The purpose of this project was to estimate and map the probability that grassland converts to cropland in the northern plains and prairie region given potential climate change. This region provides critical breeding and migratory habitat for waterfowl and other wetland-dependent species, and is also a highly productive agricultural region. Generally, the regional effects projected by climate models are increasing temperatures and more variable precipitation, which could provide incentives for private landowners to convert native and managed grassland to intensive cropland. Conversion of grassland to cropland can result in habitat loss for dependent species and the degradation of a range of ecosystem services. If climate change alters the spatial distribution of both agricultural land use and suitable habitat, land managers and conservationists may need to alter efforts to offset the negative consequences of combined climate and land-use change on habitats and dependent species. The land-use change projections associated with this report provide information for such management efforts.

The impact of climate change on land conversion was assessed by projecting the land-use model under GCM hindcast and forecast climatic conditions. For each GCM, we projected future row crop proportions under 40 years of average hindcast conditions (i.e., assuming historical climate prevails into the future), and under 20 year of average hindcast conditions followed by 20 years of average forecast conditions. We used twenty years of forecast conditions to avoid assuming that climate changes projected for mid-century would have occurred immediately. The 20-20 assumption approximates a linear transition from the historic to future climate and is not limiting since the probabilities will converge given sufficient years under a given climate regime. Projected climate change impacts differed in direction and spatial pattern between GCMs (Fig. S3). Projected changes in the proportion of the landscape planted in row crops were generally small (mean change = 0.01), but included increases of over 0.25 of the landscape and declines of over 0.3 of the landscape (Fig. S3). Conversion probabilities responded to precipitation as expected, with an increase in precipitation associated with higher probabilities that grass converts to crops and lower probabilities that crops convert to grass.

The impact of climate change on land conversion was assessed by projecting the land-use model under GCM hindcast and forecast climatic conditions. For each GCM, we projected future row crop proportions under 40 years of average hindcast conditions (i.e., assuming historical climate prevails into the future), and under 20 year of average hindcast conditions followed by 20 years of average forecast conditions. We used twenty years of forecast conditions to avoid assuming that climate changes projected for mid-century would have occurred immediately. The 20-20 assumption approximates a linear transition from the historic to future climate and is not limiting since the probabilities will converge given sufficient years under a given climate regime. Projected climate change impacts differed in direction and spatial pattern between GCMs (Fig. S3). Projected changes in the proportion of the landscape planted in row crops were generally small (mean change = 0.01), but included increases of over 0.25 of the landscape and declines of over 0.3 of the landscape (Fig. S3). Conversion probabilities responded to precipitation as expected, with an increase in precipitation associated with higher probabilities that grass converts to crops and lower probabilities that crops convert to grass.

The purpose of this project was to map the estimated distribution of grassland communities of the Southern Great Plains prior to Euro-American settlement. The Southern Great Plains Rapid Ecoregional Assessment (REA), under the direction of the Bureau of Land Management and the Great Plains Landscape Conservation Cooperative, includes four ecoregions: the High Plains, Central Great Plains, Southwestern Tablelands, and the Nebraska Sand Hills. The REA advisors and stakeholders determined that the mapping accuracy of available national land-cover maps was insufficient in many areas to adequately address management questions for the REA. Based on the recommendation of the REA stakeholders, we estimated the potential historical distribution of 10 grassland communities within the Southern Great Plains project area using data on soils, climate, and vegetation from the Natural Resources Conservation Service (NRCS) including the Soil Survey Geographic Database (SSURGO) and Ecological Site Information System (ESIS). The dominant grassland communities of the Southern Great Plains addressed as conservation elements for the REA area are shortgrass, mixed-grass, and sand prairies. We also mapped tall-grass, mid-grass, northwest mixed-grass, and cool season bunchgrass prairies, saline and foothill grasslands, and semi-desert grassland and steppe. Grassland communities were primarily defined using the annual productivity of dominant species in the ESIS data. The historical grassland community classification was linked to the SSURGO data using vegetation types associated with the predominant component of mapped soil units as defined in the ESIS data. We augmented NRCS data with Landscape Fire and Resource Management Planning Tools (LANDFIRE) Biophysical Settings classifications 1) where NRCS data were unavailable and 2) where fifth-level watersheds intersected the boundary of the High Plains ecoregion in Wyoming. Spatial data representing the estimated historical distribution of grassland communities of the Southern Great Plains are provided as a 30 x 30-meter gridded surface (raster dataset). This information will help to address the priority management questions for grassland communities for the Southern Great Plains REA and can be used to inform other regional-level land management decisions.

