating radar (GPR) acquisitions with ∼9 cm sampling resolution along transects totalling ∼44 km to map snow depth over four Canadian sub-arctic freshwater lakes. The lake snow depth derived from GPR two-way travel time (TWT) resulted in an average relative error of under 10 \% when compared to 2430 in situ snow depth observations for the early and late winter season. The snow depth derived from GPR TWTs for the early winter season was estimated with a root mean square error (RMSE) of 1.6 cm and a mean bias error of 0.01 cm, while the accuracy for the late winter season on a deeper snowpack was estimated with a RMSE of 2.9 cm and a mean bias error of 0.4 cm. The GPR-derived snow depths were interpolated to create 1 m spatial resolution snow depth maps. The findings showed improved lake snow depth retrieval accuracy and introduced a fast and efficient method to obtain high spatial resolution snow depth information. The results suggest that GPR acquisitions can be used to derive lake snow depth, providing a viable alternative to manual snow depth monitoring methods. The findings can lead to an improved understanding of snow and lake ice interactions, which is essential for northern communities' safety and wellbeing and the scientific modelling community.},
	language = {English},
	number = {6},
	urldate = {2023-06-16},
	journal = {The Cryosphere},
	author = {Pouw, Alicia F. and Kheyrollah Pour, Homa and MacLean, Alex},
	month = jun,
	year = {2023},
	note = {Publisher: Copernicus GmbH},
	keywords = {NALCMS},
	pages = {2367--2385},
}

Ice thickness across lake ice is mainly influenced by the presence of snow and its distribution, which affects the rate of lake ice growth. The distribution of snow depth over lake ice varies due to wind redistribution and snowpack metamorphism, affecting the variability of lake ice thickness. Accurate and consistent snow depth data on lake ice are sparse and challenging to obtain. However, high spatial resolution lake snow depth observations are necessary for the next generation of thermodynamic lake ice models to improve the understanding of how the varying distribution of snow depth influences lake ice formation and growth. This study was conducted using ground-penetrating radar (GPR) acquisitions with ∼9 cm sampling resolution along transects totalling ∼44 km to map snow depth over four Canadian sub-arctic freshwater lakes. The lake snow depth derived from GPR two-way travel time (TWT) resulted in an average relative error of under 10 % when compared to 2430 in situ snow depth observations for the early and late winter season. The snow depth derived from GPR TWTs for the early winter season was estimated with a root mean square error (RMSE) of 1.6 cm and a mean bias error of 0.01 cm, while the accuracy for the late winter season on a deeper snowpack was estimated with a RMSE of 2.9 cm and a mean bias error of 0.4 cm. The GPR-derived snow depths were interpolated to create 1 m spatial resolution snow depth maps. The findings showed improved lake snow depth retrieval accuracy and introduced a fast and efficient method to obtain high spatial resolution snow depth information. The results suggest that GPR acquisitions can be used to derive lake snow depth, providing a viable alternative to manual snow depth monitoring methods. The findings can lead to an improved understanding of snow and lake ice interactions, which is essential for northern communities' safety and wellbeing and the scientific modelling community.

@article{tardy_mechanistic_2023,
	title = {Mechanistic movement models to predict geographic range expansions of ticks and tick-borne pathogens: {Case} studies with {Ixodes} scapularis and {Amblyomma} americanum in eastern {North} {America}},
	volume = {14},
	issn = {1877959X},
	shorttitle = {Mechanistic movement models to predict geographic range expansions of ticks and tick-borne pathogens},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S1877959X23000432},
	doi = {10.1016/j.ttbdis.2023.102161},
	language = {en},
	number = {4},
	urldate = {2023-06-02},
	journal = {Ticks and Tick-borne Diseases},
	author = {Tardy, Olivia and Acheson, Emily Sohanna and Bouchard, Catherine and Chamberland, Éric and Fortin, André and Ogden, Nicholas H. and Leighton, Patrick A.},
	month = jul,
	year = {2023},
	keywords = {NALCMS},
	pages = {102161},
}

@article{lenaker_modeled_2023,
	title = {Modeled predictions of human-associated and fecal-indicator bacteria concentrations and loadings in the {Menomonee} {River}, {Wisconsin} using in-situ optical sensors},
	volume = {18},
	issn = {1932-6203},
	url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0286851},
	doi = {10.1371/journal.pone.0286851},
	abstract = {Human sewage contamination of waterways is a major issue in the United States and throughout the world. Models were developed for estimation of two human-associated fecal-indicator and three general fecal-indicator bacteria (HIB and FIB) using in situ optical field-sensor data for estimating concentrations and loads of HIB and FIB and the extent of sewage contamination in the Menomonee River in Milwaukee, Wisconsin. Three commercially available optical sensor platforms were installed into an unfiltered custom-designed flow-through system along with a refrigerated automatic sampler at the Menomonee River sampling location. Ten-minute optical sensor measurements were made from November 2017 to December 2018 along with the collection of 153 flow-weighted discrete water samples (samples) for HIB, FIB, dissolved organic carbon (DOC), and optical properties of water. Of those 153 samples, 119 samples were from event-runoff periods, and 34 were collected during low-flow periods. Of the 119 event-runoff samples, 43 samples were from event-runoff combined sewer overflow (CSO) influenced periods (event-CSO periods). Models included optical sensor measurements as explanatory variables with a seasonal variable as an interaction term. In some cases, separate models for event-CSO periods and non CSO-periods generally improved model performance, as compared to using all the data combined for estimates of FIB and HIB. Therefore, the CSO and non-CSO models were used in final estimations for CSO and non-CSO time periods, respectively. Estimated continuous concentrations for all bacteria markers varied over six orders of magnitude during the study period. The greatest concentrations, loads, and proportion of sewage contamination occurred during event-runoff and event-CSO periods. Comparison to water quality standards and microbial risk assessment benchmarks indicated that estimated bacteria levels exceeded recreational water quality criteria between 34 and 96\% of the entire monitoring period, highlighting the benefits of high-frequency monitoring compared to traditional grab sample collection. The application of optical sensors for estimation of HIB and FIB markers provided a thorough assessment of bacterial presence and human health risk in the Menomonee River.},
	language = {en},
	number = {6},
	urldate = {2023-06-19},
	journal = {PLOS ONE},
	author = {Lenaker, Peter L. and Corsi, Steven R. and Cicco, Laura A. De and Olds, Hayley T. and Dila, Debra K. and Danz, Mari E. and McLellan, Sandra L. and Rutter, Troy D.},
	month = jun,
	year = {2023},
	note = {Publisher: Public Library of Science},
	keywords = {Political Boundaries},
	pages = {e0286851},
}

Human sewage contamination of waterways is a major issue in the United States and throughout the world. Models were developed for estimation of two human-associated fecal-indicator and three general fecal-indicator bacteria (HIB and FIB) using in situ optical field-sensor data for estimating concentrations and loads of HIB and FIB and the extent of sewage contamination in the Menomonee River in Milwaukee, Wisconsin. Three commercially available optical sensor platforms were installed into an unfiltered custom-designed flow-through system along with a refrigerated automatic sampler at the Menomonee River sampling location. Ten-minute optical sensor measurements were made from November 2017 to December 2018 along with the collection of 153 flow-weighted discrete water samples (samples) for HIB, FIB, dissolved organic carbon (DOC), and optical properties of water. Of those 153 samples, 119 samples were from event-runoff periods, and 34 were collected during low-flow periods. Of the 119 event-runoff samples, 43 samples were from event-runoff combined sewer overflow (CSO) influenced periods (event-CSO periods). Models included optical sensor measurements as explanatory variables with a seasonal variable as an interaction term. In some cases, separate models for event-CSO periods and non CSO-periods generally improved model performance, as compared to using all the data combined for estimates of FIB and HIB. Therefore, the CSO and non-CSO models were used in final estimations for CSO and non-CSO time periods, respectively. Estimated continuous concentrations for all bacteria markers varied over six orders of magnitude during the study period. The greatest concentrations, loads, and proportion of sewage contamination occurred during event-runoff and event-CSO periods. Comparison to water quality standards and microbial risk assessment benchmarks indicated that estimated bacteria levels exceeded recreational water quality criteria between 34 and 96% of the entire monitoring period, highlighting the benefits of high-frequency monitoring compared to traditional grab sample collection. The application of optical sensors for estimation of HIB and FIB markers provided a thorough assessment of bacterial presence and human health risk in the Menomonee River.

@phdthesis{falkenstein_modeling_2023,
	type = {Master of {Science} ({MS})},
	title = {Modeling of {Surficial} and {Groundwater} {Hydrology} in {Southeastern} {Georgia} {Including} the {Okefenokee}},
	url = {https://esploro.libs.uga.edu/esploro/outputs/graduate/MODELING-OF-SURFICIAL-AND-GROUNDWATER-HYDROLOGY/9949574514802959},
	urldate = {2023-10-05},
	school = {University of Georgia},
	author = {Falkenstein, Lauryn},
	month = aug,
	year = {2023},
	keywords = {NALCMS},
}

@misc{bick_modeling_2023,
	title = {Modeling the {Spatiotemporal} {Influence} of {Climate} on {American} {Avian} {Migration}},
	copyright = {© 2023, Posted by Cold Spring Harbor Laboratory. This pre-print is available under a Creative Commons License (Attribution-NonCommercial-NoDerivs 4.0 International), CC BY-NC-ND 4.0, as described at http://creativecommons.org/licenses/by-nc-nd/4.0/},
	url = {https://www.biorxiv.org/content/10.1101/2023.03.27.534441v1},
	doi = {10.1101/2023.03.27.534441},
	abstract = {North and South American Birds have adapted to climatic and ecological patterns to inform their Spring and Fall migration timings. Temperature and precipitation patterns are shifting under anthropogenic climate change, which has downstream effects on for instance plant flowering cycles, insect populations, and habitat availability. Understanding how these cues trigger migration could improve the effectiveness and timing of bird surveys, as well as informing habitat protection and creation efforts to lessen biodiversity loss due to climate change. In this work, we train an ensemble of random forest regressors on subsets of North and South American climate data to predict distributions of historical eBird occurrence probability for passerine bird species in a North American forested region using eBird citizen science surveys from 2008-2018. By running these ensembles with lagged climate data, we study spatiotemporal effects on bird migration through the resulting error and feature importance metrics. We find statistically significant decreases in error when using lagged climate features rather than the same-month climate to predict species communities in October, when many passerines have begun their southward winter migration, with longer temporal effects for precipitation than temperature. North American climate features were more important than South American features for prediction of species communities in Fall months, suggesting the model drew upon regional climatic cues for predicting when species would migrate southward. By predicting species occurrence using 2021-2040 climate projections, we predict that projected species occurrence probabilities will increase in April and May, agreeing with existing literature suggesting earlier Spring arrival of migratory birds. These results demonstrate that machine learning models have the potential to elucidate complex relationships between climate and bird behavior that linear models may miss. A deeper understanding of such spatiotemporal effects will be required to support biodiversity protection through climate change.},
	language = {en},
	urldate = {2023-06-29},
	publisher = {bioRxiv},
	author = {Bick, I. Avery and Bakkestuen, Vegar and Pedersen, Marius and Raja, Kiran and Sethi, Sarab},
	month = mar,
	year = {2023},
	note = {Pages: 2023.03.27.534441
Section: New Results},
	keywords = {Terrestrial Ecoregions (CEC 1997)},
}

North and South American Birds have adapted to climatic and ecological patterns to inform their Spring and Fall migration timings. Temperature and precipitation patterns are shifting under anthropogenic climate change, which has downstream effects on for instance plant flowering cycles, insect populations, and habitat availability. Understanding how these cues trigger migration could improve the effectiveness and timing of bird surveys, as well as informing habitat protection and creation efforts to lessen biodiversity loss due to climate change. In this work, we train an ensemble of random forest regressors on subsets of North and South American climate data to predict distributions of historical eBird occurrence probability for passerine bird species in a North American forested region using eBird citizen science surveys from 2008-2018. By running these ensembles with lagged climate data, we study spatiotemporal effects on bird migration through the resulting error and feature importance metrics. We find statistically significant decreases in error when using lagged climate features rather than the same-month climate to predict species communities in October, when many passerines have begun their southward winter migration, with longer temporal effects for precipitation than temperature. North American climate features were more important than South American features for prediction of species communities in Fall months, suggesting the model drew upon regional climatic cues for predicting when species would migrate southward. By predicting species occurrence using 2021-2040 climate projections, we predict that projected species occurrence probabilities will increase in April and May, agreeing with existing literature suggesting earlier Spring arrival of migratory birds. These results demonstrate that machine learning models have the potential to elucidate complex relationships between climate and bird behavior that linear models may miss. A deeper understanding of such spatiotemporal effects will be required to support biodiversity protection through climate change.

