Type Shapefile
The North American Blue Carbon map shows the distribution of salt marsh, mangrove, and seagrass habitats in North America. Although this dataset represents the most comprehensive North American spatial distribution of blue carbon to date, many seagrass and salt marsh habitats have yet to be mapped.
The North American Blue Carbon map shows the distribution of salt marsh, mangrove, and seagrass habitats in North America.
Data were compiled from approximately 50 source datasets, including international (UNEP-WCMC), national (Conabio, US Geological Survey and the US National Wetlands Inventory), as well as state and provincial sources and information from individual investigators. This 2021 release represents the third update to the CEC’s mapping of blue carbon habitats, and was a priority within the Strengthening Adaptation Capacity in Marine Protected Areas project under the CEC’s 2019–2020 Operational Plan.
Although this release presents the most comprehensive picture of North American blue carbon spatial distribution at the time of publication, many seagrass and salt marsh habitats have yet to be mapped and efforts to do so are ongoing, with several pending updates underway.
Commission for Environmental Cooperation (CEC). 2021. “North American Environmental Atlas - Blue Carbon (Seagrass)”. Ed. 2.0, Vector digital data [1:10,000,000].
This material is licensed under CC BY 4.0, allowing non-exclusive rights to distribute, remix, adapt, and build upon the material in any medium or format, including for commercial purposes, so long as attribution is given to the creator.
| West | -180 | East | -50 |
| North | 85 | South | 14 |
| Maximum (zoomed in) | 1:5,000 |
| Minimum (zoomed out) | 1:150,000,000 |
The North American Blue Carbon map shows the distribution of salt marsh, mangrove, and seagrass habitats in North America. Data was compiled from approximately 50 source datasets, including international (UNEP-WCMC), national (Conabio, US Geological Survey and the US National Wetlands Inventory), as well as state and provincial sources and information from individual investigators. This 2021 release represents the third update to the CEC’s mapping of blue carbon habitats and was a priority within the Strengthening Adaptation Capacity in Marine Protected Areas project under the CEC’s 2019–2020 Operational Plan. Although this release presents the most comprehensive picture of North American blue carbon spatial distribution at the time of publication, many seagrass and salt marsh habitats have yet to be mapped and efforts to do so are ongoing, with several pending updates underway. Details on the sources are provided in the attached metadata documentation.
En este mapa se muestra la distribución de hábitats de marismas, manglares y lechos de pasto marino de América del Norte. Los datos con base en los cuales se elaboró se compilaron de alrededor de 50 conjuntos de datos de fuentes internacionales (como el Programa de las Naciones Unidas para el Medio Ambiente [PNUMA-CMCM]), nacionales (el Servicio Geológico de Estados Unidos [US Geological Survey], el Inventario Nacional de Humedales [National Wetlands Inventory] de Estados Unidos y la Comisión Nacional para el Conocimiento y Uso de la Biodiversidad [Conabio] de México) y estatales o provinciales, además de información aportada por investigadores a título individual. Esta versión correspondiente a 2021 constituye la tercera actualización a la cartografía de la Comisión para la Cooperación Ambiental (CCA) de hábitats que captan y almacenan carbono azul, y responde a una de las prioridades del proyecto Fortalecimiento de la capacidad adaptativa de áreas marinas protegidas, del Plan Operativo 2019-2020 de la misma CCA. Si bien el mapa actualizado representa la imagen más completa de la distribución espacial del carbono azul a escala regional lograda a la fecha, todavía quedan numerosos hábitats de lechos de pasto marino y marismas por cartografiarse, de manera que los esfuerzos para completar esta tarea siguen en marcha, y se prevén varias actualizaciones pendientes del material. Los detalles sobre las fuentes se proporcionan en la documentación sobre metadatos adjunta.
La carte du carbone bleu en Amérique du Nord illustre la répartition des habitats de marais salés, de mangroves et d’herbiers marins sur le continent nord-américain. Les données ont été compilées à partir d’une cinquantaine de sources internationales et nationales, dont le Programme des Nations Unies pour l’environnement (PNUE-CMSC), la Comisión Nacional para el Conocimiento y Uso de la Biodiversidad (Conabio, Commission nationale sur la connaissance et l’utilisation de la biodiversité), l’United States Geological Survey (USGS, Service géologique des États-Unis) et le National Wetlands Inventory (NWI, Inventaire national des zones humides) des États-Unis, ainsi qu’à partir de sources étatiques et provinciales, mais aussi grâce à des informations fournies individuellement par des chercheurs. Cette version de 2021, qui représente la troisième mise à jour des travaux de la CCE en matière de cartographie des habitats de carbone bleu, constituait une priorité du projet intitulé Renforcement de la capacité d’adaptation des aires marines protégées, entrepris dans le cadre du Plan opérationnel pour 2019 et 2020. Bien qu’au moment de sa publication cette version présente l’illustration la plus complète qui soit de la répartition spatiale du carbone bleu en Amérique du Nord, de nombreux habitats d’herbiers marins et de marais salés ne sont pas encore cartographiés. Des travaux à cette fin sont en cours, et plusieurs mises à jour sont en instance de publication. La documentation ci jointe sur les métadonnées donne de plus amples détails au sujet des sources de données susmentionnées."
The Commission for Environmental Cooperation (CEC) is an international organization created by Canada, Mexico, and the United States of America under the North American Agreement on Environmental Cooperation (NAAEC), which came into force at the same time as the North American Free Trade Agreement (NAFTA). The CEC was established to address regional environmental concerns, help prevent potential trade and environmental conflicts, and to promote the effective enforcement of environmental law. As of 2020, the CEC operates in accordance with the Environmental Cooperation Agreement, which entered into force at the same time as the CUSMA/T-MEC/USMCA trade agreement. This dataset was created as part of a collaborative effort between the Mexican Carbon Program that conducted an exhaustive search for data updates or new datasets available, as well as coordinate three national workshops with Blue Carbon experts from Canada, the United States and Mexico to retrieve feedback on the best practices to map Blue Carbon ecosystems across North America; and the Commission for Environmental Cooperation that conducted the review and evaluation of the datasets collected, as well as the map integration process and cartographic refinement. The goal of this dataset is to serve as a geospatial tool to estimate Blue Carbon Sink potential of North America in ecosystems such as Seagrasses, as well as provide a standardized and publicly available input dataset for various Carbon Budget analyses. The extent of Seagrasses in North America was estimated by combining datasets from different sources using different methods. These include global and national datasets that were generated from remote sensed imagery. The current dataset serves as an updated of the previously North American Seagrass distribution map published by the Commission for Environmental Cooperation in 2016. North America’s Blue Carbon: Assessing Seagrass, Salt Marsh and Mangrove Distribution and Carbon Sinks (http://www3.cec.org/islandora/en/item/11664-north-america-s-blue- carbon-assessing-seagrass-salt-marsh-and-mangrove-en.pdf) A more detailed description of all the datasets used, as well as the preprocess performed to extract Seagrasses information is available in the accompanying document “Blue Carbon Map sources data notes 2021.pdf” Information related to the Blue Carbon legacy maps produced by the Commission for Environmental Cooperation can be found in the following reports: 1) CEC. 2014. North America’s Blue Carbon: Assessing Seagrass, Salt Marsh and Mangrove Carbon Sinks A Final Report. Montreal, Canada: Commission for Environmental Cooperation. 219 pp 2) CEC. 2017. Blue Carbon Seagrass Mapping in Canada and The United States: British Columbia Washington and Oregon, Developing an Algorithm and Quantifying Eelgrass Extent A Final Report. Montreal, Canada: Commission for Environmental Cooperation. 82 pp This data set is available in several formats, including Shapefile, Map package, and a PDF Map, along with other files appropriate to particular format, such as .lyrx and .qlr files.
Commission for Environmental Cooperation (CEC). 2021. “North American Environmental Atlas - Blue Carbon (Seagrass)”. Ed. 2.0, Vector digital data [1:10,000,000].
This dataset includes seagrass distribution for all of North America
This material is licensed under CC BY 4.0, allowing non-exclusive rights to distribute, remix, adapt, and build upon the material in any medium or format, including for commercial purposes, so long as attribution is given to the creator.
This material is licensed under CC BY 4.0, allowing non-exclusive rights to distribute, remix, adapt, and build upon the material in any medium or format, including for commercial purposes, so long as attribution is given to the creator.
The international, national, and local dataset used in this analysis have known data gaps. In this dataset, the most up-to-update and spatially extended Seagrass datasets to our knowledge have been used. Future updates are envisioned as new data is available and new data providers offer spatial information over areas omitted in the current map.
Attributes and values were reviewed manually. No additional tests for attribute accuracy were performed on this data set.
No tests for logical consistency have been performed on this data set.
The North American Blue Carbon map shows the distribution of salt marsh, mangrove, and seagrass habitats in North America. Data were compiled from approximately 50 source datasets, including international (UNEP-WCMC), national (CONABIO, US Geological Survey and the US National Wetlands Inventory), as well as state and provincial sources and information from individual investigators. This 2021 release represents the third update to the CEC’s mapping of blue carbon habitats and was a priority within the Strengthening Adaptation Capacity in Marine Protected Areas project under the CEC’s 2019–2020 Operational Plan. Although this release presents the most comprehensive picture of North American blue carbon spatial distribution at the time of publication, many seagrass and salt marsh habitats have yet to be mapped and efforts to do so are ongoing, with several pending updates underway. The extent of Seagrasses in North America was estimated by combining datasets from different sources using different methods. These include global, national, and local datasets that were generated from ground surveys, and remote sensed imagery. The current dataset serves as an updated of the previously North American Seagrass distribution map published by the Commission for Environmental Cooperation in 2016. * Datasets used in the North American 2021 Seagrass Distribution Map. A more detailed description of all the datasets used, as well as the preprocess performed to extract Seagrass information is available in the accompanying document “Blue Carbon Map sources data notes 2021.pdf”
Preprocesses conducted with the Seagrasses datasets were performed between December 2020 and March 2021. NOTE: A more complete and detailed report of the North America 2021 Seagrass Distribution map is available in the accompanying report “NA Seagrass Cartographic Integration Process.pdf”
Global Distribution of Seagrasses A “selection by attributes process” was performed to isolate all seagrasses polygons corresponding to Canada, the United States and Mexico territories. All polygons located in the USA territories over the Pacific Ocean as well as Puerto Rico were deselected. A final seagrass layer was exported from the remaining polygons selection.
