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This data set includes the relative production scenarios for eight (8) grass species based on linear models from Epstein, et al. (1998). We selected two indicator species for each community: shortgrass prairie: blue grama (Bouteloua gracilis; BOGR) and buffalo grass (Bouteloua dactyloides; BODA); mixedgrass prairie: sideoats grama (Bouteloua curtipendula; BOCU) and little bluestem (Schizachyrium scoparium; SCSC); tallgrass prairie: big bluestem (Andropogon gerardii; ANGE) and Indiangrass (Sorghastrum nutans; SONU); and semiarid grasslands: black grama (Bouteloua eriopoda; BOER) and tobosagrass (Pleuraphis mutica; PLMU). Soil texture (percent by weight) came from the Earth Systems Science Center (2008) which provided...
This data set includes the relative production scenarios for bufflaograss [0.72(Temp) - 0.12(Precip) - 0.04(Sand) + 3.08]; this is the model from Epstein, et al. (1998). Soil texture (percent by weight) came from the Earth Systems Science Center (2008) which provided processed soils data from NRCS (gSSURGO), mean annual temperature (Celsius) and/or mean annual precipitation (millimeters) came from contemporary (1981 - 2010) estimates (Maurer et al. 2002) or a GCM. Global Climate Models (GCM) providing scenarios included: warmer-wetter scenario (CESM1-BGC, RCP4.5, Neale et al., 2010), warmer drier scenario (GISS-E2-R, RCP4.5, Schmidt, 2014), hotter-wetter scenario (Miroc-ESM, RCP8.5, Watanabe et al., 2011), and hotter-drier...
This data set includes the relative production scenarios for sideoats grama [1.13(Temp) + 0.41(Precip) - 0.004(Precip)^2- 0.07(Sand) - 12.3]; this is the model from Epstein, et al. (1998). Soil texture (percent by weight) came from the Earth Systems Science Center (2008) which provided processed soils data from NRCS (gSSURGO), mean annual temperature (Celsius) and/or mean annual precipitation (millimeters) came from contemporary (1981 - 2010) estimates (Maurer et al. 2002) or a GCM. Global Climate Models (GCM) providing scenarios included: warmer-wetter scenario (CESM1-BGC, RCP4.5, Neale et al., 2010), warmer drier scenario (GISS-E2-R, RCP4.5, Schmidt, 2014), hotter-wetter scenario (Miroc-ESM, RCP8.5, Watanabe et...
This data set includes the relative production scenarios for little bluestem [0.26(Precip) - 4.04]; this is the model from Epstein, et al. (1998). Soil texture (percent by weight) came from the Earth Systems Science Center (2008) which provided processed soils data from NRCS (gSSURGO), mean annual temperature (Celsius) and/or mean annual precipitation (millimeters) came from contemporary (1981 - 2010) estimates (Maurer et al. 2002) or a GCM. Global Climate Models (GCM) providing scenarios included: warmer-wetter scenario (CESM1-BGC, RCP4.5, Neale et al., 2010), warmer drier scenario (GISS-E2-R, RCP4.5, Schmidt, 2014), hotter-wetter scenario (Miroc-ESM, RCP8.5, Watanabe et al., 2011), and hotter-drier scenario (ACCESS...
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We created a probabilistic classification model using the nonparametric machine learning technique 'Random Forests' for oil and gas development potential from low (0) to high (1) across the western US. The six predictor variables used in the model were: geophysical data showing aeromagnetic, isostatic gravity, and Bouguer gravity anomalies, geology, topography and bedrock depth. Our binary response variable was geospatial point data on producing and non-producing oil and gas wells. Our estimates provide insights into the trajectory and eventual endpoint of oil and gas development, but the rate and exact location of development will be subject to additional factors not considered such as market demand, the capacity...
