Timeline / Data.gov — Environment Datasets
changed Source changed
A new raw object was archived. Both versions are preserved. 2388 line(s) added, 2059 line(s) removed.
Evidence
| Source | Data.gov — Environment Datasets |
|---|---|
| Agency | Data.gov |
| URL | https://api.gsa.gov/technology/datagov/v4/search?q=environment&sort=last_harvested_date&per_page=100&api_key=${DATAGOV_API_KEY} |
| Observed by | Civic Memory, directly, on 2026-09-28T00:19:52+00:00 |
| Content type | application/json |
| Current object |
714f2d704c5046def49dc928058046a415df292b31b7bc89a8803db82ef8f6f4
download raw
metadata
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| Previous object |
81f6af9f4189e64157c018e80ef784f3a4daaf39a6fe1390d0d7e67a0a9e7b1c
download raw
metadata
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What changed derived
This diff is not evidence. It was produced by
civic-memory.diff_engine 1.1.0 at
2026-09-28T00:19:52+00:00 by normalizing the two archived objects above. The
objects are authoritative; this reading of them can be regenerated or deleted
without loss. 2388 line(s) added, 2059 line(s) removed.
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Thompson", + "hasEmail": "mailto:rcthomps@usgs.gov" + }, + "description": "This data set contains arrays of water velocity collected on selected transects of the Missouri River \nbelow Gavin's Point Dam near River Mile 769.8.", + "distribution": [ + { + "@type": "dcat:Distribution", + "accessURL": "https://doi.org/10.5066/P9TDN8FK", + "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.b769dea1-2cd6-4336-bcd1-232466b91b32.xml", + "format": "XML", + "mediaType": "text/xml", + "title": "Original Metadata" + } + ], + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_b769dea1-2cd6-4336-bcd1-232466b91b32", + "keyword": [ + "Accoustic Doppler Current Profile data", + "Missouri River", + "Nebraska", + "South Dakota", + "USGS:b769dea1-2cd6-4336-bcd1-232466b91b32", + "Water Velocity", + "environment", + "geoscientificInformation", + "inlandWaters" + ], + "modified": "2026-02-17T00:00:00Z", + "publisher": { + "@type": "org:Organization", + "name": "U.S. Geological Survey" + }, + "spatial": "-96.912755, 42.701457, -96.822603, 42.736215", + "theme": [ + "geospatial" + ], + "title": "Postconstruction water velocity arrays collected at selected transects on the Missouri River downstream from Gavins Point Dam near River Mile 769.8" + }, + "description": "This data set contains arrays of water velocity collected on selected transects of the Missouri River \nbelow Gavin's Point Dam near River Mile 769.8.", + "distribution_titles": [ + "Digital Data", + "Original Metadata" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/abf5a8d9-f18a-4888-82d5-5a9722ee83f6", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/abf5a8d9-f18a-4888-82d5-5a9722ee83f6/raw", + "has_download": true, + "has_spatial": true, + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_b769dea1-2cd6-4336-bcd1-232466b91b32", + "keyword": [ + "Accoustic Doppler Current Profile data", + "Missouri River", + "Nebraska", + "South Dakota", + "USGS:b769dea1-2cd6-4336-bcd1-232466b91b32", + "Water Velocity", + "environment", + "geoscientificInformation", + "inlandWaters" + ], + "last_harvested_date": "2026-09-28T00:17:15.784175", + "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" + }, + "parent_identifier": null, + "popularity": 1, + "publisher": "U.S. Geological Survey", + "slug": "postconstruction-water-velocity-arrays-collected-at-selected-transects-on-the-missouri-riv", + "spatial_centroid": { + "lat": 42.7153602, + "lon": -96.8766942 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + -96.912755, + 42.701457 + ], + [ + -96.912755, + 42.736215 + ], + [ + -96.822603, + 42.736215 + ], + [ + -96.822603, + 42.701457 + ], + [ + -96.912755, + 42.701457 + ] + ] + ], + "type": "Polygon" + }, + "theme": [ + "geospatial" + ], + "title": "Postconstruction water velocity arrays collected at selected transects on the Missouri River downstream from Gavins Point Dam near River Mile 769.8", + "type": "dataset" + }, + { + "_score": 7.771073, + "_sort": [ + 1790554627100, + 7.771073, + 0, + "c74bab1d-95ab-411a-9272-8b28c2562a35" + ], + "dcat": { + "accessLevel": "public", + "bureauCode": [ + "010:12" + ], + "contactPoint": { + "@type": "vcard:Contact", + "fn": "Laura E. Luongo", + "hasEmail": "mailto:lharrington@usgs.gov" + }, + "description": "This data release contains the Land Use/Land Cover (LULC) data available in the Neponset River Basin StreamStats application. The U.S. Environmental Protection Agency (EPA) used the hydrologic response unit (HRU) approach outlined in EPA (2023) to derive the LULC raster from Massachusetts 2016 LULC data from MassGIS (2019), and the Natural Resources Conservation Service Soil Survey Geographic aggregated soil data from MassGIS (2022) and General Soil Map from NRCS (2022).\nThis release contains a complete thematic raster for the Neponset River watershed as a tag image file (.tif) format raster. 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No data are provided here. The geospatial outlines and herd size estimates of Chukchi Sea autumn walrus haulouts, interpreted from Satellite imagery, have been combined into a single updated U.S. Geological Survey data release: https://doi.org/10.5066/P9CSM0KN\n 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. Estimates of the land area occupied by walruses are provided based on interpretation by experienced image reviewers. The images are from a variety of Earth observing satellite imagery sources collected over coastal areas of the Chukchi Sea (northwestern Alaska and northeastern Russia) in autumn when walruses come ashore in large numbers to rest in the absence of sea ice. 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": "2024-06-29T00:00:00Z", + "publisher": { + "@type": "org:Organization", + "name": "U.S. Geological Survey" + }, + "spatial": "-171.7, 66.9, -163.0, 69.6", + "theme": [ + "geospatial" + ], + "title": "SUPERSEDED: Pacific Walrus Coastal Haulout Occurrences Interpreted from Satellite Imagery, 2023" + }, + "description": "This data release has been SUPERSEDED. 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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_titles": [ + "Digital Data", + "Original Metadata" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/903d5edc-5cfa-4dee-a09e-2cd52f694731", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/903d5edc-5cfa-4dee-a09e-2cd52f694731/raw", + "has_download": true, + "has_spatial": true, + "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" + ], + "last_harvested_date": "2026-09-28T00:14:09.397061", + "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" + }, + "parent_identifier": null, + "popularity": 1, + "publisher": "U.S. Geological Survey", + "slug": "pacific-walrus-coastal-haulout-occurrences-interpreted-from-satellite-imagery-2023", + "spatial_centroid": { + "lat": 67.97999999999999, + "lon": -168.21999999999997 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + -171.7, + 66.9 + ], + [ + -171.7, + 69.6 + ], + [ + -163.0, + 69.6 + ], + [ + -163.0, + 66.9 + ], + [ + -171.7, + 66.9 + ] + ] + ], + "type": "Polygon" + }, + "theme": [ + "geospatial" + ], + "title": "SUPERSEDED: Pacific Walrus Coastal Haulout Occurrences Interpreted from Satellite Imagery, 2023", + "type": "dataset" + }, + { + "_score": 6.107067, + "_sort": [ + 1790554210492, + 6.107067, + 6, + "d4f53c92-ef00-4049-9da6-8fab8b7501a3" + ], + "dcat": { + "accessLevel": "public", + "bureauCode": [ + "010:12" + ], + "contactPoint": { + "@type": "vcard:Contact", + "fn": "U.S. Geological Survey, Alaska Science Center", + "hasEmail": "mailto:gs-ak_asc_datamanagers@usgs.gov" + }, + "description": "These data are daily summary checklists of all bird species observed at U.S. Geological Survey, Alaska Science Center (ASC) field camps. Data include species observation details such as observers, dates, location, and number of individuals seen. Field camps were located in Northern, Western, Interior, Southwest, Southcentral, and Southeast Alaska, Baja California Sur Mexico, and northern Russia.", + "distribution": [ + { + "@type": "dcat:Distribution", + "accessURL": "https://doi.org/10.5066/P950QX28", + "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.ASC367.xml", + "format": "XML", + "mediaType": "text/xml", + "title": "Original Metadata" + } + ], + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_ASC367", + "keyword": [ + "Alaska", + "Albatrosses/Petrels and Allies", + "Animals/Vertebrates", + "Bahia San Quintin", + "Baja California Sur", + "Biota", + "Birds", + "Coastal ecosystems", + "Cranes", + "Ducks/Geese/Swans", + "Eagles/Falcons/Hawks and Allies", + "Environment", + "Fowl", + "Game birds", + "Laguna Ojo de Liebre", + "Laguna San Ignacio", + "Loons", + "Mexico", + "Migration (organisms)", + "Migratory birds", + "Migratory rates/routes", + "Migratory species", + "Owls", + "Perching Birds", + "Raptors", + "Russia", + "Sakha Republic", + "Sandpipers", + "Santa Rosalia", + "Seabirds", + "Seasonal distribution", + "Shorebirds", + "Songbirds", + "Tundra