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Classified probability of suitable habitat for Black Tailed Prairie Dogs for each cell of raster. Classification is based on 4 probability cutoff levels with category 1 being low habitat suitability and category 4 being high habitat suitability. Categorized probability data is created from fitting a global third-order model to county level raster data. For details on model fitting and data used to produce categorized probability raster see report. https://www.fws.gov/science/catalog
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Probability of suitable habitat for Black Tailed Prairie Dogs for each cell of raster. Probability is measured from 0 to 1 with 0 being low habitat suitability and 1 being high suitability. Probability data is created from fitting a global third-order model to county level raster data. For details on model fitting and data used to produce probability raster see report. https://www.fws.gov/science/catalog
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Probability of suitable habitat for Black Tailed Prairie Dogs for each cell of raster. Probability is measured from 0 to 1 with 0 being low habitat suitability and 1 being high suitability. Probability data is created from fitting a global second-order model to county level raster data. For details on model fitting and data used to produce probability raster see report. https://www.fws.gov/science/catalog
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Classified probability of suitable habitat for Black Tailed Prairie Dogs for each cell of raster. Classification is based on 4 probability cutoff levels with category 1 being low habitat suitability and category 4 being high habitat suitability. Categorized probability data is created from fitting a global third-order model to county level raster data. For details on model fitting and data used to produce categorized probability raster see report. https://www.fws.gov/science/catalog
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Classified probability of suitable habitat for Black Tailed Prairie Dogs for each cell of raster. Classification is based on 4 probability cutoff levels with category 1 being low habitat suitability and category 4 being high habitat suitability. Categorized probability data is created from fitting a global second-order model to county level raster data. For details on model fitting and data used to produce categorized probability raster see report. https://www.fws.gov/science/catalog
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Classified probability of suitable habitat for Black Tailed Prairie Dogs for each cell of raster. Classification is based on 4 probability cutoff levels with category 1 being low habitat suitability and category 4 being high habitat suitability. Categorized probability data is created from fitting a global second-order model to county level raster data. For details on model fitting and data used to produce categorized probability raster see report. https://www.fws.gov/science/catalog
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Classified probability of suitable habitat for Black Tailed Prairie Dogs for each cell of raster. Classification is based on 4 probability cutoff levels with category 1 being low habitat suitability and category 4 being high habitat suitability. Categorized probability data is created from fitting a global third-order model to county level raster data. For details on model fitting and data used to produce categorized probability raster see report. https://www.fws.gov/science/catalog
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Probability of suitable habitat for Black Tailed Prairie Dogs for each cell of raster. Probability is measured from 0 to 1 with 0 being low habitat suitability and 1 being high suitability. Probability data is created from fitting a global third-order model to county level raster data. For details on model fitting and data used to produce probability raster see report. https://www.fws.gov/science/catalog
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Classified probability of suitable habitat for Black Tailed Prairie Dogs for each cell of raster. Classification is based on 4 probability cutoff levels with category 1 being low habitat suitability and category 4 being high habitat suitability. Categorized probability data is created from fitting a global second-order model to county level raster data. For details on model fitting and data used to produce categorized probability raster see report. https://www.fws.gov/science/catalog
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Classified probability of suitable habitat for Black Tailed Prairie Dogs for each cell of raster. Classification is based on 4 probability cutoff levels with category 1 being low habitat suitability and category 4 being high habitat suitability. Categorized probability data is created from fitting a global third-order model to county level raster data. For details on model fitting and data used to produce categorized probability raster see report. https://www.fws.gov/science/catalog
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Note: this data release has been superseded by version 2.0, available here: https://doi.org/10.5066/P9V54H5K We developed habitat suitability models for invasive plant species selected by Department of Interior land management agencies. We applied the modeling workflow developed in Young et al. 2020 to species not included in the original case studies. Our methodology balanced trade-offs between developing highly customized models for a few species versus fitting non-specific and generic models for numerous species. We developed a national library of environmental variables known to physiologically limit plant distributions and relied on human input based on natural history knowledge to further narrow the variable...
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Probability of suitable habitat for Black Tailed Prairie Dogs for each cell of raster. Probability is measured from 0 to 1 with 0 being low habitat suitability and 1 being high suitability. Probability data is created from fitting a global second-order model to county level raster data. For details on model fitting and data used to produce probability raster see report. https://www.fws.gov/science/catalog
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Classified probability of suitable habitat for Black Tailed Prairie Dogs for each cell of raster. Classification is based on 4 probability cutoff levels with category 1 being low habitat suitability and category 4 being high habitat suitability. Categorized probability data is created from fitting a global second-order model to county level raster data. For details on model fitting and data used to produce categorized probability raster see report. https://www.fws.gov/science/catalog
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Classified probability of suitable habitat for Black Tailed Prairie Dogs for each cell of raster. Classification is based on 4 probability cutoff levels with category 1 being low habitat suitability and category 4 being high habitat suitability. Categorized probability data is created from fitting a global third-order model to county level raster data. For details on model fitting and data used to produce categorized probability raster see report. https://www.fws.gov/science/catalog
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This service definition contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the state of Ohio. This dataset is the result of clipping the feature class 'NFHAP 2010 HCI Scores and Human Disturbance Data for the Conterminous United States linked to NHDPLUSV1.gdb' to the state boundary of Ohio. Landscape factors include land uses, population density, roads, dams, mines, and point-source pollution sites. The source datasets that were compiled and attributed to catchments were identified as being: (1) meaningful for assessing fish habitat; (2) consistent across the entire study area in the way that they were assembled; (3) representative of conditions...
