Ward, David H. (ORCID: 0000-0002-5242-2526) Hogrefe, Kyle R. 20220627 vector geospatial data, tabular digital data Mapping Data of Eelgrass (Zostera marina) Distribution, Alaska and Baja California, Mexico . Anchorage, Alaska U.S. Geological Survey, Alaska Science Center Suggested Citation: Ward, D.H., Hogrefe, K.R., 2022. Mapping data of eelgrass (Zostera marina) distribution, Alaska and Baja California, Mexico: U.S. Geological Survey data release, https://doi.org/10.5066/P9WEK4JI https://doi.org/10.5066/P9WEK4JI 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. Coastal waters along the Baja California Peninsula contain extensive beds of seagrass (eelgrass: Zostera marina and widgeongrass: Ruppia marina), but the status and trends of distribution are unknown. This dataset provides baseline information on the spatial extent and distribution of seagrass, salt marshes, and mangroves in Bahia San Quintin, Laguna Ojo de Liebre, and Laguna San Ignacio enabling a monitoring program for these coastal habitats that support many species including waterfowl. The creation of this dataset was a collaborative effort between the U.S. Geological Survey, Ducks Unlimited de Mexico, and the U.S Fish and Wildlife Service. 1992 2000 observed Complete None planned Coastal areas along the Baja California Peninsula, Mexico -116.1 -112.1 30.5 26.3 USGS Metadata Identifier USGS:ASC453 ISO 19115 Topic Category Biota Environment NASA GCMD Earth Science Keyword Thesaurus Angiosperms (flowering plants) Monocots Seagrass Macroalgae (seaweeds) Animals/Invertebrates Marine environment monitoring USGS CSA Biocomplexity Thesaurus Marine ecosystems Coastal ecosystems Estuarine ecosystems Seagrass beds USGS Thesaurus Field inventory and monitoring Animal and plant census Remote sensing None Eelgrass Zostera marina Widgeongrass Ruppia marina NGA GEOnet Names Server Mexico Baja California Baja California Sur Bahía San Quintín Laguna Ojo de Liebre Laguna San Ignacio None Seagrass Eelgrass Zostera marina Widgeongrass Ruppia marina ITIS Integrated Taxonomic Information System Unknown online database online ITIS-North America Taxonomic details retrieved May 11, 2022, from the Integrated Taxonomic Information System online database https://www.itis.gov https://doi.org/10.5066/F7KH0KBK Species were identified by trained observers in the field using physical characteristics. Kingdom Plantae Subkingdom Viridiplantae Infrakingdom Streptophyta Superdivision Embryophyta Division Tracheophyta Subdivision Spermatophytina Class Magnoliopsida Superorder Lilianae Order Alismatales Family Zosteraceae Genus Zostera Species Zostera marina TSN: 39074 Family Ruppiaceae Genus Ruppia Species Ruppia maritima TSN: 39063 No access constraints. No use constraints. We request that the suggested citation of this USGS data release be included in any publications that reference or utilize these data. U.S. Geological Survey, Alaska Science Center Mailing and Physical

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Anchorage Alaska 99508 USA 907-786-7000 gs-ak_asc_datamanagers@usgs.gov Hogrefe, K.R. Ward, D.H. Donnelly, T.F. Dau, N. 2014 journal article Remote Sensing 6(12):12447-12477 online Multidisciplinary Digital Publishing Institute (MDPI) Hogrefe, K.R., Ward, D.H., Donnelly, T.F., Dau, N., 2014. Establishing a baseline for regional scale monitoring of eelgrass (Zostera marina) habitat on the lower Alaska Peninsula. Remote Sensing 6(12):12447-12477. https://doi.org/10.3390/rs61212447 https://doi.org/10.3390/rs61212447 U.S. Geological Survey, Alaska Science Center unknown journal articles A full list of scientific publications that utilize eelgrass mapping data from the USGS Alaska Science Center is included with this data package, in the file "README_related_articles_reports_data.pdf" Using Landsat imagery and the process steps provided below, we were able to differentiate eelgrass from other cover types with an overall accuracy of 70-79%. See Ward et al. 2022 for details on accuracy assessment. Attribute values fall within expected ranges. Dataset is considered complete. Imagery from the Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) sensor series provided multispectral data at 30 m spatial resolution (Hogrefe et al 2014). U.S. Geological Survey Earth Resources Observation and Science Center (EROS) 2013 raster digital data Sioux Falls, South Dakota, USA U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center Downloaded in 2014 from USGS EarthExplorer https://earthexplorer.usgs.gov/ Query parameters and Scene Identifiers for all images used for analysis are provided in the table "remoteImage_identifiers_baja_ward.csv" included with this data package. https://www.usgs.gov/centers/eros online database 1992 2000 observed EROS_Landsat Landsat satellite imagery acquired