ecosystems", + "USGS:ASC367", + "United States", + "Waders/Gulls/Auks and Allies", + "Waterfowl", + "Wetland ecosystems", + "Wildlife" + ], + "modified": "2025-03-26T00:00:00Z", + "publisher": { + "@type": "org:Organization", + "name": "U.S. Geological Survey" + }, + "spatial": "-177.18, 18.64, 175.78, 77.76", + "theme": [ + "geospatial" + ], + "title": "Bird Species Checklists from USGS Alaska Science Center Field Camps" + }, + "description": "These data are daily summary checklists of all bird species observed at U.S. Geological Survey, Alaska Science Center (ASC) field camps. Data include species observation details such as observers, dates, location, and number of individuals seen. Field camps were located in Northern, Western, Interior, Southwest, Southcentral, and Southeast Alaska, Baja California Sur Mexico, and northern Russia.", + "distribution_titles": [ + "Digital Data", + "Original Metadata" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/8625c7f6-9e3a-433f-abc4-aea237c62116", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/8625c7f6-9e3a-433f-abc4-aea237c62116/raw", + "has_download": true, + "has_spatial": true, + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_ASC367", + "keyword": [ + "Alaska", + "Albatrosses/Petrels and Allies", + "Animals/Vertebrates", + "Bahia San Quintin", + "Baja California Sur", + "Biota", + "Birds", + "Coastal ecosystems", + "Cranes", + "Ducks/Geese/Swans", + "Eagles/Falcons/Hawks and Allies", + "Environment", + "Fowl", + "Game birds", + "Laguna Ojo de Liebre", + "Laguna San Ignacio", + "Loons", + "Mexico", + "Migration (organisms)", + "Migratory birds", + "Migratory rates/routes", + "Migratory species", + "Owls", + "Perching Birds", + "Raptors", + "Russia", + "Sakha Republic", + "Sandpipers", + "Santa Rosalia", + "Seabirds", + "Seasonal distribution", + "Shorebirds", + "Songbirds", + "Tundra ecosystems", + "USGS:ASC367", + "United States", + "Waders/Gulls/Auks and Allies", + "Waterfowl", + "Wetland ecosystems", + "Wildlife" + ], + "last_harvested_date": "2026-09-28T00:10:10.492076", + "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" + }, + "parent_identifier": null, + "popularity": 6, + "publisher": "U.S. Geological Survey", + "slug": "bird-species-checklists-from-usgs-alaska-science-center-field-camps", + "spatial_centroid": { + "lat": 42.288, + "lon": -35.996 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + -177.18, + 18.64 + ], + [ + -177.18, + 77.76 + ], + [ + 175.78, + 77.76 + ], + [ + 175.78, + 18.64 + ], + [ + -177.18, + 18.64 + ] + ] + ], + "type": "Polygon" + }, + "theme": [ + "geospatial" + ], + "title": "Bird Species Checklists from USGS Alaska Science Center Field Camps", + "type": "dataset" + }, + { + "_score": 9.515972, + "_sort": [ + 1790554120553, + 9.515972, + 0, + "d3fbc2a4-d0ac-49c6-ba7b-9d1f42115926" + ], + "dcat": { + "accessLevel": "public", + "bureauCode": [ + "010:12" + ], + "contactPoint": { + "@type": "vcard:Contact", + "fn": "Kristin Trippe", + "hasEmail": "mailto:kristin.trippe@ars.usda.gov" + }, + "description": "The objective of this project was to evaluate the potential for biochar soil amendments to mitigate agricultural drought by characterizing their impacts on soil hydraulics and plant growth across a range of agricultural soil conditions. This data set contains soil water infiltration measurements using Beerkan infiltration rings in four Oregon agricultural soils amended with biochar. Gasified biochars made from wheat straw (AgEnergy, Spokane, WA) and conifer wood (BioLogical, Philomath, OR) were tilled into soils at experimental stations in Madras (loam), Pendleton (silt loam), Aurora (sandy loam), and Klamath Falls (loamy sand). The biochars were incorporated by tillage in fall 2016 to a depth of 12 cm at rates equating to 0, 9, 18, and 36 Mg/ha (about 0.5, 1, 2, and 4% by mass in the tillage zone), with three replicate plots per treatment. In April and May 2017 infiltration was measured by inserting small rings into the soil surface and determining the time required for repeated 10 0mL volumes of water to infiltrate. From each infiltration experiment we estimated steady-state infiltration rate, and where possible we also estimated field saturated soil hydraulic conductivity (Kfs). Diagnostic plots demonstrated that in about half of the measurements sets, Kfs could be estimated by modeling infiltration as a two-term function of sorptivity and Kfs. In the remaining plots, additional unknown factors that influenced infiltration prevented estimation of Kfs, possibly due to air entrapment, soil layering, or ring insertion effects in the remaining experiments. Increasing biochar amendment rates led to an increase in infiltration rate only for the CW biochar at the silt loam site. For all other soil-biochar combinations no patterns in infiltration rate were detectable.", + "distribution": [ + { + "@type": "dcat:Distribution", + "accessURL": "https://doi.org/10.5066/P1ZZ2X44", + "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.5b0ed25fe4b0c39c934b15e2.xml", + "format": "XML", + "mediaType": "text/xml", + "title": "Original Metadata" + } + ], + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_5b0ed25fe4b0c39c934b15e2", + "keyword": [ + "Klamath Falls", + "Madras", + "Oregon", + "Pacific Northwest", + "Pendleton", + "USGS:5b0ed25fe4b0c39c934b15e2", + "Willamette", + "climatologyMeteorologyAtmosphere", + "environment", + "farming", + "infiltration", + "percolation", + "porosity", + "soil moisture" + ], + "modified": "2026-09-25T00:00:00Z", + "publisher": { + "@type": "org:Organization", + "name": "U.S. Geological Survey" + }, + "spatial": "-124.2773, 41.8368, -116.8945, 46.0732", + "theme": [ + "geospatial" + ], + "title": "Soil water infiltration in four biochar-amended soils from Oregon" + }, + "description": "The objective of this project was to evaluate the potential for biochar soil amendments to mitigate agricultural drought by characterizing their impacts on soil hydraulics and plant growth across a range of agricultural soil conditions. This data set contains soil water infiltration measurements using Beerkan infiltration rings in four Oregon agricultural soils amended with biochar. Gasified biochars made from wheat straw (AgEnergy, Spokane, WA) and conifer wood (BioLogical, Philomath, OR) were tilled into soils at experimental stations in Madras (loam), Pendleton (silt loam), Aurora (sandy loam), and Klamath Falls (loamy sand). The biochars were incorporated by tillage in fall 2016 to a depth of 12 cm at rates equating to 0, 9, 18, and 36 Mg/ha (about 0.5, 1, 2, and 4% by mass in the tillage zone), with three replicate plots per treatment. In April and May 2017 infiltration was measured by inserting small rings into the soil surface and determining the time required for repeated 10 0mL volumes of water to infiltrate. From each infiltration experiment we estimated steady-state infiltration rate, and where possible we also estimated field saturated soil hydraulic conductivity (Kfs). Diagnostic plots demonstrated that in about half of the measurements sets, Kfs could be estimated by modeling infiltration as a two-term function of sorptivity and Kfs. In the remaining plots, additional unknown factors that influenced infiltration prevented estimation of Kfs, possibly due to air entrapment, soil layering, or ring insertion effects in the remaining experiments. Increasing biochar amendment rates led to an increase in infiltration rate only for the CW biochar at the silt loam site. 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Data location: GeoPlatform (\"https://www.geoplatform.gov/\") and EPA Environmental Dataset Gateway (https://edg.epa.gov/). Abstract: We apply the hydrologic landscapes (HL) concept to assess the hydrologic vulnerability of the western United States (U.S.) to projected climate conditions. Our goal is to understand the potential impacts for stakeholder-defined interests across large geographic areas. The basic assumption of the HL approach is that catchments that share similar physical and climatic characteristics are expected to have similar hydrologic characteristics. We map climate vulnerability by integrating the HL approach into a retrospective analysis of historical data to assess variability in future climate projections and hydrology, which includes temperature, precipitation, potential evapotranspiration, snow accumulation, climatic moisture, surplus water, and seasonality of water surplus. Projections that are not within two-standard deviations of the historical decadal average contribute to the vulnerability index for each metric. The resulting vulnerability maps show that temperature and potential evapotranspiration are consistently projected to have high vulnerability indices for the western U.S. Precipitation vulnerability is not as spatially-uniform as temperature. The highest elevation areas with snow are projected to experience significant changes in snow accumulation. The seasonality vulnerability map shows that specific mountainous areas in the West are most prone to changes in seasonality, whereas many transitional terrains are moderately susceptible. This paper illustrates how the HL approach can help assess climatic and hydrologic vulnerability across large spatial scales. 