This dataset was designed for Environment and Climate Change Canada's (ECCC) National Environmental Emergencies Center (NEEC) for oil spill preparedness and response. The polygons from this layer come mainly from the coastal ecosystems geodatabase as part of the Mapping of coastal ecosystems of the Estuary and Gulf of St. Lawrence project. This layer represents semi-vegetated and vegetated zones of which eelgrass is the dominant vegetation. The study area includes all of the estuarine and maritime coasts of Quebec, with the exception of certain sectors, including most of the Lower North Shore and Anticosti Island, with the exception of villages of Kegaska, la Romaine, Chevery, Blanc-Sablon and Port-Menier. Some islands off the estuary and gulf coasts are part of the region covered, such as Île d'Orléans, Isle-aux-Coudres, Île Verte and Île Bonaventure. The Mapping of coastal ecosystems of the Estuary and Gulf of St. Lawrence was carried out jointly by the Laboratory for Dynamics and Integrated Coastal Zone Management (LDGIZC) of the University of Quebec at Rimouski as part of the Coastal Resilience Project (https: //ldgizc.uqar.ca/Web/projets/projet-resilience-cotiere) funded by the MELCC; and by the Fisheries and Oceans Canada team, as part of its Integrated marine response planning (IMRP) component of the Oceans Protection Plan (OPP), with the objective of updating the Marine Oil Spill Preparedness and Response Regime of Canada. The master geodatabase of coastal ecosystems is hosted and distributed by UQAR on their SIGEC-Web mapping platform: https://ldgizc.uqar.ca/Web/sigecweb The characterization of eelgrass beds was mainly carried out using photo-interpretation of RVBI aerial photos acquired by DFO (2015-2020) and oblique photos taken by helicopter by UQAR in 2017. This dataset also includes the information from validation stations visited by UQAR (2018-2020). Data from sampling stations, carried out aboard small boats during DFO field campaigns (2017-2021), were also used to validate and refine the photo-interpretation. This dataset also includes eelgrass beds characterized in the Basse-Côte-Nord (MRC Le Golfe-de-Saint-Laurent) by the Agence Mamu Innu Kaikusseht (AMIK) as part of the project ''Involvement of Innu communities in the protection of species at risk and their habitats 2010-2011''. These data were produced during aerial overflights at low altitude (200m and 400m) of the foreshore, as 2 observers circumscribed and documented the covering of eelgrass beds. Credits © UQAR-MPO-AMIK (2023, Laboratoire de dynamique et de gestion intégrée des zones côtières, Pêches et Océans Canada, Agence Mamu Innu Kaikusseht) Provencher-Nolet, L., Paquette, L., Pitre, L.D., Grégoire, B. and Desjardins, C. 2024. Cartographie des macrophytes estuariens et marins du Québec. Rapp. Tech. Can. Sci. halieut. Aquat. 3617 : v + 99 p. Grégoire, B., Pitre, L.D., Provencher-Nolet, L., Paquette, L. and Desjardins, C. 2024. Distribution d’organismes marins de la zone côtière peu profonde du Québec recensés par imagerie sous-marine de 2017 à 2021. Rapp. tech. can. sci. halieut. aquat. 3616 : v + 78 p. Grégoire, B. 2022. Biodiversité du relevé côtier Planification pour une intervention environnementale intégrée dans l’estuaire et le golfe du Saint-Laurent (2017–2021). Observatoire global du Saint-Laurent. [Jeu de données] Nadeau, V., Le Breton, S. 2011. Inventaire aérien des herbiers de zostère de la Basse-Côte-Nord du Golfe du Saint-Laurent. Agence Mamu Innu Kaikusseht. 25 p. Jobin, A., Marquis, G., Provencher-Nolet, L., Gabaj Castrillo. M. J., Trubiano C., Drouet, M., Eustache-Létourneau, D., Drejza, S. Fraser, C. Marie, G. et P. Bernatchez (2021) Cartographie des écosystèmes côtiers du Québec maritime — Rapport méthodologique. Chaire de recherche en géoscience côtière, Laboratoire de dynamique et de gestion intégrée des zones côtières, Université du Québec à Rimouski. Rapport remis au ministère de l’Environnement et de la Lutte contre les