BC Howe Sound Eelgrass distribution The original data is available in a geodatabase that contains different polygon layers with seagrass distribution and a layer that merges all of them. The “Eelgrass_HoweSound_Merged” was selected and exported to a new polygons spatial layer.
British Columbia ShoreZone Observed Habitat Polygons This is an updated layer from the BC_ShoreZone dataset used in the CEC 2015 Blue Carbon map. The data was downloaded from the BC Geographic Warehouse Custom Download. By means of a selection by attributes, all polygons with SPECIES_NM equal to “Zostera marina” were exported to a final BC seagrasses layer.
East Canada Eelgrass Inventory Based on feedback from different experts (Brigitte Leblon, University of New Brunswick; Javier Guijarro-Sabaniel, Fisheries and Oceans Canada; Melanie Leblanc, McGill University) in relation the high uncertainty in the seagrasses distribution in James Bay derived from previous mapping efforts; all polygons in the region were removed from this dataset.
New Brunswick Eelgrass Distribution Classes corresponding to seagrass habitats were extracted from the field "CLASS NAME": Class1 "LOW", Class2 "MED", Class3 "DENSE".
St. Lawrence wetlands classification (seagrass) The layers used to generate the St. Lawrence seagrasses distribution were delivered by Environment and Climate Change Canada. The files were delivered in raster format, containing pixels of eelgrass distribution in 1991. Eelgrass data is only available in the area between Isle Verte and Trois Pistole. Base on feedback from Guy Letourneau from Environment and Climate Change Canada, data from “Map_13.tif” must be impose over “Map_14.tif”. 1. A mosaic to new raster process was performed to generate a single raster file for the region of interest. 2. Conversion from raster to vector polygons preserving pixel edges shape. 3. Values corresponding to “Fucus and Eelgrass == 14” and “Eelgrass == 15” were selected and exported to a new spatial layer. 4. A new attribute field describing g the year of origin of the data was added to the attribute table and filled with “1991”. A new attribute field describe the class name was added to the attribute table and filled with “14 == Fucus and Eelgrass” and “15 == Eelgrass”
Alaska and the Aleutians seagrass distribution Three input layers were merged into a new polygon spatial layer.
Washington coast seagrass distribution All polygons classified as different than “no_grass” class in the “generalized_eelgrass_poly” layer withing the source geoDataset were selected and exported to a new polygons spatial layer.
Washington ShoreZone seagrass distribution The polygons different than “absent” in the layer eelpoly.shp was exported to a new polygons spatial layer from the source geodatabase.
Seagrass distribution, Veracruz reef system Classes corresponding to seagrass habitats were extracted from the field "CLASE": Class 2 "low cover of seagrasses <30%"; Class 3 "medium cover of seagrasses 20-70%"; Class 4 "high cover of seagrass >70%". A new field “Coverage” was created to describe the percentage of seagrass coverages indicated by each value in the field “CLASE”.
Seagrass distribution, Veracruz reef system 2 Nine features contained in the geodatabase that describe seagrass distribution were merged and exported to a new spatial layer.
Distribution of seagrasses in eastern Yucatan Classes corresponding to seagrass habitats were extracted from the field "Clases": class 1 "Halodule wrightii"; Class2 "Mix of Thalassia testudinum and macroalgae", Class3 "Mix of seagrasses", Class4 "Mix of seagrasses and macroalgae", Class5 "Syringodium filiforme", Class6 "Thalassia testudinum". Polygons selection was exported to a new spatial layer.
Seagrass distribution, Dzilam, Yucatan As reported by the source, the file contains two grid codes describing “Sand == 1” and “Seagrass == 2”. Al polygons corresponding to grid code 2 were selected and exported to a new spatial layer.
Aquatic submerged vegetation, Yucatan Classes corresponding to seagrass habitats were extracted from the field "Habitat": class 1 "seagrass with sand"; Class2 "seagrass with macroalgae", Class3 "seagrass beds".
Aquatic submerged vegetation, Campeche Classes corresponding to seagrass habitats were extracted from the field "Habitat": Class 1 "Mix of Thalassia testudinum and macroalgae"; Class 2 "Mix of seagrasses", Class 3 "Mis of seagrasses and macroalgae".
Laguna de Términos seagrasses distribution Classes corresponding to seagrass habitats were extracted from the field "CLASE", this filed is linked to seagrasses species and percentage of seagrass coverage in the attribute table.
Los Petenes, Campeche, seagrasses distribution Classes corresponding to seagrass habitats were extracted from the field "CLASE", this filed is linked to seagrasses species and percentage of seagrass coverage in the attribute table.
Bahía Ascención, QRoo, seagrasses distribution Classes corresponding to seagrass habitats were extracted from the field "CLASE": Class1 "TT", Class2 "HW", Class3 "HW-TT", Class 4 and 5 "Algas and TT".
Catoche-Xcalak seagrasses distribution All polygons classified as sea grasses (“Comunidad de Pastos Marinos”) within Name of coverage (“Nom_Cob”) field where selected and exported to a new spatial polygons layer.
Cartographic Integration Process: As some of the datasets show spatial overlaps, some criteria were defined to deal with overlapping polygons from different data sources and keep as much spatial information as possible. In order to define the criteria to prioritize sources datasets on areas where information overlaps, the Mexican Carbon Program conducted a series of three national workshops with experts from Canada, the United States and Mexico. Experts were asked to rank the sources datasets features that should be considered when selecting the sources of information that must prevail over areas with overlapping polygons. Six quality features were evaluated by the experts, comprising: > Most updated datasets > Fine spatial resolution over coarse spatial resolution > Datasets reporting accuracy > National or regional datasets over global datasets > Independent research studies over institutional datasets > Most complete metadata A group of eleven experts participated in a survey to rank the criteria ---------------------------------------------------------------------------- Name -- Institution -- Email Nate Herold -- NOAA -- nate.herold@noaa.gov Margot Hessing-Lewis -- Hakai Institute -- margot@hakai.org Gail Chmura -- McGill University -- gail.chmura@mcgill.ca Dan Mulrooney -- Parks Canada -- dan.mulrooney@canada.ca Anna Hilting -- NOAA -- anna.hilting@noaa.gov Ma. Teresa Rodríguez -- CONABIO -- mrodrig@conabio.gob.mx Joanna Acosta Velázquez -- Aura Manglares y costas -- joanna.acosta@gmail.com Iliana Pérez Espinosa -- CONABIO -- iperez@conabio.gob.mx Carlos Troche -- CONABIO -- ctroche@conabio.gob.mx Beatriz Corral Osuna -- INECC -- beatriz.corral@gmail.com Zulia Sánchez Mejía -- ITSON -- zulia.sanchez@itson.edu ---------------------------------------------------------------------------- As a result of the experts-defined criteria and the characteristics of the information provided by each source dataset, a set of case-by-case decisions were made on areas with overlapping conflicts. Individual dataset analysis and spatial prioritization decisions were conducted as follows. >Alaska and the Aleutians seagrass distribution This layer was prioritized in the Alaska region, although the WCMC dataset is newer, the year reported in seagrasses polygons over Alaska and the Aleutians is more recent in this dataset. WCMC polygons refer to 1997 while polygons in this dataset refer to 2002-2008. >BC Howe Sound Eelgrass distribution This layer was preserved in its original shape, this dataset was prioritized over the WCMC seagrass distribution map, as this dataset shows higher spatial detail and is derived from a local field survey. >British Columbia ShoreZone Observed Habitat Polygons This layer was prioritized, although the WCMC dataset is newer, the year reported in seagrasses polygons over British Columbia that intersect this dataset are older in the WCCM dataset. WCMC polygons refer to 2009 while polygon features in British Columbia ShoreZone Observed Habitat Polygons refer to 2011. Furthermore, this dataset has mapped seagrass polygons over areas where WCVM dataset do not show any seagrass distribution. > Washington ShoreZone seagrass distribution Polygons in this layer that overlap Washington coast seagrass distribution dataset were removed, as the second one refers to more recent data and its metadata is better documented than Washington ShoreZone seagrass distribution. > Washington coast seagrass distribution No changes were made to this layer, it preserves all its original polygon features. > San Francisco Bay seagrass distribution No changes were made to this layer, it preserves all its original polygon features, there is no spatial overlap with any other layer. >Isla de Todos los Santos seagrass distribution No changes were made to this layer, it preserves all its original polygon features, there is no spatial overlap with any other layer. >Catoche-Xcalak seagrasses distribution Feature polygons in this layer that overlap Bahía Ascensión, QRoo, seagrasses distribution layer were removed, as the second layer shows more consistency and better documentation for the local area of Bahía Ascensión in the coast of Quintana Roo. Remaining polygon features were exported to a new spatial layer. >Bahía Ascención, QRoo, seagrasses distribution No changes were made to this layer, it preserves all its original polygon features. >Yalahau-Holbox seagrass distribution Feature polygons overlapping Catoche-Xcalak seagrasses distribution layer were removed and the remain polygons were exported to a new spatial layer. >Nichupte Lagoon seagrass distribution No changes were made to this layer, it preserves all its original polygon features, there is no spatial overlap with any other layer. >Seagrass distribution, Veracruz reef system No changes were made to this layer, it preserves all its original polygon features, there is no spatial overlap with any other layer. >Seagrass distribution, Veracruz reef system 2 No changes were made to this layer, it preserves all its original polygon features. >Chelem seagrass distribution No changes were made to this layer, it preserves all its original polygon features, there is no spatial overlap with any other layer. >Seagrass distribution, Dzilam, Yucatan Polygons in this layer that overlap the Distribution of seagrasses in eastern Yucatan layer are removed to prioritize spatial consistency in the second layer that covers a larger area than the Seagrass distribution, Dzilam, Yucatan dataset. This layer covers the same area as the as Seagrass distribution, Dzilam, Yucatán 2 and the mapping methodology is similar, but Seagrass distribution, Dzilam, Yucatan layer reports higher accuracy (89%) than Seagrass distribution, Dzilam, Yucatán 2 (81%). > Aquatic submerged vegetation, Yucatan A small area that overlaps the Distribution of seagrasses in eastern Yucatan layer was erased from this dataset. Both layers come from the same source institution buy Distribution of seagrasses in eastern Yucatan layer was prioritized as this represent data from a more recent year (2018 and 2020 respectively). > Distribution of seagrasses in eastern Yucatan No changes were made to this layer, it preserves all its original polygon features. >Laguna de Términos seagrasses distribution No changes were made to this layer, it preserves all its original polygon features, there is no spatial overlap with any other layer. >Los Petenes, Campeche, seagrasses distribution No changes were made to this layer, it preserves all its original polygon features. >Aquatic submerged vegetation, Campeche Feature polygons overlapping the Los Petenes, Campeche, seagrasses distribution layer ere were removed, remaining polygons were sported to a new spatial layer. Los Petenes, Campeche, seagrasses distribution layer was prioritized over Aquatic submerged vegetation, Campeche, as the first one refers to a more recent year and also reports accuracy. > Texas Christmas Bay seagrass distribution No changes were made to this layer, it preserves all its original polygon features, there is no spatial overlap with any other layer. Density of Eelgrass in the USA Northeast Atlantic No changes were made to this layer, it preserves all its original polygon features, and it is prioritized over the WCMC global seagrass distribution map, as data from Density of Eelgrass in the USA Northeast Atlantic is more recent. >St. Lawrence wetlands classification (seagrass) No changes were made to this layer, it preserves all its original polygon features, there is no spatial overlap with any other layer. >New Brunswick Eelgrass Distribution No changes were made to this layer, it preserves all its original polygon features, there is no spatial overlap with any other layer. > East Canada Eelgrass Inventory No changes were made to this layer, it preserves all its original polygon features, there is no spatial overlap with any other layer. > Global Distribution of Seagrasses a) Polygons in this layer that intersect other polygons from Alaska and the Aleutians seagrass distribution were removed and the remaining polygon features were exported to a temporary spatial layer. b) Polygons in the previous temporary layer that intersect other polygons from BC Howe Sound Eelgrass distribution were removed and the remaining polygon features were exported to a new temporary spatial layer. c) All polygon features in Washington state were removed as they are already mapped by the other two state-level layers for the same region. Remaining polygon features were exported to a new temporary spatial layer. d) Areas over Quintana Roo state that overlap the already processed layers in the region were erased. Thus, prioritizing regional or local datasets offer much higher spatial detail, while the WCMC polygons are much more generalized in the Yucatan peninsula region. A new temporary layer was generated with the resulting polygons after the spatial erase process. e) Polygons mapped along the coast of Veracruz were removed as they do not report any feature name and those polygons area already mapped in much more detail in the Seagrass distribution, Veracruz reef system 2 dataset. f) Areas over the entire Yucatan Peninsula that overlap the already processed layers in the region were erased. Thus, prioritizing regional or local datasets offer much higher spatial detail, while the WCMC polygons are much more generalized in the. A new temporary layer was generated with the resulting polygons after the spatial erase process. g) Feature polygons that overlap seagrass polygons in the Density of Eelgrass in the USA Northeast Atlantic layer were removed. Remaining polygon features were exported to a new temporary spatial layer. h) Merge of all preprocessed spatial layers.
