Geographic Determinants of Rural Land Covers and the Agricultural Margin in the Central United States

Geographic research on the Corn Belt and other regional landscapes of the central U.S. has not to date identified quantitatively the climatic, edaphic, topographic, and economic characteristics that determine rural land cover, and that therefore govern land cover change. Using the USDA/NASS Cropland Data Layer, this study identifies these characteristics by employing Multivariable Fractional Polynomials within a logistic regression framework. It maps the suitability distribution for corn, soybeans, spring and winter wheat, cotton, grassland, and forest, which collectively dominate the central U.S., at a 56 m resolution across 16 central U.S. states. The non-linear logistic regression models are successful in identifying determinants of land cover with relative operating characteristic (ROC) scores that range from 0.769 for soybeans to 0.888 for forest, with a combined corn/soybean model achieving an ROC of 0.871. For corn and soybean models, when prior land cover of a pixel is added, predictability and ROC scores increase substantially (0.07–0.10), indicating a strong temporal dependency in land cover dynamics due to crop rotation. This process also aids in the delineation of fields from pixels. When neighboring land covers are added to the models, ROC scores improve only slightly (0.014–0.019), however, indicating a weak spatial dependency or contagious diffusion mechanism. By including annual crop prices within the logit models, economically marginal cropland that comes into crop production only when prices are high is identified in a spatially-explicit manner. This capacity informs analyses of policies that affect crop prices (e.g., subsidies for crops or biofuels, changes in global supply and demand), by identifying the consequent changes in land use patterns – changes that modify the economic and environmental performance of the landscape

GEOGRAPHIC EFFECTS OF CLIMATE CHANGE ON MAJOR RURAL LAND COVERS OF THE CENTRAL UNITED STATES

Geographic research on the Corn Belt and other regional landscapes of the central U.S. has not to date identified quantitatively the climatic, edaphic, topographic, and economic characteristics that determine rural land cover, and that therefore govern land cover change. Using the USDA/NASS Cropland Data Layer, this study identifies these characteristics using Multivariable Fractional Polynomials within a logistic regression framework. It maps the suitability distribution for corn, soybeans, spring and winter wheat, cotton, grassland, and forest land covers that dominate the central U.S., at a 56m resolution across 16 central U.S. states. The non-linear logistic regression models are successful in identifying determinants of land cover with relative operating characteristic (ROC) scores that range from 0.769 for soybeans to 0.888 for forest, with a combined corn/soybean model achieving an ROC of 0.871. For corn and soybean models, when prior land cover of a pixel is added, predictability and ROC scores increase substantially (0.07-0.10), indicating a strong temporal feedback in land cover dynamics. This process also aids in the delineation of fields from pixels. Adding neighboring land covers, however, improves predictability and ROC scores only slightly (0.014-0.019), indicating a weak spatial feedback mechanism. By including annual crop prices within the logit models, economically marginal cropland that comes into crop production only when prices are high is identified in a spatially-explicit manner. This capacity improves further analyses of economic and environmental impacts of policies that affect crop prices. The sustainability of current rural land use trends in the central U.S. is highly dependent on the ability to adapt to changing climatic conditions of the 21st century. As the climate begins to shift towards longer growing seasons, more erratic rainfall patterns, and overall warmer temperatures, there is potential for major impacts on seven major land covers of the central U.S. Suitability landscapes of individual land covers (corn, soybeans, spring and winter wheat, cotton, grasslands, and forests) were utilized to determine the influence of climate change on these landscapes. Twenty-seven climate change projection scenarios based on three global climate models, three representative concentration pathways, and three time periods were applied to the land cover suitability maps utilizing raster regression. The area now identified as the Corn Belt is projected to see a dramatic shift in the suitable climate with a potential for a 30 percent increase in summer growing degree days. While the area where conditions are suitable for corn, soybeans and spring wheat are all expected to decrease, winter wheat has the potential to increase in suitable area. In order to maintain current geographic patterns of crop production, corn would need to be adapted to higher temperatures

Maps (pdf) and raster images (tif) of predicted rural land cover suitability under current (2010) conditions and future climate scenarios

This study projects land cover probabilities under climate change for corn (maize), soybeans, spring and winter wheat, winter wheat-soybean double cropping, cotton, grassland and forest across 16 central U.S. states at a high spatial resolution, while also taking into account the influence of soil characteristics and topography. The scenarios span three oceanic-atmospheric global circulation models, three Representative Concentration Pathways, and three time periods (2040, 2070, 2100). As climate change intensifies, the suitable area for all six crops display large northward shifts. Total suitable area for spring wheat, followed by corn and soybeans, diminish. Suitable area for winter wheat and for winter wheat-soybean double-cropping expand northward, while cotton suitability migrates to new, more northerly, locations. Suitability for forest intensifies in the south while yielding to crops in the north; grassland intensifies in the western Great Plains as crop suitability diminishes. To maintain current broad geographic patterns of land use, large changes in the thermal response of crops such as corn would be required. A transition from corn-soybean to winter wheat-soybean doubling cropping is an alternative adaptation