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Data location: GeoPlatform (\"https://www.geoplatform.gov/\") and EPA Environmental Dataset Gateway (https://edg.epa.gov/). Abstract: We apply the hydrologic landscapes (HL) concept to assess the hydrologic vulnerability of the western United States (U.S.) to projected climate conditions. Our goal is to understand the potential impacts for stakeholder-defined interests across large geographic areas. The basic assumption of the HL approach is that catchments that share similar physical and climatic characteristics are expected to have similar hydrologic characteristics. We map climate vulnerability by integrating the HL approach into a retrospective analysis of historical data to assess variability in future climate projections and hydrology, which includes temperature, precipitation, potential evapotranspiration, snow accumulation, climatic moisture, surplus water, and seasonality of water surplus. Projections that are not within two-standard deviations of the historical decadal average contribute to the vulnerability index for each metric. The resulting vulnerability maps show that temperature and potential evapotranspiration are consistently projected to have high vulnerability indices for the western U.S. Precipitation vulnerability is not as spatially-uniform as temperature. The highest elevation areas with snow are projected to experience significant changes in snow accumulation. The seasonality vulnerability map shows that specific mountainous areas in the West are most prone to changes in seasonality, whereas many transitional terrains are moderately susceptible. This paper illustrates how the HL approach can help assess climatic and hydrologic vulnerability across large spatial scales. By combining the HL concept and climate vulnerability analyses, we provide a planning approach that could allow resource managers to consider how future climate conditions may impact important economic and conservation resources. Purpose: These data were created in support of the US EPA’s ACE CIVA 2.3, Task Project (QAPP: E-WED-0030854). However, these climate data and hydrologic landscape summaries should have broad applicability for hydrological, geomorphic, or ecological modeling, management, and restoration. 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Superfund features are managed by regional teams of geospatial professionals and remedial program managers (RPMs), and SEGS harvests regional data on a weekly basis to refresh the national dataset and feature services.", + "distribution": [ + { + "@type": "dcat:Distribution", + "accessURL": "https://services.arcgis.com/cJ9YHowT8TU7DUyn/arcgis/rest/services/FAC_Superfund_Institutional_Control_Boundaries_EPA_Public/FeatureServer", + "describedByType": "application/octet-stream", + "mediaType": "text/html", + "title": "EPA GeoPlatform Hosted Feature Service" + }, + { + "@type": "dcat:Distribution", + "describedByType": "application/octet-stream", + "description": "Zipped File Geodatabase including all Superfund Boundary Layers.", + "downloadURL": "https://edg.epa.gov/data/PUBLIC/OLEM/OLEM-OSRTI/NPL_Boundaries.zip", + "format": "ZIP", + "mediaType": "application/zip", + "title": "Superfund Boundary Download Package" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://www.epa.gov/geospatial", + "describedByType": "application/octet-stream", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "accessURL": "http://www.epa.gov/superfund/", + "describedByType": "application/octet-stream", + "mediaType": "text/html" + } + ], + "identifier": "https://edg.epa.gov/WAFer_harvest/ISO/olem-harvest_Superfund_NPL_IC_BOUNDARIES_SF.xml", + "issued": "2018-03-06T00:00:00.000+00:00", + "keyword": [ + "United States", + "Cleanup", + "Contaminant", + "Environment", + "Facilities", + "Health", + "Human", + "Impact", + "Management", + "Monitoring", + "Regulatory", + "Remediation", + "Sites", + "Toxics", + "020:108", + "FAC", + "SEGS" + ], + "landingPage": "https://www.epa.gov/geospatial", + "language": [ + "eng" + ], + "license": "https://creativecommons.org/publicdomain/zero/1.0/", + "modified": "2026-09-26T09:14:40.000+00:00", + "publisher": { + "@type": "org:Organization", + "name": "U.S. EPA Office of Environmental Information (OEI)" + }, + "spatial": "-67.356526,37.861155,-112.180178,48.220306", + "theme": [ + "geospatial" + ], + "title": "NPL Superfund Institutional Control Boundaries (EPA)" + }, + "description": "This GIS dataset contains polygons depicting U.S. EPA Superfund Institutional Control boundaries. 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Superfund features are managed by regional teams of geospatial professionals and remedial program managers (RPMs), and SEGS harvests regional data on a weekly basis to refresh the national dataset and feature services.", + "distribution_titles": [ + "EPA GeoPlatform Hosted Feature Service", + "Superfund Boundary Download Package" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/3ef7f194-bff8-4dfc-afaa-04951aa5df6d", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/3ef7f194-bff8-4dfc-afaa-04951aa5df6d/raw", + "harvest_record_transformed": "https://catalog.data.gov/harvest_record/3ef7f194-bff8-4dfc-afaa-04951aa5df6d/transformed", + "has_download": true, + "has_spatial": true, + "identifier": "https://edg.epa.gov/WAFer_harvest/ISO/olem-harvest_Superfund_NPL_IC_BOUNDARIES_SF.xml", + "keyword": [ + "United States", + "Cleanup", + "Contaminant", + "Environment", + "Facilities", + "Health", + "Human", + "Impact", + "Management", + "Monitoring", + "Regulatory", + "Remediation", + "Sites", + "Toxics", + "020:108", + "FAC", + "SEGS" + ], + "last_harvested_date": "2026-09-27T20:37:25.917471", + "organization": { + "aliases": [ + "EPA" + ], + "code_repo_exempt": false, + "code_repo_url": null, + "description": null, + "id": "82b85475-f85d-404a-b95b-89d1a42e9f6b", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/epa.png", + "name": "U.S. Environmental Protection Agency", + "organization_type": "Federal Government", + "slug": "epa" + }, + "parent_identifier": null, + "popularity": 17, + "publisher": "U.S. EPA Office of Environmental Information (OEI)", + "slug": "npl-superfund-institutional-control-boundaries-epa-bce47", + "spatial_centroid": { + "lat": 42.0048154, + "lon": -85.2859868 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + -67.356526, + 37.861155 + ], + [ + -67.356526, + 48.220306 + ], + [ + -112.180178, + 48.220306 + ], + [ + -112.180178, + 37.861155 + ], + [ + -67.356526, + 37.861155 + ] + ] + ], + "type": "Polygon" + }, + "theme": [ + "geospatial" + ], + "title": "NPL Superfund Institutional Control Boundaries (EPA)", + "type": "dataset" + }, + { + "_score": 9.26772, + "_sort": [ + 1790541445038, + 9.26772, + 7, + "297e0aed-27b5-4e24-860c-88d8c6c8d6c8" + ], + "dcat": { + "@type": "dcat:Dataset", + "accessLevel": "public", + "accrualPeriodicity": "R/P1W", + "contactPoint": { + "@type": "vcard:Contact", + "fn": "U.S. Environmental Protection Agency, Office of Pesticide Programs", + "hasEmail": "mailto:connolly.jennifer@epa.gov" + }, + "describedByType": "application/octet-stream", + "description": "The Endangered Species Act (ESA) provides a program for the conservation of threatened and endangered species and the habitats in which they are found. 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OPP determines if ESA-listed species or their designated critical habitat may be affected by pesticide products. Pesticide products that “may affect” an ESA-listed species or its designated critical habitat may be subject to additional regulation. Species ranges represent anywhere an individual of the listed species could be found based on the best available information at the time of delineation. As defined in ESA, critical habitat delineates habitat characteristics in specific geographical areas and may be occupied or unoccupied by a threatened or endangered species at the time of listing. These areas must contain physical or biological features essential to conservation of a species and may require special management considerations or protection. Critical habitat may also include areas that are not currently occupied by the species but that may be needed for their recovery. 