Step 01 All the preprocessed spatial layers were merged into a final North America Seagrass map. > Alaska_seagrass_distribution_laea_final.shp > BahiaAscensionQRoo_seagrasses_laea_final.shp > BC_HoweSound_seagrasses_laea_final.shp > BC_ShoreZone_seagrasses_laea_final.shp > Campeche_seagrasses_laea_final.shp > Catoche_Xcalak_seagrasses_laea_final.shp > Chelem_seagrasses_laea_final.shp > DzilamYuc_seagrasses_laea_final.shp > EastCanada_eelgrass_inventory_laea_final.shp > EastYucatan_seagrasses_laea_final.shp > LagTerminos_seagrasses_laea_final.shp > LosPetenes_seagrasses_laea_final.shp > Nichupte_seagrasses_laea_final.shp > NortheastAtlantic_eelgrass_density_laea_final.shp > SFbay_seagrass_distribution_laea_final.shp > StLawrence_seagrasses_laea_final.shp > Tabusintac_NB_eelgrass_distribution_final.shp > TodosSantos_seagrasses_laea_final.shp > TX_ChristmasBay_seagrasses_laea_final.shp > VeracruzReef_seagrasses_laea_final.shp > VeracruzReef2_seagrasses_laea_input.shp > Washington_coast_seagrasses_laea_final.shp > Washington_ShoreZone_seagrass_distribution_laea_final.shp > WCMC_NorthAmerica_seagrasses_polygon_laea_final.shp > Yalahau-Holbox_seagrasses_laea_final.shp > Yucatan_seagrasses_laea_final.shp Output = NorthAmerica_seagrasses_layers_merge.shp Step 02 All records in the attribute table fields were standardized, different feature names with different codes or abbreviations to indicate species or seagrass distribution characteristics were homogenized in a standard code names, common names were included in most of the records, accompanying the scientific name descriptions when available. Step 03 A “Dissolve” process was applied to the output layer from the previous step. All individual polygons that are spatially connected and share the same values across the thirteen common attributed fields (except area) will break down into new polygons. This way, the number of polygons and the size of the final spatial layer file is reduced. No multipart features creation is allowed in this step. Output = NorthAmerica_seagrasses_polygons_dissolve.shp Step 04 A new field “AREA_SQMT” is created and the area in squared meters is calculated for this field. The area is calculated based on the map coordinate reference system, 1 decimal point and thousands separated by comas are defined. As a final clean up step, all polygons reported areas smaller than 1 m2 were removed. Step 05 After a final check of attribute table consistency and data display on different GIS platforms, a spatial data file in ESRI “shp” format is generated to provide the final CEC North America seagrasses distribution map.
"This dataset shows the global distribution of seagrasses and is composed of two subsets of point and polygon occurrence data. The data were compiled by UN Environment World Conservation Monitoring Centre in collaboration with many collaborators (e.g. Frederick Short of the University of New Hampshire), organisations (e.g. OSPAR), and projects (e.g. the European project Mediterranean Sensitive Habitats “Mediseh”), across the globe (full list available in accompanying metadata table within the dataset). > Preprocessing The original data set was acquired from the World Conservation Monitoring Centre (WCMC) that integrates two vector layers: polygons and points. A “selection by attributes process” was performed to isolate all seagrasses polygons corresponding to Canada, the United States and Mexico territories. All polygons located in the USA territories over the Pacific Ocean as well as Puerto Rico were deselected. A final seagrass layer was exported from the remaining polygons selection."
Citation: Citation: UNEP-WCMC, Short, F.T. (2020). Global distribution of seagrasses (version 7.0). Seventh update to the data layer used in Green and Short (2003). Cambridge (UK): UN Environment World Conservation Monitoring Centre. http://data.unep-wcmc.org/datasets/7 Source metadata: https://data.unep-wcmc.org/pdfs/7/WCMC_013_014_Global_Distribution_of_Seagrasses.pdf?1617122071
Global
The Howe Sound/Atl’ka7tsem Marine Reference Guide is a collaborative and community-led initiative whose goal is to build capacity to protect the human and natural values associated with Howe Sound/Atl’ka7tsem’s marine environment in the face of growing anthropogenic pressures. Atl’ka7tsem is the Squamish Nation place name for this region, which sits within their traditional and unceded territory. The Guide is a project on Tides Canada’s shared platform. To achieve its objective, the Guide is creating decision-support tools that effectively arm local decision-makers and community groups with robust data and holistic information about the region’s marine realm. One such tool is an online interactive map and database that will include hundreds of data layers about the Sound’s marine ecology, human activities, and vulnerability to anthropogenic pressures such as climate change. This map will visualize areas of multi-use and potential conflict, and provide valuable baseline data at a regional scale. In July 2019, staff from the Guide co-presented with Moonstone Enterprises to the Town of Gibsons’ mayor and council about the status of eelgrass restoration and monitoring in the Sound, and announced that the Guide would survey the Sound’s mainland eelgrass in the fall of 2019. Given the interest of the Town of Gibsons in updating their foreshore eelgrass distribution maps, which had previously been surveyed in 2004 and 2013 by Dianne Sanford, sole proprietor of Moonstone Enterprises, councilors requested that the Guide survey the Town’s recreational water lease using the same methodology. These data will support the Town’s capacity to protect critical nearshore ecosystems in the face of growing pressures facing this region. > Preprocessing The original data is available in a geodatabase that contains different polygon layers with seagrass distribution and a layer that merges all of them. The “Eelgrass_HoweSound_Merged” was selected and exported to a new polygons spatial layer.
Citation:Beaty, Fiona & Sanford, Dianne (2019). Town of Gibsons and Howe Sound/Atl’ka7tsem Eelgrass Survey Report. Howe Sound/Atl’ka7tsem Marine Reference Guide & Moonstone Enterprises Interpretation and Consulting, Canada Year of Origin: 2012 - 2018 Dataset provided by Matt Christensen, University of British Columbia (mattch85@gmail.com) Source metadata: https://howesoundguide.ca/wp-content/uploads/2020/02/Eelgrass-survey-report_MRG_final.pdf
Contact Person: Matt Christensen (University of British Columbia)
Regional
The Observed Habitat Polygons show the various types of particular habitat that have been observed or calculated by biologists as well as an expectation of different species found in the habitats. Each bioarea has several observed habitats, and it is the combination of the bioarea and habitat observed number that identifies each unique observed habitat. This dataset was formally a depiction of the SHZN_HAB_OBS_POLYS_SVW warehouse layer. > Preprocessing This is an updated layer from the BC_ShoreZone 2014 dataset used in the CEC 2015 Blue Carbon Map. The data was downloaded from the BC Geographic Warehouse Custom Download. By means of a selection by attributes, all polygons with SPECIES_NM equal to “Zostera marina” were exported to a final BC saltmarshes layer.
Citation: BC FLNRORD (2018). British Columbia ShoreZone Observed Habitat Polygons, BC Ministry of Forests, Lands, Natural Resource Operations and Rural Development – GeoBC, Victoria, BC, Canada. Source metadata: https://catalogue.data.gov.bc.ca/dataset/shorezone-observed-habitat-polygons/resource/787b45c7-4340-4c28-ba2c-051c78cfb5eb
Regional
The layer presents the information on the distribution of eelgrass (Zostera marina) beds in James Bay, Chaleur Bay, Estuary and Gulf of St. Lawrence according to a literature review of documents produced between 1987 and 2009. > Preprocessing Based on feedback from different experts (Brigitte Leblon, University of New Brunswick; Javier Guijarro-Sabaniel, Fisheries and Oceans Canada; Melanie Leblanc, McGill University) in relation the high uncertainty in the seagrasses distribution in James Bay derived from previous mapping efforts; all polygons in the region were removed from this dataset.
