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Synopsis: The purpose of this model is to indicate potential habitat for olive-backed pocket mice (Perohnathus fasciatus) within the Milk River Basin. As this is a landscape level model with course variaqbles, it may not be directly applicable to other areas for site-specific analysis. Conclusions: Olive-backed pocket mice require high proportions of grassland habitat and low proportions of shrub cover. Sites with low densities of shrubs are preferred because they provide cover from large and aerial predators, such as owls. A threshold of below 40% shrub coverage represents ideal shrub cover proportions.
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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 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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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 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 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 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 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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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 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
Conclusions:Owls avoided agricultural lands (due to prey availability), used grass-forb areas for foraging, and avoided croplands and grazed pasture. 95% of all movements occurred within 600 meters of the nest burrows.Thresholds/Learnings:At a minimum, a 600m radius should be maintained around burrowing owl nests in order to ensure the survival of burrowing owls
Conclusions:The Sprague's pipit tends to occupy native grassland habitats containing very little or no woody vegetation, with non-native areas populated to a significantly lower extentThresholds/Learnings:
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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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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 Olive-backed Pocket Mouse. Stevens KS Third Order Categorized Resource Selection Function Gove KS Third Order Resource Selection Function Hamilton KS Third Order Categorized Resource Selection Function Denver CO Third Order 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 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 Kit Carson CO Second Order Categorized Resource Selection Function Jefferson CO Second Order Resource Selection Function Forecasting Future Changes in Sagebrush Distribution and Abundance Morton KS Second Order Resource Selection Function Phillips CO Third Order Resource Selection Function Phillips CO Third Order Categorized Resource Selection Function Denver CO Third Order 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 Mora NM Second Order Categorized Resource Selection Function Jefferson CO 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 Olive-backed Pocket Mouse. Forecasting Future Changes in Sagebrush Distribution and Abundance