@article{salas-lizana_neotropical_2023,
	title = {Neotropical {Clavulina}: {Two} new species from {Mexico} and a re-evaluation of {Clavulina} floridana},
	volume = {115},
	issn = {0027-5514},
	shorttitle = {Neotropical {Clavulina}},
	url = {https://www.tandfonline.com/doi/ref/10.1080/00275514.2022.2148191},
	doi = {10.1080/00275514.2022.2148191},
	number = {1},
	urldate = {2023-06-27},
	journal = {Mycologia},
	author = {Salas-Lizana, Rodolfo and Villegas Ríos, Margarita and Alvarez-Manjarrez, Julieta and Pérez-Pazos, Eduardo and Farid, Arian and Franck, Alan and Smith, Mathew E. and Garibay-Orijel, Roberto},
	month = jan,
	year = {2023},
	note = {Publisher: Taylor \& Francis},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {135--152},
}

@article{chambers_new_2023,
	title = {New indicators of ecological resilience and invasion resistance to support prioritization and management in the sagebrush biome, {United} {States}},
	volume = {10},
	issn = {2296-701X},
	url = {https://www.frontiersin.org/articles/10.3389/fevo.2022.1009268},
	abstract = {Ecosystem transformations to altered or novel ecological states are accelerating across the globe. Indicators of ecological resilience to disturbance and resistance to invasion can aid in assessing risks and prioritizing areas for conservation and restoration. The sagebrush biome encompasses parts of 11 western states and is experiencing rapid transformations due to human population growth, invasive species, altered disturbance regimes, and climate change. We built on prior use of static soil moisture and temperature regimes to develop new, ecologically relevant and climate responsive indicators of both resilience and resistance. Our new indicators were based on climate and soil water availability variables derived from process-based ecohydrological models that allow predictions of future conditions. We asked: (1) Which variables best indicate resilience and resistance? (2) What are the relationships among the indicator variables and resilience and resistance categories? (3) How do patterns of resilience and resistance vary across the area? We assembled a large database (n = 24,045) of vegetation sample plots from regional monitoring programs and derived multiple climate and soil water availability variables for each plot from ecohydrological simulations. We used USDA Natural Resources Conservation Service National Soils Survey Information, Ecological Site Descriptions, and expert knowledge to develop and assign ecological types and resilience and resistance categories to each plot. We used random forest models to derive a set of 19 climate and water availability variables that best predicted resilience and resistance categories. Our models had relatively high multiclass accuracy (80\% for resilience; 75\% for resistance). Top indicator variables for both resilience and resistance included mean temperature, coldest month temperature, climatic water deficit, and summer and driest month precipitation. Variable relationships and patterns differed among ecoregions but reflected environmental gradients; low resilience and resistance were indicated by warm and dry conditions with high climatic water deficits, and moderately high to high resilience and resistance were characterized by cooler and moister conditions with low climatic water deficits. The new, ecologically-relevant indicators provide information on the vulnerability of resources and likely success of management actions, and can be used to develop new approaches and tools for prioritizing areas for conservation and restoration actions.},
	urldate = {2023-06-23},
	journal = {Frontiers in Ecology and Evolution},
	author = {Chambers, Jeanne C. and Brown, Jessi L. and Bradford, John B. and Board, David I. and Campbell, Steven B. and Clause, Karen J. and Hanberry, Brice and Schlaepfer, Daniel R. and Urza, Alexandra K.},
	year = {2023},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
}

Ecosystem transformations to altered or novel ecological states are accelerating across the globe. Indicators of ecological resilience to disturbance and resistance to invasion can aid in assessing risks and prioritizing areas for conservation and restoration. The sagebrush biome encompasses parts of 11 western states and is experiencing rapid transformations due to human population growth, invasive species, altered disturbance regimes, and climate change. We built on prior use of static soil moisture and temperature regimes to develop new, ecologically relevant and climate responsive indicators of both resilience and resistance. Our new indicators were based on climate and soil water availability variables derived from process-based ecohydrological models that allow predictions of future conditions. We asked: (1) Which variables best indicate resilience and resistance? (2) What are the relationships among the indicator variables and resilience and resistance categories? (3) How do patterns of resilience and resistance vary across the area? We assembled a large database (n = 24,045) of vegetation sample plots from regional monitoring programs and derived multiple climate and soil water availability variables for each plot from ecohydrological simulations. We used USDA Natural Resources Conservation Service National Soils Survey Information, Ecological Site Descriptions, and expert knowledge to develop and assign ecological types and resilience and resistance categories to each plot. We used random forest models to derive a set of 19 climate and water availability variables that best predicted resilience and resistance categories. Our models had relatively high multiclass accuracy (80% for resilience; 75% for resistance). Top indicator variables for both resilience and resistance included mean temperature, coldest month temperature, climatic water deficit, and summer and driest month precipitation. Variable relationships and patterns differed among ecoregions but reflected environmental gradients; low resilience and resistance were indicated by warm and dry conditions with high climatic water deficits, and moderately high to high resilience and resistance were characterized by cooler and moister conditions with low climatic water deficits. The new, ecologically-relevant indicators provide information on the vulnerability of resources and likely success of management actions, and can be used to develop new approaches and tools for prioritizing areas for conservation and restoration actions.

@article{munsch_northeast_2023,
	title = {Northeast {Pacific} eelgrass dynamics: interannual expansion distances and meadow area variation over time},
	volume = {705},
	issn = {0171-8630, 1616-1599},
	shorttitle = {Northeast {Pacific} eelgrass dynamics},
	url = {https://www.int-res.com/abstracts/meps/v705/p61-75/},
	doi = {10.3354/meps14248},
	abstract = {Ecosystems constantly change, yet managers often lack information to move beyond static habitat assumptions. As human impacts and geographic information systems advance, it is important and feasible to quantify past habitat boundary shifts to inform management decisions (e.g. protective perimeters) robust to near-term habitat changes. This is the case in eelgrass
              (Zostera
              spp.), an ecosystem engineer that forms dynamic, often protected meadows. Practitioners protect areas to avoid human stress to eelgrass, but they can lack quantitative descriptions of the near-term potential for eelgrass meadows to shift into unprotected areas. Here, we quantified interannual eelgrass meadow boundary shifts within 23 sites spanning 9 decades and 19° latitude. Eelgrass meadow boundaries typically shifted into areas tens of meters away from previous meadow edges, but sometimes much farther. Also, eelgrass meadows often vacated and later recolonized the same areas. By implication, eelgrass protection efforts may be enhanced by considering that presently vacant areas may be inhabited in the future, especially near currently existing meadows. Additionally, eelgrass meadows changed less over time at sites less modified by people within temperate landscapes compared to sites located within human-dominated, warmer, and drought-prone landscapes with limited water turnover. We thus hypothesize that eelgrass meadows change more over time within landscapes exposed to greater stressor regimes because they more frequently or intensely cycle through disturbance and recovery phases. These results inform tactical decisions seeking to mitigate impacts of human activities to eelgrass and underscore the potential synergy of monitoring, research, and adaptive management approaches to protect dynamic habitats.},
	language = {en},
	urldate = {2023-06-02},
	journal = {Marine Ecology Progress Series},
	author = {Munsch, Sh and Beaty, Fl and Beheshti, Km and Chesney, Wb and Endris, Ca and Gerwing, Tg and Hessing-Lewis, M and Kiffney, Pm and O’Leary, Jk and Reshitnyk, L and Sanderson, Bl and Walter, Rk},
	month = feb,
	year = {2023},
	keywords = {Temperature},
	pages = {61--75},
}

Ecosystems constantly change, yet managers often lack information to move beyond static habitat assumptions. As human impacts and geographic information systems advance, it is important and feasible to quantify past habitat boundary shifts to inform management decisions (e.g. protective perimeters) robust to near-term habitat changes. This is the case in eelgrass (Zostera spp.), an ecosystem engineer that forms dynamic, often protected meadows. Practitioners protect areas to avoid human stress to eelgrass, but they can lack quantitative descriptions of the near-term potential for eelgrass meadows to shift into unprotected areas. Here, we quantified interannual eelgrass meadow boundary shifts within 23 sites spanning 9 decades and 19° latitude. Eelgrass meadow boundaries typically shifted into areas tens of meters away from previous meadow edges, but sometimes much farther. Also, eelgrass meadows often vacated and later recolonized the same areas. By implication, eelgrass protection efforts may be enhanced by considering that presently vacant areas may be inhabited in the future, especially near currently existing meadows. Additionally, eelgrass meadows changed less over time at sites less modified by people within temperate landscapes compared to sites located within human-dominated, warmer, and drought-prone landscapes with limited water turnover. We thus hypothesize that eelgrass meadows change more over time within landscapes exposed to greater stressor regimes because they more frequently or intensely cycle through disturbance and recovery phases. These results inform tactical decisions seeking to mitigate impacts of human activities to eelgrass and underscore the potential synergy of monitoring, research, and adaptive management approaches to protect dynamic habitats.

@article{klotz_oil_2023,
	title = {Oil and natural gas wells across the {NASA} {ABoVE} domain: fugitive methane emissions and broader environmental impacts},
	volume = {18},
	issn = {1748-9326},
	shorttitle = {Oil and natural gas wells across the {NASA} {ABoVE} domain},
	url = {https://iopscience.iop.org/article/10.1088/1748-9326/acbe52},
	doi = {10.1088/1748-9326/acbe52},
	abstract = {Abstract
            
              Arctic-boreal regions are experiencing major anthropogenic disturbances in addition to intensifying natural disturbance regimes as a consequence of climate change. Oil and natural gas (OG) activities are extensive in the Arctic-boreal region of western North America, a large portion of which is underlain by permafrost. The total number and distribution of OG wells and their potential fate remain unclear. Consequently, the collective impacts of OG wells on natural and cultural resources, human health and emissions of methane (CH
              4
              ), are poorly understood. Using public OG well databases, we analysed the distribution of OG wells drilled between 1984 and 2018 across the Core Domain of the NASA Arctic-Boreal Vulnerability Experiment (‘ABoVE domain’). We identified 242 007 OG wells drilled as of 2018 in the ABoVE domain, of which almost two thirds are now inactive or abandoned OG wells. We found that annual drilling has increased from 269 to 8599 OG wells from 1984 to 2014 with around 1000, 700 and 1800 OG wells drilled annually in evergreen forest, deciduous forest and herbaceous land cover types, respectively. 65 588 OG well sites were underlain by permafrost in 2012. Fugitive CH
              4
              emissions from active and abandoned OG wells drilled in the Canadian portion of the ABoVE domain accounted for approximately 13\% of the total anthropogenic CH
              4
              emissions in Canada in 2018. Our analysis identified OG wells as an anthropogenic disturbance in the ABoVE domain with potentially non-negligible consequences to local populations, ecosystems, and the climate system.},
	number = {3},
	urldate = {2023-06-02},
	journal = {Environmental Research Letters},
	author = {Klotz, Louise A and Sonnentag, Oliver and Wang, Ziming and Wang, Jonathan A and Kang, Mary},
	month = mar,
	year = {2023},
	keywords = {Terrestrial Ecoregions},
	pages = {035008},
}

Abstract Arctic-boreal regions are experiencing major anthropogenic disturbances in addition to intensifying natural disturbance regimes as a consequence of climate change. Oil and natural gas (OG) activities are extensive in the Arctic-boreal region of western North America, a large portion of which is underlain by permafrost. The total number and distribution of OG wells and their potential fate remain unclear. Consequently, the collective impacts of OG wells on natural and cultural resources, human health and emissions of methane (CH 4 ), are poorly understood. Using public OG well databases, we analysed the distribution of OG wells drilled between 1984 and 2018 across the Core Domain of the NASA Arctic-Boreal Vulnerability Experiment (‘ABoVE domain’). We identified 242 007 OG wells drilled as of 2018 in the ABoVE domain, of which almost two thirds are now inactive or abandoned OG wells. We found that annual drilling has increased from 269 to 8599 OG wells from 1984 to 2014 with around 1000, 700 and 1800 OG wells drilled annually in evergreen forest, deciduous forest and herbaceous land cover types, respectively. 65 588 OG well sites were underlain by permafrost in 2012. Fugitive CH 4 emissions from active and abandoned OG wells drilled in the Canadian portion of the ABoVE domain accounted for approximately 13% of the total anthropogenic CH 4 emissions in Canada in 2018. Our analysis identified OG wells as an anthropogenic disturbance in the ABoVE domain with potentially non-negligible consequences to local populations, ecosystems, and the climate system.