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The last download of the species locations occurred in November 2020.", + "distribution": [ + { + "@type": "dcat:Distribution", + "accessURL": "https://services.arcgis.com/cJ9YHowT8TU7DUyn/arcgis/rest/services/Critical_Habitat/FeatureServer", + "describedByType": "application/octet-stream", + "mediaType": "text/html", + "title": "EPA GeoPlatform Hosted Feature Service" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://epa.maps.arcgis.com/home/item.html?id=d46156cc921d4b41923c70c280b82458", + "describedByType": "application/octet-stream", + "mediaType": "text/html", + "title": "EPA Geoplatform Item page" + } + ], + "identifier": "https://edg.epa.gov/WAFer_harvest/ISO/ocspp-geo-records_Endangered_Species_Critical_Habitat_Areas.xml", + "issued": "2022-10-01T00:00:00.000+00:00", + "keyword": [ + "United States", + "Agriculture", + "Biology", + "Conservation", + "Ecology", + "Ecosystem", + "Environment", + "Exposure", + "Hazards", + "Land", + "Modeling", + "Pesticides", + "Regulatory", + "Risk", + "Toxics", + "Water", + "020:083", + "Downloadable Data" + ], + "language": [], + "license": "https://creativecommons.org/publicdomain/zero/1.0/", + "modified": "2026-09-26T08:06:08.000+00:00", + "publisher": { + "@type": "org:Organization", + "name": "U.S. Environmental Protection Agency, Office of Pesticide Programs" + }, + "spatial": "179.776438,-14.548618,-179.146415,74.024896", + "theme": [ + "geospatial" + ], + "title": "Critical Habitat for Endangered Species" + }, + "description": "The Endangered Species Act (ESA) provides a program for the conservation of threatened and endangered species and the habitats in which they are found. 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Range areas represent more generalized habitat where species are or could be found based on the best available information. For some species, best available information is based on site specific surveys. For others, it will be historical location information based on political boundaries. These areas are, therefore, less geographically explicit than critical habitat. Consideration of both the species range and critical habitat ensures the conservation of the ecosystems upon which endangered and threatened species depend. To support EPA’s implementation of ESA, critical habitat and range data for species listed under ESA Section 7 were obtained by the US EPA from the USFWS Environmental Conservation Online System (ECOS) database in November 2020. These data were supplemented with areas provided by NOAA’s National Marine Fisheries Service (NMFS) where NOAA has species authority. For NMFS species not found in either location, a request was made directly to the NMFS scientists. 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7.6413245, + 7.63967, 9, "3e3f1ae3-38c3-4d58-af23-0d368264d848" ], @@ -3118,10 +5442,10 @@ "type": "dataset" }, { - "_score": 10.440749, + "_score": 10.446892, "_sort": [ 1790470891818, - 10.440749, + 10.446892, 0, "efc721ec-c9db-451d-a3f1-d3308818daa8" ], @@ -3252,10 +5576,10 @@ "type": "dataset" }, { - "_score": 7.8374085, + "_score": 7.836327, "_sort": [ 1790470873086, - 7.8374085, + 7.836327, 2, "7a6aec59-3678-486c-917f-5a0a75ac2d86" ], @@ -3412,10 +5736,10 @@ "type": "dataset" }, { - "_score": 10.266516, + "_score": 10.266861, "_sort": [ 1790470866583, - 10.266516, + 10.266861, 0, "8ba3b909-4729-4bf2-b377-e196ee659b00" ], @@ -3544,10 +5868,10 @@ "type": "dataset" }, { - "_score": 10.358255, + "_score": 10.375296, "_sort": [ 1790470761074, - 10.358255, + 10.375296, 0, "faeca83b-d32d-415d-921d-46d8095cba16" ], @@ -3676,10 +6000,10 @@ "type": "dataset" }, { - "_score": 8.698966, + "_score": 8.69755, "_sort": [ 1790470734612, - 8.698966, + 8.69755, 0, "cfaff99d-099a-4d4c-a7c7-0465b6d22924" ], @@ -3794,10 +6118,10 @@ "type": "dataset" }, { - "_score": 10.42285, + "_score": 10.432232, "_sort": [ 1790470727438, - 10.42285, + 10.432232, 2, "592bf83c-b187-4d3d-8699-c48ef2def528" ], @@ -3922,10 +6246,10 @@ "type": "dataset" }, { - "_score": 8.938049, + "_score": 8.942291, "_sort": [ 1790470669941, - 8.938049, + 8.942291, 0, "64f176d3-a8c1-4cc2-940a-61d3491a2288" ], @@ -4070,10 +6394,10 @@ "type": "dataset" }, { - "_score": 9.500395, + "_score": 9.510656, "_sort": [ 1790470502982, - 9.500395, + 9.510656, 0, "618c6785-c1dd-49cc-8257-fa3ba6954bf2" ], @@ -4135,1999 +6459,4 @@ ], "title": "Laboratory Notes: Scanned Laboratory Notebook Pages for the following project - Ecological implications of mangrove forest migration in the southeastern US (2012-2-13)" }, - "description": "Winter climate change has the potential to have a large impact on coastal wetlands in the southeastern U.S. Warmer winter temperatures and reductions in the intensity of freeze events would likely lead to mangrove forest range expansion and salt marsh displacement in parts of the U.S. Gulf of Mexico and Atlantic coast. The objective of this research was to better understand some of the ecological implications of mangrove forest migration and salt marsh displacement. The potential ecological effects of mangrove migration are diverse ranging from important biotic impacts (e.g., coastal fisheries, land bird migration; colonial nesting wading birds) to ecosystem stability (e.g., response to sea level rise and drought; habitat loss; coastal protection) to biogeochemical processes (e.g., carbon storage; water quality). In this research, our focus was on the impact of mangrove forest migration on coastal wetland soil processes and the consequent implications for coastal wetland responses to sea level rise, ecosystem resilience, and carbon storage. Our study specifically addressed the following questions: (1) How do ecological processes and ecosystem properties differ between salt marshes and mangrove forests; (2) As mangrove forests develop, how do their ecosystem properties change and how do these properties compare to salt marshes; (3) How do plant-soil interactions across mangrove forest structural gradients differ among three distinct locations that span the northern Gulf of Mexico; and (4) What are the implications of mangrove forest encroachment and development into salt marsh in terms of soil development, carbon and nitrogen storage, and soil strength? To address these questions, we utilized the salt marshes and natural mangrove forest structural gradients present at three distinct locations in the northern Gulf of Mexico: Cedar Key (Florida), Port Fourchon (Louisiana), and Port Aransas (Texas). Each of these locations represents a distinct combination of climate-driven abiotic conditions. We quantified relationships between plant community composition and structure, soil and porewater physicochemical properties, hydroperiod, and climatic conditions. The suite of measurements that we collected provide initial insights into how different geographic areas of an ecotone, with different environmental conditions, may be impacted by mangrove forest expansion and development, and how these changes may alter the supply of specific ecosystem goods and services. \nThis file includes the scanned laboratory notes associated with this project.\nThis work was conducted via a collaborative effort between scientists at the U.S. Geological Survey National Wetland Research Center and the Department of Biology of the University of Louisiana at Lafayette.", - "distribution_titles": [ - "Digital Data", - "Original Metadata" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/eb9f2a86-118a-49eb-9018-418c24b7ee2f", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/eb9f2a86-118a-49eb-9018-418c24b7ee2f/raw", - "has_download": true, - "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_545bf9b3e4b009f8aec9b5a5", - "keyword": [ - "Florida", - "Gulf of Mexico", - "Louisiana", - "Texas", - "USGS:545bf9b3e4b009f8aec9b5a5", - "climate change", - "ecology", - "ecosystem monitoring", - "environment", - "forest", - "mangrove", - "migration", - "moisture", - "soil", - "wetlands" - ], - "last_harvested_date": "2026-09-27T00:55:02.982569", - "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" - }, - "parent_identifier": null, - "popularity": 0, - "publisher": "U.S. Geological Survey", - "slug": "laboratory-notes-scanned-laboratory-notebook-pages-for-the-following-project-ecological-13", - "spatial_centroid": { - "lat": 28.377999999999997, - "lon": -91.49598 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -97.1401, - 27.83 - ], - [ - -97.1401, - 29.2 - ], - [ - -83.0298, - 29.2 - ], - [ - -83.0298, - 27.83 - ], - [ - -97.1401, - 27.83 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Laboratory Notes: Scanned Laboratory Notebook Pages for the following project - Ecological implications of mangrove forest migration in the southeastern US (2012-2-13)", - "type": "dataset" - }, - { - "_score": 8.413109, - "_sort": [ - 1790470427274, - 8.413109, - 0, - "0f524498-bdd3-444f-9550-1532c3900d6f" - ], - "dcat": { - "accessLevel": "public", - "bureauCode": [ - "010:12" - ], - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Nicholas M Enwright", - "hasEmail": "mailto:enwrightn@usgs.gov" - }, - "description": "The Barrier Island Comprehensive Monitoring (BICM) program was developed by Louisiana’s Coastal Protection and Restoration Authority (CPRA) and is implemented as a component of the System Wide Assessment and Monitoring Program (SWAMP). The program uses both historical data and contemporary data collections to assess and monitor changes in the aerial and subaqueous extent of islands, habitat types, sediment texture and geotechnical properties, environmental processes, and vegetation composition. Examples of BICM datasets include still and video aerial photography for documenting shoreline changes, shoreline positions, habitat mapping, land change analyses, light detection and ranging (lidar) surveys for topographic elevations, single-beam and swath bathymetry, and sediment grab samples. For more information