Timeline / Data.gov — Climate Datasets
changed Source changed
A new raw object was archived. Both versions are preserved. 1112 line(s) added, 1027 line(s) removed.
Evidence
| Source | Data.gov — Climate Datasets |
|---|---|
| Agency | Data.gov |
| URL | https://api.gsa.gov/technology/datagov/v4/search?q=climate&sort=last_harvested_date&per_page=100&api_key=${DATAGOV_API_KEY} |
| Observed by | Civic Memory, directly, on 2026-10-01T06:25:10+00:00 |
| Content type | application/json |
| Current object |
b98f3bf0041de889260ab6d3d8b02fda66682a23ad6a29a61321243074f2f9c7
download raw
metadata
|
| Previous object |
3d17cc7eadada48e087e9e56974a92cbe1bed5e408d9d5b8942ac2c1fe833eb2
download raw
metadata
|
What changed derived
This diff is not evidence. It was produced by
civic-memory.diff_engine 1.1.0 at
2026-10-01T06:25:10+00:00 by normalizing the two archived objects above. The
objects are authoritative; this reading of them can be regenerated or deleted
without loss. 1112 line(s) added, 1027 line(s) removed.
--- previous +++ current @@ -1,11 +1,1071 @@ { - "after": "WzE3OTA0NjgwMDE3MTksMTIuMzc1MDYzLDIsIjM0N2FlZjU4LWQxMTItNGM2ZS04YWQ4LWJhMDhhMjEyNGU1MSJd", + "after": "WzE3OTA0NjkxNjQ3MzUsMjkuNzIyNzE3LDAsIjU2YWUxMGI0LWU2NTYtNGM5Yi05MzY3LWVjYTQxZTg4M2JkMyJd", "results": [ { - "_score": 8.712244, + "_score": 10.06674, + "_sort": [ + 1790821374605, + 10.06674, + 0, + "0fcde80b-3a68-4639-8f70-7053cead0e68" + ], + "dcat": { + "accessLevel": "public", + "bureauCode": [ + "010:12" + ], + "contactPoint": { + "@type": "vcard:Contact", + "fn": "Guillaume Mauger", + "hasEmail": "mailto:gmauger@uw.edu" + }, + "description": "This dataset contains netcdf files with the peak flow statistics associated with culvert design, for the state of Washington.", + "distribution": [ + { + "@type": "dcat:Distribution", + "accessURL": "https://doi.org/10.5066/P13U2YZ2", + "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.624f2a6ad34e21f82769b53f.xml", + "format": "XML", + "mediaType": "text/xml", + "title": "Original Metadata" + } + ], + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_624f2a6ad34e21f82769b53f", + "keyword": [ + "USGS:624f2a6ad34e21f82769b53f", + "adaptation", + "biota", + "climate change", + "culvert", + "environment", + "geospatial datasets", + "inland waterways", + "streamflow", + "structure" + ], + "modified": "2026-09-28T00:00:00Z", + "publisher": { + "@type": "org:Organization", + "name": "U.S. Geological Survey" + }, + "spatial": "-124.7600, 45.5400, -116.9100, 49.0000", + "theme": [ + "geospatial" + ], + "title": "Historical and Future Peak Flow Statistics for Washington State, derived from VIC modeling and Dynamically Downscaled CMIP5 Projections" + }, + "description": "This dataset contains netcdf files with the peak flow statistics associated with culvert design, for the state of Washington.", + "distribution_titles": [ + "Digital Data", + "Original Metadata" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/5a7bbeca-8b64-47a0-ac98-a93f39e078e0", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/5a7bbeca-8b64-47a0-ac98-a93f39e078e0/raw", + "has_download": true, + "has_spatial": true, + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_624f2a6ad34e21f82769b53f", + "keyword": [ + "USGS:624f2a6ad34e21f82769b53f", + "adaptation", + "biota", + "climate change", + "culvert", + "environment", + "geospatial datasets", + "inland waterways", + "streamflow", + "structure" + ], + "last_harvested_date": "2026-10-01T02:22:54.605698", + "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": "historical-and-future-peak-flow-statistics-for-washington-state-derived-from-vic-modeling-", + "spatial_centroid": { + "lat": 46.924, + "lon": -121.62 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + -124.76, + 45.54 + ], + [ + -124.76, + 49.0 + ], + [ + -116.91, + 49.0 + ], + [ + -116.91, + 45.54 + ], + [ + -124.76, + 45.54 + ] + ] + ], + "type": "Polygon" + }, + "theme": [ + "geospatial" + ], + "title": "Historical and Future Peak Flow Statistics for Washington State, derived from VIC modeling and Dynamically Downscaled CMIP5 Projections", + "type": "dataset" + }, + { + "_score": 37.507782, + "_sort": [ + 1790820742361, + 37.507782, + 0, + "56cf6a70-58bf-4eef-9b3c-00e681bcdd1a" + ], + "dcat": { + "accessLevel": "public", + "bureauCode": [ + "010:12" + ], + "contactPoint": { + "@type": "vcard:Contact", + "fn": "Guillaume Mauger", + "hasEmail": "mailto:gmauger@uw.edu" + }, + "description": "This zipped file contains the model code, configuration files, and run scripts used to run the VIC model. All were developed by Mingliang liu at Washington State University (WSU).", + "distribution": [ + { + "@type": "dcat:Distribution", + "accessURL": "https://doi.org/10.5066/P13ICZXY", + "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.624f2b4fd34e21f82769b6ed.xml", + "format": "XML", + "mediaType": "text/xml", + "title": "Original Metadata" + } + ], + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_624f2b4fd34e21f82769b6ed", + "keyword": [ + "USGS:624f2b4fd34e21f82769b6ed", + "adaptation", + "climate change", + "climatologyMeteorologyAtmosphere", + "culvert", + "inlandWaters", + "modeling", + "streamflow", + "structure" + ], + "modified": "2026-09-28T00:00:00Z", + "publisher": { + "@type": "org:Organization", + "name": "U.S. Geological Survey" + }, + "spatial": "-124.78125, 45.53125, -116.90625, 49.03125", + "theme": [ + "geospatial" + ], + "title": "VIC model, configuration files, and run scripts for Washington State Culverts and Climate Change project" + }, + "description": "This zipped file contains the model code, configuration files, and run scripts used to run the VIC model. All were developed by Mingliang liu at Washington State University (WSU).", + "distribution_titles": [ + "Digital Data", + "Original Metadata" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/dd6cb121-d74a-4464-8cdf-48982c714c83", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/dd6cb121-d74a-4464-8cdf-48982c714c83/raw", + "has_download": true, + "has_spatial": true, + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_624f2b4fd34e21f82769b6ed", + "keyword": [ + "USGS:624f2b4fd34e21f82769b6ed", + "adaptation", + "climate change", + "climatologyMeteorologyAtmosphere", + "culvert", + "inlandWaters", + "modeling", + "streamflow", + "structure" + ], + "last_harvested_date": "2026-10-01T02:12:22.361065", + "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": "vic-model-configuration-files-and-run-scripts-for-washington-state-culverts-and-climate-ch", + "spatial_centroid": { + "lat": 46.93125, + "lon": -121.63125 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + -124.78125, + 45.53125 + ], + [ + -124.78125, + 49.03125 + ], + [ + -116.90625, + 49.03125 + ], + [ + -116.90625, + 45.53125 + ], + [ + -124.78125, + 45.53125 + ] + ] + ], + "type": "Polygon" + }, + "theme": [ + "geospatial" + ], + "title": "VIC model, configuration files, and run scripts for Washington State Culverts and Climate Change project", + "type": "dataset" + }, + { + "_score": 20.818035, + "_sort": [ + 1790819576520, + 20.818035, + 1, + "53cc3307-b797-44bd-b4a8-a54bed47446f" + ], + "dcat": { + "accessLevel": "public", + "bureauCode": [ + "010:12" + ], + "contactPoint": { + "@type": "vcard:Contact", + "fn": "Michael Osland", + "hasEmail": "mailto:mosland@usgs.gov" + }, + "description": "The northern Gulf of Mexico coast spans two major climate gradients and represents an excellent natural laboratory for developing climate-influenced ecological models. In this project, we used these zones of remarkable transition to develop macroclimate-based models for quantifying the regional responses of coastal wetland ecosystems to climate variation. In addition to providing important fish and wildlife habitat and supporting coastal food webs, these coastal wetlands provide many ecosystem goods and services including clean water, stable coastlines, food, recreational opportunities, and stored carbon. Our objective was to examine and forecast the effects of macroclimatic drivers on wetland ecosystem structure and function in the northern Gulf of Mexico.", + "distribution": [ + { + "@type": "dcat:Distribution", + "accessURL": "http://dx.doi.org/doi:10.5066/F7J1017G", + "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.57b240fce4b00148d3982cd0.xml", + "format": "XML", + "mediaType": "text/xml", + "title": "Original Metadata" + } + ], + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_57b240fce4b00148d3982cd0", + "keyword": [ + "Corpus Christi", + "Galveston", + "Grand Bay", + "Gulf of Mexico", + "Laguna Madre", + "Port Aransas", + "San Antonio", + "Slidell", + "State of Alabama", + "State of Florida", + "State of Louisiana", + "State of Mississippi", + "State of Texas", + "Tampa Bay", + "Ten Thousand Islands", + "USGS:57b240fce4b00148d3982cd0", + "Weeks Bay", + "bulk density", + "environment", + "moisture", + "soil", + "soil organic matter" + ], + "modified": "2026-09-28T00:00:00Z", + "publisher": { + "@type": "org:Organization", + "name": "U.S. Geological Survey" + }, + "spatial": "-97.365203, 25.856967, -81.499719, 30.497478", + "theme": [ + "geospatial" + ], + "title": "U.S. Gulf of Mexico coast (TX, MS, AL, and FL) Macroclimate Soil Data (2013-2014)" + }, + "description": "The northern Gulf of Mexico coast spans two major climate gradients and represents an excellent natural laboratory for developing climate-influenced ecological models. In this project, we used these zones of remarkable transition to develop macroclimate-based models for quantifying the regional responses of coastal wetland ecosystems to climate variation. In addition to providing important fish and wildlife habitat and supporting coastal food webs, these coastal wetlands provide many ecosystem goods and services including clean water, stable coastlines, food, recreational opportunities, and stored carbon. Our objective was to examine and forecast the effects of macroclimatic drivers on wetland ecosystem structure and function in the northern Gulf of Mexico.", + "distribution_titles": [ + "Digital Data", + "Original Metadata" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/d5e76c02-3210-44c3-ae21-53d506c89818", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/d5e76c02-3210-44c3-ae21-53d506c89818/raw", + "has_download": true, + "has_spatial": true, + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_57b240fce4b00148d3982cd0", + "keyword": [ + "Corpus Christi", + "Galveston", + "Grand Bay", + "Gulf of Mexico", + "Laguna Madre", + "Port Aransas", + "San Antonio", + "Slidell", + "State of Alabama", + "State of Florida", + "State of Louisiana", + "State of Mississippi", + "State of Texas", + "Tampa Bay", + "Ten Thousand Islands", + "USGS:57b240fce4b00148d3982cd0", + "Weeks Bay", + "bulk density", + "environment", + "moisture", + "soil", + "soil organic matter" + ], + "last_harvested_date": "2026-10-01T01:52:56.520198", + "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": "u-s-gulf-of-mexico-coast-tx-ms-al-and-fl-macroclimate-soil-data-2013-2014", + "spatial_centroid": { + "lat": 27.7131714, + "lon": -91.01900939999999 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + -97.365203, + 25.856967 + ], + [ + -97.365203, + 30.497478 + ], + [ + -81.499719, + 30.497478 + ], + [ + -81.499719, + 25.856967 + ], + [ + -97.365203, + 25.856967 + ] + ] + ], + "type": "Polygon" + }, + "theme": [ + "geospatial" + ], + "title": "U.S. Gulf of Mexico coast (TX, MS, AL, and FL) Macroclimate Soil Data (2013-2014)", + "type": "dataset" + }, + { + "_score": 28.067276, + "_sort": [ + 1790819268479, + 28.067276, + 0, + "f586ed7a-8c6d-49e3-a23e-32fa2e94843b" + ], + "dcat": { + "accessLevel": "public", + "bureauCode": [ + "010:12" + ], + "contactPoint": { + "@type": "vcard:Contact", + "fn": "Michael Osland", + "hasEmail": "mailto:mosland@usgs.gov" + }, + "description": "The northern Gulf of Mexico coast spans a dramatic water availability gradient (precipitation range: 700 to 1800 mm/year) and represents an excellent natural laboratory for developing climate-influenced ecological models for natural resource managers and culture keepers. In this project, we used this zone of remarkable transition to develop macroclimate-based models for quantifying the regional responses of coastal wetland ecosystems to climate variation. In addition to providing important fish and wildlife habitat and supporting coastal food webs, these coastal wetlands provide many ecosystem goods and services including clean water, stable coastlines, food, recreational opportunities, and stored carbon. Our objective was to examine and forecast the effects of macroclimatic drivers on wetland ecosystem structure and function in the northern Gulf of Mexico. Our first major step in meeting this overall objective was to develop a quantitative understanding of the connections between climate and ecosystem structure. We then incorporated the resulting information into quantitative vulnerability assessments that examine sensitivity (via observed data), exposure (via alternative future climate scenarios), and adaptive capacity (via life history literature). In the process, we identified regional climate-ecological thresholds for coastal wetland ecosystems. Our study focused on coastal wetland variations across relatively dramatic precipitation and temperature gradients in the northern Gulf of Mexico and included study areas in TX, LA, MS, AL, and FL. The project provided valuable experience and opportunities for five early-career researchers (one post-doctoral fellow, two current or recent undergraduate students, and two early-career research scientists).", + "distribution": [ + { + "@type": "dcat:Distribution", + "accessURL": "https://doi.org/10.5066/F7J1017G", + "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.5731fbace4b0dae0d5dc1e59.xml", + "format": "XML", + "mediaType": "text/xml", + "title": "Original Metadata" + } + ], + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_5731fbace4b0dae0d5dc1e59", + "keyword": [ + "Corpus Christi", + "Galveston", + "Grand Bay", + "Gulf of Mexico", + "Laguna Madre", + "Port Aransas", + "San Antonio", + "Slidell", + "State of Alabama", + "State of Florida", + "State of Louisiana", + "State of Mississippi", + "State of Texas", + "Tampa Bay", + "Ten Thousand Islands", + "USGS:5731fbace4b0dae0d5dc1e59", + "Weeks Bay", + "biota", + "climate", + "elevation", + "landscape", + "latitude", + "longitude" + ], + "modified": "2026-09-28T00:00:00Z", + "publisher": { + "@type": "org:Organization", + "name": "U.S. Geological Survey" + }, + "spatial": "-97.6907, 25.8567, -81.5252, 30.4376", + "theme": [ + "geospatial" + ], + "title": "U.S. Gulf of Mexico coast (TX, MS, AL, and FL) Vegetation, soil, and landscape data (2013-2014)" + }, + "description": "The northern Gulf of Mexico coast spans a dramatic water availability gradient (precipitation range: 700 to 1800 mm/year) and represents an excellent natural laboratory for developing climate-influenced ecological models for natural resource managers and culture keepers. In this project, we used this zone of remarkable transition to develop macroclimate-based models for quantifying the regional responses of coastal wetland ecosystems to climate variation. In addition to providing important fish and wildlife habitat and supporting coastal food webs, these coastal wetlands provide many ecosystem goods and services including clean water, stable coastlines, food, recreational opportunities, and stored carbon. Our objective was to examine and forecast the effects of macroclimatic drivers on wetland ecosystem structure and function in the northern Gulf of Mexico. Our first major step in meeting this overall objective was to develop a quantitative understanding of the connections between climate and ecosystem structure. We then incorporated the resulting information into quantitative vulnerability assessments that examine sensitivity (via observed data), exposure (via alternative future climate scenarios), and adaptive capacity (via life history literature). In the process, we identified regional climate-ecological thresholds for coastal wetland ecosystems. Our study focused on coastal wetland variations across relatively dramatic precipitation and temperature gradients in the northern Gulf of Mexico and included study areas in TX, LA, MS, AL, and FL. The project provided valuable experience and opportunities for five early-career researchers (one post-doctoral fellow, two current or recent undergraduate students, and two early-career research scientists).", + "distribution_titles": [ + "Digital Data", + "Original Metadata" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/176cae11-99e9-4bcc-afc4-3cd6d6c97d74", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/176cae11-99e9-4bcc-afc4-3cd6d6c97d74/raw", + "has_download": true, + "has_spatial": true, + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_5731fbace4b0dae0d5dc1e59", + "keyword": [ + "Corpus Christi", + "Galveston", + "Grand Bay", + "Gulf of Mexico", + "Laguna Madre", + "Port Aransas", + "San Antonio", + "Slidell", + "State of Alabama", + "State of Florida", + "State of Louisiana", + "State of Mississippi", + "State of Texas", + "Tampa Bay", + "Ten Thousand Islands", + "USGS:5731fbace4b0dae0d5dc1e59", + "Weeks Bay", + "biota", + "climate", + "elevation", + "landscape", + "latitude", + "longitude" + ], + "last_harvested_date": "2026-10-01T01:47:48.479583", + "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": "u-s-gulf-of-mexico-coast-tx-ms-al-and-fl-vegetation-soil-and-landscape-data-2013-2014", + "spatial_centroid": { + "lat": 27.68906, + "lon": -91.2245 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + -97.6907, + 25.8567 + ], + [ + -97.6907, + 30.4376 + ], + [ + -81.5252, + 30.4376 + ], + [ + -81.5252, + 25.8567 + ], + [ + -97.6907, + 25.8567 + ] + ] + ], + "type": "Polygon" + }, + "theme": [ + "geospatial" + ], + "title": "U.S. Gulf of Mexico coast (TX, MS, AL, and FL) Vegetation, soil, and landscape data (2013-2014)", + "type": "dataset" + }, + { + "_score": 54.19426, + "_sort": [ + 1790819048831, + 54.19426, + 3, + "7171d0a8-bfc0-42b5-8048-03ca719df3d4" + ], + "dcat": { + "accessLevel": "public", + "bureauCode": [ + "010:12" + ], + "contactPoint": { + "@type": "vcard:Contact", + "fn": "Michael Osland", + "hasEmail": "mailto:mosland@usgs.gov" + }, + "description": "The northern Gulf of Mexico coast spans two major climate gradients and represents an excellent natural laboratory for developing climate-influenced ecological models. In this project, we used these zones of remarkable transition to develop macroclimate-based models for quantifying the regional responses of coastal wetland ecosystems to climate variation. In addition to providing important fish and wildlife habitat and supporting coastal food webs, these coastal wetlands provide many ecosystem goods and services including clean water, stable coastlines, food, recreational opportunities, and stored carbon. Our objective was to examine and forecast the effects of macroclimatic drivers on wetland ecosystem structure and function in the northern Gulf of Mexico.", + "distribution": [ + { + "@type": "dcat:Distribution", + "accessURL": "http://dx.doi.org/doi:10.5066/F7J1017G", + "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.57b24094e4b00148d3982cce.xml", + "format": "XML", + "mediaType": "text/xml", + "title": "Original Metadata" + } + ], + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_57b24094e4b00148d3982cce", + "keyword": [ + "Corpus Christi", + "Galveston", + "Grand Bay", + "Gulf of Mexico", + "Laguna Madre", + "Port Aransas", + "San Antonio", + "Slidell", + "State of Alabama", + "State of Florida", + "State of Louisiana", + "State of Mississippi", + "State of Texas", + "Tampa Bay", + "Ten Thousand Islands", + "USGS:57b24094e4b00148d3982cce", + "Weeks Bay", + "climate", + "elevation", + "landscape", + "latitude", + "longitude" + ], + "modified": "2026-09-28T00:00:00Z", + "publisher": { + "@type": "org:Organization", + "name": "U.S. Geological Survey" + }, + "spatial": "-97.69067328, 25.85667755, -81.52517775, 30.43761712", + "theme": [ + "geospatial" + ], + "title": "U.S. Gulf of Mexico coast (TX, MS, AL, and FL) Macroclimate Landscape and Climate Data (2013-2014)" + }, + "description": "The northern Gulf of Mexico coast spans two major climate gradients and represents an excellent natural laboratory for developing climate-influenced ecological models. In this project, we used these zones of remarkable transition to develop macroclimate-based models for quantifying the regional responses of coastal wetland ecosystems to climate variation. In addition to providing important fish and wildlife habitat and supporting coastal food webs, these coastal wetlands provide many ecosystem goods