@techreport{dillon_pacific_2023,
	title = {Pacific coast temperate forest regional timber product flow analysis},
	url = {https://www.fs.usda.gov/research/treesearch/66788},
	language = {en},
	urldate = {2024-01-10},
	author = {Dillon, Thale and Morgan, Todd A.},
	year = {2023},
	keywords = {NALCMS},
}

@article{edwards_point_2023,
	title = {Point count offsets for estimating population sizes of north {American} landbirds},
	issn = {0019-1019},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/ibi.13169},
	doi = {10.1111/ibi.13169},
	journal = {Ibis International Journal of Avian Science},
	author = {Edwards, Brandon P. M. and Smith, Adam C. and Docherty, Teegan D. S. and Gahbauer, Marcel A. and Gillespie, Caitlyn R. and Grinde, Alexis R. and Harmer, Taylor and Iles, David T. and Matsuoka, Steven M. and Michel, Nicole L. and Murray, Andrew and Niemi, Gerald J. and Pasher, Jon and Pavlacky, David C. and Robinson, Barry G. and Ryder, Thomas B. and Sólymos, Péter and Stralberg, Diana and Zlonis, Edmund J.},
	month = jan,
	year = {2023},
	keywords = {NALCMS},
}

@article{walker_predation_2023,
	title = {Predation risk drives aposematic signal conformity},
	volume = {77},
	issn = {0014-3820},
	url = {https://doi.org/10.1093/evolut/qpad162},
	doi = {10.1093/evolut/qpad162},
	abstract = {Contrary to expectations regarding efficient predator education mediated by lack of ambiguity and enhanced prey recognition, aposematic signals often show considerable intraspecific variability. For example, some striped skunks (Mephitis mephitis) are almost entirely white, others have black-and-white stripes of equivalent thicknesses, yet others are mostly black. We tested the ecological correlates of this variation in patterning using 749 museum skins collected across North America. Skunks had longer white–black borders and more bilaterally symmetrical stripes in areas with a greater number of potential predator species, and this effect was more marked for mammalian than avian predators, the latter of which may be less deterred by noxious defenses. Skunks from locations with greater predator diversity were less variable in the extent of whiteness on their dorsa and less variable in the length of their white–black borders, suggesting strong selection from predators leads to greater conformity in stripe patterns, even at the same location, but weak selection from predators leads to relaxed selection on pattern conformity. Skunks exhibited greater areas of black pelage in areas of greater humidity conforming to Gloger’s rule. Our results indicate that relaxed predation pressure is key to warning signal variation in this iconic species, whereas stronger pressure leads to signal conformity and stronger signals.},
	number = {11},
	urldate = {2024-01-10},
	journal = {Evolution},
	author = {Walker, Hannah and Caro, Tim and Bell, Donovan and Ferguson, Adam and Stankowich, Theodore},
	month = nov,
	year = {2023},
	keywords = {NALCMS},
	pages = {2492--2503},
}

Contrary to expectations regarding efficient predator education mediated by lack of ambiguity and enhanced prey recognition, aposematic signals often show considerable intraspecific variability. For example, some striped skunks (Mephitis mephitis) are almost entirely white, others have black-and-white stripes of equivalent thicknesses, yet others are mostly black. We tested the ecological correlates of this variation in patterning using 749 museum skins collected across North America. Skunks had longer white–black borders and more bilaterally symmetrical stripes in areas with a greater number of potential predator species, and this effect was more marked for mammalian than avian predators, the latter of which may be less deterred by noxious defenses. Skunks from locations with greater predator diversity were less variable in the extent of whiteness on their dorsa and less variable in the length of their white–black borders, suggesting strong selection from predators leads to greater conformity in stripe patterns, even at the same location, but weak selection from predators leads to relaxed selection on pattern conformity. Skunks exhibited greater areas of black pelage in areas of greater humidity conforming to Gloger’s rule. Our results indicate that relaxed predation pressure is key to warning signal variation in this iconic species, whereas stronger pressure leads to signal conformity and stronger signals.

@phdthesis{potash_predators_2023,
	address = {Gainesville},
	type = {Doctorate ( {Ph}.{D}.)},
	title = {Predators, {Prey}, and {Acorns} an {Exploration} of {Predator} {Distributions}, {Prey} {Behavior}, and {Ecosystem} {Process} in the {Southeastern} {US}},
	url = {https://original-ufdc.uflib.ufl.edu/UFE0060261/00001/citation},
	language = {en},
	urldate = {2024-01-09},
	school = {University of Florida},
	author = {Potash, Alex D.},
	year = {2023},
	keywords = {Terrestrial Ecoregions (Griffith 2010)},
}

@article{calef_predicting_2023,
	title = {Predicting the {Unpredictable}: {Predicting} {Landcover} in {Boreal} {Alaska} and the {Yukon} {Including} {Succession} and {Wildfire} {Potential}},
	volume = {14},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {1999-4907},
	shorttitle = {Predicting the {Unpredictable}},
	url = {https://www.mdpi.com/1999-4907/14/8/1577},
	doi = {10.3390/f14081577},
	abstract = {The boreal forest of northwestern North America covers an extensive area, contains vast amounts of carbon in its vegetation and soil, and is characterized by extensive wildfires. Catastrophic crown fires in these forests are fueled predominantly by only two evergreen needle-leaf tree species, black spruce (Picea mariana (Mill.) B.S.P.) and lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.). Identifying where these flammable species grow through time in the landscape is critical for understanding wildfire risk, damages, and human exposure. Because medium resolution landcover data that include species detail are lacking, we developed a compound modeling approach that enabled us to refine the available evergreen forest category into highly flammable species and less flammable species. We then expanded our refined landcover at decadal time steps from 1984 to 2014. With the aid of an existing burn model, FlamMap, and simple succession rules, we were able to predict future landcover at decadal steps until 2054. Our resulting land covers provide important information to communities in our study area on current and future wildfire risk and vegetation changes and could be developed in a similar fashion for other areas.},
	language = {en},
	number = {8},
	urldate = {2023-08-11},
	journal = {Forests},
	author = {Calef, Monika P. and Schmidt, Jennifer I. and Varvak, Anna and Ziel, Robert},
	month = aug,
	year = {2023},
	note = {Number: 8
Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {NALCMS},
	pages = {1577},
}

The boreal forest of northwestern North America covers an extensive area, contains vast amounts of carbon in its vegetation and soil, and is characterized by extensive wildfires. Catastrophic crown fires in these forests are fueled predominantly by only two evergreen needle-leaf tree species, black spruce (Picea mariana (Mill.) B.S.P.) and lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.). Identifying where these flammable species grow through time in the landscape is critical for understanding wildfire risk, damages, and human exposure. Because medium resolution landcover data that include species detail are lacking, we developed a compound modeling approach that enabled us to refine the available evergreen forest category into highly flammable species and less flammable species. We then expanded our refined landcover at decadal time steps from 1984 to 2014. With the aid of an existing burn model, FlamMap, and simple succession rules, we were able to predict future landcover at decadal steps until 2054. Our resulting land covers provide important information to communities in our study area on current and future wildfire risk and vegetation changes and could be developed in a similar fashion for other areas.

@article{currie_prioritizing_2023,
	title = {Prioritizing ecological restoration of converted lands in {Canada} by spatially integrating organic carbon storage and biodiversity benefits},
	issn = {2578-4854, 2578-4854},
	url = {https://conbio.onlinelibrary.wiley.com/doi/10.1111/csp2.12924},
	doi = {10.1111/csp2.12924},
	language = {en},
	urldate = {2023-06-02},
	journal = {Conservation Science and Practice},
	author = {Currie, Jessica and Merritt, Will and Liang, Chris and Sothe, Camile and Beatty, Craig R. and Shackelford, Nancy and Hirsh‐Pearson, Kristen and Gonsamo, Alemu and Snider, James},
	month = apr,
	year = {2023},
	keywords = {NALCMS},
	pages = {e12924},
}

@article{coffer_providing_2023,
	title = {Providing a framework for seagrass mapping in {United} {States} coastal ecosystems using high spatial resolution satellite imagery},
	volume = {337},
	issn = {03014797},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0301479723004577},
	doi = {10.1016/j.jenvman.2023.117669},
	language = {en},
	urldate = {2023-06-02},
	journal = {Journal of Environmental Management},
	author = {Coffer, Megan M. and Graybill, David D. and Whitman, Peter J. and Schaeffer, Blake A. and Salls, Wilson B. and Zimmerman, Richard C. and Hill, Victoria and Lebrasse, Marie Cindy and Li, Jiang and Keith, Darryl J. and Kaldy, James and Colarusso, Phil and Raulerson, Gary and Ward, David and Kenworthy, W. Judson},
	month = jul,
	year = {2023},
	keywords = {Blue Carbon},
	pages = {117669},
}

@phdthesis{braden_quantifying_2023,
	title = {Quantifying uncertainty of forest extent estimates in {Mexico} by comparing satellite-derived land and tree cover products},
	url = {https://udspace.udel.edu/handle/19716/32760},
	abstract = {Information about forest extent and tree cover is needed to evaluate the status of natural resources, conservation practices and environmental policies. The challenge is that different forest definitions, remote sensing products, and data availability can lead to discrepancies in reporting forest area and ultimately forest carbon estimates. Here, I compared forest extent estimates from 7 regional and global land or tree cover products at 30 m resolution across mainland Mexico. Comparison results presented significant uncertainty in forest extent estimates for Mexico, ranging from 387,607 km2 to 675,239 km2 depending on which satellite-derived product and forest definition is utilized. Next, I compared these satellite-derived products with two independent forest inventory datasets at the national scale (n=21,167) and at the local scale (n=486). The highest agreement between satellite-derived products and forest inventory data is within the tropical moist forest, and the least agreement is within the subtropical steppe ecozones. I further developed a hybrid uncertainty product by combining the 7 forest extents to calculate forest likelihood. I identified a forest area of 340,661 km2 that has low agreement among satellite-derived products. The tropical dry forest and subtropical mountain system represented the two ecozones with the greatest amount of disagreement among satellite-derived products. These findings identify uncertainty surrounding forest extent estimates across ecozones in Mexico where additional ground data and research is needed.},
	language = {en},
	urldate = {2023-06-02},
	school = {University of Delaware},
	author = {Braden, Dustin S.},
	year = {2023},
	keywords = {NALCMS},
}

Information about forest extent and tree cover is needed to evaluate the status of natural resources, conservation practices and environmental policies. The challenge is that different forest definitions, remote sensing products, and data availability can lead to discrepancies in reporting forest area and ultimately forest carbon estimates. Here, I compared forest extent estimates from 7 regional and global land or tree cover products at 30 m resolution across mainland Mexico. Comparison results presented significant uncertainty in forest extent estimates for Mexico, ranging from 387,607 km2 to 675,239 km2 depending on which satellite-derived product and forest definition is utilized. Next, I compared these satellite-derived products with two independent forest inventory datasets at the national scale (n=21,167) and at the local scale (n=486). The highest agreement between satellite-derived products and forest inventory data is within the tropical moist forest, and the least agreement is within the subtropical steppe ecozones. I further developed a hybrid uncertainty product by combining the 7 forest extents to calculate forest likelihood. I identified a forest area of 340,661 km2 that has low agreement among satellite-derived products. The tropical dry forest and subtropical mountain system represented the two ecozones with the greatest amount of disagreement among satellite-derived products. These findings identify uncertainty surrounding forest extent estimates across ecozones in Mexico where additional ground data and research is needed.

@article{hale_recent_2023,
	title = {Recent decreases in snow water storage in western {North} {America}},
	volume = {4},
	copyright = {2023 The Author(s)},
	issn = {2662-4435},
	url = {https://www.nature.com/articles/s43247-023-00751-3},
	doi = {10.1038/s43247-023-00751-3},
	abstract = {Mountain snowpacks act as natural water towers, storing winter precipitation until summer months when downstream water demand is greatest. We introduce a Snow Storage Index (SSI), representing the temporal phase difference between daily precipitation and surface water inputs—sum of rainfall and snowmelt into terrestrial systems—weighted by relative magnitudes. Different from snow water equivalent or snow fraction, the SSI represents the degree to which the snowpack delays the timing and magnitude of surface water inputs relative to precipitation, a fundamental component of how snow water storage influences the hydrologic cycle. In western North America, annual SSI has decreased (p {\textless} 0.05) from 1950–2013 in over 25\% of mountainous areas, as a result of substantially earlier snowmelt and rainfall in spring months, with additional declines in winter precipitation. The SSI and associated trends offer a new perspective on hydrologic sensitivity to climate change which have broad implications for water resources and ecosystems.},
	language = {en},
	number = {1},
	urldate = {2023-06-28},
	journal = {Communications Earth \& Environment},
	author = {Hale, Katherine E. and Jennings, Keith S. and Musselman, Keith N. and Livneh, Ben and Molotch, Noah P.},
	month = may,
	year = {2023},
	note = {Number: 1
Publisher: Nature Publishing Group},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {1--11},
}

Mountain snowpacks act as natural water towers, storing winter precipitation until summer months when downstream water demand is greatest. We introduce a Snow Storage Index (SSI), representing the temporal phase difference between daily precipitation and surface water inputs—sum of rainfall and snowmelt into terrestrial systems—weighted by relative magnitudes. Different from snow water equivalent or snow fraction, the SSI represents the degree to which the snowpack delays the timing and magnitude of surface water inputs relative to precipitation, a fundamental component of how snow water storage influences the hydrologic cycle. In western North America, annual SSI has decreased (p \textless 0.05) from 1950–2013 in over 25% of mountainous areas, as a result of substantially earlier snowmelt and rainfall in spring months, with additional declines in winter precipitation. The SSI and associated trends offer a new perspective on hydrologic sensitivity to climate change which have broad implications for water resources and ecosystems.

