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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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This map layer consists of federally owned or administered lands of the United States, Puerto Rico, and the U.S. Virgin Islands. For the most part, only areas of 320 acres or more are included; some smaller areas deemed to be important or significant are also included. There may be private inholdings within the boundaries of Federal lands in this map layer. Some established Federal lands which are larger than 320 acres are not included in this map layer, because their boundaries were not available from the owning or administering agency.
Tags: Air Force, Alabama, Alaska, Arizona, Arkansas, All tags...
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Digital orthophotos combine the geometric qualities of a map with the image qualities of a photograph. The orthophotos in this series are a mosaic of digital orthophoto quarter quads (DOQs) produced through the National Digital Ortho Photo Program (NDOP). The image characteristics of the orthophotos in this series follow that of the source DOQs. The ground sample distance is 1 meter in the x direction and 1 meter in the y direction. The images are resampled to 2 meters when an order is placed. The images are rectified to the UTM Coordinate System, NAD83. The images are in JPEG format and each image covers a 7.5-minute quadrangle. The USGS DOQs are replaced by enhanced DOQs from APFO where available. The enhanced...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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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. http://www.greatplainslcc.org/wp-content/uploads/2012/11/BTPD-Habitat-Suitability-Final-Report.pdf
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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. http://www.greatplainslcc.org/wp-content/uploads/2012/11/BTPD-Habitat-Suitability-Final-Report.pdf
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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. http://www.greatplainslcc.org/wp-content/uploads/2012/11/BTPD-Habitat-Suitability-Final-Report.pdf
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. http://www.greatplainslcc.org/wp-content/uploads/2012/11/BTPD-Habitat-Suitability-Final-Report.pdf
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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. http://www.greatplainslcc.org/wp-content/uploads/2012/11/BTPD-Habitat-Suitability-Final-Report.pdf
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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. http://www.greatplainslcc.org/wp-content/uploads/2012/11/BTPD-Habitat-Suitability-Final-Report.pdf
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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. http://www.greatplainslcc.org/wp-content/uploads/2012/11/BTPD-Habitat-Suitability-Final-Report.pdf


map background search result map search result map USDA Terraserver Enhanced Digital Ortho Mosaic 7.5 min Quadrangle Stevens KS Third Order Categorized Resource Selection Function Hamilton KS Third Order Categorized Resource Selection Function Phillips CO Third Order Resource Selection Function Beaver OK Third Order Categorized Resource Selection Function Gray KS Second Order Resource Selection Function Morton KS Second Order Resource Selection Function Deuel NE Second Order Categorized Resource Selection Function Precipitation (Proportion July - Sep) - 2020-2050 - RCP8.5 - Min Temperature (Mean: Annual) - 2020-2050 - RCP4.5 - Max Temperature (Mean: Annual) - 2020-2050 - RCP8.5 - Min Precipitation (Proportion May - Oct) - 1980-2010 Precipitation (Proportion May - Oct) - 2070-2100 - RCP4.5 - Min Precipitation (Proportion May - Oct) - 2020-2050 - RCP4.5 - Min Precipitation (Mean: Apr - June) - 2070-2100 - RCP4.5 - Max Precipitation (Mean: Dec - Mar) - 2020-2050 - RCP4.5 - Min Temperature (Mean: Apr - June) - 2020-2050 - RCP8.5 - Mean Temperature (Mean: Dec - Mar) - 2070-2100 - RCP8.5 - Min Temperature (Minimum: January) - 2070-2100 - RCP8.5 - Mean USGS 1:1,000,000-Scale Federal Lands of the United States 201412 FileGDB Morton KS Second Order Resource Selection Function Phillips CO Third Order Resource Selection Function Stevens KS Third Order Categorized Resource Selection Function Beaver OK Third Order Categorized Resource Selection Function Precipitation (Proportion July - Sep) - 2020-2050 - RCP8.5 - Min Temperature (Mean: Annual) - 2020-2050 - RCP4.5 - Max Temperature (Mean: Annual) - 2020-2050 - RCP8.5 - Min Precipitation (Proportion May - Oct) - 1980-2010 Precipitation (Proportion May - Oct) - 2070-2100 - RCP4.5 - Min Precipitation (Proportion May - Oct) - 2020-2050 - RCP4.5 - Min Precipitation (Mean: Apr - June) - 2070-2100 - RCP4.5 - Max Precipitation (Mean: Dec - Mar) - 2020-2050 - RCP4.5 - Min Temperature (Mean: Apr - June) - 2020-2050 - RCP8.5 - Mean Temperature (Mean: Dec - Mar) - 2070-2100 - RCP8.5 - Min Temperature (Minimum: January) - 2070-2100 - RCP8.5 - Mean USGS 1:1,000,000-Scale Federal Lands of the United States 201412 FileGDB USDA Terraserver Enhanced Digital Ortho Mosaic 7.5 min Quadrangle