Year of Origin: 1987 - 2009 Dataset provided by Matt Christensen, University of British Columbia (mattch85@gmail.com)
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"This layer comprises results obtained by Mélanie-Louise Leblanc PhD research. ""Connections Between Eelgrass, Geese, and Cree Harvest and Culture in Eastern James Bay"". Methodology: produced from Landsat 8 + ground truth data - the extent of eelgrass meadows in the estuary. > Preprocessing Classes corresponding to seagrass habitats were extracted from the field ""CLASS NAME"": Class1 ""LOW"", Class2 ""MED"", Class3 ""DENSE""."
Citation: Leblanc, Melanie-Louise, Armand LaRocque, Brigitte Leblon, Al Hanson & Murray M. Humphries (2021). Using Landsat Time-Series to Monitor and Inform Seagrass Dynamics: A Case Study in the Tabusintac Estuary, New Brunswick, Canada, Canadian Journal of Remote Sensing, DOI: 10.1080/07038992.2021.1893672 Dataset provided by Melanie Leblanc, McGill University (leblanc.melanie.louise@gmail.com) Source metadata: https://www.tandfonline.com/doi/full/10.1080/07038992.2021.1893672
Contact Person: Melanie Leblanc
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The Saint-Lawrence Wetlands Mapping Project is a multi-year project that mapped portions of shores of the St-Lawrence River. The 64 land use categories, including wetland classes were mapped using remote-sensed imagery from 1990/1991, 1996/97, 2000, and 2002. The data and associated reports are published by Environment Canada's Saint-Lawrence Centre. > Preprocessing The layers used to generate the St. Lawrence seagrasses distribution were delivered by Environment and Climate Change Canada. The files were delivered in raster format, containing pixels of eelgrass distribution in 1991. Eelgrass data is only available in the area between Isle Verte and Trois Pistole. Based on feedback from Guy Letourneau (Environment and Climate Change Canada), data from “Map_13.tif” must be impose over “Map_14.tif”. 1. A mosaic to new raster process was performed to generate a single raster file for the region of interest. 2. Conversion from raster to vector polygons preserving pixel edges shape. 3. Values corresponding to “Fucus and Eelgrass == 14” and “Eelgrass == 15” were selected and exported to a new spatial layer. 4. A new attribute field describing the year of origin of the data was added to the attribute table and filled with “1991”. A new attribute field describe the class name was added
Citation: Létourneau, G and M. Jean (1996). Cartographie des marais, marécages et herbiers aquatiques le long du Saint-Laurent par télédétection aéroportée. Environnement Canada - Région du Québec, Conservation de l’environnement, Centre Saint-Laurent. Rapport scientifique et technique ST-61, 114 pages. ISBN 0-662-81544-0 (French only) Dataset provided by Guy Letourneau, Environment Canada (guy.letourneau@canada.ca)
Contact Person: Guy Letourneau
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The creation of this dataset was a collaborative effort between the U.S. Geological Survey and the U.S. Fish and Wildlife Service. The dataset serves as baseline information for the spatial extent and distribution of eelgrass (Zostera marina) in waters adjacent to the Togiak National Wildlife Refuge enabling a monitoring program for this important coastal habitat. These data were derived from satellite imagery (Ikonos-2 and Quickbird-2) acquired in June/August 2002 – 2008. After conversion of the raw data from digital number to at sensor radiance and atmospheric correction using dark pixel subtraction, the imagery was classified into the land cover categories of eelgrass, bare substrate, and water. The eelgrass distribution data was then extracted from the raster grid and converted to vector data. The spatial data was obtained as unpublished shape files for parts of the Alaskan coastline. From David Ward, United States Geological Survey, Anchorage, Alaska. > Preprocessing Three input layers were merged into a new polygon spatial layer.
Dataset provided by Frederick T. Short (fredtshort@gmail.com), from David Ward, U.S. Geological Survey
Contact Person: Frederick Short
Contact Person: David Ward
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The Submerged Vegetation Monitoring Program (SVMP) has conducted annual monitoring of the status and trends of native seagrass in greater Puget Sound since 2000. The native seagrasses monitored include the dominant eelgrass (Zostera marina) as well as the less abundant surfgrass (Phyllospadix scouleri and P. serrulatus). This geoDataset is the central component of the 2000-2019 Puget Sound eelgrass monitoring dataset. This dataset is produced by the Submerged Vegetation Monitoring Program (SVMP) within the Washington Department of Natural Resources. Polygons represent general area where eelgrass has been recorded over the 2000-2017 monitoring period at each site sampled. The polygon for each site is based on the individual polygons used for surveying each year. > Preprocessing All polygons classified as different than “no_grass” class in the “generalized_eelgrass_poly” layer withing the source geodatabase were selected and exported to a new polygons spatial layer.
Citation: Citation: WA-DNR, (2020). Submerged Vegetation Monitoring Program 2000-2019 Database, Washington Department of Natural Resources, Aquatic Resources Division, Olympia, WA, USA. Year of Origin: 2000 - 2019 Source metadata: https://fortress.wa.gov/dnr/adminsa/gisdata/datadownload/SVMP_distribution.zip
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The Washington State ShoreZone Inventory is a statewide inventory of shoreline habitat. The ShoreZone Inventory describes the physical and biological characteristics of intertidal and shallow subtidal areas. It can be used to better understand and manage Washington’s coastal ecosystem. It was completed by the Nearshore Habitat Program in the Washington State Department of Natural Resources (DNR), Aquatic Resources Division (AQR). > Preprocessing The polygons different than “absent” in the layer eelpoly.shp was exported to a new polygons spatial layer from the source geodatabase.
Source metadata: https://geo.wa.gov/datasets/wadnr::shorezone-inventory-seagrass?geometry=- 129.287%2C46.339%2C-117.641%2C48.929
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The purpose of mapping the distribution of eelgrass (Submerged Aquatic Vegetation - SAV) is to determine areas where eelgrass is present throughout coastal New England waters in order to support coastal and ocean planning. For the dataset ""Wetlands"" represents the extent and approximate location of coastal wetlands in the northeastern United States. The data presented was exclusively derived from the National Wetlands Inventory (NWI). The classification system used by the NWI was assessed by wetland specialists and classes were selected to specifically represent coastal wetlands. Coastal wetlands were defined as vegetated wetlands in saline or brackish waters that were not permanently flooded, or not in open water. The NWI classes that applied to this definition included: A) Estuarine intertidal emergent, B) Estuarine intertidal scrub- shrub, C) Estuarine intertidal forested, D) Estuarine intertidal unconsolidated shore with organic soil types that were irregularly flooded. > Preprocessing No preprocessing was needed for this dataset.
Citation: Longley, K. (2014). Eelgrass Beds, Northeast United States, SeaPlan, Boston, MA, USA. Source metadata: https://www.northeastoceandata.org/files/metadata/Themes/Restoration/EelgrassBeds.pdf
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San Francisco baywide eelgrass layer with density attributes developed from data collected in October and November of 2009. Data were developed for the California Department of Transportation and the National Marine Fisheries Service”, “Use Constrains: These data are considered to be draft-final and are subject to further revision by the authors. Data are for planning and regional management purposes only. Data have a higher degree of error expectation than would be anticipated from a survey of a smaller survey area. and shall not be used for project specific applications, nor shall they replace site specific investigations or data. > Preprocessing No preprocessing was needed for this dataset.
Citation: Draft San Francisco Bay Eelgrass Atlas (October - November 2009). Prepared for California Department of Transportation and National Marine Fisheries Service. Dataset provided by Frederick T. Short (fredtshort@gmail.com) Source metadata: https://www.dropbox.com/s/9jp9bzg19ta902u/2009_sfbay_eelgrass_metadata.htm?dl=0
Contact Person: Frederick Short
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Areas in West Galveston Bay and Christmas Bay where seagrass is present. Aerial photo interpretation and groundtruthing by Texas Parks and Wildlife Department Coastal Fisheries Division Habitat Assessment Team. The area was ground truthed for the presence of seagrass in March 2015. Polygons of areas where seagrass is present were digitized in April 2015 through photointerpretation. The underlying imagery used was flown on January 16, 2015. > Preprocessing No preprocessing was needed for this dataset.
Source metadata: https://tpwd.maps.arcgis.com/apps/webappviewer/index.html?id=af7ff35381144b97b38fe553f2e7b56
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The seagrass distribution was carried out with field and satellite information (wordview-2) using spectral algorithms (maximum likelihood) and manual editing. The accuracy of the map was 77%. > Preprocessing Classes corresponding to seagrass habitats were extracted from the field ""CLASE"": Class 2 ""low cover of seagrasses <30%""; Class 3 ""medium cover of seagrasses 20-70%""; Class 4 ""high cover of seagrass >70%".
Citation: Mendoza-Martínez J. E; Herrera-Silveira J.A. Morales-Ojeda S.M; Ramírez-Ramírez J. 2019. Almacenes de carbono en biomasa de pastos marinos de una laguna arrecifal y su relación con variables ambientales. en: Paz, F., A. Velázquez y M. Rojo (Editores). 2019. Estado Actual del Conocimiento del Ciclo del Carbono y sus Interacciones en México: Síntesis a 2019. Serie Síntesis Nacionales. Programa Mexicano del Carbono en colaboración con el Centro Nayarita de Innovación y Transferencia de Tecnología, Universidad Autónoma de Nayarit, Consejo de Ciencia y Tecnología del Estado de Nayarit y Stanford University-México Economía Limpia 2050-USAID. Texcoco, Estado de México, México. 544 p. Dataset provided by Juan Mendoza, CINVESTAV (juan.mendoza@cinvestav.mx) Source metadata: http://pmcarbono.org/pmc/publicaciones/count.php?file=EACCIM_Sintesis_Nacional_2019
Contact Person: Juan Mendoza Martínez
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A classification of the reef bottom was carried out on a WordView2 image with 2m resolution. The classification method was Maximum Likelihood by means of supervised classification and feedback with field data. The global accuracy of the seagrass maps of 9 reef lagoons was 92%. > Preprocessing Nine features contained in the geodatabase that describe seagrass distribution were merged and exported to a new spatial layer.