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This service definition contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the state of Montana. This dataset is the result of clipping the feature class 'NFHAP 2010 HCI Scores and Human Disturbance Data for the Conterminous United States linked to NHDPLUSV1.gdb' to the state boundary of Montana. Landscape factors include land uses, population density, roads, dams, mines, and point-source pollution sites. The source datasets that were compiled and attributed to catchments were identified as being: (1) meaningful for assessing fish habitat; (2) consistent across the entire study area in the way that they were assembled; (3) representative of...
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This service definition contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the state of New York. This dataset is the result of clipping the feature class 'NFHAP 2010 HCI Scores and Human Disturbance Data for the Conterminous United States linked to NHDPLUSV1.gdb' to the state boundary of New York. Landscape factors include land uses, population density, roads, dams, mines, and point-source pollution sites. The source datasets that were compiled and attributed to catchments were identified as being: (1) meaningful for assessing fish habitat; (2) consistent across the entire study area in the way that they were assembled; (3) representative of...
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This service definition contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the state of Tennessee. This dataset is the result of clipping the feature class 'NFHAP 2010 HCI Scores and Human Disturbance Data for the Conterminous United States linked to NHDPLUSV1.gdb' to the state boundary of Tennessee. Landscape factors include land uses, population density, roads, dams, mines, and point-source pollution sites. The source datasets that were compiled and attributed to catchments were identified as being: (1) meaningful for assessing fish habitat; (2) consistent across the entire study area in the way that they were assembled; (3) representative...
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This service definition contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the Ohio River Basin Fish Habitat Partnership. This dataset is the result of clipping the feature class 'NFHAP 2010 HCI Scores and Human Disturbance Data for the Conterminous United States linked to NHDPLUSV1.gdb' to the boundary of the Ohio River Basin Fish Habitat Partnership. Landscape factors include land uses, population density, roads, dams, mines, and point-source pollution sites. The source datasets that were compiled and attributed to catchments were identified as being: (1) meaningful for assessing fish habitat; (2) consistent across the entire study area in...
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Covering 120 million acres across 14 western states and 3 Canadian provinces, sagebrush provides critical habitat for species such as pronghorn, mule deer, and sage-grouse – a species of conservation concern. The future of these and other species is closely tied to the future of sagebrush. Yet this important ecosystem has already been affected by fire, invasive species, land use conversion, and now, climate change. In the western U.S., temperatures are rising and precipitation patterns are changing. However, there is currently a limited ability to anticipate the impacts of climate change on sagebrush. Current methods suffer from a range of weakness that limits the reliability of results. In fact, the current uncertainty...
map background search result map search result map Stevens KS Third Order Categorized Resource Selection Function Gove KS Third Order Resource Selection Function Hamilton KS Third Order Categorized Resource Selection Function Yuma CO Third Order Categorized Resource Selection Function Phillips CO Third Order Resource Selection Function Phillips CO Third Order Categorized Resource Selection Function Beaver OK Third Order Categorized Resource Selection Function Rawlins KS Second Order Resource Selection Function Gray KS Second Order Resource Selection Function Kimbal NE Second Order Resource Selection Function Deuel NE Second Order Categorized Resource Selection Function Kit Carson CO Second Order Categorized Resource Selection Function Crowley CO Second Order Categorized Resource Selection Function Forecasting Future Changes in Sagebrush Distribution and Abundance National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Montana: ESRI Service Definition National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for New York: ESRI Service Definition National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Ohio: ESRI Service Definition National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Tennessee: ESRI Service Definition National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Ohio River Basin Fish Habitat Partnership: ESRI Service Definition INHABIT species potential distribution across the contiguous United States Crowley CO Second Order Categorized Resource Selection Function Phillips CO Third Order Resource Selection Function Phillips CO Third Order Categorized Resource Selection Function Stevens KS Third Order Categorized Resource Selection Function Deuel NE Second Order Categorized Resource Selection Function Gray KS Second Order Resource Selection Function Hamilton KS Third Order Categorized Resource Selection Function Gove KS Third Order Resource Selection Function Rawlins KS Second Order Resource Selection Function Kimbal NE Second Order Resource Selection Function Beaver OK Third Order Categorized Resource Selection Function Kit Carson CO Second Order Categorized Resource Selection Function Yuma CO Third Order Categorized Resource Selection Function National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Tennessee: ESRI Service Definition National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Ohio: ESRI Service Definition National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for New York: ESRI Service Definition National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Montana: ESRI Service Definition National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Ohio River Basin Fish Habitat Partnership: ESRI Service Definition Forecasting Future Changes in Sagebrush Distribution and Abundance INHABIT species potential distribution across the contiguous United States