This dataset provides an additional "Grazing Potential" land use class to the previously published U.S. Geological Survey (USGS) National Water-Quality Program (NAWQA) Wall-to-Wall Anthropogenic Land-use Trends (NWALT) product (Falcone, 2015, USGS Data Series 948). As with the NWALT, the dataset consists of five national 60-m land use grids, for the years 1974, 1982, 1992, 2002, 2012. The only change to the dataset is, for every year, some pixels which are class 50 "Low-use" in the NWALT, are reclassified to a new class 46 "Grazing Potential Expanded". The purpose of the re-classification is to identify areas which are likely to have had at least some grazing activity based on agreement of historical land cover/use datasets, and not already captured as another land use class by the original NWALT. The re-classification occurred as follows: pixel would otherwise be in class 50 (Low Use), is in an Agriculture or Grazed class in Marschner and Anderson (1967), is in an Agriculture or Rangeland class in 1970s-era GIRAS, and is in a Grassland/Herbaceous class (71) in the NLCD 2011, without restrictions to proximity to water or slope. Falcone, J.A., 2015, U.S. conterminous wall-to-wall anthropogenic land use trends (NWALT), 1974–2012: U.S. Geological Survey Data Series 948, 33 p. plus appendixes 3–6 as separate files, http://dx.doi.org/10.3133/ds948. Marschner, F.J. and Anderson, J.R., 1967, Major land uses in the United States, U.S. Geological Survey, http://water.usgs.gov/GIS/metadata/usgswrd/XML/na70_landuse.xml

The USGS Forecasting Scenarios of Land-use Change (FORE-SCE) model was used to produce an agricultural biofuel scenarios for the Northern Glaciated Plains, from 2012 to 2030. The modeling used parcel data from the USDA's Common Land Unit (CLU) data set to represent real, contiguous ownership and land management units. A Monte Carlo approach was used to create 50 unique replicates of potential landscape conditions in the future, based on a agricultural scenario from the U.S. Department of Energy's Billion Ton Update. The data are spatially explicit, covering the entire Northern Glaciated Plains ecoregions (an EPA Level III ecoregion), with a spatial resolution of 30-meters and 22 unique land-cover classes (including common crop types in the region). Files included are 1) the starting land cover data set for 2012, 2) 50 Monte Carlo replicates of 2030 land cover, and 3) supporting metadata. data represent 50 individual Monte Carlo runs for the 2012 to 2030 biofuel scenario in the Northern Glaciated Plains ecoregion,

The USGS Forecasting Scenarios of Land-use Change (FORE-SCE) model was used to produce an agricultural biofuel scenarios for the Northern Glaciated Plains, from 2012 to 2030. The modeling used parcel data from the USDA's Common Land Unit (CLU) data set to represent real, contiguous ownership and land management units. A Monte Carlo approach was used to create 50 unique replicates of potential landscape conditions in the future, based on a agricultural scenario from the U.S. Department of Energy's Billion Ton Update. The data are spatially explicit, covering the entire Northern Glaciated Plains ecoregions (an EPA Level III ecoregion), with a spatial resolution of 30-meters and 22 unique land-cover classes (including common crop types in the region). Files included are 1) the starting land cover data set for 2012, 2) 50 Monte Carlo replicates of 2030 land cover, and 3) supporting metadata. data represent 50 individual Monte Carlo runs for the 2012 to 2030 biofuel scenario in the Northern Glaciated Plains ecoregion,

Land use change ranges in each panel are in acres per thousand county acres. The white colored counties represent missing yields for at least one crop in all years.

Land use change ranges in each panel are in acres per thousand county acres. The white colored counties represent missing yields for at least one crop in all years.

Probability map of Crested wheatgrass occurrence in relation to vegetation, abiotic, and anthropogenic features.