Citation: Herrera-Silveira, J.A., Mendoza-Martínez. J.E., Morales-Ojeda S.M., Iturria-Dawn R., Ramírez-Ramírez J., Osorio-Moreno, I., García T. A., Ramírez, S., Pech, E. & Palafox B. (2018). Evaluación y monitoreo de los pastos marinos en el contexto del proyecto de ampliación del Puerto de Veracruz-Fase I. API-GI-CS-62601-066-17. Programa Mexicano del Carbono-CINVESTAV-IPN Unidad Mérida. Dataset provided by Sara Morales, CINVESTAV (sara.morales@cinvestav.mx)
Contact Person: Jorge Herrera Silveira
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Polygons representing the distribution of the seagrasses of the species Thalassia testudinum (Tt) Syringodium filiforme (Sf), Halodule wrightii (Hw), mixed vegetation of seagrass (MxPP), Macroalgae (Ma) and mixed vegetation of grasses marine and macroalgae in the eastern coastal area of the state of Yucatan, derived through the records obtained during the year 2018 to 2019 with a Hydroacoustic Echosounder and two Sentinel 2A satellite images from the year 2018. > Preprocessing Classes corresponding to seagrass habitats were extracted from the field ""Classes"": class 1 ""Halodule wrightii""; Class2 ""Mix of Thalassia testudinum and macroalgae"", Class3 ""Mix of seagrasses"", Class4 ""Mix of seagrasses and macroalgae"", Class5 ""Syringodium filiforme"", Class6 ""Thalassia testudinum"". Polygons selection was exported to a new spatial layer.
Citation: Pérez-Espinosa, I., Gallegos-Martínez, M., Cruz-López, M. I., Ressl, R., Valderrama- Landeros, L. H., Herrera-Moro Chao, I, (23/06/2020). Distribución espacial de los pastos marinos y las macroalgas en la zona costera Este del estado de Yucatán, escala: 1:20000, edición: 1. Universidad Autónoma Metropolitana Unidad Iztapalapa. Mexico City, Mexico. Year of Origin: 2018- 2019 Source metadata: http://geoportal.conabio.gob.mx/metadatos/doc/html/mcalgas20gw.html
Contact Person: Iliana Pérez
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The distribution of seagrass was carried out with acoustic information (side scan sonar) and feedback with field information (wordview-2) through principal component analysis of 29 acoustic properties calculated by sonar over training areas of 33 pixels by 17 pixels. (6 m ± 0.5). The accuracy of the map was 89%. > Preprocessing As reported by the source, the file contains two grid codes describing “Sand == 1” and “Seagrass == 2”. Al polygons corresponding to grid code 2 were selected and exported to a new spatial layer.
Citation: Mendoza-Martínez J. E; Herrera-Silveira J.A; Liceaga-Correa M. A. Almacenes de Carbono en Biomasa de Pastos Marinos Costeros Tropicales de Regiones Cársticas. En: Paz, F., A. Velázquez y M. Rojo (Ed). 2018, Estado Actual del Conocimiento del Ciclo del Carbono y sus Interacciones en México: Síntesis a 2018. Serie Síntesis Nacionales. Programa Mexicano del Carbono en colaboración con el Instituto Tecnológico de Sonora. Texcoco, Estado de México, México. 686 p. Dataset provided by Juan Mendoza, CINVESTAV (juan.mendoza@cinvestav.mx) Source metadata: https://pmcarbono.org/pmc/publicaciones/Sintesis_Nacional_2018.pdf
Contact Person: Juan Mendoza Martínez
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Derived from field work in 290 sampling sites on the seabed of the Central-West Region of the State of Yucatán, the submerged aquatic vegetation and the type of associated substrate were identified. The disposition and spatial arrangement of the benthic community defined seven types of habitat along the coastline. Using remote sensing techniques, the map of the 7 submerged habitats of the region was constructed: Bare substrate, Sand with seagrasses, Seagrass meadows, Seagrasses with macroalgae, Macroalgae on sand, Laja with macroalgae and Forest of macroalgae. > Preprocessing Classes corresponding to seagrass habitats were extracted from the field ""Habitat"": class 1 ""seagrass with sand""; Class2 ""seagrass with macroalgae"", Class3 ""seagrass beds"".
Citation: Palafox Juárez E. B., Liceaga Correa M. A. (2013). Vegetación acuática sumergida de la Región Centro - Poniente del estado de Yucatán, escala: 1:450,000. edición: 1. Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional - Unidad Mérida. Mérida, Yucatán. Year of Origin: 2010- 2012 Source metadata: http://www.conabio.gob.mx/informacion/metadata/gis/vas_yucgw.xml?_httpcache=yes&_xsl=/db/metadata/xsl/fgd c_html.xsl&_indent=no
Contact Person: Isabel Cruz
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A classification of the seabed was carried out on an atmospherically corrected Sentinel 2A image from the year 2018, water column was corrected as well. The classification method was Maximum Likelihood, supervised classification using information collected in the field and spectral signatures. Overall map accuracy: 85%. > Preprocessing No preprocessing was needed for this dataset.
Dataset provided by Javier Ramírez, CINVESTAV (javier.ramirez@cinvestav.mx)
Contact Person: Javier Ramírez
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Polygonal layer representing the distribution of marine grasses and submerged aquatic vegetation in the Petenes Biosphere Reserve, Campeche, derived from the records obtained from 2011 to 2017 with a Hydroacoustic Echosounder and one Sentinel 2A satellite image of the year 2017. > Preprocessing Classes corresponding to seagrass habitats were extracted from the field ""Habitat"": Class 1 ""Mix of Thalassia testudinum and macroalgae""; Class 2 ""Mix of seagrasses"", Class 3 ""Mis of seagrasses and macroalgae"".
Citation: Pérez-Espinosa, I., Gallegos-Martínez, M. E., Ressl, R., Valderrama-Landeros, L. H., G. Hernández-Cárdenas (2019). Distribución espacial de los pastos marinos y la vegetación acuática sumergida en los Petenes, Campeche, escala: 1:350000. edición: 1. Universidad Autónoma Metropolitana Unidad Iztapalapa. Mexico City, Mexico. Year of Origin: 2011- 2017 Source metadata: http://geoportal.conabio.gob.mx/metadatos/doc/html/vaspetenesgw.html
Contact Person: Iliana Pérez
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The general objective of this study was to evaluate and quantify the carbon capture and storage capacity of coastal wetlands in Mexico (Blue Carbon), and to provide a first approximation of the GHG capture and emission potential in different regions. The work, entrusted to the Mexican Carbon Program, A.C, was carried out through four studies that were prepared independently but interconnected, which were developed by various teams coordinated by Dr. Jorge Herrera Silveira from CINVESTAV-IPN, Mérida. A classification of the lagoon bottom was performed on a 30m resolution Landsat8 and Landsat7 image. The classification method was that of Maximum likelihood by supervised classification. Final map accuracy was 74.5%. > Preprocessing Classes corresponding to seagrass habitats were extracted from the field ""CLASE"", this field is linked to seagrasses species and percentage of seagrass coverage in the attribute table.
Citation: Instituto Nacional de Ecología y Cambio Climático, INECC-PNUD-México (2017). Estudio para la identificación, caracterización y evaluación del balance entre las emisiones de GEIs y las zonas de captura y almacenamiento de carbono en zonas de ecosistemas costero/marinos del Pacífico, Golfo de México y la Península de Yucatán (Carbono azul). Proyecto 85488 ""Sexta Comunicación Nacional de México ante la Convención Marco de las Naciones Unidas sobre el Cambio Climático"", Programa Mexicano del Carbono, A.C., 415 pp., México. Dataset provided by Sara Morales, CINVESTAV (sara.morales@cinvestav.mx) Source metadata: http://cambioclimatico.gob.mx:8080/xmlui/handle/publicaciones/253?show=full
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The general objective of this study was to evaluate and quantify the carbon capture and storage capacity of coastal wetlands in Mexico (Blue Carbon), and to provide a first approximation of the GHG capture and emission potential in different regions. The work, entrusted to the Mexican Carbon Program, A.C, was carried out through four studies that were prepared independently but interconnected, which were developed by various teams coordinated by Dr. Jorge Herrera Silveira from CINVESTAV-IPN, Mérida. A classification of the lagoon bottom was performed on a 30m resolution Landsat8 and Landsat7 image. The classification method was that of Maximum likelihood by supervised classification. Final map accuracy, 73%. > Preprocessing Classes corresponding to seagrass habitats were extracted from the field ""CLASE"", this filed is linked to seagrasses species and percentage of seagrass coverage in the attribute table.
Citation: Instituto Nacional de Ecología y Cambio Climático, INECC-PNUD-México (2017). Estudio para la identificación, caracterización y evaluación del balance entre las emisiones de GEIs y las zonas de captura y almacenamiento de carbono en zonas de ecosistemas costero/marinos del Pacífico, Golfo de México y la Península de Yucatán (Carbono azul). Proyecto 85488 ""Sexta Comunicación Nacional de México ante la Convención Marco de las Naciones Unidas sobre el Cambio Climático"", Programa Mexicano del Carbono, A.C., 415 pp., México. Dataset provided by Sara Morales, CINVESTAV (sara.morales@cinvestav.mx) Source metadata: http://cambioclimatico.gob.mx:8080/xmlui/handle/publicaciones/253?show=full
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The general objective of this study was to evaluate and quantify the carbon capture and storage capacity of coastal wetlands in Mexico (Blue Carbon), and to provide a first approximation of the GHG capture and emission potential in different regions. The work, entrusted to the Mexican Carbon Program, A.C, was carried out through four studies that were prepared independently but interconnected, which were developed by various teams coordinated by Dr. Jorge Herrera Silveira from CINVESTAV-IPN, Mérida. A classification of the lagoon bottom was performed on a 30m resolution Landsat8 and Landsat7 image. The classification method was that of Maximum likelihood by supervised classification. Final map accuracy, 45.8%. > Preprocessing Classes corresponding to seagrass habitats were extracted from the field ""CLASE"": Class1 ""TT"", Class2 ""HW"", Class3 ""HW-TT"", Class 4 and 5 ""Algas and TT"".