and services including clean water, stable coastlines, food, recreational opportunities, and stored carbon. Our objective was to examine and forecast the effects of macroclimatic drivers on wetland ecosystem structure and function in the northern Gulf of Mexico.", + "distribution_titles": [ + "Digital Data", + "Original Metadata" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/99d9b25a-44c7-43f7-ae7f-f375fe2abc82", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/99d9b25a-44c7-43f7-ae7f-f375fe2abc82/raw", + "has_download": true, + "has_spatial": true, + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_57b24094e4b00148d3982cce", + "keyword": [ + "Corpus Christi", + "Galveston", + "Grand Bay", + "Gulf of Mexico", + "Laguna Madre", + "Port Aransas", + "San Antonio", + "Slidell", + "State of Alabama", + "State of Florida", + "State of Louisiana", + "State of Mississippi", + "State of Texas", + "Tampa Bay", + "Ten Thousand Islands", + "USGS:57b24094e4b00148d3982cce", + "Weeks Bay", + "climate", + "elevation", + "landscape", + "latitude", + "longitude" + ], + "last_harvested_date": "2026-10-01T01:44:08.831133", + "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": 3, + "publisher": "U.S. Geological Survey", + "slug": "u-s-gulf-of-mexico-coast-tx-ms-al-and-fl-macroclimate-landscape-and-climate-data-2013-2014", + "spatial_centroid": { + "lat": 27.689053378, + "lon": -91.22447506799999 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + -97.69067328, + 25.85667755 + ], + [ + -97.69067328, + 30.43761712 + ], + [ + -81.52517775, + 30.43761712 + ], + [ + -81.52517775, + 25.85667755 + ], + [ + -97.69067328, + 25.85667755 + ] + ] + ], + "type": "Polygon" + }, + "theme": [ + "geospatial" + ], + "title": "U.S. Gulf of Mexico coast (TX, MS, AL, and FL) Macroclimate Landscape and Climate Data (2013-2014)", + "type": "dataset" + }, + { + "_score": 20.751318, + "_sort": [ + 1790818927685, + 20.751318, + 3, + "a5ff12e3-ae64-42e5-b5f9-73697a150cef" + ], + "dcat": { + "accessLevel": "public", + "bureauCode": [ + "010:12" + ], + "contactPoint": { + "@type": "vcard:Contact", + "fn": "Michael Osland", + "hasEmail": "mailto:mosland@usgs.gov" + }, + "description": "The northern Gulf of Mexico coast spans two major climate gradients and represents an excellent natural laboratory for developing climate-influenced ecological models. In this project, we used these zones of remarkable transition to develop macroclimate-based models for quantifying the regional responses of coastal wetland ecosystems to climate variation. In addition to providing important fish and wildlife habitat and supporting coastal food webs, these coastal wetlands provide many ecosystem goods and services including clean water, stable coastlines, food, recreational opportunities, and stored carbon. Our objective was to examine and forecast the effects of macroclimatic drivers on wetland ecosystem structure and function in the northern Gulf of Mexico.", + "distribution": [ + { + "@type": "dcat:Distribution", + "accessURL": "http://dx.doi.org/doi:10.5066/F7J1017G", + "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.57aa11efe4b05e859be06932.xml", + "format": "XML", + "mediaType": "text/xml", + "title": "Original Metadata" + } + ], + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_57aa11efe4b05e859be06932", + "keyword": [ + "Corpus Christi", + "Galveston", + "Grand Bay", + "Gulf of Mexico", + "Laguna Madre", + "Port Aransas", + "San Antonio", + "Slidell", + "State of Alabama", + "State of Florida", + "State of Louisiana", + "State of Mississippi", + "State of Texas", + "Tampa Bay", + "Ten Thousand Islands", + "USGS:57aa11efe4b05e859be06932", + "Weeks Bay", + "environment", + "vegetation" + ], + "modified": "2026-09-28T00:00:00Z", + "publisher": { + "@type": "org:Organization", + "name": "U.S. Geological Survey" + }, + "spatial": "-97.365203, 25.856967, -81.499719, 30.497478", + "theme": [ + "geospatial" + ], + "title": "U.S. Gulf of Mexico coast (TX, MS, AL, and FL) Macroclimate Vegetation Data Section 1 (2013-2014)" + }, + "description": "The northern Gulf of Mexico coast spans two major climate gradients and represents an excellent natural laboratory for developing climate-influenced ecological models. In this project, we used these zones of remarkable transition to develop macroclimate-based models for quantifying the regional responses of coastal wetland ecosystems to climate variation. In addition to providing important fish and wildlife habitat and supporting coastal food webs, these coastal wetlands provide many ecosystem goods and services including clean water, stable coastlines, food, recreational opportunities, and stored carbon. Our objective was to examine and forecast the effects of macroclimatic drivers on wetland ecosystem structure and function in the northern Gulf of Mexico.", + "distribution_titles": [ + "Digital Data", + "Original Metadata" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/7e1f101e-e418-4e76-8f25-80e8590941dd", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/7e1f101e-e418-4e76-8f25-80e8590941dd/raw", + "has_download": true, + "has_spatial": true, + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_57aa11efe4b05e859be06932", + "keyword": [ + "Corpus Christi", + "Galveston", + "Grand Bay", + "Gulf of Mexico", + "Laguna Madre", + "Port Aransas", + "San Antonio", + "Slidell", + "State of Alabama", + "State of Florida", + "State of Louisiana", + "State of Mississippi", + "State of Texas", + "Tampa Bay", + "Ten Thousand Islands", + "USGS:57aa11efe4b05e859be06932", + "Weeks Bay", + "environment", + "vegetation" + ], + "last_harvested_date": "2026-10-01T01:42:07.685326", + "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": 3, + "publisher": "U.S. Geological Survey", + "slug": "u-s-gulf-of-mexico-coast-tx-ms-al-and-fl-macroclimate-vegetation-data-section-1-2013-2014", + "spatial_centroid": { + "lat": 27.7131714, + "lon": -91.01900939999999 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + -97.365203, + 25.856967 + ], + [ + -97.365203, + 30.497478 + ], + [ + -81.499719, + 30.497478 + ], + [ + -81.499719, + 25.856967 + ], + [ + -97.365203, + 25.856967 + ] + ] + ], + "type": "Polygon" + }, + "theme": [ + "geospatial" + ], + "title": "U.S. Gulf of Mexico coast (TX, MS, AL, and FL) Macroclimate Vegetation Data Section 1 (2013-2014)", + "type": "dataset" + }, + { + "_score": 37.222042, + "_sort": [ + 1790818056734, + 37.222042, + 0, + "0cc48ef7-7236-46d3-82db-02e26cd734d9" + ], + "dcat": { + "accessLevel": "public", + "bureauCode": [ + "010:12" + ], + "contactPoint": { + "@type": "vcard:Contact", + "fn": "Rosemary M Fanelli", + "hasEmail": "mailto:rfanelli@usgs.gov" + }, + "description": "This data release contains summary metrics describing stream stage, stream water temperature, and short-term climate conditions (daily precipitation and air temperature) for 30 streams spanning gradients of forest and developed land uses and the implementation of agricultural best management practices in the Piedmont region within Maryland, Washington, DC, and Virginia, USA. This setting is the fourth of four settings or \"typologies\" that will be assessed for the USGS Chesapeake Stream Team project. High-frequency stage, water temperature, and air temperature (15-minute data) were measured by the U.S. Geological Survey (USGS) from March 2024 to September 2024 and are available at McFarland and others (2025; DOI: https://doi.org/10.5066/P13JW8QF). Additional daily air temperature and precipitation data were acquired from the Parameter-elevation Regressions on Independent Slopes Model (PRISM) climate data website. Air temperature and water temperature data were used to compute stream water temperature metrics describing stream temperature conditions in each stream during the monitoring period. Stream stage and precipitation data were used to derive stream stage metrics describing stage conditions (a surrogate for flow) for each stream during the monitoring period. Precipitation and air temperature data from PRISM were also used to compute air temperature metrics and precipitation metrics describing climate conditions during the monitoring period. The metrics include:\nAir temperature metrics \n- Mean daily minimum, mean, and maximum air temperature\nPrecipitation metrics \n- Total precipitation depth\n- Maximum daily precipitation depth\n- Average precipitation depth per days with precipitation\n- Frequency of precipitation days\nStream stage metrics\n- Number of runoff events\n- Frequency of runoff events \n- Standard deviation in unit-value stage\nStream water temperature metrics\n- Coefficient of variation of mean and maximum daily water temperatures\n- Number of days with temperatures of 20 or 25 degrees Celsius or greater\n- Duration of time above 20 or 25 degrees Celsius or greater\n- Maximum of seven-day moving average of daily maximum temperature and daily mean temperature\n- Mean of daily minimum, mean, maximum, and daily water temperature range\n- A thermal sensitivity metric, which is the slope estimate from linear regression model of mean daily water temperature versus mean daily air temperature\nThis data release contains six files:\n1. \"Readme.pdf\": This is an expanded narrative describing the methods by which the input data were compiled and screened, and metrics were computed\n2. \"typology_4_temperature_stage_climate_metric_data_dictionary.csv\": This file contains descriptions of each metric and the time periods for which they were computed in the “typology_4_temperature_stage_climate_summary_metrics.csv\" file\n3. \"typology_4_temperature_stage_climate_summary_metrics.csv\": This file contains stream temperature metrics, stage metrics, and climate summary metrics for each of the 30 stream sites for different time periods within the overall monitoring period.\n4. \"typology_4_input_data_high_frequency_temperature_and_stage.zip\": This zipped folder contains 30 .csv files, which contain the high-frequency stage, water temperature, and air temperature data collected at each of the 30 stream sites. The file names include the SiteID, which is the four-letter site identification listed in the \"typology_3_temperature_stage_climate_summary_metrics.csv\" file.\n5. \"typology_4_input_data_daily_climate.csv\": This file contains daily climate estimates (precipitation depth, daily minimum, mean, and maximum air temperatures) from PRISM paired to each of the 30 sites.