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The Great Plains Landscape Conservation Cooperative (GPLCC, http://www.greatplainslcc.org/) is a partnership that provides applied science and decision support tools to assist natural resource managers conserve plants, fish and wildlife in the mid- and short-grass prairie of the southern Great Plains. It is part of a national network of public-private partnerships — known as Landscape Conservation Cooperatives (LCCs, http://www.fws.gov/science/shc/lcc.html) — that work collaboratively across jurisdictions and political boundaries to leverage resources and share science capacity. The Great Plains LCC identifies science priorities for the region and helps foster science that addresses these priorities to support wildlife...
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This dataset consists of 102 magnetotelluric (MT) stations collected in 2012-2014 in the Rio Grande Rift and southern Rocky Mountains. The U.S. Geological Survey acquired these data to improve regional conductivity models of the western United States. This work is in support of studies of the effect of lithospheric modification on electrical resistivity structure and tectonic evolution of the western United States.
We capitalized on a regional-scale, anthropogenic experiment?the reduction of black-tailed prairie dog (Cynomys ludovicianus) towns across the Great Plains of North America?to test the hypothesis that decline of this species has led to declines in diversity of native grassland vertebrates of this region. We compared species richness and species composition of non-volant mammals, reptiles and amphibians at 36 prairie dog towns and 36 paired sites in the Panhandle Region of Oklahoma during the summers and falls of 1997, 1998 and 1999. We detected 30 species of mammals, 18 species of reptiles and seven species of amphibians. Comparisons between communities at prairie dog towns and paired sites in the adjacent landscape...
Prairie restoration at the northern edge of the Great Plains can be frustrated by previously established non-native perennial grasses. We compared the emergence of a widely introduced grass, Agropyron cristatum, and a common native grass, Bouteloua gracilis, in a 4-year-old field experiment in which the Agropyron-dominated vegetation had either been left intact or treated annually with herbicide. This was done at two levels of water supply, reflecting conditions expected in wet and dry years, to examine the effects of among-year variability in precipitation. Water addition significantly increased the emergence of both surface-sown and buried (1 cm deep) seeds. Herbicide treatment of neighbors did not increase the...
Concern over the status of species associated with prairie dog colonies has increased with the recent proposed listing of black-tailed prairie dogs (Cynomys ludovicianus). We monitored burrowing owl (Athene cunicularia) populations and prairie dog densities in 17 black-tailed prairie dog colonies in the Nebraska panhandle between 1990 and 1996. All prairie dog colonies were controlled at least once during the study. We observed a 63% decline in nesting pairs of burrowing owls and significant declines in burrow densities. Results indicated a time lag in owl response to changes in active burrow densities. However, in the later years of the study when burrow densities were lowest, owl numbers were positively correlated...
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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
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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
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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
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
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
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
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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