about the BICM program, see Kindinger and others (2013). \nThe U.S. Geological Survey, Wetland and Aquatic Research Center provides support to the BICM program through the development of habitat map products using aerial imagery and lidar elevation data and assessing change in habitats over time. These data provide a snapshot of barrier island habitats and can be combined with other past and/or future maps to monitor these valuable natural resources over time. Previous efforts of this habitat mapping program included developing habitat maps for 2008 and 2015–2016 for the following BICM regions (Enwright and others, 2020): 1) West Chenier; 2) East Chenier; 3) Acadiana Bays (only Marsh Island); 4) Early Lafourche Delta; 5) Late Lafourche Delta; 6) Modern Delta (only Chaland Headland and Shell Island); and 7) Chandeleur Islands. Additionally, a habitat change analysis was conducted comparing reaches mapped in 2008 and 2015–2016. The current effort of this habitat mapping program includes developing habitat maps for 2021 for the previously mentioned regions. A habitat change analysis will be conducted comparing reaches mapped 2015–2016 and 2021. The BICM program has developed two habitat classification schemes which include a detailed 15-class habitat scheme and a general eight-class habitat scheme. The detailed scheme was developed specifically for this habitat mapping effort and builds off the general scheme used in previous BICM habitat mapping efforts (Fearnley and others, 2009). The additional classes developed in the detailed scheme are primarily used to further delineate various dune habitats, separate marsh and mangrove, and distinguish between beach and unvegetated barrier flat habitats. To ensure comparability between this effort and previous BICM map products, we have crosswalked the detailed classes to general habitat classes previously used by Fearnley and others (2009). \nIn other words, the general habitat classes included in these products were not directly interpreted using aerial imagery and lidar elevation data. Thus, we recommend only using these general habitat classes for analyses that include previous BICM habitat maps (1996–2005). For more information about the BICM program, see Kindinger and others (2013). For more details on BICM habitat classes, see the Entity and Attribute Information section of the metadata. Please consult the accompanying readME.txt file for information and recommendations on the contents of this dataset (i.e., dataset and recommended symbology). For more information about the BICM program, see Kindinger and others (2013). \nReferences:\nKindinger, J.L., Buster, N.A., Flocks, J.G., Bernier, J.C., and Kulp, M.A., 2013, Louisiana Barrier Island Comprehensive Monitoring (BICM) program summary report—Data and analyses 2006 through 2010: U.S. Geological Survey Open-File Report 2013–1083, 86 p., at https://pubs.usgs.gov/of/2013/1083/.\nEnwright, N.M., SooHoo, W.M., Dugas, J.L., Conzelmann, C.P., Laurenzano, C., Lee, D.M., Mouton, K., and Stelly, S.J., 2020, Louisiana Barrier Island Comprehensive Monitoring Program—Mapping habitats in beach, dune, and intertidal environments along the Louisiana Gulf of Mexico shoreline, 2008 and 2015–16: U.S. Geological Survey Open-File Report 2020–1030, 57 p., https://doi.org/10.3133/ofr20201030.\nFearnley, S., Brien, L., Martinez, L., Miner, M., Kulp, M., and Penland, S., 2009, Chenier Plain, South-Central Louisiana, and Chandeleur Islands, Habitat mapping and change analysis 1996 to 2005, Part 1—Methods for habitat mapping and change analysis 1996 to 2005—Louisiana Barrier Island Comprehensive Monitoring Program (BICM) 5: New Orleans, University of New Orleans, Pontchartrain Institute for Environmental Sciences, 11 p.", - "distribution": [ - { - "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/P1ZQP7SN", - "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.68505a2cd4be025b9e8c6b6a.xml", - "format": "XML", - "mediaType": "text/xml", - "title": "Original Metadata" - } - ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_68505a2cd4be025b9e8c6b6a", - "keyword": [ - "Gulf of America", - "Louisiana", - "Louisiana Coastal", - "Modern Delta Region", - "Plaquemines Parish", - "USGS:68505a2cd4be025b9e8c6b6a", - "barrier islands", - "barrier vegetation", - "beach", - "coastal wetlands", - "dune", - "environment", - "farming", - "habitat map", - "mangrove", - "marsh", - "planningCadastre", - "remote sensing", - "scrub/shrub" - ], - "modified": "2026-09-17T00:00:00Z", - "publisher": { - "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-89.8837, 29.1798, -89.4280, 29.3839", - "theme": [ - "geospatial" - ], - "title": "Louisiana Barrier Island Comprehensive Monitoring Program – 2021 habitat map, Modern Delta Region (ver. 2.0, September 2026)" - }, - "description": "The Barrier Island Comprehensive Monitoring (BICM) program was developed by Louisiana’s Coastal Protection and Restoration Authority (CPRA) and is implemented as a component of the System Wide Assessment and Monitoring Program (SWAMP). The program uses both historical data and contemporary data collections to assess and monitor changes in the aerial and subaqueous extent of islands, habitat types, sediment texture and geotechnical properties, environmental processes, and vegetation composition. Examples of BICM datasets include still and video aerial photography for documenting shoreline changes, shoreline positions, habitat mapping, land change analyses, light detection and ranging (lidar) surveys for topographic elevations, single-beam and swath bathymetry, and sediment grab samples. For more information about the BICM program, see Kindinger and others (2013). \nThe U.S. Geological Survey, Wetland and Aquatic Research Center provides support to the BICM program through the development of habitat map products using aerial imagery and lidar elevation data and assessing change in habitats over time. These data provide a snapshot of barrier island habitats and can be combined with other past and/or future maps to monitor these valuable natural resources over time. Previous efforts of this habitat mapping program included developing habitat maps for 2008 and 2015–2016 for the following BICM regions (Enwright and others, 2020): 1) West Chenier; 2) East Chenier; 3) Acadiana Bays (only Marsh Island); 4) Early Lafourche Delta; 5) Late Lafourche Delta; 6) Modern Delta (only Chaland Headland and Shell Island); and 7) Chandeleur Islands. Additionally, a habitat change analysis was conducted comparing reaches mapped in 2008 and 2015–2016. The current effort of this habitat mapping program includes developing habitat maps for 2021 for the previously mentioned regions. A habitat change analysis will be conducted comparing reaches mapped 2015–2016 and 2021. The BICM program has developed two habitat classification schemes which include a detailed 15-class habitat scheme and a general eight-class habitat scheme. The detailed scheme was developed specifically for this habitat mapping effort and builds off the general scheme used in previous BICM habitat mapping efforts (Fearnley and others, 2009). The additional classes developed in the detailed scheme are primarily used to further delineate various dune habitats, separate marsh and mangrove, and distinguish between beach and unvegetated barrier flat habitats. To ensure comparability between this effort and previous BICM map products, we have crosswalked the detailed classes to general habitat classes previously used by Fearnley and others (2009). \nIn other words, the general habitat classes included in these products were not directly interpreted using aerial imagery and lidar elevation data. Thus, we recommend only using these general habitat classes for analyses that include previous BICM habitat maps (1996–2005). For more information about the BICM program, see Kindinger and others (2013). For more details on BICM habitat classes, see the Entity and Attribute Information section of the metadata. Please consult the accompanying readME.txt file for information and recommendations on the contents of this dataset (i.e., dataset and recommended symbology). For more information about the BICM program, see Kindinger and others (2013). \nReferences:\nKindinger, J.L., Buster, N.A., Flocks, J.G., Bernier, J.C., and Kulp, M.A., 2013, Louisiana Barrier Island Comprehensive Monitoring (BICM) program summary report—Data and analyses 2006 through 2010: U.S. Geological Survey Open-File Report 2013–1083, 86 p., at https://pubs.usgs.gov/of/2013/1083/.\nEnwright, N.M., SooHoo, W.M., Dugas, J.L., Conzelmann, C.P., Laurenzano, C., Lee, D.M., Mouton, K., and Stelly, S.J., 2020, Louisiana Barrier Island Comprehensive Monitoring Program—Mapping habitats in beach, dune, and intertidal environments along the Louisiana Gulf of Mexico shoreline, 2008 and 2015–16: U.S. Geological Survey Open-File Report 2020–1030, 57 p., https://doi.org/10.3133/ofr20201030.