\n6. \"typology_4_runoff_events.csv\": This file contains the stage rise and precipitation data used for some of the stage metric computations.", + "distribution": [ + { + "@type": "dcat:Distribution", + "accessURL": "https://doi.org/10.5066/P14XBLPB", + "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.6a030eacb66b01f153e0563a.xml", + "format": "XML", + "mediaType": "text/xml", + "title": "Original Metadata" + } + ], + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_6a030eacb66b01f153e0563a", + "keyword": [ + "Chesapeake Bay watershed", + "Maryland", + "USGS:6a030eacb66b01f153e0563a", + "United States", + "Virginia", + "Washington, D.C.", + "biota", + "farming", + "freshwater ecosystems", + "health", + "hydrology", + "water temperature" + ], + "modified": "2026-09-28T00:00:00Z", + "publisher": { + "@type": "org:Organization", + "name": "U.S. Geological Survey" + }, + "spatial": "-77.6500, 38.2560, -76.6500, 39.4200", + "theme": [ + "geospatial" + ], + "title": "Stream stage, stream temperature, and climate metrics for 30 streams spanning land use and management gradients in the Maryland-Washington, DC-Virginia Developed Piedmont Region, 2024" + }, + "description": "This data release contains summary metrics describing stream stage, stream water temperature, and short-term climate conditions (daily precipitation and air temperature) for 30 streams spanning gradients of forest and developed land uses and the implementation of agricultural best management practices in the Piedmont region within Maryland, Washington, DC, and Virginia, USA. This setting is the fourth of four settings or \"typologies\" that will be assessed for the USGS Chesapeake Stream Team project. High-frequency stage, water temperature, and air temperature (15-minute data) were measured by the U.S. Geological Survey (USGS) from March 2024 to September 2024 and are available at McFarland and others (2025; DOI: https://doi.org/10.5066/P13JW8QF). Additional daily air temperature and precipitation data were acquired from the Parameter-elevation Regressions on Independent Slopes Model (PRISM) climate data website. Air temperature and water temperature data were used to compute stream water temperature metrics describing stream temperature conditions in each stream during the monitoring period. Stream stage and precipitation data were used to derive stream stage metrics describing stage conditions (a surrogate for flow) for each stream during the monitoring period. Precipitation and air temperature data from PRISM were also used to compute air temperature metrics and precipitation metrics describing climate conditions during the monitoring period. The metrics include:\nAir temperature metrics \n- Mean daily minimum, mean, and maximum air temperature\nPrecipitation metrics \n- Total precipitation depth\n- Maximum daily precipitation depth\n- Average precipitation depth per days with precipitation\n- Frequency of precipitation days\nStream stage metrics\n- Number of runoff events\n- Frequency of runoff events \n- Standard deviation in unit-value stage\nStream water temperature metrics\n- Coefficient of variation of mean and maximum daily water temperatures\n- Number of days with temperatures of 20 or 25 degrees Celsius or greater\n- Duration of time above 20 or 25 degrees Celsius or greater\n- Maximum of seven-day moving average of daily maximum temperature and daily mean temperature\n- Mean of daily minimum, mean, maximum, and daily water temperature range\n- A thermal sensitivity metric, which is the slope estimate from linear regression model of mean daily water temperature versus mean daily air temperature\nThis data release contains six files:\n1. \"Readme.pdf\": This is an expanded narrative describing the methods by which the input data were compiled and screened, and metrics were computed\n2. \"typology_4_temperature_stage_climate_metric_data_dictionary.csv\": This file contains descriptions of each metric and the time periods for which they were computed in the “typology_4_temperature_stage_climate_summary_metrics.csv\" file\n3. \"typology_4_temperature_stage_climate_summary_metrics.csv\": This file contains stream temperature metrics, stage metrics, and climate summary metrics for each of the 30 stream sites for different time periods within the overall monitoring period.\n4. \"typology_4_input_data_high_frequency_temperature_and_stage.zip\": This zipped folder contains 30 .csv files, which contain the high-frequency stage, water temperature, and air temperature data collected at each of the 30 stream sites. The file names include the SiteID, which is the four-letter site identification listed in the \"typology_3_temperature_stage_climate_summary_metrics.csv\" file.\n5. \"typology_4_input_data_daily_climate.csv\": This file contains daily climate estimates (precipitation depth, daily minimum, mean, and maximum air temperatures) from PRISM paired to each of the 30 sites.\n6. \"typology_4_runoff_events.csv\": This file contains the stage rise and precipitation data used for some of the stage metric computations.", + "distribution_titles": [ + "Digital Data", + "Original Metadata" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/f70c91ed-3f1b-4253-b972-51d5311f5e5f", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/f70c91ed-3f1b-4253-b972-51d5311f5e5f/raw", + "has_download": true, + "has_spatial": true, + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_6a030eacb66b01f153e0563a", + "keyword": [ + "Chesapeake Bay watershed", + "Maryland", + "USGS:6a030eacb66b01f153e0563a", + "United States", + "Virginia", + "Washington, D.C.", + "biota", + "farming", + "freshwater ecosystems", + "health", + "hydrology", + "water temperature" + ], + "last_harvested_date": "2026-10-01T01:27:36.734639", + "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": "stream-stage-stream-temperature-and-climate-metrics-for-30-streams-spanning-land-use--2024", + "spatial_centroid": { + "lat": 38.7216, + "lon": -77.25 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + -77.65, + 38.256 + ], + [ + -77.65, + 39.42 + ], + [ + -76.65, + 39.42 + ], + [ + -76.65, + 38.256 + ], + [ + -77.65, + 38.256 + ] + ] + ], + "type": "Polygon" + }, + "theme": [ + "geospatial" + ], + "title": "Stream stage, stream temperature, and climate metrics for 30 streams spanning land use and management gradients in the Maryland-Washington, DC-Virginia Developed Piedmont Region, 2024", + "type": "dataset" + }, + { + "_score": 8.765196, "_sort": [ 1790803976042, - 8.712244, + 8.765196, 1, "34f8f458-4822-4417-9ab2-041fef6ef3b5" ], @@ -196,10 +1256,10 @@ "type": "dataset" }, { - "_score": 9.401405, + "_score": 9.506643, "_sort": [ 1790803955484, - 9.401405, + 9.506643, 0, "b6c5d6d6-15b9-4b5d-9be3-a9b7382ad8fc" ], @@ -336,10 +1396,10 @@ "type": "dataset" }, { - "_score": 5.6510468, + "_score": 5.724514, "_sort": [ 1790803954972, - 5.6510468, + 5.724514, 0, "fb56cfff-57ad-4836-a5e6-65a0776b2e24" ], @@ -589,10 +1649,10 @@ "type": "dataset" }, { - "_score": 8.670719, + "_score": 8.858665, "_sort": [ 1790803952041, - 8.670719, + 8.858665, 1, "8735f6d5-ca99-4844-bff2-b4d1f3804945" ], @@ -790,10 +1850,10 @@ "type": "dataset" }, { - "_score": 7.71714, + "_score": 7.8060284, "_sort": [ 1790803895703, - 7.71714, + 7.8060284, 4, "1a85cb8e-bfcd-4ee3-b40f-ea15e087a213" ], @@ -985,10 +2045,10 @@ "type": "dataset" }, { - "_score": 4.16868, + "_score": 4.224415, "_sort": [ 1790803845020, - 4.16868, + 4.224415, 3, "64eb3d36-297a-42e0-8ada-993f0f668373" ], @@ -1087,10 +2147,10 @@ "type": "dataset" }, { - "_score": 14.382005, + "_score": 14.509617, "_sort": [ 1790803842515, - 14.382005, + 14.509617, 1, "a592d3cf-ad2e-4a98-a2bf-e2f7fdd71671" ], @@ -1170,10 +2230,10 @@ "type": "dataset" }, { - "_score": 7.664015, + "_score": 7.7570076, "_sort": [ 1790794424534, - 7.664015, + 7.7570076, 4, "374f22e6-71ff-41c8-ad59-226d7c041e6e" ], @@ -1282,10 +2342,10 @@ "type": "dataset" }, { - "_score": 11.07199, + "_score": 11.18476, "_sort": [ 1790794365880, - 11.07199, + 11.18476, 3, "a10e5023-e04a-489e-bb3e-1a02043b2958" ], @@ -1395,10 +2455,10 @@ "type": "dataset" }, { - "_score": 33.12436, + "_score": 33.416286, "_sort": [ 1790794311147, - 33.12436, + 33.416286, 2, "60e490e3-4e75-48f6-ae19-3af1c9f26565" ], @@ -1518,10 +2578,10 @@ "type": "dataset" }, { - "_score": 41.284286, + "_score": 41.51039, "_sort": [ 1790724150193, - 41.284286, + 41.51039, 0, "eb5841ea-bfc2-4a06-9919-27f20a791664" ], @@ -1603,10 +2663,10 @@ "type": "dataset" }, { - "_score": 1.4809256, + "_score": 1.4838133, "_sort": [ 1790722114415, - 1.4809256, + 1.4838133, 6, "aa3ec6b7-e87c-4b2d-bd9e-a8ba8bce61de" ], @@ -1959,10 +3019,10 @@ "type": "dataset" }, { - "_score": 2.307909, + "_score": 2.320284, "_sort": [ 1790722008932, - 2.307909, + 2.320284, 0, "6190e5f3-b470-4186-972c-5fb43ca6325c" ], @@ -2206,10 +3266,10 @@ "type": "dataset" }, { - "_score": 8.652378, + "_score": 8.751923, "_sort": [ 1790722007003, - 8.652378, + 8.751923, 0, "568dfc80-0faf-4183-998b-bf8dc8f7b763" ], @@ -2552,10 +3612,10 @@ "type": "dataset" }, { - "_score": 21.028957, + "_score": 21.212225, "_sort": [ 1790719430488, - 21.028957, + 21.212225, 1, "f7b550e9-2307-4b7d-84fe-355ff778cb91" ], @@ -2646,10 +3706,10 @@ "type": "dataset" }, { - "_score": 21.541767, + "_score": 21.728222, "_sort": [ 1790719428300, - 21.541767, + 21.728222, 5, "5da319e2-0c01-447c-b624-8d86bb902784" ], @@ -2740,10 +3800,10 @@ "type": "dataset" }, { - "_score": 9.747269, + "_score": 9.856808, "_sort": [ 1790719015222, - 9.747269, + 9.856808, 9, "db000b57-a3c5-4244-90ba-1ceb8978ffe5" ], @@ -2914,10 +3974,10 @@ "type": "dataset" }, { - "_score": 15.82171, + "_score": 15.956786, "_sort": [ 1790716967608, - 15.82171, + 15.956786, 0, "b2ec759a-d36c-4a8a-8737-6ad81de3c29f" ], @@ -3039,10 +4099,10 @@ "type": "dataset" }, { - "_score": 15.132757, + "_score": 15.266255, "_sort": [ 1790627147421, - 15.132757, + 15.266255, 0, "2a97fdb4-c319-49c1-8ff4-bbbd67a56189" ], @@ -3130,10 +4190,10 @@ "type": "dataset" }, { - "_score": 11.115782, + "_score": 11.326736, "_sort": [ 1790626214864, - 11.115782, + 11.326736, 0, "4bea04d4-95b3-4714-a356-3f9d4e7f8e01" ], @@ -3239,10 +4299,10 @@ "type": "dataset" }, { - "_score": 10.804387, + "_score": 10.919045, "_sort": [ 1790626177254, - 10.804387, + 10.919045, 0, "9ba67666-f4e2-413a-98be-194135780418" ], @@ -3348,10 +4408,10 @@ "type": "dataset" }, { - "_score": 