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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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Northern spotted owl (NSO) habitat for all ownerships within the Western Oregon Plan Revision (WOPR) area for year 2016. 25 meter pixels are classified as either Non-Habitat, Dispersal Habitat, Nesting Habitat, or Non-Capable. Classification of BLM lands are derived from the WOPR OPTIONS models. Classification of non-BLM lands are cross-walked from the WOPR Forest Structural Stages raster datasets.BLM: (Bureau of Land Management) WOPR: (Western Oregon Plan Revision) PRMP: (Proposed Resource Management Plan) NSO: (Northern Spotted Owl) IVMP: (Interagency Vegetation Mapping Project) LSOG: (Late Stage Old Growth) CVS: (Current Vegetation Survey) FIA: (Forest Inventory Analysis) This analysis addresses those portions...
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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 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 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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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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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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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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Synopsis: Reviews information on grassland bird habitat requirements including a focus on the importance of grassland cover, size of contiguous patches, and other landscape factors. Some species require large blocks of unbroken grassland habitat for nesting. In general, where large blocks of undisturbed grassland occur, grassland birds are able to fulfill most of their requirements during the nesting season. For many bird species, these habitats provide winter and migration cover as well. The more grassland available in an area, particularly in large unbroken blocks, the greater the number of area-sensitive grassland birds the area is able to support. Pastures and crop fields also often provide attractive cover...
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This dataset represents the diversity of woody cover types (averaged per 1.5 ha) as mapped along the Colorado River bottomland from the Colorado state line (San Juan and Grand Counties, Utah) to the southern Canyonlands NP boundary, as of September 2010. This mapping was conducted as part of the Colorado River Conservation Planning Project, a joint effort between the National Park Service, The Nature Conservancy, US Geological Survey, Bureau of Land Management, and Utah Forestry Fire and State Lands.
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This dataset represents the prevalence of tamarisk (tamarisk penalty) as mapped along the Colorado River bottomland from the Colorado state line (San Juan and Grand Counties, Utah) to the southern Canyonlands NP boundary, as of September 2010. Traditional image interpretation cues were used to develop the polygons, such as shape, size, pattern, tone, texture, color, and shadow, from high resolution, true color, aerial imagery (0.3m resolution), acquired for the project. Additional, public available aerial photos (NAIP, 2011) were used to cross-reference cover classes. As with any digital layer, this layer is a representation of what is actually occurring on the ground. Errors are inherent in any interpretation of...
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This shapefile contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the Great Lakes 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 Great Lakes 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 the way...
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This shapefile contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the state of Virginia. 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 Virginia. 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 shapefile contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the state of Delaware. 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 Delaware. 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...
map background search result map search result map Delaware: NFHAP 2010 HCI Scores and Disturbances Virginia: NFHAP 2010 HCI Scores and Disturbances National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Great Lakes Basin Fish Habitat Partnership WOPR Northern Spotted Owl Habitat (2016) Grassland Birds Cheyenne KS Third Order Resource Selection Function Dundy NE Third Order Resource Selection Function Lincoln NE Third Order Resource Selection Function Chase NE Third Order Resource Selection Function Mora NM Third Order Categorized Resource Selection Function Larimer CO Third Order Resource Selection Function Morgan CO Third Order Categorized Resource Selection Function Morton KS Second Order Categorized Resource Selection Function Union NM Second Order Categorized Resource Selection Function Prowers CO Second Order Categorized Resource Selection Function Elbert CO Second Order Resource Selection Function Phillips CO Second Order Resource Selection Function Weld CO Second Order Resource Selection Function Conservation Planning for the Colorado River in Utah - Tamarisk Penalty for Riparian Overstory Model Conservation Planning for the Colorado River in Utah - Diversity of Woody Structure for Riparian Overstory Model Morton KS Second Order Categorized Resource Selection Function Phillips CO Second Order Resource Selection Function Morgan CO Third Order Categorized Resource Selection Function Prowers CO Second Order Categorized Resource Selection Function Lincoln NE Third Order Resource Selection Function Elbert CO Second Order Resource Selection Function Conservation Planning for the Colorado River in Utah - Diversity of Woody Structure for Riparian Overstory Model Conservation Planning for the Colorado River in Utah - Tamarisk Penalty for Riparian Overstory Model Union NM Second Order Categorized Resource Selection Function Larimer CO Third Order Resource Selection Function Delaware: NFHAP 2010 HCI Scores and Disturbances Weld CO Second Order Resource Selection Function WOPR Northern Spotted Owl Habitat (2016) Virginia: NFHAP 2010 HCI Scores and Disturbances National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for Great Lakes Basin Fish Habitat Partnership Grassland Birds