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Earth observing imagery sources used in this data release include (but are not limited to) optical imagery collections by: (1) the European Space Agency's Sentinel-2 mission and (2) the Plant Labs Planet Scope constellation, as well as synthetic aperture radar imagery collected by: (1) European Space Agency's Sentinel-1 mission; (2) the DLR (German Aerospace Agency) TerraSAR-X satellite (X-band), and (3) the Umbra Space satellite constellation (X-band).","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P97NFTDU","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.ASC557.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_ASC557","keyword":["Alaska","Animals/vertebrates","Biota","Cape Serdtse-Kamen","Carnivores","Chukchi Sea","Chukotka","Coastal ecosystems","Environment","Field inventory and monitoring","Image collections","Mammals","Marine ecosystems","Marine mammals","Migratory species","Odobenus rosmarus divergens","Pacific Walrus","Pinniped","Point Lay","Remote sensing","Russia","Satellite imagery","Seals/sea lions/walruses","Seasonal distribution","USGS:ASC557","Walrus","Wildlife"],"modified":"2023-09-14T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-171.7, 66.9, -163.0, 69.6","theme":["geospatial"],"title":"Pacific Walrus Coastal Haulout Occurrences Interpreted from Satellite Imagery, 2023"},"description":"This data release contains maps, geospatial files, and a table of the satellite imagery types with the dates when they were collected and examined to interpret the presence of, and area occupied by, walruses at terrestrial haulouts. 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The first product depicts change in land and water coverage and the second product highlights changes based on inundation zones (for example, water, intertidal-unvegetated, intertidal-vegetated, supratidal, and developed/shoreline protection). This product also includes recommended symbology for these data layers. 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We then projected future distributions of the species using data from four climate models: Community Climate System Model version 4 (CCSM4), Hadley Centre Global Environment Model version 2-Earth System (HadGEM2-ES), Model for Interdisciplinary Research on Climate version 5 (MIROC5), and Max Planck Institute Earth System Model, low resolution (MPI-ESM-LR).  We ran the climate models according to two greenhouse gas concentration pathways (RCP2.6 and RCP8.5).  Datasets in this file are the results for models RCP2.6 and RCP8.5 for the years 2050 and 2070.  It shows a comparison of ensembles of suitable bioclimatic conditions between present day and future day.  The dataset shows areas where ensembles agree and suitable conditions are stable (stable represented in green), future ensemble projects new suitable conditions (gain represented in yellow), present ensemble may be converted to unsuitable in the future (loss represented in red), and areas where conditions are unsuitable in the future (non represented in gray).","distribution":[{"@type":"dcat:Distribution","accessURL":"http://doi.org/10.5066/F7B27SGV","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.01db4134-3223-406f-ab88-6ba612317729.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_01db4134-3223-406f-ab88-6ba612317729","keyword":["Aneides hardii","Chiricahua Leopard Frog","Jemez Mountains Salamander","Lithobates chiricahuensis","Plethodon neomexicanus","Sacramento Mountain Salamander","USGS:01db4134-3223-406f-ab88-6ba612317729","amphibians","bioclimatic-envelope","biota","climatologyMeteorologyAtmosphere","external research support","geospatial datasets","herpetofauna"],"modified":"2026-08-19T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-112.5861, 31.3322, -106.4861, 35.4988","theme":["geospatial"],"title":"Projected future bioclimate-envelope suitability for amphibian species in South Central USA"},"description":"This dataset contains the result of the bioclimatic-envelope modeling of the three amphibian species -- the Sacramento Mountain Salamander (Aneides hardii), the Jemez Mountains Salamander (Plethodon neomexicanus), and the Chiricahua Leopard Frog (Lithobates chiricahuensis) -- in the South Central US using the downscaled data provided by WorldClim.  We used five species distribution models (SDM) including Generalized Linear Model, Random Forest, Boosted Regression Tree, Maxent, and Multivariate Adaptive Regression Splines (MARS) and ensembles to develop the present day distributions of the species based on climate-driven models alone.  We then projected future distributions of the species using data from four climate models: Community Climate System Model version 4 (CCSM4), Hadley Centre Global Environment Model version 2-Earth System (HadGEM2-ES), Model for Interdisciplinary Research on Climate version 5 (MIROC5), and Max Planck Institute Earth System Model, low resolution (MPI-ESM-LR).  We ran the climate models according to two greenhouse gas concentration pathways (RCP2.6 and RCP8.5).  Datasets in this file are the results for models RCP2.6 and RCP8.5 for the years 2050 and 2070.  It shows a comparison of ensembles of suitable bioclimatic conditions between present day and future day.  