11.106911, + "_score": 11.233236, "_sort": [ 1790626069263, - 11.106911, + 11.233236, 0, "aa65ddf0-6c74-47ab-9a12-3945c9347a5d" ], @@ -3457,10 +4517,10 @@ "type": "dataset" }, { - "_score": 10.718442, + "_score": 10.834426, "_sort": [ 1790625991368, - 10.718442, + 10.834426, 0, "195b09f9-9b1c-4cb2-a6b9-ee0ddbfa35ca" ], @@ -3566,10 +4626,10 @@ "type": "dataset" }, { - "_score": 6.774248, + "_score": 6.9353294, "_sort": [ 1790625807855, - 6.774248, + 6.9353294, 0, "b5d2a808-de12-45de-bcee-2696e0e118de" ], @@ -3690,10 +4750,10 @@ "type": "dataset" }, { - "_score": 6.765745, + "_score": 6.8488865, "_sort": [ 1790625807543, - 6.765745, + 6.8488865, 0, "5867b442-5645-45c0-a6bd-21d467fafb64" ], @@ -3744,979 +4804,4 @@ ], "title": "The National Survey on Child and Adolescent Well-Being II (NSCAW II) General Release, Waves 1-3" }, - "description": "The second National Survey of Child and Adolescent Well-Being (NSCAW II) is a longitudinal study intended to answer a range of fundamental questions about the well-being, functioning, service needs, and service use of children who come in contact with the child welfare system. The study is sponsored by the Administration for Children and Families (ACF), U.S. Department of Health and Human Services (DHHS). It examines the well-being of children involved with child welfare agencies; captures information about their families; provides information about child welfare interventions and other services; and describes key characteristics of child development. Of particular interest to the study are children's health, mental health, and developmental risks, especially for those children who experienced the most severe abuse and exposure to violence. The NSCAW II study design essentially mirrors that of NSCAW I. The NSCAW II cohort includes 5,872 children, aged birth to 17.5 years old, who had contact with the child welfare system within a 15-month period that began in February 2008. Children were sampled from investigations closed during the reference period. The cohort of 5,872 children was selected from 81 of the original NSCAW 92 Primary Sampling Units (PSUs) in 83 counties in 30 states that agreed to participate in NSCAW II. Retaining most of the NSCAW I PSUs will allow researchers to assess the change in context from the late 1990s and enable longitudinal analysis of organizational measures such as staff turnover, climate, and work environment. The sample of investigated/assessed cases includes both cases that receive ongoing services and cases that are not receiving services, either because they were not substantiated or because it was determined that services were not required. The sample design—with oversampling of infants and children in out-of-home placement and undersampling of cases not receiving services to ensure appropriate representation among subgroups—allows in-depth analysis of subgroups of special interest (e.g., young children, adolescents in foster care) while providing national estimates for the full population of children and families entering the system. Like NSCAW I, NSCAW II is a longitudinal study with multiple informants associated with each sampled child to get the fullest possible depiction of that child. Face-to-face interviews or assessments were conducted with children, parents, and nonparent adult caregivers (e.g., foster parents, kin caregivers, and group home caregivers), and investigative caseworkers. Baseline data collection began in March 2008 and was completed in September 2009. The second wave of the study, 18 months after the close of the NSCAW II index investigation, began in October 2009 and was completed in January 2011. At Wave 3, children and families were reinterviewed approximately 36 months after the close of the NSCAW II index investigation. The NSCAW II cohort of children who were approximately 2 months to 17.5 years old at baseline ranged in age from 34 months to 20 years old at Wave 3. Data collection for the third wave of the study began in June 2011 and was completed in December 2012.", - "distribution_titles": [], - "harvest_record": "https://catalog.data.gov/harvest_record/699cc39c-ffa0-4c4d-9249-f2fdaef7cab0", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/699cc39c-ffa0-4c4d-9249-f2fdaef7cab0/raw", - "has_download": false, - "has_spatial": true, - "identifier": "acf-opre-0121", - "keyword": [ - "child welfare", - "family support services" - ], - "last_harvested_date": "2026-09-28T20:03:27.543313", - "organization": { - "aliases": [ - "US", - "dept" - ], - "code_repo_exempt": false, - "code_repo_url": null, - "description": null, - "id": "2c2fc21f-21d0-4450-af01-cf8c69b44156", - "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/hhs.png", - "name": "U.S. Department of Health & Human Services", - "organization_type": "Federal Government", - "slug": "hhs" - }, - "parent_identifier": null, - "popularity": 0, - "publisher": "Office of Planning, Research & Evaluation (OPRE)", - "slug": "the-national-survey-on-child-and-adolescent-well-being-ii-nscaw-ii-general-release-waves-1-a41bb", - "spatial_centroid": { - "lat": 34.4819914, - "lon": -101.6218762 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - [ - -124.733253, - 24.544245 - ], - [ - -124.733253, - 49.388611 - ], - [ - -66.954811, - 49.388611 - ], - [ - -66.954811, - 24.544245 - ], - [ - -124.733253, - 24.544245 - ] - ] - ] - ], - "type": "MultiPolygon" - }, - "theme": [ - "human services" - ], - "title": "The National Survey on Child and Adolescent Well-Being II (NSCAW II) General Release, Waves 1-3", - "type": "dataset" - }, - { - "_score": 5.7003593, - "_sort": [ - 1790625799376, - 5.7003593, - 0, - "a594f1ae-14e3-4ffc-8e27-789ab01b5f70" - ], - "dcat": { - "@type": "Dataset", - "accessRights": "restricted public", - "contactPoint": [ - { - "@type": "Kind", - "fn": "OPRE Hub", - "hasEmail": "mailto:OPREhub@acf.hhs.gov" - } - ], - "description": "In 1990, the United States Congress authorized a major program designed to enhance the early public school transitions of former Head Start children and their families. Former Head Start children, like many other children living in poverty, were at risk for poor school achievement. This new program was launched to test the value of extending comprehensive, Head Start-like supports \"upward\" through the first four years of elementary school. This project, administered by the Head Start Bureau of the Administration on Children, Youth, and Families, funded 31 local Transition Demonstration Programs in 30 states and the Navajo Nation from the 1991-1992 school year through the 1997-1998 school year and involved more than 450 public schools. The National Transition Demonstration Study was conducted to provide information about the implementation of this program and its impact on children, families, schools, and communities. More than 7,500 former Head Start children and families were enrolled in the National Study. Thousands of other children and families, however, participated in the Transition Demonstration Program, since supports and educational enhancements were offered to all children and families in the classrooms. The datasets are organized into four broad categories: Family Units -- There are six family unit files. A \"family unit\" record consists of information about a child or family as the result of source data taken from family interviews, records of child test scores on a child instrument, school archival records, or teacher questionnaires (Part B). If data were available from any combination of these source documents, a family unit record was generated. A broad range of variables are included under this heading. Variables range from simple demographics to standardized scores of social skill ratings as well as neighborhood factor scores and child outcome scores in reading and mathematics. These files are associated with each year of the child's schooling (kindergarten through third grade). School Unit -- There are five school unit files, organized around the year of data collection. A \"school unit\" record consists of information about a school as the result of source data captured from family interviews, a classroom teacher, or the school principal. The structure of this data file is different from others in that rather than being merged on a common key, the records are actually stacked one upon the other in groups. The first part of the file consists of family data, the middle portion consists of teacher data, and the final portion consists of principal data. A key variable to the construction of this dataset is the REC_SRC (record source) variable. It informs the user as to the source of the data in the record. The abbreviations are \"fi,\" \"ta,\" and \"qp\" for family interview, teacher questionnaire (Part A), and questionnaire for principals, respectively. The data viewed as the centerpiece of these datasets are the school climate survey variables and their associated factor scores. Classroom Unit -- There are five classroom unit files organized around the year of data collection. The data recorded focus on the classroom and are from the following sources: classroom composition, assessment profile, a developmentally appropriate practice template, and a teacher questionnaire (part a). Some of the data available address the social skills the teacher views as important to his or her particular classroom. Variables addressing diversity of both gender and ethnicity within a single classroom are included when available. Exit Interviews -- There are five Exit Interviews. Exit information was collected from the following groups: experimental and control families, family service specialists, school principals, and classroom teachers. These exit interviews were conducted upon exit from the third grade, and have been combined for both cohorts. Community Characteristics Data -- The community characteristics dataset is a hierarchical file having four distinct levels of data. The type of information available in this file may include data that describe the site, county, school district, or study school. Users of these data are strongly encouraged to consult the accompanying documentation before attempting to use these files.", - "distribution": [ - { - "@type": "Distribution", - "accessURL": "https://www.childandfamilydataarchive.org/cfda/archives/cfda/studies/4712" - } - ], - "identifier": "acf-opre-0087", - "inventoried": "2026-09-27", - "keyword": [ - "early childhood services", - "education", - "family support services", - "public health" - ], - "landingPage": { - "@type": "Document", - "accessURL": "https://www.childandfamilydataarchive.org/cfda/pages/cfda/data.html", - "title": "National Head Start/Public School Early Childhood Transition Demonstration Study, 1991-1999 - Landing Page" - }, - "publisher": { - "@type": "Organization", - "name": "Office of Planning, Research & Evaluation (OPRE)", - "subOrganizationOf": [ - { - "@type": "Organization", - "name": "Administration for Children and Families (ACF)" - } - ] - }, - "spatial": "[{\"@type\": \"Location\", \"prefLabel\": \"united states\"}]", - "theme": [ - { - "@type": "Concept", - "prefLabel": "human services" - } - ], - "title": "National Head Start/Public School Early Childhood Transition Demonstration Study, 1991-1999" - }, - "description": "In 1990, the United States Congress authorized a major program designed to enhance the early public school transitions of former Head Start children and their families. Former Head Start children, like many other children living in poverty, were at risk for poor school achievement. This new program was launched to test the value of extending comprehensive, Head Start-like supports \"upward\" through the first four years of elementary school. This project, administered by the Head Start Bureau of the Administration on Children, Youth, and Families, funded 31 local Transition Demonstration Programs in 30 states and the Navajo Nation from the 1991-1992 school year through the 1997-1998 school year and involved more than 450 public schools. The National Transition Demonstration Study was conducted to provide information about the implementation of this program and its impact on children, families, schools, and communities. More than 7,500 former Head Start children and families were enrolled in the National Study. Thousands of other children and families, however, participated in the Transition Demonstration Program, since supports and educational enhancements were offered to all children and families in the classrooms. The datasets are organized into four broad categories: Family Units -- There are six family unit files. A \"family unit\" record consists of information about a child or family as the result of source data taken from family interviews, records of child test scores on a child instrument, school archival records, or teacher questionnaires (Part B). If data were available from any combination of these source documents, a family unit record was generated. A broad range of variables are included under this heading. Variables range from simple demographics to standardized scores of social skill ratings as well as neighborhood factor scores and child outcome scores in reading and mathematics. These files are associated with each year of the child's schooling (kindergarten through third grade). School Unit -- There are five school unit files, organized around the year of data collection. A \"school unit\" record consists of information about a school as the result of source data captured from family interviews, a classroom teacher, or the school principal. The structure of this data file is different from others in that rather than being merged on a common key, the records are actually stacked one upon the other in groups. The first part of the file consists of family data, the middle portion consists of teacher data, and the final portion consists of principal data. A key variable to the construction of this dataset is the REC_SRC (record source) variable. It informs the user as to the source of the data in the record. The abbreviations are \"fi,\" \"ta,\" and \"qp\" for family interview, teacher questionnaire (Part A), and questionnaire for principals, respectively. The data viewed as the centerpiece of these datasets are the school climate survey variables and their associated factor scores. Classroom Unit -- There are five classroom unit files organized around the year of data collection. The data recorded focus on the classroom and are from the following sources: classroom composition, assessment profile, a developmentally appropriate practice template, and a teacher questionnaire (part a). Some of the data available address the social skills the teacher views as important to his or her particular classroom. Variables addressing diversity of both gender and ethnicity within a single classroom are included when available. Exit Interviews -- There are five Exit Interviews. Exit information was collected from the following groups: experimental and control families, family service specialists, school principals, and classroom teachers. These exit interviews were conducted upon exit from the third grade, and have been combined for both cohorts. Community Characteristics Data -- The community characteristics dataset is a hierarchical file having four distinct levels of data. The type of information available in this file may include data that describe the site, county, school district, or study school. Users of these data are strongly encouraged to consult the accompanying documentation before attempting to use these files.", - "distribution_titles": [], - "harvest_record": "https://catalog.data.gov/harvest_record/8e43b650-29db-40ce-a16f-7e5b8d2d0460", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/8e43b650-29db-40ce-a16f-7e5b8d2d0460/raw", - "has_download": false, - "has_spatial": true, - "identifier": "acf-opre-0087", - "keyword": [ - "early childhood services", - "education", - "family support services", - "public health" - ], - "last_harvested_date": "2026-09-28T20:03:19.376882", - "organization": { - "aliases": [ - "US", - "dept" - ], - "code_repo_exempt": false, - "code_repo_url": null, - "description": null, - "id": "2c2fc21f-21d0-4450-af01-cf8c69b44156", - "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/hhs.png", - "name": "U.S. Department of Health & Human Services", - "organization_type": "Federal Government", - "slug": "hhs" - }, - "parent_identifier": null, - "popularity": 0, - "publisher": "Office of Planning, Research & Evaluation (OPRE)", - "slug": "national-head-start-public-school-early-childhood-transition-demonstration-study-1991-1999-1bf47", - "spatial_centroid": { - "lat": 34.4819914, - "lon": -101.6218762 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - [ - -124.733253, - 24.544245 - ], - [ - -124.733253, - 49.388611 - ], - [ - -66.954811, - 49.388611 - ], - [ - -66.954811, - 24.544245 - ], - [ - -124.733253, - 24.544245 - ] - ] - ] - ], - "type": "MultiPolygon" - }, - "theme": [ - "human services" - ], - "title": "National Head Start/Public School Early Childhood Transition Demonstration Study, 1991-1999", - "type": "dataset" - }, - { - "_score": 24.167027, - "_sort": [ - 1790558805887, - 24.167027, - 0, - "212db81d-5389-43b8-8ca1-7e2620d9efa0" - ], - "dcat": { - "accessLevel": "public", - "bureauCode": [ - "010:12" - ], - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Ethan B. Plunkett", - "hasEmail": "mailto:plunkett@eco.umass.edu" - }, - "description": "This package contains results from the Designing Sustainable Landscapes (DSL) Species Refugia project for Saltmarsh sparrow. The following files are included:\n1. Raster of Landscape Capability (LC) for (Saltmarsh sparrow)\n2. Raster of Climate Refugia (CRefugia) for (Saltmarsh sparrow) \n3. Polygon shapefile of all cores for (Saltmarsh sparrow)\n4. Conductance among 2020 cores for (Saltmarsh sparrow)\n5. Conductance among 2080 cores for (Saltmarsh sparrow)", - "distribution": [ - { - "@type": "dcat:Distribution", - "accessURL": "https://landeco.umass.edu/web/lcc/dsl/refugia/species_refugia_sals.zip", - "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.6388dbfcd34ed907bf78e881.xml", - "format": "XML", - "mediaType": "text/xml", - "title": "Original Metadata" - } - ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_6388dbfcd34ed907bf78e881", - "keyword": [ - "Connecticut", - "Delaware", - "District of Columbia", - "Maine", - "Maryland", - "Massachusetts", - "New Hampshire", - "New Jersey", - "New York", - "North America", - "Pennsylvania", - "Rhode Island", - "USGS:6388dbfcd34ed907bf78e881", - "United States", - "Vermont", - "Virginia", - "West Virginia", - "biota", - "climate change", - "environment", - "geospatial datasets" - ], - "modified": "2026-09-25T00:00:00Z", - "publisher": { - "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-83.8015, 34.4437, -65.8410, 49.4647", - "theme": [ - "geospatial" - ], - "title": "Current condition and refugia conservation cores for the Saltmarsh sparrow and conductance among them" - }, - "description": "This package contains results from the Designing Sustainable Landscapes (DSL) Species Refugia project for Saltmarsh sparrow. The following files are included:\n1. Raster of Landscape Capability (LC) for (Saltmarsh sparrow)\n2. Raster of Climate Refugia (CRefugia) for (Saltmarsh sparrow) \n3. Polygon shapefile of all cores for (Saltmarsh sparrow)\n4. Conductance among 2020 cores for (Saltmarsh sparrow)\n5. Conductance among 2080 cores for (Saltmarsh sparrow)", - "distribution_titles": [ - "Digital Data", - "Original Metadata" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/2c062b20-fd05-43c8-9931-7b492ffbe5c6", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/2c062b20-fd05-43c8-9931-7b492ffbe5c6/raw", - "has_download": true, - "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_6388dbfcd34ed907bf78e881", - "keyword": [ - "Connecticut", - "Delaware", - "District of Columbia", - "Maine", - "Maryland", - "Massachusetts", - "New Hampshire", - "New Jersey", - "New York", - "North America", - "Pennsylvania", - "Rhode Island", - "USGS:6388dbfcd34ed907bf78e881", - "United States", - "Vermont", - "Virginia", - "West Virginia", - "biota", - "climate change", - "environment", - "geospatial datasets" - ], - "last_harvested_date": "2026-09-28T01:26:45.887264", - "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": "current-condition-and-refugia-conservation-cores-for-the-saltmarsh-sparrow-and-conductance", - "spatial_centroid": { - "lat": 40.4521, - "lon": -76.6173 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -83.8015, - 34.4437 - ], - [ - -83.8015, - 49.4647 - ], - [ - -65.841, - 49.4647 - ], - [ - -65.841, - 34.4437 - ], - [ - -83.8015, - 34.4437 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Current condition