Historic and future trends in exotic annual grass (%) cover in the western US (1985 to 2019 and 2025 to 2040)
Exotic annual grasses [EAG] are one of the most damaging biological stressors in western North America. Despite numerous environmental and societal impacts associated with EAG there remains a need to enhance regional monitoring capabilities to better guide management and conservation efforts. Here we provide estimates of historic and potential future trends in EAG abundance that were developed using linear trend analysis and machine learning techniques at a 30-m spatial resolution. Specifically, these data represent historic (1985 to 2019) and potential future (2025-2040) rates of exotic annual grass change as estimated using Theil-Sen regression and a process-constrained, random forest model assuming only changes in climate under Representative Concentration Pathways (RCP 4.5 and 8.5), respectively.
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Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[ "010:12" ] |
| contactPoint |
{ "fn": "Neal J Pastick", "@type": "vcard:Contact", "hasEmail": "mailto:njpastick@usgs.gov" } |
| description | Exotic annual grasses [EAG] are one of the most damaging biological stressors in western North America. Despite numerous environmental and societal impacts associated with EAG there remains a need to enhance regional monitoring capabilities to better guide management and conservation efforts. Here we provide estimates of historic and potential future trends in EAG abundance that were developed using linear trend analysis and machine learning techniques at a 30-m spatial resolution. Specifically, these data represent historic (1985 to 2019) and potential future (2025-2040) rates of exotic annual grass change as estimated using Theil-Sen regression and a process-constrained, random forest model assuming only changes in climate under Representative Concentration Pathways (RCP 4.5 and 8.5), respectively. |
| distribution |
[ { "@type": "dcat:Distribution", "title": "Digital Data", "format": "XML", "accessURL": "https://doi.org/10.5066/P9Z85VET", "mediaType": "application/http", "description": "Landing page for access to the data" }, { "@type": "dcat:Distribution", "title": "Original Metadata", "format": "XML", "mediaType": "text/xml", "description": "The metadata original format", "downloadURL": "https://data.usgs.gov/datacatalog/metadata/USGS.602301c8d34e31ed20c8733c.xml" } ] |
| identifier | http://datainventory.doi.gov/id/dataset/USGS_602301c8d34e31ed20c8733c |
| keyword |
[ "Exotic annual grasses, cheatgrass, remote sensing", "USGS:602301c8d34e31ed20c8733c", "biota" ] |
| modified | 2022-04-21T00:00:00Z |
| publisher |
{ "name": "U.S. Geological Survey", "@type": "org:Organization" } |
| spatial | -121.87704, 36.90701, -104.87570, 47.84742 |
| theme |
[ "geospatial" ] |
| title | Historic and future trends in exotic annual grass (%) cover in the western US (1985 to 2019 and 2025 to 2040) |