@article{tack_regional_2023,
	title = {Regional {Context} for {Balancing} {Sagebrush}- and {Woodland}-{Dependent} {Songbird} {Needs} with {Targeted} {Pinyon}-{Juniper} {Management}},
	volume = {88},
	issn = {1550-7424},
	url = {https://www.sciencedirect.com/science/article/pii/S1550742423000404},
	doi = {10.1016/j.rama.2023.03.006},
	abstract = {In the western United States, pinyon-juniper woodlands have expanded by as much as sixfold among sagebrush landscapes since the late 19th century, with demonstrated negative impacts to the behavior, demography, and population dynamics of species that rely on intact sagebrush rangelands. Notably, greater sage-grouse (Centrocercus urophasianus) are unable to tolerate even low conifer cover, which can result in population declines and local extirpation, whereas removing expanding conifer cover has been demonstrated to increase sage grouse population growth rates and sagebrush obligate songbird abundance. Yet conifer management among sagebrush landscapes has been met with concerns about unintended impacts to species that rely on conifer woodlands, notably the pinyon jay (Gymnorhinus cyanocephalus), whose population declines are distinctive among birds breeding in pinyon-juniper woodlands. Spatial models of bird abundance can help management prioritize future actions in light of multiple species requirements, while also providing a framework to retroactively test the impact of past treatments. We used Breeding Bird Survey data to model indices to abundance in relation to multiscale habitat features including landcover, fire, topography, and climate variables for nine songbird species reliant on sagebrush and pinyon-juniper woodlands for breeding. Predictive maps allowed us to also examine the overlap of conifer management conducted by the Sage Grouse Initiative (SGI), which targets management of early successional conifers among priority sage-grouse habitats, with predicted indices to abundance of songbirds. Our findings demonstrate that targeted sage grouse habitat restoration under SGI was not at odds with protection of pinyon jay populations. Rather, conifer management has largely occurred among northern sagebrush landscapes where models suggest that past cuts likely benefit Brewer's sparrow and sage thrasher while avoiding pinyon jay habitats.},
	language = {en},
	urldate = {2023-07-07},
	journal = {Rangeland Ecology \& Management},
	author = {Tack, Jason D. and Smith, Joseph T. and Doherty, Kevin E. and Donnelly, Patrick J. and Maestas, Jeremy D. and Allred, Brady W. and Reinhardt, Jason and Morford, Scott L. and Naugle, David E.},
	month = may,
	year = {2023},
	keywords = {Terrestrial Ecoregions (CEC 1997)},
	pages = {182--191},
}

In the western United States, pinyon-juniper woodlands have expanded by as much as sixfold among sagebrush landscapes since the late 19th century, with demonstrated negative impacts to the behavior, demography, and population dynamics of species that rely on intact sagebrush rangelands. Notably, greater sage-grouse (Centrocercus urophasianus) are unable to tolerate even low conifer cover, which can result in population declines and local extirpation, whereas removing expanding conifer cover has been demonstrated to increase sage grouse population growth rates and sagebrush obligate songbird abundance. Yet conifer management among sagebrush landscapes has been met with concerns about unintended impacts to species that rely on conifer woodlands, notably the pinyon jay (Gymnorhinus cyanocephalus), whose population declines are distinctive among birds breeding in pinyon-juniper woodlands. Spatial models of bird abundance can help management prioritize future actions in light of multiple species requirements, while also providing a framework to retroactively test the impact of past treatments. We used Breeding Bird Survey data to model indices to abundance in relation to multiscale habitat features including landcover, fire, topography, and climate variables for nine songbird species reliant on sagebrush and pinyon-juniper woodlands for breeding. Predictive maps allowed us to also examine the overlap of conifer management conducted by the Sage Grouse Initiative (SGI), which targets management of early successional conifers among priority sage-grouse habitats, with predicted indices to abundance of songbirds. Our findings demonstrate that targeted sage grouse habitat restoration under SGI was not at odds with protection of pinyon jay populations. Rather, conifer management has largely occurred among northern sagebrush landscapes where models suggest that past cuts likely benefit Brewer's sparrow and sage thrasher while avoiding pinyon jay habitats.

@phdthesis{johnston_representativeness_2023,
	type = {thesis},
	title = {Representativeness of {Protected} {Areas} in the {Algonquin} to {Adirondacks} {Region}: {A} {Gap} {Analysis}},
	shorttitle = {Representativeness of {Protected} {Areas} in the {Algonquin} to {Adirondacks} {Region}},
	url = {https://qspace.library.queensu.ca/handle/1974/31671},
	abstract = {Protected area networks play an important role in the conservation of biodiversity. A useful approach for determining their suitability is assessing how represented certain ecosystem types are in these networks, in comparison to the region as a whole. Here, a gap analysis was performed to analyze representation of ecosystem types within protected areas of the Algonquin to Adirondacks region. ArcGIS Pro software was used to create a map of ecosystem types across the region based on land cover and topography. The composition of ecosystems contained within protected areas was then compared with the composition of the region as a whole. The results show certain ecosystem types as overrepresented in protected areas, while others are underrepresented, and that this varies by ecoregion. These findings have implications for how new protected areas should be established moving forward, with protected areas potentially needing to be modified to account for representation. The next step in this analysis would be the addition of current and future climate data, as climate change will very likely affect the composition of ecosystem types in protected areas.},
	language = {en},
	urldate = {2023-06-02},
	school = {Queen's University},
	author = {Johnston, Grace},
	month = may,
	year = {2023},
	note = {Accepted: 2023-05-26T13:37:14Z},
	keywords = {NALCMS, Terrestrial Ecoregions},
}

Protected area networks play an important role in the conservation of biodiversity. A useful approach for determining their suitability is assessing how represented certain ecosystem types are in these networks, in comparison to the region as a whole. Here, a gap analysis was performed to analyze representation of ecosystem types within protected areas of the Algonquin to Adirondacks region. ArcGIS Pro software was used to create a map of ecosystem types across the region based on land cover and topography. The composition of ecosystems contained within protected areas was then compared with the composition of the region as a whole. The results show certain ecosystem types as overrepresented in protected areas, while others are underrepresented, and that this varies by ecoregion. These findings have implications for how new protected areas should be established moving forward, with protected areas potentially needing to be modified to account for representation. The next step in this analysis would be the addition of current and future climate data, as climate change will very likely affect the composition of ecosystem types in protected areas.

@article{chenery_revealing_2023,
	title = {Revealing large‐scale parasite ranges: {An} integrated spatiotemporal database and multisource analysis of the winter tick},
	volume = {14},
	issn = {2150-8925, 2150-8925},
	shorttitle = {Revealing large‐scale parasite ranges},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/ecs2.4376},
	doi = {10.1002/ecs2.4376},
	language = {en},
	number = {1},
	urldate = {2023-06-01},
	journal = {Ecosphere},
	author = {Chenery, Emily S. and Harms, N. Jane and Fenton, Heather and Mandrak, Nicholas E. and Molnár, Péter K.},
	month = jan,
	year = {2023},
	keywords = {Terrestrial Ecoregions (CEC 1997)},
}

@book{delong_rivers_2023,
	edition = {Second Edition},
	title = {Rivers of {North} {America}},
	isbn = {978-0-12-818847-7},
	url = {https://linkinghub.elsevier.com/retrieve/pii/C20180044266},
	language = {en},
	urldate = {2023-06-28},
	publisher = {Elsevier},
	editor = {Delong, Michael D. and Jardine, Timothy D. and Benke, Arthur C. and Cushing, Colbert E.},
	year = {2023},
	doi = {10.1016/C2018-0-04426-6},
	keywords = {Terrestrial Ecoregions (CEC 1997)},
}

@incollection{beck_sage-grouse_2023,
	title = {Sage-{Grouse}},
	isbn = {978-3-031-34037-6},
	url = {https://link.springer.com/chapter/10.1007/978-3-031-34037-6_10},
	abstract = {In this chapter, we summarize the ecology and conservation issues affecting greater (Centrocercus urophasianus) and Gunnison (C. minimus) sage-grouse, iconic and obligate species of rangelands in the sagebrush (Artemisia spp.) biome in western North America. Greater...},
	language = {en},
	urldate = {2026-05-20},
	booktitle = {Rangeland {Wildlife} {Ecology} and {Conservation}},
	publisher = {Springer, Cham},
	author = {Beck, Jeffrey L. and Christiansen, Thomas J. and Davies, Kirk W. and Dinkins, Jonathan B. and Monroe, Adrian P. and Naugle, David E. and Schroeder, Michael A.},
	year = {2023},
	doi = {10.1007/978-3-031-34037-6_10},
	keywords = {NALCMS},
	pages = {295--338},
}

In this chapter, we summarize the ecology and conservation issues affecting greater (Centrocercus urophasianus) and Gunnison (C. minimus) sage-grouse, iconic and obligate species of rangelands in the sagebrush (Artemisia spp.) biome in western North America. Greater...

@article{comer_sampling_2023,
	title = {Sampling methods for archaeological predictive modeling: {Spatial} autocorrelation and model performance},
	volume = {48},
	issn = {2352-409X},
	shorttitle = {Sampling methods for archaeological predictive modeling},
	url = {https://www.sciencedirect.com/science/article/pii/S2352409X22004874},
	doi = {10.1016/j.jasrep.2022.103824},
	abstract = {With a case study of a direct detection model (DDM) designed for Fort Irwin, in southern California, we compare models that are identical except for the sampling methods that draw the data used to train and test them. We find that models trained and tested with a random cell sampling strategy perform better than do models that implement a kind of leave-one-out cross-validation (LOOCV) that focuses on discrete sites and non-site areas. We argue that this difference in measured predictive performance is due to spatial autocorrelation, and that it underscores the importance of clarity and specificity in describing the sampling methods used in archaeological predictive modeling and site detection. Different sampling methods are not necessarily superior or inferior, but they generate models that may be more or less appropriate for different tasks. Different sampling methods can also yield calculations of predictive ability that over- or understate a model’s performance at the task for which it was designed.},
	language = {en},
	urldate = {2023-06-23},
	journal = {Journal of Archaeological Science: Reports},
	author = {Comer, Jacob A. and Comer, Douglas C. and Dumitru, Ioana A. and Priebe, Carey E. and Patsolic, Jesse L.},
	month = apr,
	year = {2023},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {103824},
}

With a case study of a direct detection model (DDM) designed for Fort Irwin, in southern California, we compare models that are identical except for the sampling methods that draw the data used to train and test them. We find that models trained and tested with a random cell sampling strategy perform better than do models that implement a kind of leave-one-out cross-validation (LOOCV) that focuses on discrete sites and non-site areas. We argue that this difference in measured predictive performance is due to spatial autocorrelation, and that it underscores the importance of clarity and specificity in describing the sampling methods used in archaeological predictive modeling and site detection. Different sampling methods are not necessarily superior or inferior, but they generate models that may be more or less appropriate for different tasks. Different sampling methods can also yield calculations of predictive ability that over- or understate a model’s performance at the task for which it was designed.

@article{parada_san_2023,
	title = {San {Marcos}, {Guerrero} {Y} {Su} {Desafio} {Turistico} {Para} {Una} {Construcción} {Socioecológica} {Del} {Paisaje}},
	copyright = {Derechos de autor 2024 Papeles de Geografía},
	issn = {1989-4627},
	url = {https://revistas.um.es/geografia/article/view/572111},
	doi = {10.6018/geografia.572111},
	abstract = {The socio-ecological consequences of the appropriation and dispossession processes originated by tourism megaprojects have been documented, as well as the beneficial changes and the way to reduce their negative impacts. In the coastal municipality of San Marcos, Guerrero, Mexico, a project of this nature will be developed, so the objective of the work was to analyze the possible effects that it may have on the socioecosystem. The "agency" and "social structure" were established, based on semi-structured interviews, field observations and land use cartography. The current scenario shows an agency defined by multiple labor identities, the cattle ranch among them. The social structure exhibits 3 driving forces, the agrarian policy supported by the "sistema de cargos", the economic-cultural ones mainly due to the use of grasslands, and the natural forces, represented by labor activities in the not "transformed" ecosystems, threatened by land use changes and pollution. Social risks conjecture a differential impact between urban and rural residents, and ecological risks, depending on whether they are ecosystems such as beaches, jungle or aquatic environments. The standardization of new practices is necessary together with a socio-institutional perspective and the bottom-up organization to counteract the impacts of the project.},
	language = {es},
	number = {69},
	urldate = {2024-06-13},
	journal = {Papeles de Geografía},
	author = {Parada, Jaime Matus and Aragón, Ivan Ernesto Roldán and Carpio-Cortes, Leticia and Maldonado, Marco Antonio},
	year = {2023},
	note = {Number: 69},
	keywords = {NALCMS},
}

The socio-ecological consequences of the appropriation and dispossession processes originated by tourism megaprojects have been documented, as well as the beneficial changes and the way to reduce their negative impacts. In the coastal municipality of San Marcos, Guerrero, Mexico, a project of this nature will be developed, so the objective of the work was to analyze the possible effects that it may have on the socioecosystem. The "agency" and "social structure" were established, based on semi-structured interviews, field observations and land use cartography. The current scenario shows an agency defined by multiple labor identities, the cattle ranch among them. The social structure exhibits 3 driving forces, the agrarian policy supported by the "sistema de cargos", the economic-cultural ones mainly due to the use of grasslands, and the natural forces, represented by labor activities in the not "transformed" ecosystems, threatened by land use changes and pollution. Social risks conjecture a differential impact between urban and rural residents, and ecological risks, depending on whether they are ecosystems such as beaches, jungle or aquatic environments. The standardization of new practices is necessary together with a socio-institutional perspective and the bottom-up organization to counteract the impacts of the project.