Citation: Instituto Nacional de Ecología y Cambio Climático, INECC-PNUD-México (2017). Estudio para la identificación, caracterización y evaluación del balance entre las emisiones de GEIs y las zonas de captura y almacenamiento de carbono en zonas de ecosistemas costero/marinos del Pacífico, Golfo de México y la Península de Yucatán (Carbono azul). Proyecto 85488 ""Sexta Comunicación Nacional de México ante la Convención Marco de las Naciones Unidas sobre el Cambio Climático"", Programa Mexicano del Carbono, A.C., 415 pp., México. Dataset provided by Sara Morales, CINVESTAV (sara.morales@cinvestav.mx) Source metadata: http://cambioclimatico.gob.mx:8080/xmlui/handle/publicaciones/253?show=full
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A classification of the lagoon bottom was carried out on a sentinel image 2A of the year 2018. The image was atmospherically corrected, water column was corrected as well. The classification method Maximum likelihood, supervised classification. Final map accuracy, 92% > Preprocessing No preprocessing was needed for this dataset.
Citation: Herrera-Silveira, J.A., Mendoza-Martínez, J.E., Camal-Sosa, J.P., Robles-Toral, P. J. (2020). Evaluación y monitoreo de los pastos marinos como parte del servicio: Evaluación de carbono azul del Área de Protección de Flora y Fauna Manglares de Nichupté y Sistema Lagunar Nichupté-Bojórquez. Programa Mexicano del Carbono-CINVESTAV-IPN Unidad Mérida. Dataset provided by Juan Mendoza, CINVESTAV (juan.mendoza@cinvestav.mx)
Contact Person: Jorge Herrera Silveira
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A classification of the lagoon and marine bottom was carried out on a Sentinel2A image of the year 2017 atmospherically corrected, water column was corrected as well. The classification method was Maximum likelihood, supervised classification. The overall map accuracy, 78%. > Preprocessing No preprocessing was needed for this dataset.
Citation: Herrera- Silveira, J. A., Mendoza-Martínez, J. E., Pérez-Martínez, O., Solís-Gamboa, S., García-Trasviña, A., Pech,E., Caamal, J., Rosette, M. (2018). Almacenes de carbono en manglar y pastos marinos del área de protección de flora y fauna reserva de Yum Balam. Informe Técnico Final, PMC-CINVESTAV-CEMDA Dataset provided by Juan Mendoza, CINVESTAV (juan.mendoza@cinvestav.mx) Source metadata: https://www.cemda.org.mx/wp-content/uploads/2018/09/Almacenes-de-Carbono-Azul-Yum-Balam-2018.pdf
Contact Person: Jorge Herrera Silveira
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The map represents the spatial distribution and extension of the benthic habitats of the marine ecosystems of the Mexican Caribbean, covering the shallow waters of the Mesoamerican reef system between Cabo Catoche and Xcalak. The resulting map was generated from the union of the benthic coverage maps and the underwater relief, 50 classes were defined in an area of 1001.3 km2 with an average maximum depth of 18 m. > Preprocessing All polygons classified as sea grasses (“Comunidad de Pastos Marinos”) within Name of coverage (“Nom_Cob”) field where selected and exported to a new spatial polygons layer.
Citation: Cerdeira-Estrada, S., M.I. Martínez-Clorio, L.O. Rosique-De La Cruz, M. Kolb, A.M. Gonzales-Posada, A. Uribe-Martínez, R. Martell-Dubois, M.I. Cruz-López, R. Ressl (2018). Hábitats Bentónicos de los Ecosistemas Marinos del Caribe Mexicano: Cabo Catoche - Xcalak. 2018, escala: 1:8000. edición: 2. Comisión Nacional para el Conocimiento y Uso de la Biodiversidad. Mexico. Source metadata: http://geoportal.conabio.gob.mx/metadatos/doc/html/habitatv2gw.html
Contact Person: Sergio Cerdeira
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Distribution of a perennial meadow of Phyllospadix sp. surrounding the Natural Protected Area of Isla de Todos los Santos, Baja California. > Preprocessing No preprocessing was needed for this dataset.
Dataset provided by José Miguel Sandoval Gil, UABC (jmsandovalgil@gmail.com)
Contact Person: José Miguel Sandoval Gil
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Vector polygons representing Seagrass areas in North America.
Commission for Environmental Cooperation
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Feature geometry.
Esri
Coordinates defining the features.
Country where the Seagrass polygon is located.
Commission for Environmental Cooperation
State or province code defining the location of each seagrass polygon (two letters country code + two letters state/province code).
Commission for Environmental Cooperation
Name of the features described by each polygon, as reported by the source of each dataset.
Commission for Environmental Cooperation
> Algae - Turtle Grass (Thalassia testudinum) > Beaked Tasselweed - (Ruppia maritima) > Beaked Tasselweed - (Ruppia maritima) - Sago Pondweed (Stuckenia pectinata) > Broadleaf Watermilfoil (Myriophyllum heterophyllum) - Utricularia gibba > Caribbean Seagrass (Halophila decipiens) > Continuous Seagrass > Dwarf Eelgrass (Zostera japonica) > Eelgrass (Zostera marina) > Eelgrass (Zostera marina) - continuous > Eelgrass (Zostera marina) - Dwarf Eelgrass (Zostera japonica) > Eelgrass (Zostera marina) - Kelp > Eelgrass (Zostera marina) - patchy > Eelgrass (Zostera marina) - Surfgrass (Phyllospadix) > Eurasian Watermilfoil (Myriophyllum spicatum) > Eurasian Watermilfoil (Myriophyllum spicatum) - Beaked Tasselweed - (Ruppia maritima) > Eurasian Watermilfoil (Myriophyllum spicatum) - Leafy Bladderwort (Utricularia foliosa) > Eurasian Watermilfoil (Myriophyllum spicatum) - Southern Waternymph (Najas guadalupensis) > Eurasian Watermilfoil (Myriophyllum spicatum) - Southern Waternymph (Najas guadalupensis) - Beaked Tasselweed - (Ruppia maritima) > Eurasian Watermilfoil (Myriophyllum spicatum) - Southern Waternymph (Najas guadalupensis) - Water Stargrass (Heteranthera dubia) - Hornwort (Ceratophyllum demersum) > Eurasian Watermilfoil (Myriophyllum spicatum) - Southern Waternymph (Najas guadalupensis) - Water Stargrass (Heteranthera dubia) - Hornwort (Ceratophyllum demersum) - Carolina Fanwort (Cabomba caroliniana) > Eurasian Watermilfoil (Myriophyllum spicatum) - Water Stargrass (Heteranthera dubia) > Eurasian Watermilfoil (Myriophyllum spicatum) - Water Stargrass (Heteranthera dubia) - Hornwort (Ceratophyllum demersum) > Eurasian Watermilfoil (Myriophyllum spicatum) - Waterthyme (Hydrilla verticillata) > Macroalgae - Turtle Grass (Thalassia testudinum) > Manatee Grass (Syringodium Filiforme) > Manatee Grass (Syringodium filiforme) - Shoal Grass (Halodule wrightii) > Mixed Seagrasses > Mixed Seagrasses - Macroalgae > Not Reported > Rockweed (Fucus) - Eelgrass (Zostera marina) > Sand with Seagrasses > Seagrass > Seagrass - Brown Algae > Seagrass - dense > Seagrass - dense (>70%) > Seagrass - medium > Seagrass - medium (20-70%) > Seagrass - patchy > Seagrass - Red Algae > Seagrass - Rockweed > Seagrass - sparse > Seagrass - sparse (<30%) > Seagrass (A. Afuera) > Seagrass (Chopas) > Seagrass (En Medio) > Seagrass (Gallega) > Seagrass (Galleguilla) > Seagrass (Pájaros) > Seagrass (Rizo) > Seagrass (Sacrificio) > Seagrass (Verde) > Seagrass (Zostera spp.) > Seagrass Meadows > Seagrasses - Macroalgae > Shoal Grass (Halodule wrightii) > Shoal Grass (Halodule wrightii) - Ruppia maritima > Southern Waternymph (Najas guadalupensis) > Southern Waternymph (Najas guadalupensis) - Hornwort (Ceratophyllum demersum) - Small Pondweed (Potamogeton pusilis) > Surfgrass (Phyllospadix) > Tape Grass (Valisneria neotropicalis) - Beaked Tasselweed (Ruppia maritima) > Tape Grass (Valisneria neotropicalis) - Beaked Tasselweed (Ruppia maritima) - Sago Pondweed (Stuckenia pectinata) > Tape Grass (Valisneria neotropicalis) - Beaked Tasselweed (Ruppia maritima) - Water Stargrass (Heteranthera dubia) > Tape Grass (Valisneria neotropicalis) - Eurasian Watermilfoil (Myriophyllum spicatum) > Tape Grass (Valisneria neotropicalis) - Eurasian Watermilfoil (Myriophyllum spicatum) - Beaked Tasselweed (Ruppia maritima) - Water Stargrass (Heteranthera dubia) > Tape Grass (Valisneria neotropicalis) - Eurasian Watermilfoil (Myriophyllum spicatum) - Sago Pondweed (Stuckenia pectinata) > Tape Grass (Valisneria neotropicalis) - Eurasian Watermilfoil (Myriophyllum spicatum) - Southern Waternymph (Najas guadalupensis) > Tape Grass (Valisneria neotropicalis) - Eurasian Watermilfoil (Myriophyllum spicatum) - Southern Waternymph (Najas guadalupensis) - Beaked Tasselweed (Ruppia maritima) > Tape Grass (Valisneria neotropicalis) - Eurasian Watermilfoil (Myriophyllum spicatum) - Southern Waternymph (Najas guadalupensis) - Beaked Tasselweed (Ruppia maritima) - Hornwort (Ceratophyllum demersum) > Tape Grass (Valisneria neotropicalis) - Eurasian Watermilfoil (Myriophyllum spicatum) - Southern Waternymph (Najas guadalupensis) - Beaked Tasselweed (Ruppia maritima) - Water Stargrass (Heteranthera dubia) > Tape Grass (Valisneria neotropicalis) - Eurasian Watermilfoil (Myriophyllum spicatum) - Southern Waternymph (Najas guadalupensis) - Hornwort (Ceratophyllum demersum) > Tape Grass (Valisneria neotropicalis) - Eurasian Watermilfoil (Myriophyllum spicatum) - Southern Waternymph (Najas guadalupensis) - Hornwort (Ceratophyllum demersum) - Small Pondweed (Potamogeton pusilis) > Tape Grass (Valisneria neotropicalis) - Eurasian Watermilfoil (Myriophyllum spicatum) - Southern Waternymph (Najas guadalupensis) - Hornwort (Ceratophyllum