\nFearnley, S., Brien, L., Martinez, L., Miner, M., Kulp, M., and Penland, S., 2009, Chenier Plain, South-Central Louisiana, and Chandeleur Islands, Habitat mapping and change analysis 1996 to 2005, Part 1—Methods for habitat mapping and change analysis 1996 to 2005—Louisiana Barrier Island Comprehensive Monitoring Program (BICM) 5: New Orleans, University of New Orleans, Pontchartrain Institute for Environmental Sciences, 11 p.", - "distribution_titles": [ - "Digital Data", - "Original Metadata" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/91f4fa35-a0c9-4c30-8895-1246a701f24a", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/91f4fa35-a0c9-4c30-8895-1246a701f24a/raw", - "has_download": true, - "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_68505a2cd4be025b9e8c6b6a", - "keyword": [ - "Gulf of America", - "Louisiana", - "Louisiana Coastal", - "Modern Delta Region", - "Plaquemines Parish", - "USGS:68505a2cd4be025b9e8c6b6a", - "barrier islands", - "barrier vegetation", - "beach", - "coastal wetlands", - "dune", - "environment", - "farming", - "habitat map", - "mangrove", - "marsh", - "planningCadastre", - "remote sensing", - "scrub/shrub" - ], - "last_harvested_date": "2026-09-27T00:53:47.274481", - "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" - }, - "parent_identifier": null, - "popularity": 0, - "publisher": "U.S. Geological Survey", - "slug": "louisiana-barrier-island-comprehensive-monitoring-program-2021-habitat-map-modern-delta-re", - "spatial_centroid": { - "lat": 29.26144, - "lon": -89.70142000000001 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -89.8837, - 29.1798 - ], - [ - -89.8837, - 29.3839 - ], - [ - -89.428, - 29.3839 - ], - [ - -89.428, - 29.1798 - ], - [ - -89.8837, - 29.1798 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Louisiana Barrier Island Comprehensive Monitoring Program – 2021 habitat map, Modern Delta Region (ver. 2.0, September 2026)", - "type": "dataset" - }, - { - "_score": 9.086859, - "_sort": [ - 1790470404474, - 9.086859, - 0, - "be0ef096-7975-4ffc-8d91-459c3339e3ce" - ], - "dcat": { - "accessLevel": "public", - "bureauCode": [ - "010:12" - ], - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Lindsay E. F. Hunt", - "hasEmail": "mailto:lhunt@usgs.gov" - }, - "description": "This dataset is the sixth installment of a yearly connectivity update for forested habitat within the Great Lakes Restoration Initiative's (GLRI) Terrestrial Habitats & Connectivity (TH&C) work group's Pilot Area. The Pilot Area is a region of the northern Great Lakes Basin between Ashland, WI and the Keweenaw Peninsula and is bounded by Lake Superior in the north and the basin boundary in the south, including a 70 km buffer. Each year the TH&C selects project proposals for funding within the pilot area. These proposals involve either restoration, research, or land acquisition aimed at improving or increasing forest connectivity in this area. The intended purpose of each year’s update is to understand the effects of funded projects on the groundwork and help inform the location and purpose of future project proposals. The post-fiscal year 2025 forest connectivity maps serve as an additional time step for comparison from each previous fiscal year into the future. \nTo create the post FY25 installment of GLRI's Terrestrial Habitats & Connectivity work group's pilot area yearly connectivity maps, we identified the geospatial locations where restoration work benefitting forested habitats was completed throughout FY25. These locations were then assigned the lowest resistance value. Then using the forest habitat resistance layer from Great Lakes Restoration Initiative's Terrestrial Habitats and Connectivity Work group's Pilot Area's post-fiscal year 2025 we overwrote the post FY24 resistance values with the resistance values assigned to the FY25 locations where work was done. This analysis produced two connectivity maps: a cumulative current map and a normalized current map. The cumulative current map shows where potential movement pathways between forests are located within the pilot area, while the normalized current map shows where obstructed movement, diffuse movement, and channelized movement occurs within the pilot area. These maps provide important information on how restoration efforts from FY21, FY22, FY23, FY24, and FY25 in the pilot area are affecting forest habitat connectivity.", - "distribution": [ - { - "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/P14MMKBI", - "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.6a42901e1ba49b09ad17da03.xml", - "format": "XML", - "mediaType": "text/xml", - "title": "Original Metadata" - } - ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_6a42901e1ba49b09ad17da03", - "keyword": [ - "Connectivity", - "Forest Habitat", - "Great Lakes", - "Northern Wisconsin/Michigan", - "USGS:6a42901e1ba49b09ad17da03", - "biota", - "dispersal (organisms)", - "environment", - "habitat fragmentation", - "imageryBaseMapsEarthCover", - "land use change", - "remote sensing", - "structure" - ], - "modified": "2026-09-24T00:00:00Z", - "publisher": { - "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-92.7750, 45.2500, -86.3710, 48.2097", - "theme": [ - "geospatial" - ], - "title": "Great Lakes Restoration Initiative's Terrestrial Habitats & Connectivity Work Group's Pilot Area's Post-Fiscal Year 2025 Forest Habitat Connectivity" - }, - "description": "This dataset is the sixth installment of a yearly connectivity update for forested habitat within the Great Lakes Restoration Initiative's (GLRI) Terrestrial Habitats & Connectivity (TH&C) work group's Pilot Area. The Pilot Area is a region of the northern Great Lakes Basin between Ashland, WI and the Keweenaw Peninsula and is bounded by Lake Superior in the north and the basin boundary in the south, including a 70 km buffer. Each year the TH&C selects project proposals for funding within the pilot area. These proposals involve either restoration, research, or land acquisition aimed at improving or increasing forest connectivity in this area. The intended purpose of each year’s update is to understand the effects of funded projects on the groundwork and help inform the location and purpose of future project proposals. The post-fiscal year 2025 forest connectivity maps serve as an additional time step for comparison from each previous fiscal year into the future. \nTo create the post FY25 installment of GLRI's Terrestrial Habitats & Connectivity work group's pilot area yearly connectivity maps, we identified the geospatial locations where restoration work benefitting forested habitats was completed throughout FY25. These locations were then assigned the lowest resistance value. Then using the forest habitat resistance layer from Great Lakes Restoration Initiative's Terrestrial Habitats and Connectivity Work group's Pilot Area's post-fiscal year 2025 we overwrote the post FY24 resistance values with the resistance values assigned to the FY25 locations where work was done. This analysis produced two connectivity maps: a cumulative current map and a normalized current map. The cumulative current map shows where potential movement pathways between forests are located within the pilot area, while the normalized current map shows where obstructed movement, diffuse movement, and channelized movement occurs within the pilot area. These maps provide important information on how restoration efforts from FY21, FY22, FY23, FY24, and FY25 in the pilot area are affecting forest habitat connectivity.", - "distribution_titles": [ - "Digital Data", - "Original Metadata" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/5422c2a9-4fa8-430c-a53d-81bdd06b1016", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/5422c2a9-4fa8-430c-a53d-81bdd06b1016/raw", - "has_download": true, - "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_6a42901e1ba49b09ad17da03", - "keyword": [ - "Connectivity", - "Forest Habitat", - "Great Lakes", - "Northern Wisconsin/Michigan", - "USGS:6a42901e1ba49b09ad17da03", - "biota", - "dispersal (organisms)", - "environment", - "habitat fragmentation", - "imageryBaseMapsEarthCover", - "land use change", - "remote sensing", - "structure" - ], - "last_harvested_date": "2026-09-27T00:53:24.474463", - "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" - }, - "parent_identifier": null, - "popularity": 0, - "publisher": "U.S. Geological Survey", - "slug": "great-lakes-restoration-initiatives-terrestrial-habitats-amp-connectivity-work-groups-pilo-e7121", - "spatial_centroid": { - "lat": 46.43388, - "lon": -90.21340000000001 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -92.775, - 45.25 - ], - [ - -92.775, - 48.2097 - ], - [ - -86.371, - 48.2097 - ], - [ - -86.371, - 45.25 - ], - [ - -92.775, - 45.25 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Great Lakes Restoration Initiative's Terrestrial Habitats & Connectivity Work Group's Pilot Area's Post-Fiscal Year 2025 Forest Habitat Connectivity", - "type": "dataset" - }, - { - "_score": 9.613821, - "_sort": [ - 1790470384979, - 9.613821, - 0, - "c4170fa3-939e-496d-a857-9731e41d87d4" - ], - "dcat": { - "accessLevel": "public", - "bureauCode": [ - "010:12" - ], - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Andy Bock", - "hasEmail": "mailto:abock@usgs.gov" - }, - "description": "The National Hydrologic Geospatial Fabric Reference and Derived Hydrofabrics is a geospatial dataset of connected rivers, streams, lakes, catchments, hydrologic locations, and relevant attributes to support multi-scale and integrative hydrologic modeling and analysis.