and refugia conservation cores for the Saltmarsh sparrow and conductance among them", - "type": "dataset" - }, - { - "_score": 24.703028, - "_sort": [ - 1790558576514, - 24.703028, - 0, - "f4f44ad4-d0f5-40f0-afee-7954aae64e28" - ], - "dcat": { - "accessLevel": "public", - "bureauCode": [ - "010:12" - ], - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Ethan Plunkett", - "hasEmail": "mailto:eplunkett@eco.umass.edu" - }, - "description": "This package contains results from the Designing Sustainable Landscapes (DSL) Species Refugia project for Moose. The following files are included:\n1. Raster of Landscape Capability (LC) for Moose\n2. Raster of Climate Refugia (CRefugia) for Moose\n3. Polygon shapefile of all cores for Moose\n4. Conductance among 2020 cores for Moose\n5. Conductance among 2080 cores for Moose", - "distribution": [ - { - "@type": "dcat:Distribution", - "accessURL": "https://landeco.umass.edu/web/lcc/dsl/refugia/species_refugia_moose.zip", - "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.636aa41dd34ed907bf6a6b22.xml", - "format": "XML", - "mediaType": "text/xml", - "title": "Original Metadata" - } - ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_636aa41dd34ed907bf6a6b22", - "keyword": [ - "Connecticut", - "Delaware", - "District of Columbia", - "Maine", - "Maryland", - "Massachusetts", - "New Hampshire", - "New Jersey", - "New York", - "North America", - "Pennsylvania", - "Rhode Island", - "USGS:636aa41dd34ed907bf6a6b22", - "United States", - "Vermont", - "Virginia", - "West Virginia", - "biota", - "climate change", - "environment", - "geospatial datasets" - ], - "modified": "2026-09-25T00:00:00Z", - "publisher": { - "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-83.8015, 34.4437, -65.8410, 49.4647", - "theme": [ - "geospatial" - ], - "title": "Current condition and refugia conservation cores for Moose and conductance among them" - }, - "description": "This package contains results from the Designing Sustainable Landscapes (DSL) Species Refugia project for Moose. The following files are included:\n1. Raster of Landscape Capability (LC) for Moose\n2. Raster of Climate Refugia (CRefugia) for Moose\n3. Polygon shapefile of all cores for Moose\n4. Conductance among 2020 cores for Moose\n5. Conductance among 2080 cores for Moose", - "distribution_titles": [ - "Digital Data", - "Original Metadata" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/f1e11442-e447-40b6-be2d-3c66f90c5273", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/f1e11442-e447-40b6-be2d-3c66f90c5273/raw", - "has_download": true, - "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_636aa41dd34ed907bf6a6b22", - "keyword": [ - "Connecticut", - "Delaware", - "District of Columbia", - "Maine", - "Maryland", - "Massachusetts", - "New Hampshire", - "New Jersey", - "New York", - "North America", - "Pennsylvania", - "Rhode Island", - "USGS:636aa41dd34ed907bf6a6b22", - "United States", - "Vermont", - "Virginia", - "West Virginia", - "biota", - "climate change", - "environment", - "geospatial datasets" - ], - "last_harvested_date": "2026-09-28T01:22:56.514107", - "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": "current-condition-and-refugia-conservation-cores-for-moose-and-conductance-among-them", - "spatial_centroid": { - "lat": 40.4521, - "lon": -76.6173 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -83.8015, - 34.4437 - ], - [ - -83.8015, - 49.4647 - ], - [ - -65.841, - 49.4647 - ], - [ - -65.841, - 34.4437 - ], - [ - -83.8015, - 34.4437 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Current condition and refugia conservation cores for Moose and conductance among them", - "type": "dataset" - }, - { - "_score": 23.866062, - "_sort": [ - 1790558194744, - 23.866062, - 0, - "79ae3bf4-8b57-4695-acd8-fb902a2a14ce" - ], - "dcat": { - "accessLevel": "public", - "bureauCode": [ - "010:12" - ], - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Ethan B. Plunkett", - "hasEmail": "mailto:plunkett@eco.umass.edu" - }, - "description": "This package contains results from the Designing Sustainable Landscapes (DSL) Species Refugia project for Box turtle (teca). The following files are included:\n1. Raster of Landscape Capability (LC) for Box turtle\n2. Raster of Climate Refugia (CRefugia) for Box turtle\n3. Polygon shapefile of all cores for Box turtle\n4. Conductance among 2020 cores for Box turtle\n5. Conductance among 2080 cores for Box turtle", - "distribution": [ - { - "@type": "dcat:Distribution", - "accessURL": "https://landeco.umass.edu/web/lcc/dsl/refugia/species_refugia_teca.zip", - "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.63867543d34ed907bf77a190.xml", - "format": "XML", - "mediaType": "text/xml", - "title": "Original Metadata" - } - ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_63867543d34ed907bf77a190", - "keyword": [ - "Connecticut", - "Delaware", - "District of Columbia", - "Maine", - "Maryland", - "Massachusetts", - "New Hampshire", - "New Jersey", - "New York", - "North America", - "Pennsylvania", - "Rhode Island", - "USGS:63867543d34ed907bf77a190", - "United States", - "Vermont", - "Virginia", - "West Virginia", - "biota", - "climate change", - "environment", - "geospatial dataset" - ], - "modified": "2026-09-25T00:00:00Z", - "publisher": { - "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-83.8015, 34.4437, -65.8410, 49.4647", - "theme": [ - "geospatial" - ], - "title": "Current condition and refugia conservation cores for the Box turtle and conductance among them" - }, - "description": "This package contains results from the Designing Sustainable Landscapes (DSL) Species Refugia project for Box turtle (teca). The following files are included:\n1. Raster of Landscape Capability (LC) for Box turtle\n2. Raster of Climate Refugia (CRefugia) for Box turtle\n3. Polygon shapefile of all cores for Box turtle\n4. Conductance among 2020 cores for Box turtle\n5. Conductance among 2080 cores for Box turtle", - "distribution_titles": [ - "Digital Data", - "Original Metadata" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/3dee1bb1-d71f-481c-a97a-ebe13159fb27", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/3dee1bb1-d71f-481c-a97a-ebe13159fb27/raw", - "has_download": true, - "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_63867543d34ed907bf77a190", - "keyword": [ - "Connecticut", - "Delaware", - "District of Columbia", - "Maine", - "Maryland", - "Massachusetts", - "New Hampshire", - "New Jersey", - "New York", - "North America", - "Pennsylvania", - "Rhode Island", - "USGS:63867543d34ed907bf77a190", - "United States", - "Vermont", - "Virginia", - "West Virginia", - "biota", - "climate change", - "environment", - "geospatial dataset" - ], - "last_harvested_date": "2026-09-28T01:16:34.744668", - "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": "current-condition-and-refugia-conservation-cores-for-the-box-turtle-and-conductance-among-", - "spatial_centroid": { - "lat": 40.4521, - "lon": -76.6173 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -83.8015, - 34.4437 - ], - [ - -83.8015, - 49.4647 - ], - [ - -65.841, - 49.4647 - ], - [ - -65.841, - 34.4437 - ], - [ - -83.8015, - 34.4437 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Current condition and refugia conservation cores for the Box turtle and conductance among them", - "type": "dataset" - }, - { - "_score": 24.950487, - "_sort": [ - 1790558150225, - 24.950487, - 0, - "66bdb0c0-0a01-4ec7-b687-d237ceb6c06b" - ], - "dcat": { - "accessLevel": "public", - "bureauCode": [ - "010:12" - ], - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Climate Adaptation Science Centers", - "hasEmail": "mailto:casc-data@usgs.gov" - }, - "description": "Cold-induced mortality is a key factor driving mountain pine beetle, Dendroctonus ponderosae, population dynamics. In this species, the supercooling point (SCP) is representative of mortality induced by acute cold exposure. Mountain pine beetle SCP and associated cold-induced mortality fluctuate throughout a generation, with the highest SCPs prior to and following winter. Using observed SCPs of field-collected D. ponderosae larvae throughout the developmental season and associated phloem temperatures, we developed a mechanistic model that describes the SCP distribution of a population as a function of daily changes in the temperature-dependent processes leading to gain and loss of cold tolerance. It is based on the changing proportion of individuals in three states: (1) a non cold-hardened, feeding state, (2) an intermediate state in which insects have ceased feeding, voided their gut content and eliminated as many ice-nucleating agents as possible from the body, and (3) a fully cold-hardened state where insects have accumulated a maximum concentration of cryoprotectants (e.g. glycerol). Shifts in the proportion of individuals in each state occur in response to the driving variables influencing the opposite rates of gain and loss of cold hardening. The level of cold-induced mortality predicted by the model and its relation to extreme winter temperature is in good agreement with a range of field and laboratory observations. Our model predicts that cold tolerance of D. ponderosae varies within a season, among seasons, and among geographic locations depending on local climate. This variability is an emergent property of the model, and has important implications for understanding the insect's response to seasonal fluctuations in temperature, as well as population response to climate change. Because cold-induced mortality is but one of several major influences of climate on D. ponderosae population dynamics, we suggest that this model be integrated with others simulating the insect's biology.", - "distribution": [ - { - "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/P1BIZ9OI", - "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.57474116e4b07e28b663d884.xml", - "format": "XML", - "mediaType": "text/xml", - "title": "Original Metadata" - } - ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_57474116e4b07e28b663d884", - "keyword": [ - "Cold hardiness", - "Cold resistance", - "Cold tolerance", - "Idaho", - "Model", - "Montana", - "Mountain pine beetle", - "Supercooling point", - "USGS:57474116e4b07e28b663d884", - "Washington", - "Winter mortality", - "biota", - "climate change", - "external research support", - "geospatial