@incollection{norman_satellite_2023,
	title = {Satellite {Observations} of {Forest} {Disturbances} for the {Conterminous} {United} {States} for the 2021 {Growing} {Season}},
	volume = {General Technical Report SRS-273},
	url = {https://www.fs.usda.gov/research/treesearch/66983},
	booktitle = {Forest {Health} {Monitoring}: {National} {Status}, {Trends}, and {Analysis} 2022},
	publisher = {U.S. Department of Agriculture},
	author = {Norman, Steven P. and Christie, William M.},
	editor = {Potter, Kevin M. and Conkling, Barbara L.},
	year = {2023},
	note = {Section: 4},
	keywords = {NALCMS},
	pages = {83--90},
}

@article{zulian_seasonal_2023,
	title = {Seasonal variation in drivers of bird-window collisions on the west coast of {British} {Columbia}, {Canada}},
	volume = {18},
	copyright = {© 2023 by the author(s)},
	issn = {1712-6568},
	url = {https://ace-eco.org/vol18/iss2/art15/},
	doi = {10.5751/ACE-02482-180215},
	abstract = {We examined the effects of façade-level building and vegetation features on bird-window collision risk, and how these effects varied across seasons at a Pacific coastal campus with mild winters, abundant evergreen vegetation, and seasonally varied bird communities. We searched for bird carcasses at 57 façades of 8 buildings at the University of British Columbia (UBC) over 155 days between January 2015 and March 2017 (total: 8835 façade surveys). Collision monitoring occurred across five equal sampling periods that represented stages of the annual cycle of the bird community, including the fall and spring migratory periods, the breeding season, and the long overwintering period. For each season, we compared logistic regression models predicting the odds of a collision from different sets of façade and vegetation characteristics expected to influence collisions: façade area, area of glass, porous surface cover (ground and shrub vegetation, soil, leaf litter), tree cover, and the number of building stories reflecting vegetation. Consistent with other studies, area of glass had a positive influence on collision probability in all seasons; however, the effect was strongest during the fall migratory period, when daily collision mortality rates peaked at UBC. The number of stories reflecting vegetation also increased collision probability, but only in the fall, indicating that the vertical extent of vegetation and reflective glass may affect collision risk differently as bird communities change across seasons. Façade area increased collision probability only in the winter (a long and lethal period for bird collisions at UBC), reflecting different risk factors associated with the species most vulnerable to collisions in this season. Our results highlight the need to measure building and vegetation effects across the longest and most lethal stages of the annual cycle of birds, both to predict the impact of proposed buildings and to prioritize mitigation strategies that will result in the greatest conservation benefits.},
	language = {en},
	number = {2},
	urldate = {2024-01-10},
	journal = {Avian Conservation and Ecology},
	author = {Zulian, Viviane and Norris, Andrea R. and Cockle, Kristina L. and Porter, Alison N. and Do, Lauryn G. and Groot, Krista L. De},
	month = nov,
	year = {2023},
	note = {Publisher: The Resilience Alliance},
	keywords = {NALCMS},
}

We examined the effects of façade-level building and vegetation features on bird-window collision risk, and how these effects varied across seasons at a Pacific coastal campus with mild winters, abundant evergreen vegetation, and seasonally varied bird communities. We searched for bird carcasses at 57 façades of 8 buildings at the University of British Columbia (UBC) over 155 days between January 2015 and March 2017 (total: 8835 façade surveys). Collision monitoring occurred across five equal sampling periods that represented stages of the annual cycle of the bird community, including the fall and spring migratory periods, the breeding season, and the long overwintering period. For each season, we compared logistic regression models predicting the odds of a collision from different sets of façade and vegetation characteristics expected to influence collisions: façade area, area of glass, porous surface cover (ground and shrub vegetation, soil, leaf litter), tree cover, and the number of building stories reflecting vegetation. Consistent with other studies, area of glass had a positive influence on collision probability in all seasons; however, the effect was strongest during the fall migratory period, when daily collision mortality rates peaked at UBC. The number of stories reflecting vegetation also increased collision probability, but only in the fall, indicating that the vertical extent of vegetation and reflective glass may affect collision risk differently as bird communities change across seasons. Façade area increased collision probability only in the winter (a long and lethal period for bird collisions at UBC), reflecting different risk factors associated with the species most vulnerable to collisions in this season. Our results highlight the need to measure building and vegetation effects across the longest and most lethal stages of the annual cycle of birds, both to predict the impact of proposed buildings and to prioritize mitigation strategies that will result in the greatest conservation benefits.

@article{kershaw_seasonally_2023,
	title = {Seasonally distinct runoff–recharge partitioning in an alpine tundra catchment},
	volume = {34},
	issn = {1045-6740, 1099-1530},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/ppp.2174},
	doi = {10.1002/ppp.2174},
	language = {en},
	number = {1},
	urldate = {2023-06-01},
	journal = {Permafrost and Periglacial Processes},
	author = {Kershaw, Geoffrey G. L. and English, Michael C. and Wolfe, Brent B.},
	month = jan,
	year = {2023},
	keywords = {NALCMS},
	pages = {94--107},
}

@article{chen_shifting_2023,
	title = {Shifting taxonomic and functional community composition of rivers under land use change},
	volume = {104},
	copyright = {© 2023 The Ecological Society of America.},
	issn = {1939-9170},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/ecy.4155},
	doi = {10.1002/ecy.4155},
	abstract = {Land use intensification has led to conspicuous changes in plant and animal communities across the world. Shifts in trait-based functional composition have recently been hypothesized to manifest at lower levels of environmental change when compared to species-based taxonomic composition; however, little is known about the commonalities in these responses across taxonomic groups and geographic regions. We investigated this hypothesis by testing for taxonomic and geographic similarities in the composition of riverine fish and insect communities across gradients of land use in major hydrological regions of the conterminous United States. We analyzed an extensive data set representing 556 species and 33 functional trait modalities from 8023 fish communities and 1434 taxa and 50 trait modalities from 5197 aquatic insect communities. Our results demonstrate abrupt threshold changes in both taxonomic and functional community composition due to land use conversion. Functional composition consistently demonstrated lower land use threshold responses compared to taxonomic composition for both fish (urban p = 0.069; agriculture p = 0.029) and insect (urban p = 0.095; agriculture p = 0.043) communities according to gradient forest models. We found significantly lower thresholds for urban versus agricultural land use for fishes (taxonomic and functional p {\textless} 0.001) and insects (taxonomic p = 0.001; functional p = 0.033). We further revealed that threshold responses in functional composition were more geographically consistent than for taxonomic composition to both urban and agricultural land use change. Traits contributing the most to overall functional composition change differed along urban and agricultural land gradients and conformed to predicted ecological mechanisms underpinning community change. This study points to reliable early-warning thresholds that accurately forecast compositional shifts in riverine communities to land use conversion, and highlight the importance of considering trait-based indicators of community change to inform large-scale land use management strategies and policies.},
	language = {en},
	number = {11},
	urldate = {2024-01-10},
	journal = {Ecology},
	author = {Chen, Kai and Midway, Stephen R. and Peoples, Brandon K. and Wang, Beixin and Olden, Julian D.},
	year = {2023},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/ecy.4155},
	keywords = {NALCMS},
	pages = {e4155},
}

Land use intensification has led to conspicuous changes in plant and animal communities across the world. Shifts in trait-based functional composition have recently been hypothesized to manifest at lower levels of environmental change when compared to species-based taxonomic composition; however, little is known about the commonalities in these responses across taxonomic groups and geographic regions. We investigated this hypothesis by testing for taxonomic and geographic similarities in the composition of riverine fish and insect communities across gradients of land use in major hydrological regions of the conterminous United States. We analyzed an extensive data set representing 556 species and 33 functional trait modalities from 8023 fish communities and 1434 taxa and 50 trait modalities from 5197 aquatic insect communities. Our results demonstrate abrupt threshold changes in both taxonomic and functional community composition due to land use conversion. Functional composition consistently demonstrated lower land use threshold responses compared to taxonomic composition for both fish (urban p = 0.069; agriculture p = 0.029) and insect (urban p = 0.095; agriculture p = 0.043) communities according to gradient forest models. We found significantly lower thresholds for urban versus agricultural land use for fishes (taxonomic and functional p \textless 0.001) and insects (taxonomic p = 0.001; functional p = 0.033). We further revealed that threshold responses in functional composition were more geographically consistent than for taxonomic composition to both urban and agricultural land use change. Traits contributing the most to overall functional composition change differed along urban and agricultural land gradients and conformed to predicted ecological mechanisms underpinning community change. This study points to reliable early-warning thresholds that accurately forecast compositional shifts in riverine communities to land use conversion, and highlight the importance of considering trait-based indicators of community change to inform large-scale land use management strategies and policies.

@article{greaves_simulating_2023,
	title = {Simulating future climate change impacts on snow- and ice-related driving hazards in {Arctic}-boreal regions},
	volume = {18},
	issn = {1748-9326},
	url = {https://iopscience.iop.org/article/10.1088/1748-9326/acb5b1},
	doi = {10.1088/1748-9326/acb5b1},
	abstract = {Abstract
            
              As Arctic and boreal regions rapidly warm, the frequency and seasonal timing of hazardous driving conditions on all-season Arctic-boreal roads are likely to change. Because these roads link remote Arctic areas to the rest of the North American road system, climate change may substantially affect safety and quality of life for northern residents and commercial enterprises. To gain insight into future hazardous driving conditions, we built Random Forest models that predict the occurrence of hazardous driving conditions by linking snow, ice, and weather simulated by a spatially explicit modeling system (SnowModel) to archived road condition reports from two highly trafficked all-season northern roads: the Dalton Highway (Alaska, USA) and Dempster Highway (Yukon, Canada). We applied these models to downscaled future climate trajectories for the study period of 2006–2100. We estimated future trends in the frequency and timing of icy, wet-icy, and snowy road surfaces, blowing and drifting snow, and high winds. We found that as the climate warms, and the portion of the year when snow and ice occur becomes shorter, overall frequency of snow storms and ice- and snow-related driving hazards decreased. For example, the mean number of days per year when roads are covered in snow or ice decreased by 51 d (−21\%) on the Dalton Highway between the 2006–2020 and 2081–2100 time periods. However, the intensity of storms was predicted to increase, resulting in higher mean annual storm wind speeds (Dalton +0.56 m s
              −1
              [+17\%]) and snowfall totals (Dalton +0.3 cm [+36\%]). Our models also predicted increasing frequency of wet-icy driving conditions during November, December, January, and February, when daylength is short and hazardous conditions may be more difficult to perceive. Our findings may help road managers and drivers adapt their expectations and behaviors to minimize accident risk on Arctic-boreal roads in the future.},
	number = {2},
	urldate = {2023-06-02},
	journal = {Environmental Research Letters},
	author = {Greaves, Heather E and Boelman, Natalie T and Brinkman, Todd J and Liston, Glen E and Prugh, Laura R and Reinking, Adele K},
	month = feb,
	year = {2023},
	keywords = {NALCMS},
	pages = {025006},
}

Abstract As Arctic and boreal regions rapidly warm, the frequency and seasonal timing of hazardous driving conditions on all-season Arctic-boreal roads are likely to change. Because these roads link remote Arctic areas to the rest of the North American road system, climate change may substantially affect safety and quality of life for northern residents and commercial enterprises. To gain insight into future hazardous driving conditions, we built Random Forest models that predict the occurrence of hazardous driving conditions by linking snow, ice, and weather simulated by a spatially explicit modeling system (SnowModel) to archived road condition reports from two highly trafficked all-season northern roads: the Dalton Highway (Alaska, USA) and Dempster Highway (Yukon, Canada). We applied these models to downscaled future climate trajectories for the study period of 2006–2100. We estimated future trends in the frequency and timing of icy, wet-icy, and snowy road surfaces, blowing and drifting snow, and high winds. We found that as the climate warms, and the portion of the year when snow and ice occur becomes shorter, overall frequency of snow storms and ice- and snow-related driving hazards decreased. For example, the mean number of days per year when roads are covered in snow or ice decreased by 51 d (−21%) on the Dalton Highway between the 2006–2020 and 2081–2100 time periods. However, the intensity of storms was predicted to increase, resulting in higher mean annual storm wind speeds (Dalton +0.56 m s −1 [+17%]) and snowfall totals (Dalton +0.3 cm [+36%]). Our models also predicted increasing frequency of wet-icy driving conditions during November, December, January, and February, when daylength is short and hazardous conditions may be more difficult to perceive. Our findings may help road managers and drivers adapt their expectations and behaviors to minimize accident risk on Arctic-boreal roads in the future.