\nThis child dataset contains features and attributes representing the National Hydrologic Geospatial Fabric Refactored Hydrofabric. The Refactored Hydrofabric is a processed version of the Reference Hydrofabric with a more uniform distribution of catchment size. The complexity of different models requires flexibility to create different spatial levels of resolution and detail. Catchments with flowpath-lengths shorter than the user-specified minimum length threshold that increase data volume and compute cost but don't add hydrologic fidelity have been consolidated into larger ones. Catchments whose flowpath lengths are longer than the user-specified maximum flowpath-length threshold are split apart to provide uniform fidelity and better represent network outlets such as streamgages. When refactoring, key hydrologic locations like stream gages are preserved precisely, unless they are specified specifically as split events.\nThis item contains an Open Geospatial Consortium geopackage (gpkg) containing refactored flowlines, catchments, and other layers for all of Conterminous United States CONUS (refactor_CONUS.gpkg). See the processing steps for specific refactoring details.", - "distribution": [ - { - "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/P9NFPB5S", - "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.61fbfdced34e622189cb1b0a.xml", - "format": "XML", - "mediaType": "text/xml", - "title": "Original Metadata" - } - ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_61fbfdced34e622189cb1b0a", - "keyword": [ - "Geographic Information Systems", - "Hydrologic Response Units", - "Hydrologic modeling", - "Points of Interest", - "Routing Network", - "USGS:61fbfdced34e622189cb1b0a", - "environment", - "geoscientificInformation", - "inlandWaters" - ], - "modified": "2026-09-24T00:00:00Z", - "publisher": { - "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-124.7337, 24.6304, -66.9496, 52.8800", - "theme": [ - "geospatial" - ], - "title": "National Hydrologic Geospatial Fabric Refactored Hydrofabric" - }, - "description": "The National Hydrologic Geospatial Fabric Reference and Derived Hydrofabrics is a geospatial dataset of connected rivers, streams, lakes, catchments, hydrologic locations, and relevant attributes to support multi-scale and integrative hydrologic modeling and analysis.\nThis child dataset contains features and attributes representing the National Hydrologic Geospatial Fabric Refactored Hydrofabric. The Refactored Hydrofabric is a processed version of the Reference Hydrofabric with a more uniform distribution of catchment size. The complexity of different models requires flexibility to create different spatial levels of resolution and detail. Catchments with flowpath-lengths shorter than the user-specified minimum length threshold that increase data volume and compute cost but don't add hydrologic fidelity have been consolidated into larger ones. Catchments whose flowpath lengths are longer than the user-specified maximum flowpath-length threshold are split apart to provide uniform fidelity and better represent network outlets such as streamgages. When refactoring, key hydrologic locations like stream gages are preserved precisely, unless they are specified specifically as split events.\nThis item contains an Open Geospatial Consortium geopackage (gpkg) containing refactored flowlines, catchments, and other layers for all of Conterminous United States CONUS (refactor_CONUS.gpkg). See the processing steps for specific refactoring details.", - "distribution_titles": [ - "Digital Data", - "Original Metadata" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/5ce2a524-b4e4-4a7c-a960-065aa548f0fc", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/5ce2a524-b4e4-4a7c-a960-065aa548f0fc/raw", - "has_download": true, - "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_61fbfdced34e622189cb1b0a", - "keyword": [ - "Geographic Information Systems", - "Hydrologic Response Units", - "Hydrologic modeling", - "Points of Interest", - "Routing Network", - "USGS:61fbfdced34e622189cb1b0a", - "environment", - "geoscientificInformation", - "inlandWaters" - ], - "last_harvested_date": "2026-09-27T00:53:04.979454", - "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" - }, - "parent_identifier": null, - "popularity": 0, - "publisher": "U.S. Geological Survey", - "slug": "national-hydrologic-geospatial-fabric-refactored-hydrofabric", - "spatial_centroid": { - "lat": 35.930240000000005, - "lon": -101.62006 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -124.7337, - 24.6304 - ], - [ - -124.7337, - 52.88 - ], - [ - -66.9496, - 52.88 - ], - [ - -66.9496, - 24.6304 - ], - [ - -124.7337, - 24.6304 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "National Hydrologic Geospatial Fabric Refactored Hydrofabric", - "type": "dataset" - }, - { - "_score": 10.322443, - "_sort": [ - 1790470292050, - 10.322443, - 0, - "81e5e55c-faeb-46d2-859e-0475af612e5b" - ], - "dcat": { - "accessLevel": "public", - "bureauCode": [ - "010:12" - ], - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Cody Hudson", - "hasEmail": "mailto:chudson@intera.com" - }, - "description": "Daily streamflow and reservoir water elevation data for modeled locations in the Red River Basin. Values reported are for 18 different GCM (Global Climate Model) / RCP (Representative Concentration Pathway) / GDM Downscaling scenarios. Climate data from each scenario was input into a Variable Infiltration Capacity (VIC) model, that output flow values. These values were then input into RiverWare, to determine the impacts on regulated flows, lake levels and water availability. RiverWare was used for this project, because of its ability to simulate water use, reservoir operations, and local/interstate regulations.", - "distribution": [ - { - "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.21429/C91599", - "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.57d84d1ae4b090824ff9ac7b.xml", - "format": "XML", - "mediaType": "text/xml", - "title": "Original Metadata" - } - ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_57d84d1ae4b090824ff9ac7b", - "keyword": [ - "Climate Change", - "Oklahoma", - "Red River", - "RiverWare", - "USGS:57d84d1ae4b090824ff9ac7b", - "Water Availability", - "environment" - ], - "modified": "2026-09-23T00:00:00Z", - "publisher": { - "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-99.9612, 33.7317, -94.6297, 35.6655", - "theme": [ - "geospatial" - ], - "title": "RiverWare Daily Simulated values of Streamflow from 2006-2099: Oklahoma" - }, - "description": "Daily streamflow and reservoir water elevation data for modeled locations in the Red River Basin. Values reported are for 18 different GCM (Global Climate Model) / RCP (Representative Concentration Pathway) / GDM Downscaling scenarios. Climate data from each scenario was input into a Variable Infiltration Capacity (VIC) model, that output flow values. These values were then input into RiverWare, to determine the impacts on regulated flows, lake levels and water availability. RiverWare was used for this project, because of its ability to simulate water use, reservoir operations, and local/interstate regulations.", - "distribution_titles": [ - "Digital Data", - "Original Metadata" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/59b7ae13-b980-452b-ba0e-ba20a3f31439", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/59b7ae13-b980-452b-ba0e-ba20a3f31439/raw", - "has_download": true, - "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_57d84d1ae4b090824ff9ac7b", - "keyword": [ - "Climate Change", - "Oklahoma", - "Red River", - "RiverWare", - "USGS:57d84d1ae4b090824ff9ac7b", - "Water Availability", - "environment" - ], - "last_harvested_date": "2026-09-27T00:51:32.050796", - "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" - }, - "parent_identifier": null, - "popularity": 0, - "publisher": "U.S. Geological Survey", - "slug": "riverware-daily-simulated-values-of-streamflow-from-2006-2099-oklahoma", - "spatial_centroid": { - "lat": 34.505219999999994, - "lon": -97.82860000000001 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -99.9612, - 33.7317 - ], - [ - -99.9612, - 35.6655 - ], - [ - -94.6297, - 35.6655 - ], - [ - -94.6297, - 33.7317 - ], - [ - -99.9612, - 33.7317 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "RiverWare Daily Simulated values of Streamflow from 2006-2099: Oklahoma", - "type": "dataset" - }, - { - "_score": 4.813553, - "_sort": [ - 1790470273412, - 4.813553, - 0, - "2b991e1f-2b8f-45e0-99c2-aec7a26b77e7" - ], - "dcat": { - "accessLevel": "public", - "bureauCode": [ - "010:12" - ], - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Tabitha A Graves", - "hasEmail": "mailto:tgraves@usgs.gov" - }, - "description": "This data release contains the citation details, abstracts, and expert annotations of 235 publications on the topic of the potential effects of oil and gas development on pollinating insects in the western United States.