This data set includes the relative production scenarios for blue grama [4.15(Temp) -0.3(Precip) - 0.15(Temp)^2 + 0.08]; this is the model from Epstein, et al. (1998). Soil texture (percent by weight) came from the Earth Systems Science Center (2008) which provided processed soils data from NRCS (gSSURGO), mean annual temperature (Celsius) and/or mean annual precipitation (millimeters) came from contemporary (1981 - 2010) estimates (Maurer et al. 2002) or a GCM. Global Climate Models (GCM) providing scenarios included: warmer-wetter scenario (CESM1-BGC, RCP4.5, Neale et al., 2010), warmer drier scenario (GISS-E2-R, RCP4.5, Schmidt, 2014), hotter-wetter scenario (Miroc-ESM, RCP8.5, Watanabe et al., 2011), and hotter-drier...
This data set includes the relative production scenarios for black grama [0.37(Temp) - 0.06(Precip) + 0.24]; this is the model from Epstein, et al. (1998). Soil texture (percent by weight) came from the Earth Systems Science Center (2008) which provided processed soils data from NRCS (gSSURGO), mean annual temperature (Celsius) and/or mean annual precipitation (millimeters) came from contemporary (1981 - 2010) estimates (Maurer et al. 2002) or a GCM. Global Climate Models (GCM) providing scenarios included: warmer-wetter scenario (CESM1-BGC, RCP4.5, Neale et al., 2010), warmer drier scenario (GISS-E2-R, RCP4.5, Schmidt, 2014), hotter-wetter scenario (Miroc-ESM, RCP8.5, Watanabe et al., 2011), and hotter-drier scenario...
This data set includes the relative production scenarios for Indiangrass [0.17(Precip) + 0.02(Sand) - 7.4]; this is the model from Epstein, et al. (1998). Soil texture (percent by weight) came from the Earth Systems Science Center (2008) which provided processed soils data from NRCS (gSSURGO), mean annual temperature (Celsius) and/or mean annual precipitation (millimeters) came from contemporary (1981 - 2010) estimates (Maurer et al. 2002) or a GCM. Global Climate Models (GCM) providing scenarios included: warmer-wetter scenario (CESM1-BGC, RCP4.5, Neale et al., 2010), warmer drier scenario (GISS-E2-R, RCP4.5, Schmidt, 2014), hotter-wetter scenario (Miroc-ESM, RCP8.5, Watanabe et al., 2011), and hotter-drier scenario...
This data set includes the relative production scenarios for tobosagrass [0.08(Temp) - 0.58]; this is the model from Epstein, et al. (1998). Soil texture (percent by weight) came from the Earth Systems Science Center (2008) which provided processed soils data from NRCS (gSSURGO), mean annual temperature (Celsius) and/or mean annual precipitation (millimeters) came from contemporary (1981 - 2010) estimates (Maurer et al. 2002) or a GCM. Global Climate Models (GCM) providing scenarios included: warmer-wetter scenario (CESM1-BGC, RCP4.5, Neale et al., 2010), warmer drier scenario (GISS-E2-R, RCP4.5, Schmidt, 2014), hotter-wetter scenario (Miroc-ESM, RCP8.5, Watanabe et al., 2011), and hotter-drier scenario (ACCESS...
This data set includes the relative production scenarios for big bluestem [3.08(Temp) -0.41(Precip)+0.14(Silt) - 0.16(Temp)^2 -31.9]; this is the model from Epstein, et al. (1998). Soil texture (percent by weight) came from the Earth Systems Science Center (2008) which provided processed soils data from NRCS (gSSURGO), mean annual temperature (Celsius) and/or mean annual precipitation (millimeters) came from contemporary (1981 - 2010) estimates (Maurer et al. 2002) or a GCM. Global Climate Models (GCM) providing scenarios included: warmer-wetter scenario (CESM1-BGC, RCP4.5, Neale et al., 2010), warmer drier scenario (GISS-E2-R, RCP4.5, Schmidt, 2014), hotter-wetter scenario (Miroc-ESM, RCP8.5, Watanabe et al., 2011),...
    map background search result map search result map Potential productivity and change estimates for eight grassland species to evaluate vulnerability to climate change in the southern Great Plains Oil and gas development potential in the US Intermountain West Potential productivity and change estimates for eight grassland species to evaluate vulnerability to climate change in the southern Great Plains Oil and gas development potential in the US Intermountain West