@article{hoppinen_snow_2023,
	title = {Snow {Water} {Equivalent} {Retrieval} {Over} {Idaho}, {Part} {B}: {Using} {L}-band {UAVSAR} {Repeat}-{Pass} {Interferometry}},
	shorttitle = {Snow {Water} {Equivalent} {Retrieval} {Over} {Idaho}, {Part} {B}},
	url = {https://tc.copernicus.org/preprints/tc-2023-127/},
	doi = {10.5194/tc-2023-127},
	abstract = {{\textless}p{\textgreater}{\textless}strong class="journal-contentHeaderColor"{\textgreater}Abstract.{\textless}/strong{\textgreater} This study evaluates using interferometry on low frequency synthetic aperture radar (SAR) images to monitor snow water equivalent (SWE) over seasonal and synoptic scales. We retrieved SWE changes from nine pairs of SAR images, mean 8 days temporal baseline, captured by an L-band aerial platform, NASA's UAVSAR, over central Idaho as part of the NASA SnowEx 2020 and 2021 campaigns. The retrieved SWE changes were compared against coincident in situ measurements (SNOTEL and snow pits from the SnowEx field campaign) and to 100 m gridded SnowModel modeled SWE changes. The comparison of in situ to retrieved shows a strong Pearson correlation (R = 0.80) and low RMSE (0.1 m, n = 64) for snow depth change and similar results for SWE change (RMSE = 0.04 m, R = 0.52, n = 57). The comparison between retrieved SWE changes to SnowModel SWE change also showed good correlation (R = 0.60, RMSD = 0.023 m, n = 3.2e6) and especially high correlation for a subset of pixels with no modeled melt and low tree coverage (R = 0.72, RMSD = 0.013 m, n = 6.5e4). Finally, we bin the retrievals for a variety of factors and show decreasing correlation between the modeled and retrieved values for lower elevations, higher incidence angles, higher tree percentages and heights, and greater cumulative melt. This study builds on previous interferometry work by using a full winter season time series of L-band SAR images over a large spatial extent to evaluate the accuracy of SWE change retrievals against both in situ and modeled results and the controlling factors of the retrieval accuracy.{\textless}/p{\textgreater}},
	language = {English},
	urldate = {2024-01-31},
	journal = {The Cryosphere Discussions},
	author = {Hoppinen, Zachary Marshall and Oveisgharan, Shadi and Marshall, Hans-Peter and Mower, Ross and Elder, Kelly and Vuyovich, Carrie},
	month = aug,
	year = {2023},
	note = {Publisher: Copernicus GmbH},
	keywords = {NALCMS},
	pages = {1--24},
}

\textlessp\textgreater\textlessstrong class="journal-contentHeaderColor"\textgreaterAbstract.\textless/strong\textgreater This study evaluates using interferometry on low frequency synthetic aperture radar (SAR) images to monitor snow water equivalent (SWE) over seasonal and synoptic scales. We retrieved SWE changes from nine pairs of SAR images, mean 8 days temporal baseline, captured by an L-band aerial platform, NASA's UAVSAR, over central Idaho as part of the NASA SnowEx 2020 and 2021 campaigns. The retrieved SWE changes were compared against coincident in situ measurements (SNOTEL and snow pits from the SnowEx field campaign) and to 100 m gridded SnowModel modeled SWE changes. The comparison of in situ to retrieved shows a strong Pearson correlation (R = 0.80) and low RMSE (0.1 m, n = 64) for snow depth change and similar results for SWE change (RMSE = 0.04 m, R = 0.52, n = 57). The comparison between retrieved SWE changes to SnowModel SWE change also showed good correlation (R = 0.60, RMSD = 0.023 m, n = 3.2e6) and especially high correlation for a subset of pixels with no modeled melt and low tree coverage (R = 0.72, RMSD = 0.013 m, n = 6.5e4). Finally, we bin the retrievals for a variety of factors and show decreasing correlation between the modeled and retrieved values for lower elevations, higher incidence angles, higher tree percentages and heights, and greater cumulative melt. This study builds on previous interferometry work by using a full winter season time series of L-band SAR images over a large spatial extent to evaluate the accuracy of SWE change retrievals against both in situ and modeled results and the controlling factors of the retrieval accuracy.\textless/p\textgreater

@article{oyarbide_sperm_2023,
	title = {Sperm and northern bottlenose whale interactions with deep-water trawlers in the western {North} {Atlantic}},
	volume = {18},
	issn = {1932-6203},
	url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0289626},
	doi = {10.1371/journal.pone.0289626},
	abstract = {Commercial fisheries have increased in all the world’s oceans with diverse unintended impacts on marine ecosystems. As a result of resource overlap, interactions between cetaceans and fisheries are a common occurrence and, in many cases, can give rise to significant conservation issues. Research on the distribution and types of such interactions is important for efficient management. In this study, we describe the behaviors of two whale species: sperm whales (Physeter macrocephalus) and northern bottlenose whales (Hyperoodon ampullatus), interacting with benthic trawlers fishing off the eastern Grand Banks of the western North Atlantic in 2007. Whale interactions were only observed when vessels were targeting Greenland halibut (Reinhardtius hippoglossoides) in deep-water fishing areas and were most common during net hauling. Sperm whales and northern bottlenose whales appeared to engage in feeding behavior close to the surface during hauling, especially during the latter stages, suggesting they targeted fish escapees rather than discards. Using photo-identification methods, seven individual sperm whales were identified with multiple resights of six individuals being recorded over an almost two month period. The maximum distance between two resights was 234 km, suggesting individual sperm whales were repeatedly targeting and even following fishing vessels over multiple days and between fishing areas. By contrast, there were no photographic resights of individual northern bottlenose whales within this study, or with substantial photo-identification catalogues from other adjacent high density areas, suggesting that individuals of this species may be less likely to follow vessels or move between areas. This study documents the earliest confirmed records of northern bottlenose whales in this remote region. These interactions and high encounter rates may indicate that adjacent populations are recovering from the previous century of commercial whaling. Our study provides new insights and details on whale-fisheries interactions, which can inform future research and help managers understand the real and perceived impacts of depredation behaviour on fisheries and whales.},
	language = {en},
	number = {8},
	urldate = {2026-05-28},
	journal = {PLOS ONE},
	author = {Oyarbide, Usua and Feyrer, Laura Joan and Gordon, Jonathan},
	month = aug,
	year = {2023},
	note = {Publisher: Public Library of Science},
	keywords = {Bathymetry},
	pages = {e0289626},
}

Commercial fisheries have increased in all the world’s oceans with diverse unintended impacts on marine ecosystems. As a result of resource overlap, interactions between cetaceans and fisheries are a common occurrence and, in many cases, can give rise to significant conservation issues. Research on the distribution and types of such interactions is important for efficient management. In this study, we describe the behaviors of two whale species: sperm whales (Physeter macrocephalus) and northern bottlenose whales (Hyperoodon ampullatus), interacting with benthic trawlers fishing off the eastern Grand Banks of the western North Atlantic in 2007. Whale interactions were only observed when vessels were targeting Greenland halibut (Reinhardtius hippoglossoides) in deep-water fishing areas and were most common during net hauling. Sperm whales and northern bottlenose whales appeared to engage in feeding behavior close to the surface during hauling, especially during the latter stages, suggesting they targeted fish escapees rather than discards. Using photo-identification methods, seven individual sperm whales were identified with multiple resights of six individuals being recorded over an almost two month period. The maximum distance between two resights was 234 km, suggesting individual sperm whales were repeatedly targeting and even following fishing vessels over multiple days and between fishing areas. By contrast, there were no photographic resights of individual northern bottlenose whales within this study, or with substantial photo-identification catalogues from other adjacent high density areas, suggesting that individuals of this species may be less likely to follow vessels or move between areas. This study documents the earliest confirmed records of northern bottlenose whales in this remote region. These interactions and high encounter rates may indicate that adjacent populations are recovering from the previous century of commercial whaling. Our study provides new insights and details on whale-fisheries interactions, which can inform future research and help managers understand the real and perceived impacts of depredation behaviour on fisheries and whales.

@techreport{delphey_standing_2023,
	address = {Bloomington, MN, United States},
	title = {Standing {Analysis} and {Implementation} {Plan} - {Northern} {Long}-{Eared} {Bat} {Assisted} {Determination} {Key}},
	url = {https://www.fws.gov/media/standing-analysis-nleb-determination-key},
	language = {en},
	urldate = {2023-06-27},
	institution = {U.S. Fish and Wildlife Service},
	author = {Delphey, Phil},
	month = apr,
	year = {2023},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
	pages = {36},
}

@incollection{dumont_status_2023,
	title = {Status and {Management} of {Freshwater} and {Diadromous} {Fisheries} in {Québec}},
	isbn = {978-1-934874-70-7},
	shorttitle = {Freshwater {Fisheries} in {Canada}},
	url = {https://fisheries.org/doi/9781934874707-ch9},
	abstract = {With half a million lakes, 4,300 rivers, and one of the largest rivers in the world that connects with the Atlantic Ocean, the province of Québec has a unique geographic context that favors a diversity of aquatic habitats and thriving fish communities. By legislative delegation, the provincial government is responsible for the management of freshwater, anadromous, and catadromous species. Each year, 43 million fish are harvested by recreational anglers and about 400 tons by commercial fishers, so fisheries management and conservation must rely on robust monitoring networks, strong scientific studies, and constant collaborations with a diverse array of partners. The aim of this chapter is to present a portrait of Québec's fish community, the legislative framework, and the scientific background behind fisheries management and conservation in Québec. We present eight case studies highlighting the variety of challenges faced in fisheries management.},
	urldate = {2023-07-07},
	booktitle = {Freshwater {Fisheries} in {Canada}: {Historical} and {Contemporary} {Perspectives} on the {Resources} and {Their} {Management}},
	publisher = {American Fisheries Society},
	author = {Dumont, Pierre and Lecompte, Frédéric and Legault, Michel and Arvisais, Martin and Paradis, Yves and April, Julien and Verreault, Guy and Magnan, Pierre},
	year = {2023},
	doi = {10.47886/9781934874707.ch9},
	keywords = {Terrestrial Ecoregions (CEC 1997)},
}

With half a million lakes, 4,300 rivers, and one of the largest rivers in the world that connects with the Atlantic Ocean, the province of Québec has a unique geographic context that favors a diversity of aquatic habitats and thriving fish communities. By legislative delegation, the provincial government is responsible for the management of freshwater, anadromous, and catadromous species. Each year, 43 million fish are harvested by recreational anglers and about 400 tons by commercial fishers, so fisheries management and conservation must rely on robust monitoring networks, strong scientific studies, and constant collaborations with a diverse array of partners. The aim of this chapter is to present a portrait of Québec's fish community, the legislative framework, and the scientific background behind fisheries management and conservation in Québec. We present eight case studies highlighting the variety of challenges faced in fisheries management.

@article{lauriault_stocking_2023,
	title = {Stocking {Density} {Influences} {Predominantly} {Blue} {Grama} {Pasture} {Mass} and {Animal} {Performance}},
	volume = {2},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {2813-3463},
	url = {https://www.mdpi.com/2813-3463/2/3/12},
	doi = {10.3390/grasses2030012},
	abstract = {The optimum grazing management practices to sustain or increase grassland resilience must be determined. The effects of the current and previous year’s stocking densities (light, medium, and heavy stocking densities of 0.53, 0.89, and 1.24 AU ha−1, respectively) at the same stocking rate (35 AUD ha−1 yr−1) of yearling heifers (Bos taurus) grazing predominately blue grama [Bouteloua gracilis (Willd. ex Kunth) Lag. ex Griffiths] pastures on animal gains and pasture mass during the growing season were evaluated at New Mexico State University’s Rex E. Kirksey Agricultural Science Center at Tucumcari, NM USA, over three years. Previous grazing management had no influence on animal performance (p {\textgreater} 0.14) but seasonal average daily gains and total gains ha−1 were decreased from low- to high-density grazing (p {\textless} 0.002). Nevertheless, for grassland resilience, when low followed either high or medium, blue grama mass increased compared to low following low. Alternatively, when medium followed high, blue grama mass was reduced, but when high followed either low or medium, forage mass numerically increased (p {\textless} 0.0117 for the previous × current year’s stocking density interaction). Consequently, short-duration, high stocking density may be best using multiple pastures, each with the same grazing period each year to allow for a long-duration rest. Otherwise, during persistent drought, a longer-duration, medium stocking density could be used to allow for recovery.},
	language = {en},
	number = {3},
	urldate = {2023-07-26},
	journal = {Grasses},
	author = {Lauriault, Leonard M. and Scholljegerdes, Eric J. and Sawyer, Jason E.},
	month = sep,
	year = {2023},
	note = {Number: 3
Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {Climate Zones},
	pages = {142--155},
}

The optimum grazing management practices to sustain or increase grassland resilience must be determined. The effects of the current and previous year’s stocking densities (light, medium, and heavy stocking densities of 0.53, 0.89, and 1.24 AU ha−1, respectively) at the same stocking rate (35 AUD ha−1 yr−1) of yearling heifers (Bos taurus) grazing predominately blue grama [Bouteloua gracilis (Willd. ex Kunth) Lag. ex Griffiths] pastures on animal gains and pasture mass during the growing season were evaluated at New Mexico State University’s Rex E. Kirksey Agricultural Science Center at Tucumcari, NM USA, over three years. Previous grazing management had no influence on animal performance (p \textgreater 0.14) but seasonal average daily gains and total gains ha−1 were decreased from low- to high-density grazing (p \textless 0.002). Nevertheless, for grassland resilience, when low followed either high or medium, blue grama mass increased compared to low following low. Alternatively, when medium followed high, blue grama mass was reduced, but when high followed either low or medium, forage mass numerically increased (p \textless 0.0117 for the previous × current year’s stocking density interaction). Consequently, short-duration, high stocking density may be best using multiple pastures, each with the same grazing period each year to allow for a long-duration rest. Otherwise, during persistent drought, a longer-duration, medium stocking density could be used to allow for recovery.