between 1992 and 2000, used to classify eelgrass, salt marshes, and mangroves in waters of three bays along the west coast of the Baja California Peninsula, Mexico (Bahia San Quintin, Laguna Ojo de Liebre, and Laguna San Ignacio) METHODS - FIELD: Ground-truth data were collected during field surveys and are reported in a separate U.S. Geological Survey data releases (Ward 2022). Ground-truth data were collected at numerous points in bays over 9 to 19-day periods in late fall and early winter of 1998, 1999, 2005, and 2012 at 3 sites: Bahia San Quintin, Laguna Ojo de Liebre, and Laguna San Ignacio. In short, survey points were distributed across each of these embayments using a systematic design and accessed points by boat using a global positioning system (GPS) unit. Points were sampled by snorkeling in dry suits during high tide. At each point, substrate type and depth and percent cover of eelgrass and seaweeds were estimated within four 0.25 square meters quadrats. Unknown METHODS - DATA PROCESSING: We used the survey points to guide selection of training polygons for each classification category (Ozesmi and Bauer, 2002). This approach enabled the selection of training data across thousands of pixels in each of the images, greatly improving the accuracy of the classifications. These data were derived from satellite imagery (Landsat 5 TM) acquired in March-September 1992-2000 (EROS_Landsat). Image data were calibrated to at-sensor radiance, corrected for atmospheric path interference, and checked for georeferencing accuracy. The images were corrected for atmospheric interference using dark pixel subtraction. The imagery was classified into land cover categories of eelgrass, salt marsh, and mangrove. The classification was conducted using a combined Isodata (Unsupervised) / Maximum Likelihood (Supervised) methodology. The Isodata classification was used to identify 35 statistically distinct spectral classes which were then assigned to training classes for subsequent Maximum Likelihood analysis. Seagrass and seaweed distribution data were extracted from the raster grid and converted to vector data. ENVI 4.8 was used for all imagery processing and analysis while ArcGIS was used for some analysis and map preparation. Details of image acquisition, processing, and interpretation are provided in Hogrefe et al 2014. EROS_Landsat Unknown LITERATURE CITED: Hogrefe, K.R., Ward, D.H., Donnelly, T.F., Dau, N., 2014. Establishing a baseline for regional scale monitoring of eelgrass (Zostera marina) habitat on the lower Alaska Peninsula. Remote Sensing 6(12):12447-12477. https://doi.org/10.3390/rs61212447 Ozesmi, S.L., Bauer, M.E., 2002. Satellite remote sensing of wetlands. Wetlands Ecology and Management 10(5):381–402. https://doi.org/10.1023/A:1020908432489 Ward, D.H. 2022, Point sampling data for eelgrass (Zostera marina) and widgeongrass (Ruppia marina) abundance in embayments of the north Pacific coast of Baja California, Mexico, 1998-2012: U.S. Geological Survey data release, https://doi.org/10.5066/P9H4LBP3 Unknown Location names are local geographic place names of sampling areas and do not describe precise geographic points. Vector Universal Transverse Mercator 12 0.9996 -111.0 0 500000 0 coordinate pair 1 1 meters World Geodetic System of 1984 (WGS84) World Geodetic System of 1984 (WGS84) 6378137 298.257223563 remoteImage_identifiers_baja_ward.csv Table with query parameters and Landsat Scene Identifiers used to access and download each Landsat image analyzed from the USGS EarthExplorer https://earthexplorer.usgs.gov Presented in a Comma Separated Value (CSV) formatted table. Author defined Locations_Analyzed Place names of regions on the Baja California Peninsula, Mexico that were analyzed from the Landsat image. Author defined Place names of regions on the Baja California Peninsula that were analyzed from the Landsat image. Sensor Unique identifier of the Landsat satellite and sensor used to acquire the Landsat image. Author defined L5-TM Landsat 5 Thematic Mapper EROS_Landsat WRS2_Path Worldwide Reference System (WRS-2) 'path' coordinate of Landsat image. EROS_Landsat 36 39 WRS2_Row Worldwide Reference System (WRS-2) 'row' coordinate of Landsat image. EROS_Landsat 39 42 Date_Acquired Date of Landsat image acquisition Author defined 1992-09-05 2000-05-11 Date (YYYY-MM-DD) EROS_dataset_name Name of the dataset in the EROS database EROS_Landsat Name of the dataset in the EROS database. Landsat_Scene_Identifier Unique identifier for each Landsat image EROS_Landsat Unique identifier for each Landsat image. A concatenation of satellite ID, sensor, path, row, date, and receiving station. Landsat_Product_Identifier_L1 Unique identifier for each Landsat image EROS_Landsat Unique identifier for each Landsat image. A concatenation of