demersum) - Waterthyme (Hydrilla verticillata) > Tape Grass (Valisneria neotropicalis) - Eurasian Watermilfoil (Myriophyllum spicatum) - Southern Waternymph (Najas guadalupensis) - Small Pondweed (Potamogeton pusilis) > Tape Grass (Valisneria neotropicalis) - Eurasian Watermilfoil (Myriophyllum spicatum) - Southern Waternymph (Najas guadalupensis) - Water Stargrass (Heteranthera dubia) > Tape Grass (Valisneria neotropicalis) - Eurasian Watermilfoil (Myriophyllum spicatum) - Southern Waternymph (Najas guadalupensis) - Water Stargrass (Heteranthera dubia) - Hornwort (Ceratophyllum demersum) > Tape Grass (Valisneria neotropicalis) - Eurasian Watermilfoil (Myriophyllum spicatum) - Southern Waternymph (Najas guadalupensis) - Water Stargrass (Heteranthera dubia) - Small Pondweed (Potamogeton pusilis) > Tape Grass (Valisneria neotropicalis) - Eurasian Watermilfoil (Myriophyllum spicatum) - Southern Waternymph (Najas guadalupensis) - Water Stargrass (Heteranthera dubia) - Small Pondweed (Potamogeton pusilis) - Waterthyme (Hydrilla verticillata) > Tape Grass (Valisneria neotropicalis) - Eurasian Watermilfoil (Myriophyllum spicatum) - Water Stargrass (Heteranthera dubia) > Tape Grass (Valisneria neotropicalis) - Eurasian Watermilfoil (Myriophyllum spicatum) - Water Stargrass (Heteranthera dubia) - Waterthyme (Hydrilla verticillata) - Small Pondweed (Potamogeton pusilis) > Tape Grass (Valisneria neotropicalis) - Horned Pondweed (Zannichellia palustris) > Tape Grass (Valisneria neotropicalis) - Sago Pondweed (Stuckenia pectinata) > Tape Grass (Valisneria neotropicalis) - Southern Waternymph (Najas guadalupensis) > Tape Grass (Valisneria neotropicalis) - Southern Waternymph (Najas guadalupensis) - Beaked Tasselweed (Ruppia maritima) - Water Stargrass (Heteranthera dubia) > Tape Grass (Valisneria neotropicalis) - Southern Waternymph (Najas guadalupensis) - Hornwort (Ceratophyllum demersum) > Tape Grass (Valisneria neotropicalis) - Southern Waternymph (Najas guadalupensis) - Hornwort (Ceratophyllum demersum) - Leafy Bladderwort (Utricularia foliosa) > Tape Grass (Valisneria neotropicalis) - Southern Waternymph (Najas guadalupensis) - Sago Pondweed (Stuckenia pectinata) > Tape Grass (Valisneria neotropicalis) - Southern Waternymph (Najas guadalupensis) - Water Stargrass (Heteranthera dubia) > Tape Grass (Valisneria neotropicalis) - Southern Waternymph (Najas guadalupensis) - Water Stargrass (Heteranthera dubia) - Hornwort (Ceratophyllum demersum) - Small Pondweed (Potamogeton pusilis) > Tape Grass (Valisneria neotropicalis) - Water Stargrass (Heteranthera dubia) > Tape Grass (Vallisneria americana) > Turtle Grass (Thalassia testudinum) > Turtle Grass (Thalassia testudinum) - Macroalgae > Turtle Grass (Thalassia testudinum) - Manatee Grass (Syringodium Filiforme) > Turtle Grass (Thalassia testudinum) - Manatee Grass (Syringodium Filiforme) - Shoal Grass (Halodule wrightii) > Turtle Grass (Thalassia testudinum) - Manatee Grass (Syringodium Filiforme) - Shoal Grass (Halodule wrightii) - Macroalgae > Turtle Grass (Thalassia testudinum) - Shoal Grass (Halodule wrightii) > Turtle Grass (Thalassia testudinum) - Shoal Grass (Halodule wrightii) - Manatee Grass (Syringodium Filiforme) > Twoleaf Watermilfoil (Myriophyllum heterophyllum) > Water Chestnut (Trapa natans) > Water Stargrass (Heteranthera dubia)
Description of the original dataset used to acquire each polygon.
Commission for Environmental Cooperation
> BC Ministry of Forests, Lands, Natural Resource Operations and Rural Development > Botánica Marina del Instituto de Investigaciones Oceanológicas, UABC > Environment and Climate Change Canada > Fisheries and Oceans Canada (DFO) > Frederick T. Short (University of New Hampshire) > Herrera-Silveira et al., 2018 > Herrera-Silveira et al., 2020 > Howe Sound/Átl’ḵa7tsem Marine Reference Guide > INECC-PNUD México > Laboratorio de Producción Primaria, CINVESTAV (Unidad Mérida) > Melanie Leblanc (McGill University) > Mendoza-Martínez et al., 2018 > Mendoza-Martínez et al., 2019 > National Commission for the Knowledge and Use of Biodiversity (CONABIO) > Northeast Ocean Data > Texas Parks and Wildlife, Coastal Fisheries Division > UN Environment Programme World Conservation Monitoring Centre (UNEP-WCMC) > Washington State Department of Natural Resources > Washington State Department of Natural Resources Submerged Vegetation Monitoring Program
Year of the publication of the last update of the dataset used as input.
Commission for Environmental Cooperation
Name of the entity responsible on providing each dataset.
Commission for Environmental Cooperation
> Calderón, I., 1996 (Provided by Matt Christensen, University of British Columbia) > CAN: BC Ministry of Forests, Lands, Natural Resource Operations and Rural Development > CAN: British Columbia Marine Conservation Analysis (BCMCA) > CAN: British Columbia Parks > CAN: Environment and Climate Change Canada > CAN: Moonstone Enterprises > CAN: SeaChange Marine Conservation Society > Comité côtier Les Escoumins à la Rivière Betsiamites, 2004 (Provided by Matt Christensen, University of British Columbia) > Comité ZIP Côte-Nord du Golfe, 2001 (Provided by Matt Christensen, University of British Columbia) > Comité ZIP de la rive nord de l'estuaire, 2008 (Provided by Matt Christensen, University of British Columbia) > Conseil Régional de l'Environnement Gaspésie et des Îles-de-la- Madeleine, 2004 (Provided by Matt Christensen, University of British Columbia) > CRC Marine Science Series, 16 > Danièle Morin (MRNF), 2009 (Provided by Matt Christensen, University of British Columbia) > Frederick T. Short (University of New Hampshire) > Giguère, M. et al., 2006 (Provided by Matt Christensen, University of British Columbia) > Hans-Frederic Ellefsen (MPO), 2009 (Provided by Matt Christensen, University of British Columbia) > Harvey, C. & Brouard, D., 1992 (Provided by Matt Christensen, University of British Columbia) > Hazel, F., 2002 (Provided by Matt Christensen, University of British Columbia) > Jacquaz & Coll, 1990 (Provided by Matt Christensen, University of British Columbia) > Kedney, G. & Kaltenback, P., 1996 (Provided by Matt Christensen, University of British Columbia) > Leblanc, J., 2002 (Provided by Matt Christensen, University of British Columbia) > Lemieux, C. & Lalumière, R., 1995 (Provided by Matt Christensen, University of British Columbia) > Lemieux, C., 1995 (Provided by Matt Christensen, University of British Columbia) > Melanie Leblanc (McGill University) > MEX: Botánica Marina del Instituto de Investigaciones Oceanológicas, UABC > MEX: Laboratorio de Producción Primaria - CINVESTAV (Unidad Mérida) > MEX: National Commission for the Knowledge and Use of Biodiversity (CONABIO) > MEX: Programa Mexicano del Carbono > MEX: Programa Mexicano del Carbono - Centro Nayarita de Innovación y Transferencia de Tecnología - Universidad Autónoma de Nayarit - Consejo de Ciencia y Tecnología del Estado de Nayarit - Stanford University - México Economía Limpia > MEX: Programa Mexicano del Carbono - CINVESTAV (Unidad Mérida) > MEX: Programa Mexicano del Carbono - Instituto Tecnológico de Sonora > Naturam Environnement, 1999 (Provided by Matt Christensen, University of British Columbia) > Not Reported > Pelletier, C., 2003 (Provided by Matt Christensen, University of British Columbia) > Raz-Guzmán, Andrea (Instituto de Investigaciones sobre los Recursos Naturales, Universidad Michoacana de San Nicolas de Hidalgo, Morelia, México) > Selma Pereira (MPO), 2009 (Provided by Matt Christensen, University of British Columbia) > UN Environment Programme World Conservation Monitoring Centre (UNEP-WCMC) - University of California Press > United Nations Educational, Scientific and Cultural Organization (UNESCO) > USA: Earth Design Consultants, Inc. > USA: Florida Fish and Wildlife Conservation Commission - Fish and Wildlife Research Institute > USA: National Geographic Society > USA: NOAA Coastal Services Center > USA: Northeast Ocean Data > USA: Port of San Diego - U.S. Department of the Navy > USA: Seattle Pacific University > USA: Texas Parks and Wildlife, Coastal Fisheries Division > USA: U.S. Army Corps of Engineers > USA: United States Geological Survey and Fish and Wildlife Service > USA: University of California, Los Angeles > USA: Washington State Department of Natural Resources > USA: Washington State Department of Natural Resources Submerged Vegetation Monitoring Program > Vaillancourt, M.A. & Lafontaine, C., 1999 (Provided by Matt Christensen, University of British Columbia) > Vaillancourt, M.A. & Lafontaine, C., 1999. (Provided by Matt Christensen, University of British Columbia)
Year of origin of data reported by the source of each dataset (this can be year when data was taken or when the data was originally published by the source).
Commission for Environmental Cooperation
> 1979 > 1987-2009 > 1989 > 1990 > 1991 > 1996 > 1998 > 2000 > 2000-2019 > 2001 > 2002 > 2002-2008 > 2003 > 2004 > 2005 > 2008 > 2009 > 2010 > 2010-2012 > 2011 > 2011-2017 > 2012 > 2013 > 2014 > 2015 > 2016 > 2017 > 2018 > 2018-2019 > 2019 > 2020
Reported method of data acquisition as reported by the source of each dataset.
Commission for Environmental Cooperation
> Data Collection > Field Survey > Not Reported > Remote Sensing > Remote Sensing, Field Survey > Remote Sensing, Ground-Truth
Scale of the input data used in each polygon or general dataset as reported by the source.