@phdthesis{walker_summer_2023,
	title = {Summer spatial ecology of woodland caribou across northern {Ontario}},
	url = {https://era.library.ualberta.ca/items/51d3c670-2df6-414f-9195-aa28166689e6},
	abstract = {Caribou (Rangifer tarandus) numbers continue to decline across their circumpolar range with boreal woodland caribou (R. t. caribou;...},
	language = {en},
	urldate = {2024-01-09},
	author = {Walker, Philip},
	year = {2023},
	doi = {10.7939/r3-2r8s-cq77},
	keywords = {NALCMS},
}

Caribou (Rangifer tarandus) numbers continue to decline across their circumpolar range with boreal woodland caribou (R. t. caribou;...

@article{mulrooney_value_2023,
	title = {The value of natural capital in {Canada}’s national parks and national marine conservation areas},
	issn = {24112119, 0960233X},
	url = {https://parksjournal.com/wp-content/uploads/2023/12/10.2305-EKNN8645-Mulrooney.pdf},
	doi = {10.2305/EKNN8645},
	abstract = {Growing attention is being given to protected areas and the ability of their natural capital assets to provide a varied and long-term stream of benefits to individuals and society in general. These areas are often heralded for ensuring natural capital assets persist, but value is often limited to the economic impact of visitor expenditures and the associated effects on regional and national economies. Few studies have attempted to quantify the economic value of natural capital assets in protected areas, especially in Canada. This study uses a benefit transfer approach to produce an initial estimate of the potential economic value of ecosystem services and natural capital associated with the terrestrial and marine environments in Canada’s federal system of national parks and national marine conservation areas. The results suggest that the economic value of these assets ranges between CA\$ 156 billion and CA\$ 588 billion annually.},
	number = {29.2},
	urldate = {2024-05-15},
	journal = {PARKS},
	author = {Mulrooney, Dan and Jones, Brenda},
	month = nov,
	year = {2023},
	keywords = {NALCMS},
	pages = {41--51},
}

Growing attention is being given to protected areas and the ability of their natural capital assets to provide a varied and long-term stream of benefits to individuals and society in general. These areas are often heralded for ensuring natural capital assets persist, but value is often limited to the economic impact of visitor expenditures and the associated effects on regional and national economies. Few studies have attempted to quantify the economic value of natural capital assets in protected areas, especially in Canada. This study uses a benefit transfer approach to produce an initial estimate of the potential economic value of ecosystem services and natural capital associated with the terrestrial and marine environments in Canada’s federal system of national parks and national marine conservation areas. The results suggest that the economic value of these assets ranges between CA$ 156 billion and CA$ 588 billion annually.

@phdthesis{duran_vanegas_three_2023,
	type = {Thesis},
	title = {Three {Essays} in {Labor} and {Regional} {Economics}},
	url = {http://www.tara.tcd.ie/handle/2262/102495},
	abstract = {This dissertation consists of three chapters. Chapter 1 uses the 1994 North American
Free Trade Agreement (NAFTA) and granular data on Mexican municipalities to study
the local effects of trade liberalization on college wage premiums, housing costs, and
urban amenities between 1990 and 2010. I measure local exposure to international trade
by constructing a market access database of each municipality's lowest-cost route to the
closest US truck port. I find that municipalities facing larger trade exposure experienced:
(1) declines in local wage differences between college and non-college graduates, both in
nominal and real terms; (2) smaller increases in local urban amenities. I interpret these
results under the notion of spatial equilibrium in which non-monetary urban amenities
compensate for gaps in real wages across cities.

Chapter 2 analyzes the effects of the COVID-19 pandemic on labor market outcomes
for men and women in Mexico. Using a large longitudinal dataset and an event-study
design, I find that the labor market effects of the pandemic differed by gender and changed
considerably over time. While men temporarily suffered from a higher probability of
unemployment, women experienced greater and more persistent declines in labor force
participation. By exploring the heterogeneity of the effects across sub-samples, I show
that these disparities in the recovery of labor participation are mainly driven by increased
childcare needs and are linked to women being over-represented in informal and part-time
jobs.

Chapter 3 investigates how gender gaps vary across space and time using census microdata
for Mexico during 1990-2010. I document that female-to-male gaps in working hours
increased on average for all municipality sizes, but this increase was disproportionately
greater in smaller compared to larger municipalities. This novel empirical pattern also
coincides with a more rapid increase in the share of services in smaller locations that initially
specialized in producing goods (primary activities and manufacturing). Motivated
by these stylized facts, I quantify the impact of industry-specific labor demand shocks
on local gender gaps in working hours and explore the heterogeneity of the effects across municipality sizes. I find that labor demand shocks in the goods industry only affect
female relative work hours in small municipalities. My results suggest that the interaction
between industry specialization across locations, industry differences in female labor
intensities, and the rise of the service economy boosted female employment in smaller
cities.},
	language = {en},
	urldate = {2023-06-02},
	school = {Trinity College Dublin. School of Social Sciences \& Philosophy. Discipline of Economics},
	author = {Duran Vanegas, Juan David},
	year = {2023},
	note = {Accepted: 2023-04-18T16:24:22Z},
	keywords = {Major Roads},
}

This dissertation consists of three chapters. Chapter 1 uses the 1994 North American Free Trade Agreement (NAFTA) and granular data on Mexican municipalities to study the local effects of trade liberalization on college wage premiums, housing costs, and urban amenities between 1990 and 2010. I measure local exposure to international trade by constructing a market access database of each municipality's lowest-cost route to the closest US truck port. I find that municipalities facing larger trade exposure experienced: (1) declines in local wage differences between college and non-college graduates, both in nominal and real terms; (2) smaller increases in local urban amenities. I interpret these results under the notion of spatial equilibrium in which non-monetary urban amenities compensate for gaps in real wages across cities. Chapter 2 analyzes the effects of the COVID-19 pandemic on labor market outcomes for men and women in Mexico. Using a large longitudinal dataset and an event-study design, I find that the labor market effects of the pandemic differed by gender and changed considerably over time. While men temporarily suffered from a higher probability of unemployment, women experienced greater and more persistent declines in labor force participation. By exploring the heterogeneity of the effects across sub-samples, I show that these disparities in the recovery of labor participation are mainly driven by increased childcare needs and are linked to women being over-represented in informal and part-time jobs. Chapter 3 investigates how gender gaps vary across space and time using census microdata for Mexico during 1990-2010. I document that female-to-male gaps in working hours increased on average for all municipality sizes, but this increase was disproportionately greater in smaller compared to larger municipalities. This novel empirical pattern also coincides with a more rapid increase in the share of services in smaller locations that initially specialized in producing goods (primary activities and manufacturing). Motivated by these stylized facts, I quantify the impact of industry-specific labor demand shocks on local gender gaps in working hours and explore the heterogeneity of the effects across municipality sizes. I find that labor demand shocks in the goods industry only affect female relative work hours in small municipalities. My results suggest that the interaction between industry specialization across locations, industry differences in female labor intensities, and the rise of the service economy boosted female employment in smaller cities.

@phdthesis{jensen_top_2023,
	title = {Top {Down} {Effects} and {Resource} {Selection} by {Coyotes} in {South} {Carolina}},
	url = {https://tigerprints.clemson.edu/all_dissertations/3312},
	author = {Jensen, Alex},
	month = may,
	year = {2023},
	keywords = {Terrestrial Ecoregions (Griffith 2010)},
}

@article{larabi_towards_2023,
	title = {Towards reducing the high cost of parameter sensitivity analysis in hydrologic modeling: a regional parameter sensitivity analysis approach},
	volume = {27},
	issn = {1027-5606},
	shorttitle = {Towards reducing the high cost of parameter sensitivity analysis in hydrologic modeling},
	url = {https://hess.copernicus.org/articles/27/3241/2023/},
	doi = {10.5194/hess-27-3241-2023},
	abstract = {Land surface models have many parameters that have a spatially variable impact on model outputs. In applying these models, sensitivity analysis (SA) is sometimes performed as an initial step to select calibration parameters. As these models are applied to large domains, performing sensitivity analysis across the domain is computationally prohibitive. Here, using a Variable Infiltration Capacity model (VIC) deployment to a large domain as an example, we show that watershed classification based on climatic attributes and vegetation land cover helps to identify the spatial pattern of parameter sensitivity within the domain at a reduced cost. We evaluate the sensitivity of 44 VIC model parameters with regard to streamflow, evapotranspiration and snow water equivalent over 25 basins with a median size of 5078 km2. Basins are clustered based on their climatic and land cover attributes. Performance in transferring parameter sensitivity between basins of the same cluster is evaluated by the F1 score. Results show that two donor basins per cluster are sufficient to correctly identify sensitive parameters in a target basin, with F1 scores ranging between 0.66 (evapotranspiration) and 1 (snow water equivalent). While climatic attributes are sufficient to identify sensitive parameters for streamflow and evapotranspiration, including the vegetation class significantly improves skill in identifying sensitive parameters for the snow water equivalent. This work reveals that there is opportunity to leverage climate and land cover attributes to greatly increase the efficiency of parameter sensitivity analysis and facilitate more rapid deployment of land surface models over large spatial domains.},
	language = {English},
	number = {17},
	urldate = {2023-10-04},
	journal = {Hydrology and Earth System Sciences},
	author = {Larabi, Samah and Mai, Juliane and Schnorbus, Markus and Tolson, Bryan A. and Zwiers, Francis},
	month = sep,
	year = {2023},
	note = {Publisher: Copernicus GmbH},
	keywords = {NALCMS},
	pages = {3241--3263},
}

Land surface models have many parameters that have a spatially variable impact on model outputs. In applying these models, sensitivity analysis (SA) is sometimes performed as an initial step to select calibration parameters. As these models are applied to large domains, performing sensitivity analysis across the domain is computationally prohibitive. Here, using a Variable Infiltration Capacity model (VIC) deployment to a large domain as an example, we show that watershed classification based on climatic attributes and vegetation land cover helps to identify the spatial pattern of parameter sensitivity within the domain at a reduced cost. We evaluate the sensitivity of 44 VIC model parameters with regard to streamflow, evapotranspiration and snow water equivalent over 25 basins with a median size of 5078 km2. Basins are clustered based on their climatic and land cover attributes. Performance in transferring parameter sensitivity between basins of the same cluster is evaluated by the F1 score. Results show that two donor basins per cluster are sufficient to correctly identify sensitive parameters in a target basin, with F1 scores ranging between 0.66 (evapotranspiration) and 1 (snow water equivalent). While climatic attributes are sufficient to identify sensitive parameters for streamflow and evapotranspiration, including the vegetation class significantly improves skill in identifying sensitive parameters for the snow water equivalent. This work reveals that there is opportunity to leverage climate and land cover attributes to greatly increase the efficiency of parameter sensitivity analysis and facilitate more rapid deployment of land surface models over large spatial domains.

@article{wang_tree_2023,
	title = {Tree species growth response to climate warming varies by forest canopy position in boreal and temperate forests},
	volume = {n/a},
	copyright = {© 2023 The Authors. Global Change Biology published by John Wiley \& Sons Ltd.},
	issn = {1365-2486},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/gcb.16853},
	doi = {10.1111/gcb.16853},
	abstract = {Reports of forest sensitivity to climate change are based largely on the study of overstory trees, which contribute significantly to forest growth and wood supply. However, juveniles in the understory are also critical to predict future forest dynamics and demographics, but their sensitivity to climate remains less known. In this study, we applied boosted regression tree analysis to compare the sensitivity of understory and overstory trees for the 10 most common tree species in eastern North America using growth information from an unprecedented network of nearly 1.5 million tree records from 20,174 widely distributed, permanent sample plots across Canada and the United States. Fitted models were then used to project the near-term (2041–2070) growth for each canopy and tree species. We observed an overall positive effect of warming on tree growth for both canopies and most species, leading to an average of 7.8\%–12.2\% projected growth gains with climate change under RCP 4.5 and 8.5. The magnitude of these gains peaked in colder, northern areas for both canopies, while growth declines are projected for overstory trees in warmer, southern regions. Relative to overstory trees, understory tree growth was less positively affected by warming in northern regions, while displaying more positive responses in southern areas, likely driven by the buffering effect of the canopy from warming and climate extremes. Observed differences in climatic sensitivity between canopy positions underscore the importance of accounting for differential growth responses to climate between forest strata in future studies to improve ecological forecasts. Furthermore, latitudinal variation in the differential sensitivity of forest strata to climate reported here may help refine our comprehension of species range shift and changes in suitable habitat under climate change.},
	language = {en},
	number = {n/a},
	urldate = {2023-08-11},
	journal = {Global Change Biology},
	author = {Wang, Jiejie and D'Orangeville, Loïc and Taylor, Anthony R.},
	month = jul,
	year = {2023},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/gcb.16853},
	keywords = {Terrestrial Ecoregions (Wiken 2011)},
}

Reports of forest sensitivity to climate change are based largely on the study of overstory trees, which contribute significantly to forest growth and wood supply. However, juveniles in the understory are also critical to predict future forest dynamics and demographics, but their sensitivity to climate remains less known. In this study, we applied boosted regression tree analysis to compare the sensitivity of understory and overstory trees for the 10 most common tree species in eastern North America using growth information from an unprecedented network of nearly 1.5 million tree records from 20,174 widely distributed, permanent sample plots across Canada and the United States. Fitted models were then used to project the near-term (2041–2070) growth for each canopy and tree species. We observed an overall positive effect of warming on tree growth for both canopies and most species, leading to an average of 7.8%–12.2% projected growth gains with climate change under RCP 4.5 and 8.5. The magnitude of these gains peaked in colder, northern areas for both canopies, while growth declines are projected for overstory trees in warmer, southern regions. Relative to overstory trees, understory tree growth was less positively affected by warming in northern regions, while displaying more positive responses in southern areas, likely driven by the buffering effect of the canopy from warming and climate extremes. Observed differences in climatic sensitivity between canopy positions underscore the importance of accounting for differential growth responses to climate between forest strata in future studies to improve ecological forecasts. Furthermore, latitudinal variation in the differential sensitivity of forest strata to climate reported here may help refine our comprehension of species range shift and changes in suitable habitat under climate change.

