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The ecologically-relevant geophysical (ERGo) landforms dataset is a comprehensive classification of landforms based on hillslope position and dominant physical processes that covers most of North America. Four hillslope positions form a natural sequence of topographic units along the catena: ridges/peaks (summits), upper slopes (shoulders), lower slopes (foot slopes), and valley bottoms (toe slopes). The position within each of these hillslopes as a function of solar orientation to reflect how ecological processes (especially soil moisture and evapotranspiration) are influenced by insolation. Also included are very flat (i.e. areas 50°). We provide these data here at 30 m resolution, grouped by Landscape Conservation...
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The ecologically-relevant geophysical (ERGo) landforms dataset is a comprehensive classification of landforms based on hillslope position and dominant physical processes that covers most of North America. Four hillslope positions form a natural sequence of topographic units along the catena: ridges/peaks (summits), upper slopes (shoulders), lower slopes (foot slopes), and valley bottoms (toe slopes). The position within each of these hillslopes as a function of solar orientation to reflect how ecological processes (especially soil moisture and evapotranspiration) are influenced by insolation. Also included are very flat (i.e. areas 50°). We provide these data here at 30 m resolution, grouped by Landscape Conservation...
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This dataset is one of a dozen or so datasets that provide the basis for a vulnerability assessment of the Great Northern LCC that examines land use and climate changes at landscape scales, for the full LCC boundary. It provides a measure of vulnerability based on temperature change using a watershed-based analysis. The values range from 0 to 1 and are unitless, where Vtw = Et x (1-Aw). The original floating point values ranging from 0-1.0 were multiplied by 100 and converted to integer format for this dataset.
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This dataset is one of a dozen or so datasets that provide the basis for a vulnerability assessment of the Great Northern LCC that examines land use and climate changes at landscape scales, for the full LCC boundary. It provides a measure of vulnerability based on biome velocity and using a terrestrial (moving window) anlaysis. The values range from 0 to 1 and are unitless, where Vhg = Eh x (1-Ag). The original floating point values ranging from 0-1.0 were multiplied by 100 and converted to integer format for this dataset.
We obtained statewide spatially explicit gridded soil survey data for Nebraska from the Soil Survey Geographic (SSURGO) database. The ‘chorizon,’ ‘chtexture,’ ‘chtexturegrp,’ ‘mapunit,’ and ‘mutext’ tables in the Gridded SSURGO database were joined together using the “mukey” attribute field in a geographic information system (GIS). The representative values for slope (rvslope) and slope length (rvslopelenusle), the susceptibility of the soil to water erosion (Kw), and the soil loss tolerance (t_fact) values were obtained from the set of joined tables and were included in the Water Erosion Index calculation. We acquired county-specific rainfall and runoff factor values (R) from the U.S. Department ofAgriculture’s...
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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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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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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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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


map background search result map search result map BURNSCAR_2012_183_213_conus.tif Gove KS Third Order Resource Selection Function Hamilton KS Third Order Categorized Resource Selection Function Hayes NE Third Order Resource Selection Function Denver CO Third Order Resource Selection Function Yuma CO Third Order Categorized Resource Selection Function Douglas CO Third Order Categorized Resource Selection Function Phillips CO Third Order Categorized Resource Selection Function Rawlins KS Second Order Resource Selection Function Morton KS Second Order Resource Selection Function Kimbal NE Second Order Resource Selection Function Deuel NE Second Order Categorized Resource Selection Function Mora NM Second Order Categorized Resource Selection Function Jefferson CO Second Order Resource Selection Function Jefferson CO Second Order Categorized Resource Selection Function Nebraska Soil Erosion Index Vhg: terrestrially-defined vulnerability, biome velocity for Great Northern LCC Vtw: hydrologically-defined vulnerability, temperature change for Great Northern LCC Ecologically-relevant landforms for Upper Midwest and Great Lakes LCC Ecologically-relevant landforms for Plains and Prairie Potholes LCC Douglas CO Third Order Categorized Resource Selection Function Morton KS Second Order Resource Selection Function Phillips CO Third Order Categorized Resource Selection Function Denver CO Third Order Resource Selection Function Hayes NE Third Order Resource Selection Function Deuel NE Second Order Categorized 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 Mora NM Second Order Categorized Resource Selection Function Jefferson CO Second Order Resource Selection Function Jefferson CO Second Order Categorized Resource Selection Function Kimbal NE Second Order Resource Selection Function Yuma CO Third Order Categorized Resource Selection Function Nebraska Soil Erosion Index Ecologically-relevant landforms for Plains and Prairie Potholes LCC Ecologically-relevant landforms for Upper Midwest and Great Lakes LCC Vhg: terrestrially-defined vulnerability, biome velocity for Great Northern LCC Vtw: hydrologically-defined vulnerability, temperature change for Great Northern LCC BURNSCAR_2012_183_213_conus.tif