Commission for Environmental Cooperation
> 1:2,000 - 1:50,000 > 1:20,000 > 1:24,000 > 1:28,510,000 > 1:350,000 > 1:40,000 > 1:450,000 > 1:5,000 - 1:3,000,000 > 1:50,000 - 1:625,000 > 1:8,000 > 1:80,000 > Not Reported
Resolution of the input data used in each polygon or general dataset as reported by the source.
Commission for Environmental Cooperation
> 7 m > 2 m > 30 m > 6 m > Not Reported
General description of the source dataset used to derive each polygon.
Commission for Environmental Cooperation
> A classification of the lagoon bottom was performed on a 30m resolution Landsat8 and Landsat7 image. Maximum likelihood classification method, supervised classification. Map accuracy: 45.8% > A classification of the lagoon bottom was performed on a 30m resolution Landsat8 and Landsat7 image. Maximum likelihood classification method, supervised classification. Map accuracy: 74.5% > A classification of the seabed was performed on a 2018 Sentinel 2A image. Maximum likelihood classification method, supervised classification using information collected in the field and spectral signatures. Map accuracy: 85% > Areas in West Galveston Bay and Christmas Bay where seagrass is present. The area was ground truthed for the presence of seagrass in March 2015. Polygons of areas where seagrass is present were digitized in April 2015 through photointerpretation > British Columbia Marine Conservation Analysis, 2010. Marine Plants - Eelgrass polygons data. In: Marine Atlas of Pacific Canada, British Columbia, Canada > Classification derived from a 2017 Sentinel 2A image. Maximum likelihood classification method, supervised classification. Map accuracy: 78% > Classification derived from a 2018 Sentinel 2A image. Maximum likelihood classification method, supervised classification. Map accuracy: 92% > Classification of the reef bottom based on a WordView2 image, 2m resolution. Maximum Likelihood classification method, supervised classification and field data. Global accuracy: 92% > Classification performed on 30m resolution Landsat8 and Landsat7 images. Maximum likelihood classification method, supervised classification. Map accuracy: 73% > Clinton, P.J., Young, D.R., Specht, D.T., 2002. A hybrid high resolution image classification method for mapping eelgrass distributions in Yaquina Bay Estuary, Oregon > Creed, J.C. et al, 2003. The Seagrasses of the Caribbean. In: Green, E.P., Short, F.T. (Eds.), World Atlas of Seagrasses. UNEP World Conservation Monitoring Centre, University of California Press, pp. 234–242 > Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Coastal Services Center (CSC), October 2013 > Derived from field work in 290 sampling sites on the seabed of the Central-West Region of the State of Yucatán, the submerged aquatic vegetation and the type of associated substrate were identified > Distribution of a perennial meadow of Phyllospadix sp. surrounding the Natural Protected Area of Isla de Todos los Santos, Baja California > Distribution of marine grasses and submerged aquatic vegetation in the Petenes Biosphere Reserve, Campeche, derived from the records obtained from 2011 to 2017 with a Hydroacoustic Echosounder and a 2017 Sentinel 2A image > Distribution of seagrass was identified with side scan sonar and field information through principal component analysis of 29 acoustic properties. Map accuracy: 89% > Florida Fish and Wildlife Conservation Commission - Fish and Wildlife Research Institute (2011), Seagrass Florida > Harding, L.W. & Butler, J.H., 1979. The standing stock and production of eelgrass, Zostera marina, in Humboldt Bay, California. Calif. Fish Game 65, 151-158 > Herrera-Silveira, J.A. et al, 2000. Seagrass bed recovery after hydrological restoration in a coastal lagoon with groundwater discharges in the north of Yucatan. In: Seagrasses: monitoring, ecology, physiology, and management, 219-229 > McRoy, C.P. & Bridges, K.W., 1998. Eelgrass survey of eastern Prince William Sound. US Army Corps of Engineers. Unpublished Final Report, Anchorage, Alaska > National Geographic Society, 2000. Coral World. 1:28,510,000. 1 pp > Phillips, R.C. & Echeverria, S.W., 1990. Zostera asiatica Miki on the Pacific coast of North America. Pacific Sci. 44, 130-134 > Polygons representing the distribution of the seagrasses in the eastern coast of Yucatan, derived from Hydroacoustic Echosounder records in 2018-2019 and two Sentinel 2A images from 2018 > Port of San Diego and U.S. Department of the Navy, Southwest Division (USDoN, SWDIV), 2000. San Diego Bay 2000 Eelgrass Survey > Raz-Guzmán, Andrea (Instituto de Investigaciones sobre los Recursos Naturales, Universidad Michoacana de San Nicolas de Hidalgo, Morelia, México) \[Personal communication reported by UNEP-WCMC] > Results obtained by Mélanie Leblanc PhD research. Connections Between Eelgrass, Geese, and Cree Harvest and Culture in Eastern James Bay. Produced from Landsat 8 and ground truth data > Ruíz-Rentería, F. et al, 1998. Puerto Morelos, Quintana Roo, Mexico. In: Kjerfve, B. (Ed.), CARICOMP - Caribbean Coral Reef, Seagrass and Mangrove Sites. UNESCO, 57-66 > San Francisco baywide eelgrass layer with density attributes developed from data collected in October and November of 2009. Data were developed for the California Department of Transportation and the National Marine Fisheries Service > Seagrass distribution derived from field data and satellite information (WorldView-2) using spectral algorithms (Maximum Likelihood) and manual editing. Map accuracy: 77% > Spratt, J.D., 1989. The distribution and density of eelgrass, Zostera marina, in Tomales Bay, California. California Fish and Game, 75 (4), 204-212 > Strittholt, J.R. & Frost, P.A., 1996. Determining abundance and distribution of Eelgrass (Zostera spp.) in Tillamook Bay Estuary, Oregon using multispectral airborne imagery. Tillamook Bay National Estuary Project. 13 pp > Survey of Eelgrass for Bowen Island municipality > Survey of Eelgrass for Gambier Island local trust area > Survey of Eelgrass for Porteau Cove provincial park > Survey of Eelgrass in West Howe Sound > The layer presents the information on the distribution of eelgrass (Zostera marina) beds in James Bay, Chaleur Bay, Estuary and Gulf of St. Lawrence according to a literature review of documents produced between 1987 and 2009 > The map represents the spatial distribution and extension of the benthic habitats of the marine ecosystems of the Mexican Caribbean, covering the shallow waters of the Mesoamerican reef system between Cabo Catoche and Xcalak > The Observed Habitat Polygons show the various types of particular habitat that have been observed or calculated by biologists as well as an expectation of different species found in the habitats > The purpose of mapping the distribution of eelgrass (Submerged Aquatic Vegetation-SAV) is to determine areas where eelgrass is present throughout coastal New England waters in order to support coastal and ocean planning > The Saint-Lawrence Wetlands Mapping Project is a multi-year project that mapped portions of shores of the St-Lawrence river, mapped using remote-sensed imagery from 1990/1991, 1996/97, 2000, and 2002 > The ShoreZone Inventory describes the physical and biological characteristics of intertidal and shallow subtidal areas. It was completed by the Nearshore Habitat Program in the WA State Department of Natural Resources, Aquatic Resources Division > The SVMP has conducted annual monitoring of the status and trends of native seagrass in greater Puget Sound since 2000. This is the central component of the 2000-2019 Puget Sound Eelgrass monitoring dataset > These data were derived from satellite imagery (Ikonos-2 and Quickbird-2) acquired in June/August 2002-2008. The dataset serves as baseline information for the spatial extent and distribution of Eelgrass (Zostera marina)
Full citation of the used data source. Modified APA 7th citation style to fit in a maximum of 254 characters.
Commission for Environmental Cooperation
> Létourneau, G & M. Jean (1996) 'Cartographie des marais, marécages et herbiers aquatiques le long du Saint-Laurent par télédétection aéroportée', Environment and Climate Change Canada Longley, Kate (2014) 'Eelgrass Beds, Northeast United States', SeaPlan, Boston, MA, USA > Mendoza-Martínez et al. (2018) 'Estado Actual del Conocimiento del Ciclo del Carbono y sus Interacciones in México', Serie Síntesis Nacionales, Programa Mexicano del Carbono en colaboración con el Instituto Tecnológico de Sonora > Mendoza-Martínez et al. (2019) 'Almacenes de carbono en biomasa de pastos marinos de una laguna arrecifal y su relación con variables ambientales', In: Estado Actual del Conocimiento del Ciclo del Carbono y sus Interacciones en México > Not Reported > Palafox-Juárez et al. (2013) 'Vegetación acuática sumergida de la Región Centro-Poniente del estado de Yucatán', 1:450,000. Ed: 1. Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (Unidad Mérida), México > Pérez-Espinosa et al. (2019) 'Distribución espacial de los pastos marinos y la vegetación acuática sumergida en los Petenes, Campeche', 1:350,000. Ed: 1. Universidad Autónoma Metropolitana Unidad Iztapalapa, Ciudad de México, México > Pérez-Espinosa et al. (2020) 'Distribución espacial de los pastos marinos y las macroalgas en la zona costera Este del estado de Yucatán', 1:20,000. Ed: 1. Universidad Autónoma Metropolitana Unidad Iztapalapa, Ciudad de México, México > UNEP-WCMC, Short, F.T. (2020) ‘Global distribution of seagrasses (version 7.0). Seventh update to the data layer used in Green and Short (2003)’, Cambridge (UK): UN Environment World Conservation Monitoring Centre > WA-DNR (2020) ‘Submerged Vegetation Monitoring Program 2000-2019 Database’, Washington Department of Natural Resources, Aquatic Resources Division, Olympia, WA, USA
Identification code of the datasets reported in the data sources full description document.
Commission for Environmental Cooperation
> SG_01 > SG_02 > SG_03 > SG_04 > SG_05 > SG_06 > SG_07 > SG_08 > SG_09 > SG_10 > SG_11 > SG_12 > SG_13 > SG_14 > SG_15 > SG_16 > SG_17 > SG_18 > SG_19 > SG_20 > SG_21 > SG_22 > SG_23 > SG_24 > SG_25 > SG_26
The size of the shape in square meters.
ESRI
None. Acknowledgement of the Commission for Environmental Cooperation would be appreciated in products derived from these data.
This material is licensed under CC BY 4.0, allowing non-exclusive rights to distribute, remix, adapt, and build upon the material in any medium or format, including for commercial purposes, so long as attribution is given to the creator.