@phdthesis{malesis_urban_2023,
	type = {Thesis},
	title = {Urban {Landscape} {Complexity} as a {Driver} of {Urban} {Evolution} in {White} {Clover} ({Trifolium} repens)},
	copyright = {none},
	url = {https://digital.lib.washington.edu:443/researchworks/handle/1773/50932},
	abstract = {Cities are influencing evolution on contemporary timescales, but the mechanisms driving evolutionary change are not well understood. Previous studies on urban eco-evolutionary dynamics generally assume that urban structures predictably evolve from a dense core to less intensive peripheries, discounting their spatial complexities. Cities are mosaics of patches, each governed by a unique set of parameters that interact to create a unique set of ecological conditions and stressors distributed unevenly across the landscape. Using an urban-rural transects approach, prior studies identified variance in Hydrogen Cyanide (HCN) production in Trifolium repens (white clover) contingent on the distance from city centers. This investigation introduces a refined approach via the urban complexity framework, incorporating measures of landscape heterogeneity, connectivity, and historical contingency to explicate variability in HCN production across 20 North American cities. A model selection approach was employed to comparatively evaluate the explanatory power of these predictors to distance from city center along an urban-rural transect in multi-city and single city models. The results reveal that multivariate models incorporating urban complexity variables, notably the connectivity of cropland, demonstrated higher adjusted R2 values than univariate distance-based models in multi-city contexts.  Although this finding does not significantly augment the predictive efficacy of single city models, it underscores the shared explanatory contribution of these variables. In conclusion, this investigation posits urban complexity as a critical determinant of urban eco-evolutionary dynamics, warranting further exploration to effectively inform the practice of urban planning.},
	language = {en\_US},
	urldate = {2024-01-09},
	author = {Malesis, Anna},
	year = {2023},
	note = {Accepted: 2023-09-27T17:22:19Z},
	keywords = {NALCMS, Terrestrial Ecoregions (CEC 1997)},
}

Cities are influencing evolution on contemporary timescales, but the mechanisms driving evolutionary change are not well understood. Previous studies on urban eco-evolutionary dynamics generally assume that urban structures predictably evolve from a dense core to less intensive peripheries, discounting their spatial complexities. Cities are mosaics of patches, each governed by a unique set of parameters that interact to create a unique set of ecological conditions and stressors distributed unevenly across the landscape. Using an urban-rural transects approach, prior studies identified variance in Hydrogen Cyanide (HCN) production in Trifolium repens (white clover) contingent on the distance from city centers. This investigation introduces a refined approach via the urban complexity framework, incorporating measures of landscape heterogeneity, connectivity, and historical contingency to explicate variability in HCN production across 20 North American cities. A model selection approach was employed to comparatively evaluate the explanatory power of these predictors to distance from city center along an urban-rural transect in multi-city and single city models. The results reveal that multivariate models incorporating urban complexity variables, notably the connectivity of cropland, demonstrated higher adjusted R2 values than univariate distance-based models in multi-city contexts. Although this finding does not significantly augment the predictive efficacy of single city models, it underscores the shared explanatory contribution of these variables. In conclusion, this investigation posits urban complexity as a critical determinant of urban eco-evolutionary dynamics, warranting further exploration to effectively inform the practice of urban planning.

@phdthesis{wagner_using_2023,
	type = {Master of {Science}, {Civil} and {Environmental} {Engineering}},
	title = {Using {Unpiloted} {Aerial} {Vehicle} {Structure} from {Motion} and {SnowModel} to {Map} {Spatial} {Distribution} of {Wind} {Deposited} {Snow} in {Mount} {Washington}, {NH} {Avalanche} {Terrain}},
	url = {https://unh.primo.exlibrisgroup.com/discovery/fulldisplay?context=PC&vid=01USNH_UNH:MAIN&search_scope=MyInst_and_CI&tab=Everything&docid=cdi_proquest_journals_2825660613},
	abstract = {East of the Rocky Mountains, United States avalanche terrain is almost exclusive to Mount Washington, New Hampshire. Mount Washington’s east-aspect glacial cirques are subject to frequent wind slab avalanche problems due to high winds and ample snowfall in fetch areas above the cirques. Quantification of these slabs’ location, extent, and depth is an integral part of avalanche forecasting and risk assessment. This research used SnowModel, a spatially distributed snow-evolution model, to simulate wind slab depth maps using Mount Washington Observatory meteorologic station data on a 1 m grid. SnowModel’s SnowTran-3D, a snow redistribution by wind algorithm, is tested for one of the first times in the Eastern United States. Snowpack seasonal evolution and accumulation event-based model performance is calibrated and validated using 15 snow depth maps collected throughout the winter of 2021-2022. Snow depth maps were constructed via Structure from Motion (SfM) analysis photogrammetry. SfM maps were derived from optical imagery collected using an Unpiloted Aerial Vehicle (UAV) and were able to quantify wind slab depth with a 5 cm spatial resolution. Limited ground validation showed UAV SfM values are accurate with a 30 cm RMSE on the 2/01/2022 sample date. Total snow depth and snow depth change map time series of each study location consistently show wind-transported snow accumulation and erosion patterns on Mount Washington. SnowModel can capture Mount Washington’s widespread snow redistribution trends but fails to quantify the magnitude and distribution of wind slabs as the UAV SfM can. SnowModel-derived snow depth was compared to Landsat 8’s Normalized Difference Snow Index (NDSI) and shows a significant signal in snow depth increase when NDSI exceeds 0.4. This study provides the first of its kind approach for capturing Mount Washington’s winter snowpack evolution using UAV SfM and a physically based snow evolution model.},
	language = {eng},
	urldate = {2023-08-11},
	school = {University of New Hampshire},
	author = {Wagner, Cameron},
	year = {2023},
	note = {Book Title: Using Unpiloted Aerial Vehicle Structure from Motion and SnowModel to Map Spatial Distribution of Wind Deposited Snow in Mount Washington, NH Avalanche Terrain
ISBN: 9798379712600},
	keywords = {NALCMS},
}

East of the Rocky Mountains, United States avalanche terrain is almost exclusive to Mount Washington, New Hampshire. Mount Washington’s east-aspect glacial cirques are subject to frequent wind slab avalanche problems due to high winds and ample snowfall in fetch areas above the cirques. Quantification of these slabs’ location, extent, and depth is an integral part of avalanche forecasting and risk assessment. This research used SnowModel, a spatially distributed snow-evolution model, to simulate wind slab depth maps using Mount Washington Observatory meteorologic station data on a 1 m grid. SnowModel’s SnowTran-3D, a snow redistribution by wind algorithm, is tested for one of the first times in the Eastern United States. Snowpack seasonal evolution and accumulation event-based model performance is calibrated and validated using 15 snow depth maps collected throughout the winter of 2021-2022. Snow depth maps were constructed via Structure from Motion (SfM) analysis photogrammetry. SfM maps were derived from optical imagery collected using an Unpiloted Aerial Vehicle (UAV) and were able to quantify wind slab depth with a 5 cm spatial resolution. Limited ground validation showed UAV SfM values are accurate with a 30 cm RMSE on the 2/01/2022 sample date. Total snow depth and snow depth change map time series of each study location consistently show wind-transported snow accumulation and erosion patterns on Mount Washington. SnowModel can capture Mount Washington’s widespread snow redistribution trends but fails to quantify the magnitude and distribution of wind slabs as the UAV SfM can. SnowModel-derived snow depth was compared to Landsat 8’s Normalized Difference Snow Index (NDSI) and shows a significant signal in snow depth increase when NDSI exceeds 0.4. This study provides the first of its kind approach for capturing Mount Washington’s winter snowpack evolution using UAV SfM and a physically based snow evolution model.

@phdthesis{pouw_utilizing_2023,
	title = {Utilizing {Ground}-{Penetrating} {Radar} to {Estimate} the {Spatial} {Distribution} of {Snow} {Depth} over {Lake} {Ice} in {Canada}’s {Sub}-{Arctic}},
	url = {https://scholars.wlu.ca/etd/2510},
	author = {Pouw, Alicia},
	month = jan,
	year = {2023},
	keywords = {NALCMS, Terrestrial Ecoregions},
}

@article{fernandes_validation_2023,
	title = {Validation of {Simplified} {Level} 2 {Prototype} {Processor} {Sentinel}-2 fraction of canopy cover, fraction of absorbed photosynthetically active radiation and leaf area index products over {North} {American} forests},
	volume = {293},
	issn = {00344257},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0034425723001517},
	doi = {10.1016/j.rse.2023.113600},
	language = {en},
	urldate = {2023-06-02},
	journal = {Remote Sensing of Environment},
	author = {Fernandes, Richard and Brown, Luke and Canisius, Francis and Dash, Jadu and He, Liming and Hong, Gang and Huang, Lucy and Le, Nhu Quynh and MacDougall, Camryn and Meier, Courtney and Darko, Patrick Osei and Shah, Hemit and Spafford, Lynsay and Sun, Lixin},
	month = aug,
	year = {2023},
	keywords = {NALCMS},
	pages = {113600},
}

@techreport{caldwell_wassi_2023,
	title = {{WaSSI} {Ecosystem} {Services} {Model}, ver. 1.2, {User} {Guide}},
	url = {https://www.fs.usda.gov/research/srs/understory/wassi-ecosystem-services-model-user-guide},
	language = {en},
	urldate = {2023-06-09},
	institution = {U.S. Department of Agriculture, Forest Service},
	author = {Caldwell, P. and Sun, G. and McNulty, S. and Myers, J.M. and Cohen, E. and Herring, R. and Martinez, E.},
	month = feb,
	year = {2023},
	keywords = {NALCMS},
}

@article{martlin_water-related_2023,
	title = {Water-related fatalities: {An} examination of body displacement and recovery patterns in {British} {Columbia}, {Canada}},
	volume = {n/a},
	copyright = {© 2023 American Academy of Forensic Sciences.},
	issn = {1556-4029},
	shorttitle = {Water-related fatalities},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/1556-4029.15395},
	doi = {10.1111/1556-4029.15395},
	abstract = {Early recovery of human bodies from the water requires an understanding of how a body acts in the water. However, there is currently a lack of baseline data surrounding body movement in British Columbian (B.C.) waters. This study aims to assist Canadian response agencies with understanding and predicting body movement in outdoor waterbodies in B.C. One hundred and eighty-six water-related fatalities in B.C. waters, including lakes, rivers, and the coastal Pacific Ocean, were examined to determine the recovery times and displacement patterns of submerged decedents. Cases between 2010 and 2021 were extracted from the Police Records Information Management Environment (PRIME-BC) for analysis. Most deaths were unintentional, followed by suicide and homicide, and most often occurred in rivers, followed by lakes and the ocean. Regardless of waterbody, the first day was the most successful recovery period, with decedents most often recovered close to the incident location. Nearly 16\% of individuals in this study were not recovered. Recovery success was greatest in lakes, followed by rivers and the ocean. Body displacement was the least in lakes, while rivers resulted in the furthest and most variable displacement. Low recovery success in the ocean is likely due to decedents being quickly displaced out of the search area, never to be found. The results of this study suggest that knowledge of body movement in outdoor aquatic environments remains incomplete. Further empirical research based on known data is necessary to continue improving prediction of body movement and increase early recovery success.},
	language = {en},
	number = {n/a},
	urldate = {2023-10-04},
	journal = {Journal of Forensic Sciences},
	author = {Martlin, Britny A. and Bell, Lynne S.},
	year = {2023},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/1556-4029.15395},
	keywords = {Political Boundaries},
}

Early recovery of human bodies from the water requires an understanding of how a body acts in the water. However, there is currently a lack of baseline data surrounding body movement in British Columbian (B.C.) waters. This study aims to assist Canadian response agencies with understanding and predicting body movement in outdoor waterbodies in B.C. One hundred and eighty-six water-related fatalities in B.C. waters, including lakes, rivers, and the coastal Pacific Ocean, were examined to determine the recovery times and displacement patterns of submerged decedents. Cases between 2010 and 2021 were extracted from the Police Records Information Management Environment (PRIME-BC) for analysis. Most deaths were unintentional, followed by suicide and homicide, and most often occurred in rivers, followed by lakes and the ocean. Regardless of waterbody, the first day was the most successful recovery period, with decedents most often recovered close to the incident location. Nearly 16% of individuals in this study were not recovered. Recovery success was greatest in lakes, followed by rivers and the ocean. Body displacement was the least in lakes, while rivers resulted in the furthest and most variable displacement. Low recovery success in the ocean is likely due to decedents being quickly displaced out of the search area, never to be found. The results of this study suggest that knowledge of body movement in outdoor aquatic environments remains incomplete. Further empirical research based on known data is necessary to continue improving prediction of body movement and increase early recovery success.