\nPublications were collected through a structured literature search and a semi-automated content analysis. We developed a search string designed to pull relevant papers from Scopus and Web of Science. We used a set of benchmark publications identified by experts that were known to be relevant to the topic to refine the search string. The search returned 1,435 unique publications. Text mining of the title, abstract, and keywords quantified the relevancy of each paper to the topic and was used to discard the least relevant papers. We divided the remaining 731 publications into ten disturbance-based categories. The publications went through a three-step review process to remove irrelevant papers and to annotate relevant papers with key information related to the disturbance category. Lastly, text mining of the full manuscripts using the KWICer R code (Bailey and others 2026) was used to count the number of mentions of key words and phrases related to disturbance type, pollinator taxa, effect on pollinators, geographic location, ecosystem type, and study methodology.\nThe annotated bibliography contains 235 unique publications across the 10 disturbances categories: Air and chemical pollution (87 publications), air turbulence (4), dust (6), habitat loss and fragmentation (23), invasive plants (52), light pollution (37), noise pollution (6), oil and gas (7), roads (38), and soil compaction and trampling (10). The publications date from 1992 to 2026 and are mostly scientific articles (220) with some review papers (13), one editorial material, and one brief report. Full-manuscript text mining results are summarized in a set of figures that show the publication year, ecosystem type, and geographic area, as well as matrices that show the frequency and co-occurrence of pollinator taxa, disturbance type, and effect on pollinators in the body of literature. Together with the annotated bibliography, these elements provide key information that can help streamline regulatory processes related to oil and gas development on public lands.\nBailey, L.N., Varner, D.M., Whipple, S.E., 2026, KWICer: Producing an annotated bibliography from a set of PDFs by quantifying keywords, (Version 1.0.0): U.S. Geological Survey software release, https://doi.org/10.5066/P1476GUY.", - "distribution": [ - { - "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/P14A5GRG", - "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.6a8619cc1ba49b21c50f4f5e.xml", - "format": "XML", - "mediaType": "text/xml", - "title": "Original Metadata" - } - ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_6a8619cc1ba49b21c50f4f5e", - "keyword": [ - "Argentina", - "Austria", - "Belarus", - "Belgium", - "Bolivia", - "Brazil", - "Canada", - "Chad", - "Chile", - "China", - "Costa Rica", - "Czech Republic", - "Denmark", - "Estonia", - "Finland", - "France", - "Georgia", - "Germany", - "Ghana", - "Greece", - "Guinea", - "Hungary", - "India", - "Indonesia", - "Iran", - "Ireland", - "Israel", - "Italy", - "Japan", - "Jordan", - "Kenya", - "Latvia", - "Lesotho", - "Libya", - "Lithuania", - "Luxembourg", - "Madagascar", - "Maldives", - "Mexico", - "Monaco", - "Mongolia", - "Nepal", - "Netherlands", - "Niger", - "Norway", - "Pakistan", - "Panama", - "Poland", - "Portugal", - "Romania", - "Russia", - "Seychelles", - "Singapore", - "Slovakia", - "Slovenia", - "South Africa", - "Spain", - "Sri Lanka", - "Sweden", - "Switzerland", - "Taiwan", - "Thailand", - "Turkey", - "USGS:6a8619cc1ba49b21c50f4f5e", - "Ukraine", - "United Kingdom", - "United States", - "Venezuela", - "Zimbabwe", - "air pollution", - "air turbulence", - "biota", - "dust pollution", - "energy resources", - "environment", - "habitat alteration and disturbance", - "habitat fragmentation", - "invasive species", - "light pollution", - "natural gas resources", - "natural resource extraction", - "natural resource management", - "noise pollution", - "oil resources", - "pollination", - "pollinators", - "roads", - "soil compaction", - "soil resources" - ], - "modified": "2026-09-22T00:00:00Z", - "publisher": { - "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-180.0000, -90.0000, 180.0000, 90.0000", - "theme": [ - "geospatial" - ], - "title": "Potential effects of oil and gas development on pollinating insects in the western United States: An annotated bibliography produced through a structured literature search and semi-automated content analysis" - }, - "description": "This data release contains the citation details, abstracts, and expert annotations of 235 publications on the topic of the potential effects of oil and gas development on pollinating insects in the western United States.\nPublications were collected through a structured literature search and a semi-automated content analysis. We developed a search string designed to pull relevant papers from Scopus and Web of Science. We used a set of benchmark publications identified by experts that were known to be relevant to the topic to refine the search string. The search returned 1,435 unique publications. Text mining of the title, abstract, and keywords quantified the relevancy of each paper to the topic and was used to discard the least relevant papers. We divided the remaining 731 publications into ten disturbance-based categories. The publications went through a three-step review process to remove irrelevant papers and to annotate relevant papers with key information related to the disturbance category. Lastly, text mining of the full manuscripts using the KWICer R code (Bailey and others 2026) was used to count the number of mentions of key words and phrases related to disturbance type, pollinator taxa, effect on pollinators, geographic location, ecosystem type, and study methodology.\nThe annotated bibliography contains 235 unique publications across the 10 disturbances categories: Air and chemical pollution (87 publications), air turbulence (4), dust (6), habitat loss and fragmentation (23), invasive plants (52), light pollution (37), noise pollution (6), oil and gas (7), roads (38), and soil compaction and trampling (10). The publications date from 1992 to 2026 and are mostly scientific articles (220) with some review papers (13), one editorial material, and one brief report. Full-manuscript text mining results are summarized in a set of figures that show the publication year, ecosystem type, and geographic area, as well as matrices that show the frequency and co-occurrence of pollinator taxa, disturbance type, and effect on pollinators in the body of literature. 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The objective of this research was to better understand some of the ecological implications of mangrove forest migration and salt marsh displacement. The potential ecological effects of mangrove migration are diverse ranging from important biotic impacts (e.g., coastal fisheries, land bird migration; colonial nesting wading birds) to ecosystem stability (e.g., response to sea level rise and drought; habitat loss; coastal protection) to biogeochemical processes (e.g., carbon storage; water quality). In this research, our focus was on the impact of mangrove forest migration on coastal wetland soil processes and the consequent implications for coastal wetland responses to sea level rise, ecosystem resilience, and carbon storage. Our study specifically addressed the following questions: (1) How do ecological processes and ecosystem properties differ between salt marshes and mangrove forests; (2) As mangrove forests develop, how do their ecosystem properties change and how do these properties compare to salt marshes; (3) How do plant-soil interactions across mangrove forest structural gradients differ among three distinct locations that span the northern Gulf of Mexico; and (4) What are the implications of mangrove forest encroachment and development into salt marsh in terms of soil development, carbon and nitrogen storage, and soil strength? To address these questions, we utilized the salt marshes and natural mangrove forest structural gradients present at three distinct locations in the northern Gulf of Mexico: Cedar Key (Florida), Port Fourchon (Louisiana), and Port Aransas (Texas). Each of these locations represents a distinct combination of climate-driven abiotic conditions. 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The objective of this research was to better understand some of the ecological implications of mangrove forest migration and salt marsh displacement. The potential ecological effects of mangrove migration are diverse ranging from important biotic impacts (e.g., coastal fisheries, land bird migration; colonial nesting wading birds) to ecosystem stability (e.g., response to sea level rise and drought; habitat loss; coastal protection) to biogeochemical processes (e.g., carbon storage; water quality). In this research, our focus was on the impact of mangrove forest migration on coastal wetland soil processes and the consequent implications for coastal wetland responses to sea level rise, ecosystem resilience, and carbon storage. 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