This collection of eelgrass data has been collated to produce a national map of the location and distribution of eelgrass beds across Canada. The data providers collaborating in this initiative include Federal, Provincial and Municipal government departments and agencies, academia, non-governmental organizations, community groups, private sector, Indigenous groups and independent science organizations. The National Eelgrass Task Force (NETForce) is a collaborative, diverse and inclusive partnership of scientists, managers, and stakeholders working towards a concrete vision which is to create a national map of eelgrass distribution in Canada that is publicly accessible, dynamic, and useful for monitoring and collective decision-making. The eelgrass data were collected using various mapping techniques including species distribution models, benthic sonar, field measurements of habitat presence or absence, video transects, aerial photography, field validation, literature review, satellite imageries, LiDAR, Airborne spectrographic imaging, and Unoccupied Aerial Vehicle (UAV). The metadata provided by the partners relevant for their own projects and the field names were made similar for the compiled dataset. We also created additional fields that differentiated the datasets, and these include data provider, institution code, water body, mapping techniques, province, biogeographic region, eelgrass observation... Other fields are included depending on the original metadata provided by the data provider (i.e. eelgrass percentage cover, eelgrass density, map reference, image classification technique). The data span from 1987 to present, with some eelgrass beds being surveyed only once while others were sampled across several years. Uncertainty information associated with a dataset is included in the metadata when available. This map is intended to be evergreen and more eelgrass data will be added when available. This compiled dataset has been collected by many organizations for different purposes, using different survey techniques and different methodologies and, therefore, considerable care must be taken when using these data. For further information concerning specific datasets contact the data provider/institution and/or see the associated technical report (if available) included in the Report folder under the ‘Data and Resources’ section. This group of eelgrass data has been divided using the geographic boundaries of the Federal Marine Bioregions (https://open.canada.ca/data/en/dataset/23eb8b56-dac8-4efc-be7c-b8fa11ba62e9). The title of each geodatabase (FGDB/GDB) contains the name of the bioregion. The Data Dictionary guide provides the fields description (English and French) from each layer included in the geodatabases. For additional information please see: Gomez C., Guijarro-Sabaniel J., Wong M. 2021. National Eelgrass Task (NET) Force: engagement in support of a dynamic map of eelgrass distribution in Canada to support monitoring, research and decision making. Can. Tech. Rep. Aquat. Sci. 3437: vi + 48 p. https://waves-vagues.dfo-mpo.gc.ca/library-bibliotheque/4098218x.pdf Guijarro-Sabaniel, J., Thomson, J. A., Vercaemer, B. and Wong, M. C. 2024. National Eelgrass Task Force (NETForce): Building a dynamic, open eelgrass map for Canada. Can. Tech. Rep. Fish. Aquat. Sci. 3583: v + 31 p. https://waves-vagues.dfo-mpo.gc.ca/library-bibliotheque/41223147.pdf

This dataset was designed for Environment and Climate Change Canada's (ECCC) National Environmental Emergencies Center (NEEC) for oil spill preparedness and response. The polygons from this layer come from the coastal ecosystems geodatabase as part of the Mapping of coastal ecosystems of the Estuary and Gulf of St. Lawrence project. This layer represents semi-vegetated (25-75%) and vegetated (75-100%) zones of which marsh vegetation is the dominant. The study area includes all of the estuarine and maritime coasts of Quebec, with the exception of certain sectors, including most of the Lower North Shore and Anticosti Island, with the exception of villages of Kegaska, la Romaine, Chevery, Blanc-Sablon and Port-Menier. Some islands off the estuary and gulf coasts are part of the region covered, such as Île d'Orléans, Isle-aux-Coudres, Île Verte and Île Bonaventure. The mapping of coastal ecosystems was carried out jointly by the Laboratory for Dynamics and Integrated Coastal Zone Management (LDGIZC) of the University of Quebec at Rimouski as part of the Coastal Resilience Project (https: //ldgizc.uqar.ca/Web/projets/projet-resilience-cotiere) funded by the MELCC; and by the Fisheries and Oceans Canada team, as part of its Integrated marine response planning (IMRP) component of the Oceans Protection Plan (OPP), with the objective of updating the Marine Oil Spill Preparedness and Response Regime of Canada. The master geodatabase of coastal ecosystems is hosted and distributed by UQAR on their SIGEC-Web mapping platform: https://ldgizc.uqar.ca/Web/sigecweb The characterization of marshes was mainly carried out using photo-interpretation of RVBI aerial photos acquired by DFO (2015-2020) and oblique photos taken by helicopter acquired by UQAR in 2017. This dataset also includes the information from validation stations visited by UQAR (2018-2020), used to validate and refine the photo-interpretation.

This dataset includes metrics of eelgrass size, cover, and biomass from field sites along the Atlantic coast of Nova Scotia, Canada. Field sites were located across a gradient of environmental conditions, and field sampling was conducted in July to August 2022. Eelgrass percent cover, shoot density, and plants were sampled at 10 haphazardly distributed sampling stations within each eelgrass bed at approximately the same depth. Stations were ~10m apart and at least 2m from any eelgrass-bare interface. At each sampling station eelgrass leaves in a 0.5 x 0.5m quadrat were photographed for later computer image analysis to determine percent cover. The number of shoots were then counted in a 0.25 x 0.25m quadrat, and 3 vegetative shoots were collected. Shoots were measured for leaf length, width, and weight in the laboratory. These data were used to determine allometric and cover-biomass relationships for use in non-destructive estimation of bed biomass. Cite this data as: Wong, M.C., & Thomson, J. A. Data of eelgrass (Zostera marina) plant size (length, width), cover, and biomass from the Atlantic Coast of Nova Scotia. Published: February 2025. Coastal Ecosystems Science Division, Maritimes Region, Fisheries and Oceans Canada, Dartmouth NS. For additional information please see: Thomson, J. A., Vercaemer, B., & Wong, M. C. (2025). Non-destructive biomass estimation for eelgrass (Zostera marina): Allometric and percent cover-biomass relationships vary with environmental conditions. Aquatic Botany, 198, 103853. https://doi.org/10.1016/j.aquabot.2024.103853

This data package includes 40 geospatial rasters (maps) depicting various metrics about eelgrass (Zostera marina) coverage at Izembek Lagoon, Alaska, during 2016 and 2020. Two maps were produced from two Sentinel-2 satellite images collected on July 1, 2016, and August 14, 2020. Spectral classes derived from each satellite image were annotated and mapped based on data collected in the field at plots within each spectral class.