satellite ID, sensor, path, row, date, and EROS imaging processing. eelgrass_landsatDerived_baja_ward.shp Vector polygon geospatial file delineating eelgrass beds in three bays along the west coast of the Baja California Peninsula, Mexico (Bahia San Quintin, Laguna San Ignacio, and Laguna Ojo de Liebre). Eelgrass beds were determined by interpretation of Landsat image data (Hogrefe et al 2014). Presented in Esri shapefile (SHP) format. Additionally, a JPG browse map is provided for convenience of viewing. Author defined Id Sequential numerical identifier of feature assigned by ArGIS Esri Sequential numerical identifier of feature grid_code Raster value from classified raster grid, generated by ArcGIS Esri 1 1 Location Name of the bay or connecting section of coastline. Author defined Bahia San Quintin Bahia San Quintin, Mexico (approximately 30.42 N, 115.96 W) NGA GEOnet Names Server Laguna Ojo de Liebre Laguna Ojo de Liebre, Mexico (also known as Scammon Bay; approximately 27.72 N, 114.18 W) NGA GEOnet Names Server Laguna San Ignacio Laguna San Ignacio, Mexico (approximately 26.84 N, 113.18 W) NGA GEOnet Names Server Shape_Length Length of polygon perimeter in internal units. Esri 100 964350 Shape_Area Area of feature in internal units. Esri 625 129512500 marsh_landsatDerived_baja_ward.shp Vector polygon geospatial file delineating salt marshes in waters of three bays along the west coast of the Baja California Peninsula, Mexico (Bahia San Quintin, Laguna San Ignacio, and Laguna Ojo de Liebre). Salt marshes were determined by interpretation of Landsat image data (Hogrefe et al 2014). Presented in Esri shapefile (SHP) format. Additionally, a JPG browse map is provided for convenience of viewing. Author defined Id Sequential numerical identifier of feature assigned by ArGIS Esri Sequential numerical identifier of feature grid_code Raster value from classified raster grid, generated by ArcGIS. Esri 1 1 Location Name of the bay or connecting section of coastline. Author defined Bahia San Quintin Bahia San Quintin, Mexico (approximately 30.42 N, 115.96 W) NGA GEOnet Names Server Laguna Ojo de Liebre Laguna Ojo de Liebre, Mexico (also known as Scammon Bay; approximately 27.72 N, 114.18 W) NGA GEOnet Names Server Laguna San Ignacio Laguna San Ignacio, Mexico (approximately 26.84 N, 113.18 W) NGA GEOnet Names Server Shape_Length Length of polygon perimeter in internal units. Esri 100 216800 Shape_Area Area of feature in internal units. Esri 625 15691875 mangrove_landsatDerived_baja_ward.shp Vector polygon geospatial file delineating mangroves in waters of three bays along the west coast of the Baja California Peninsula, Mexico (Bahia San Quintin, Laguna San Ignacio, and Laguna Ojo de Liebre). Mangroves were determined by interpretation of Landsat image data (Hogrefe et al 2014). Presented in Esri shapefile (SHP) format. Additionally, a JPG browse map is provided for convenience of viewing. Author defined Id Sequential numerical identifier of feature assigned by ArGIS Esri Sequential numerical identifier of feature grid_code Raster value from classified raster grid, generated by ArcGIS. Esri 1 1 Location Name of the bay or connecting section of coastline. Author defined Bahia San Quintin Bahia San Quintin, Mexico (approximately 30.42 N, 115.96 W) NGA GEOnet Names Server Laguna Ojo de Liebre Laguna Ojo de Liebre, Mexico (also known as Scammon Bay; approximately 27.72 N, 114.18 W) NGA GEOnet Names Server Laguna San Ignacio Laguna San Ignacio, Mexico (approximately 26.84 N, 113.18 W) NGA GEOnet Names Server Shape_Length Length of polygon perimeter in internal units. Esri 114 28443 Shape_Area Area of feature in internal units. Esri 812 3051623 U.S. Geological Survey USGS ScienceBase Team Mailing and Physical

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Denver Colorado 80225 USA 1-888-275-8747 sciencebase@usgs.gov The U.S. Geological Survey, Alaska Science Center is the authoritative source of these data, distributed by ScienceBase (a USGS Trusted Digital Repository). Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey, no warranty expressed or implied is made regarding the display or utility of the data for other purposes or on all computer systems, nor shall the act of distribution constitute any such warranty. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. SHP, CSV Vector geospatial data in SHP format; tabular data in CSV format; FGDC metadata in XML and HTML formats. https://doi.org/10.5066/P9WEK4JI None 20241228 U.S. Geological Survey, Alaska Science Center Mailing and Physical

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Anchorage Alaska 99508 USA 907-786-7000 gs-ak_asc_datamanagers@usgs.gov FGDC Biological Data Profile of the Content Standard for Digital Geospatial Metadata (CSDGM) FGDC-STD-001.1-1999