The dataset shows areas where ensembles agree and suitable conditions are stable (stable represented in green), future ensemble projects new suitable conditions (gain represented in yellow), present ensemble may be converted to unsuitable in the future (loss represented in red), and areas where conditions are unsuitable in the future (non represented in gray).","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/a436f8a5-d4d9-4d55-b36a-fb26d59fdbc3","harvest_record_raw":"https://catalog.data.gov/harvest_record/a436f8a5-d4d9-4d55-b36a-fb26d59fdbc3/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_01db4134-3223-406f-ab88-6ba612317729","keyword":["Aneides hardii","Chiricahua Leopard Frog","Jemez Mountains Salamander","Lithobates chiricahuensis","Plethodon neomexicanus","Sacramento Mountain Salamander","USGS:01db4134-3223-406f-ab88-6ba612317729","amphibians","bioclimatic-envelope","biota","climatologyMeteorologyAtmosphere","external research support","geospatial datasets","herpetofauna"],"last_harvested_date":"2026-08-22T01:19:56.896364","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"popularity":0,"publisher":"U.S. Geological Survey","slug":"projected-future-bioclimate-envelope-suitability-for-amphibian-species-in-south-central-us","spatial_centroid":{"lat":32.99884,"lon":-110.1461},"spatial_shape":{"coordinates":[[[-112.5861,31.3322],[-112.5861,35.4988],[-106.4861,35.4988],[-106.4861,31.3322],[-112.5861,31.3322]]],"type":"Polygon"},"theme":["geospatial"],"title":"Projected future bioclimate-envelope suitability for amphibian species in South Central USA","type":"dataset"},{"_score":9.201437,"_sort":[1787361517523,9.201437,0,"7f2deaef-5754-4e49-b1f9-d709f050b46f"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Rachel G Gidley","hasEmail":"mailto:rgidley@usgs.gov"},"description":"This data release accompanies a U.S. Geological Survey study on arroyo formation and sediment transport in the Stinking Water Creek Basin in Rio Blanco County, Colorado, which has undergone land-use change including rangeland grazing and energy development (oil exploration). 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This data release compiles data previously published in Reynolds and Richey (2023) from the 2008\u20132014 time interval with additional data through completion in 2020, as well as new information on the Gulf sediment trap time series (GMT). For more information, refer to the associated journal article by Richey and others (2026).","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P14TKHYR","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.9f2df387-7e84-45ab-9423-5aefaefff6b9.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_9f2df387-7e84-45ab-9423-5aefaefff6b9","keyword":["CTD measurement","USGS:9f2df387-7e84-45ab-9423-5aefaefff6b9","biota","ecology","environment","faunal and floral census (microscopic)","geoscientificInformation","marine geology","micropaleontology","oceans","plankton","protists","time series datasets"],"modified":"2026-08-18T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-90.3800, 27.5200, -89.4700, 27.9400","theme":["geospatial"],"title":"2008\u20132020 planktic foraminiferal assemblage data from subtropical Atlantic Ocean sediment traps"},"description":"Sediment trap time series studies collect data on planktic foraminiferal flux, assemblage composition, and geochemical responses to environmental variables, which are used in paleoceanographic research. 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In this data release, the eight videos were reanalyzed using IVyTools, which applies Space-Time Image Velocimetry (STIV) techniques to estimate surface water velocities and compute discharge.\nThe release includes: (1) per-site discharge station tables summarizing the midsection discharge computation at each measurement station; (2) per-site STIV velocity results tables containing the pixel-level velocity vectors computed by the STIV algorithm; (3) per-site STI (Space-Time Image) review tables documenting the STIV streak angles, auto-detected and manually corrected velocity magnitudes, and operator comments for each grid node; (4) summary comparison tables presenting IVyTools discharge estimates alongside VGC2020 reference values and uncertainty metrics (corresponding to Tables 2 and 3 in Engel and others, 2026); and (5) uncertainty contribution analysis data indicating the fractional contribution of each uncertainty component to total discharge variance for all eight sites (corresponding to Figure 6 in Engel and others, 2026).\nThis dataset supports reproducibility and transparency in image-based streamflow measurement and contributes to ongoing efforts to evaluate operator and software effects in video-based hydrometry. 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In this data release, the eight videos were reanalyzed using IVyTools, which applies Space-Time Image Velocimetry (STIV) techniques to estimate surface water velocities and compute discharge.\nThe release includes: (1) per-site discharge station tables summarizing the midsection discharge computation at each measurement station; (2) per-site STIV velocity results tables containing the pixel-level velocity vectors computed by the STIV algorithm; (3) per-site STI (Space-Time Image) review tables documenting the STIV streak angles, auto-detected and manually corrected velocity magnitudes, and operator comments for each grid node; (4) summary comparison tables presenting IVyTools discharge estimates alongside VGC2020 reference values and uncertainty metrics (corresponding to Tables 2 and 3 in Engel and others, 2026); and (5) uncertainty contribution analysis data indicating the fractional contribution of each uncertainty component to total discharge variance for all eight sites (corresponding to Figure 6 in Engel and others, 2026).\nThis dataset supports reproducibility and transparency in image-based streamflow measurement and contributes to ongoing efforts to evaluate operator and software effects in video-based hydrometry. 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