datasets", - "pre-SM502.8" - ], - "modified": "2026-09-25T00:00:00Z", - "publisher": { - "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-125.0000, 46.5000, -114.0000, 49.0000", - "theme": [ - "geospatial" - ], - "title": "Modeling cold tolerance in the mountain pine beetle, Dendroctonus ponderosae" - }, - "description": "Cold-induced mortality is a key factor driving mountain pine beetle, Dendroctonus ponderosae, population dynamics. In this species, the supercooling point (SCP) is representative of mortality induced by acute cold exposure. Mountain pine beetle SCP and associated cold-induced mortality fluctuate throughout a generation, with the highest SCPs prior to and following winter. Using observed SCPs of field-collected D. ponderosae larvae throughout the developmental season and associated phloem temperatures, we developed a mechanistic model that describes the SCP distribution of a population as a function of daily changes in the temperature-dependent processes leading to gain and loss of cold tolerance. It is based on the changing proportion of individuals in three states: (1) a non cold-hardened, feeding state, (2) an intermediate state in which insects have ceased feeding, voided their gut content and eliminated as many ice-nucleating agents as possible from the body, and (3) a fully cold-hardened state where insects have accumulated a maximum concentration of cryoprotectants (e.g. glycerol). Shifts in the proportion of individuals in each state occur in response to the driving variables influencing the opposite rates of gain and loss of cold hardening. The level of cold-induced mortality predicted by the model and its relation to extreme winter temperature is in good agreement with a range of field and laboratory observations. Our model predicts that cold tolerance of D. ponderosae varies within a season, among seasons, and among geographic locations depending on local climate. This variability is an emergent property of the model, and has important implications for understanding the insect's response to seasonal fluctuations in temperature, as well as population response to climate change. Because cold-induced mortality is but one of several major influences of climate on D. ponderosae population dynamics, we suggest that this model be integrated with others simulating the insect's biology.", - "distribution_titles": [ - "Digital Data", - "Original Metadata" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/23c3114a-ed15-41d0-b1b9-fba956e01212", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/23c3114a-ed15-41d0-b1b9-fba956e01212/raw", - "has_download": true, - "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_57474116e4b07e28b663d884", - "keyword": [ - "Cold hardiness", - "Cold resistance", - "Cold tolerance", - "Idaho", - "Model", - "Montana", - "Mountain pine beetle", - "Supercooling point", - "USGS:57474116e4b07e28b663d884", - "Washington", - "Winter mortality", - "biota", - "climate change", - "external research support", - "geospatial datasets", - "pre-SM502.8" - ], - "last_harvested_date": "2026-09-28T01:15:50.225353", - "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": "modeling-cold-tolerance-in-the-mountain-pine-beetle-dendroctonus-ponderosae", - "spatial_centroid": { - "lat": 47.5, - "lon": -120.6 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -125.0, - 46.5 - ], - [ - -125.0, - 49.0 - ], - [ - -114.0, - 49.0 - ], - [ - -114.0, - 46.5 - ], - [ - -125.0, - 46.5 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Modeling cold tolerance in the mountain pine beetle, Dendroctonus ponderosae", - "type": "dataset" - }, - { - "_score": 29.455347, - "_sort": [ - 1790558055217, - 29.455347, - 4, - "423fc091-fe9a-4198-ba15-a156134fd8fe" - ], - "dcat": { - "accessLevel": "public", - "bureauCode": [ - "010:12" - ], - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Ethan B. Plunkett", - "hasEmail": "mailto:plunkett@eco.umass.edu" - }, - "description": "These data delineate and characterize conservation cores built for seven species based on their current 2020 Landscape Capability and future (2080) Climate Refugia, as well as the conductivity among the future and current cores. For seven species: American woodcock (amwo), Bicknell's thrush (bith), Blackburnian warbler (blbw), Box turtle (teca), Cerulean warbler (cerw), Moose (moose), and Saltmarsh sparrow (sals) we provide five distinct datasets. Species codes (in parentheses) are used in file names and represented by \"[species]\" below.\n1. A set of conservation cores that represent areas of high local, relative value to the species either in the present, the future, or both: [species]_allcores.shp\n2. Conductance among the present condition cores: [species]_conduct.tif \n3. Conductance among the future cores: [species]_conduct_futr.tif\n4. The landscape capability of the species in 2020 (an input dataset to this analysis): [species]_LC_2020_v5.1.tif\n5. The climate refugia for the species in 2080 (an input dataset to this analysis): [species]_Crefugia_2080_v5.1.tif", - "distribution": [ - { - "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.21429/94ey-r171", - "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.5d5ae337e4b01d82ce8ed143.xml", - "format": "XML", - "mediaType": "text/xml", - "title": "Original Metadata" - } - ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_5d5ae337e4b01d82ce8ed143", - "keyword": [ - "Climate", - "Refugia", - "USGS:5d5ae337e4b01d82ce8ed143", - "biota", - "climate change", - "geospatial datasets" - ], - "modified": "2026-09-25T00:00:00Z", - "publisher": { - "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-83.8015, 34.4437, -65.8410, 49.4647", - "theme": [ - "geospatial" - ], - "title": "Current condition and refugia conservation cores for seven species and conductance among them." - }, - "description": "These data delineate and characterize conservation cores built for seven species based on their current 2020 Landscape Capability and future (2080) Climate Refugia, as well as the conductivity among the future and current cores. For seven species: American woodcock (amwo), Bicknell's thrush (bith), Blackburnian warbler (blbw), Box turtle (teca), Cerulean warbler (cerw), Moose (moose), and Saltmarsh sparrow (sals) we provide five distinct datasets. Species codes (in parentheses) are used in file names and represented by \"[species]\" below.\n1. A set of conservation cores that represent areas of high local, relative value to the species either in the present, the future, or both: [species]_allcores.shp\n2. Conductance among the present condition cores: [species]_conduct.tif \n3. Conductance among the future cores: [species]_conduct_futr.tif\n4. The landscape capability of the species in 2020 (an input dataset to this analysis): [species]_LC_2020_v5.1.tif\n5. The climate refugia for the species in 2080 (an input dataset to this analysis): [species]_Crefugia_2080_v5.1.tif", - "distribution_titles": [ - "Digital Data", - "Original Metadata" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/2548ce7e-20de-4534-9617-a7db61e32fa4", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/2548ce7e-20de-4534-9617-a7db61e32fa4/raw", - "has_download": true, - "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_5d5ae337e4b01d82ce8ed143", - "keyword": [ - "Climate", - "Refugia", - "USGS:5d5ae337e4b01d82ce8ed143", - "biota", - "climate change", - "geospatial datasets" - ], - "last_harvested_date": "2026-09-28T01:14:15.217628", - "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": 4, - "publisher": "U.S. Geological Survey", - "slug": "current-condition-and-refugia-conservation-cores-for-seven-species-and-conductance-among-t", - "spatial_centroid": { - "lat": 40.4521, - "lon": -76.6173 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -83.8015, - 34.4437 - ], - [ - -83.8015, - 49.4647 - ], - [ - -65.841, - 49.4647 - ], - [ - -65.841, - 34.4437 - ], - [ - -83.8015, - 34.4437 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Current condition and refugia conservation cores for seven species and conductance among them.", - "type": "dataset" - }, - { - "_score": 8.648157, - "_sort": [ - 1790557674977, - 8.648157, - 0, - "23a3b81c-25e7-43d4-8a7f-deaefef6723b" - ], - "dcat": { - "accessLevel": "public", - "bureauCode": [ - "010:12" - ], - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Curtis M. Belyea", - "hasEmail": "mailto:cbelyea@ncsu.edu" - }, - "description": "This dataset represents the extent of urbanization (for the year indicated) predicted by the model SLEUTH, developed by Dr. Keith C. Clarke + "description": "The second National Survey of Child and Adolescent Well-Being (NSCAW II) is a longitudinal study intended to answer a range of fundamental questions about the well-being, functioning, service needs, and service use of children who come in contact with the child welfare system. The study is sponsored by the Administration for Children and Families (ACF), U.S. Department of Health and Human Services (DHHS). It examines the well-being of children involved with child welfare agencies; captures information about their families; provides information about child welfare interventions and other services; and describes key characteristics of child development. Of particular interest to the study are children's health, mental health, and developmental risks, especially for those children who experienced the most severe abuse and exposure to violence. The NSCAW II study design essentially mirrors that of NSCAW I. The NSCAW II cohort includes 5,872 children, aged birth to 17.5 years old, who had contact with the child welfare system within a 15-month period that began in February 2008. Children were sampled from investigations closed during the reference period. The cohort of 5,872 children was selected from 81 of the original NSCAW 92 Primary Sampling Units (PSUs) in 83 counties in 30 states that agreed to participate in NSCAW II. Retaining most of the NSCAW I PSUs will allow researchers to assess the change in context from the late 1990s and enable longitudinal analysis of organizational measures such as staff turnover, climate, and work environment. The sample of investigated/assessed cases includes both cases that receive ongoing services and cases that are not receiving services, either because they were not substantiated or because it was determined that services were not required. The sample design—with oversampling o