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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...
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The "_archive_workflow_FinalModel.zip" data bundle is comprised of the metadata and Vistrails workflow that contains the following history nodes, which contain modeling workflows: "NLCD2016 state bckgrnd" and "NLCD2016 wostate bckgrnd". These nodes produced the following 9 output rasters: 1) Probability map (without state) 2) MPP threshold (without state) 3) Five percent threshold (without state) 4) Ten percent threshold (without state) 5) Probability map (with state) 6) MPP threshold (with state) 7) Five percent threshold (with state) 8) Ten percent threshold (with state) 9) Maxent MESS map
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The 'archive_raster_inputs.zip' data bundle contains '_archive_raster_inputs_XX.tif' and archive_raster_inputs_XX.xml where XX is the name of 1 of 8 input rasters that were created and used to generate these model results. The original layers and sources used to produce each predictor, as well as processing steps, are specified in each .xml file.
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The purpose of this data release and associated data series (Carr and Fancher, 2021) was to compile occurrence records and map the distribution of a freshwater mussel assemblage for the Bureau of Land Management Rapid Ecoregional Assessment for the Southern Great Plains. The freshwater mussel assemblage includes Amblema plicata (threeridge), Fusconaia flava (Wabash pigtoe), Lampsilis cardium (plain pocketbook), Lampsilis teres (yellow sandshell), Pyganodon grandis (giant floater), and Uniomerus tetralasmus (pondhorn). The focal species in the assemblage were selected based on the following criteria: (1) the species are regionally significant, (2) occurrence records are sufficient to map the distribution of the species...
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 developed a second iteration of habitat suitability models for Lesser Prairie Chicken leks, across their range. The first modeling iteration used lek data collected from 2002 to 2012, land cover data ranging from 2001 to 2013, and anthropogenic features from 2011. Our second iteration model used occurrence points from new lek surveys (2015 to 2019) and updated predictor layers to evaluate changes in lek suitability and to quantify current range-wide habitat suitability. We created suitability models from 2 predictor sets: one including all predictors, and the other excluding state as a predictor. All 11 predictors included in the "with state" predictor set were: average Enhanced Vegetation Index (EVI), distance...
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The 'archive_raster_outputs.zip' data bundle includes 'XX.tif' and 'XX.xml' where XX is the name of 1 of 9 specific output rasters produced from '_archive_workflow_FinalModel.vt'. These outputs include continuous and thresholded probability maps for models including and excluding state as a predictor, as well as a MESS (Multivariate Environmental Similarity Surface) map that describes areas with restricted environmental conditions for this species.
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 Distribution of a freshwater mussel assemblage in Nebraska, Kansas, and Oklahoma Second Iteration of Range Wide Lesser Prairie Chicken Lek Habitat Suitability in 2019, Predicted in Southern Great Plains archive_raster_inputs archive_workflow_FinalModel archive_raster_outputs Second Iteration of Range Wide Lesser Prairie Chicken Lek Habitat Suitability in 2019, Predicted in Southern Great Plains archive_raster_inputs archive_workflow_FinalModel archive_raster_outputs Distribution of a freshwater mussel assemblage in Nebraska, Kansas, and Oklahoma Potential productivity and change estimates for eight grassland species to evaluate vulnerability to climate change in the southern Great Plains