This data package includes 40 geospatial rasters (maps) depicting various metrics about eelgrass (Zostera marina) coverage at Izembek Lagoon, Alaska, during 2016 and 2020. Two maps were produced from two Sentinel-2 satellite images collected on July 1, 2016, and August 14, 2020. Spectral classes derived from each satellite image were annotated and mapped based on data collected in the field at plots within each spectral class.

These feature classes reside within the BIOLOGY Feature Data Set of the Lake Erie - 2022 ESI Geodatabase. It contains vector polygons and points representing FISH data for Lake Erie. The study area includes the United States portion of Lake Erie, covering the coastal portions of Ohio, Pennsylvania, and New York from the Michigan/Ohio border to the west to the New York/Canada border to the east. These data sets contain sensitive biological resource data for freshwater fish species in Lake Erie. Vector polygons in this data set represent fish distribution, concentration areas, and spawning areas. Vector points in this data set represent fish spawning areas. Species-specific abundance, seasonality, status, life history, and source information are stored in associated data tables (described in Entity Attribute Overview below) designed to be used in conjunction with this spatial data layer. This data set is a portion of the ESI data for Lake Erie. As a whole, the ESI data characterize the marine and coastal environments and wildlife by their sensitivity to spilled oil, and include information for three main components: shoreline habitats, sensitive biological resources, and human-use resources.

Provided here are three vector geospatial datasets that characterize the distribution of (1) eelgrass (Zostera marina), (2) salt marshes, and (3) mangroves in three bays along the west coast of the Baja California Peninsula, Mexico (Bahia San Quintin, Laguna Ojo de Liebre, and Laguna San Ignacio). These data were derived from satellite imagery (Landsat 5 TM) acquired on three different days (1992-09-05, 1999-03-24, 2000-05-11). After pre-processing, imagery was classified into land cover categories. The habitat distribution data were then extracted from the raster grid and converted to vector data.

These feature classes reside within the BIOLOGY Feature Data Set of the Lake Ontario 2023 ESI Geodatabase. It contains vector polygons and points representing FISH data for Lake Ontario. The study area includes the United States portion of Lake Ontario, covering the islands in New York: Association Island, Bass Island, Calf Island, Carl Island, Cherry Island, Eagle Island, Fox Island, Galloo Islands, Grenadier Island, Horse Island, Hoveys Island, Six Point Town, and Stony Island. Major Lake Ontario bays mapped include: Black River Bay, Blind Sodus Bay, Braddock Bay, Chaumont Bay, Guffin Bay, Irondequoit Bay, Henderson Bay, Little Sodus Bay, Mexico Bay, Port Bay, Sawyer Bay, and Sodus Bay. These data sets contain sensitive biological resource data for freshwater fish species in Lake Ontario. Vector polygons in this data set represent fish distribution, concentration areas, and spawning areas. Vector points in this data set represent fish spawning areas. Species-specific abundance, seasonality, status, life history, and source information are stored in associated data tables (described in Entity Attribute Overview below) designed to be used in conjunction with this spatial data layer. This data set is a portion of the ESI data for Lake Ontario. As a whole, the ESI data characterize the marine and coastal environments and wildlife by their sensitivity to spilled oil, and include information for three main components: shoreline habitats, sensitive biological resources, and human-use resources.

These feature classes reside within the BIOLOGY Feature Data Set of the Lake Erie - 2022 ESI Geodatabase. It contains vector polygons and points representing BIRDS data for Lake Erie. The study area includes the United States portion of Lake Erie, covering the coastal portions of Ohio, Pennsylvania, and New York from the Michigan/Ohio border to the west to the New York/Canada border to the east. This data set contains sensitive biological resource data for wading birds, shorebirds, waterfowl, raptors, diving birds, passerine birds, and gulls and terns in Lake Erie. Vector polygons in this data set represent bird nesting, migratory staging, and wintering sites. Species-specific abundance, seasonality, status, life history, and source information are stored in associated data tables (described in Entity Attribute Overview below) designed to be used in conjunction with this spatial data layer. This data set is a portion of the ESI data for Lake Erie. As a whole, the ESI data characterize the marine and coastal environments and wildlife by their sensitivity to spilled oil, and include information for three main components: shoreline habitats, sensitive biological resources, and human-use resources.