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U.S. Farmland under Threat of Urbanization: Future Development Scenarios to 2040

Author

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  • Yanhua Xie

    (Nelson Institute Center for Sustainability and the Global Environment (SAGE), University of Wisconsin-Madison, 1710 University Avenue, Madison, WI 53726, USA
    DOE Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI 53726, USA)

  • Mitch Hunter

    (Forever Green Initiative and Department of Agronomy and Plant Genetics, University of Minnesota, Saint Paul, MN 55108, USA)

  • Ann Sorensen

    (American Farmland Trust, 1150 Connecticut Ave NW, Suite 600, Washington, DC 20036, USA)

  • Theresa Nogeire-McRae

    (American Farmland Trust, 1150 Connecticut Ave NW, Suite 600, Washington, DC 20036, USA)

  • Ryan Murphy

    (American Farmland Trust, 1150 Connecticut Ave NW, Suite 600, Washington, DC 20036, USA)

  • Justin P. Suraci

    (Conservation Science Partners, Inc., Truckee, CA 96161, USA)

  • Stacy Lischka

    (Conservation Science Partners, Inc., Truckee, CA 96161, USA
    Social Ecological Solutions LLC, Fort Collins, CO 80526, USA)

  • Tyler J. Lark

    (Nelson Institute Center for Sustainability and the Global Environment (SAGE), University of Wisconsin-Madison, 1710 University Avenue, Madison, WI 53726, USA
    DOE Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI 53726, USA)

Abstract

Urbanization imperils agriculture by converting farmland into uncultivable impervious surfaces and other uses that limit land productivity. Despite the considerable loss of productive croplands due to historic urbanization in the United States, little is known about the locations and magnitudes of extant agricultural land still under threat of future urban expansion. In this study, we developed a spatially explicit machine learning-based method to predict urban development through 2040 under a business-as-usual scenario and explored its occurrence on existing farmland. We found that if urban development continues at the same pace as that between 2001 and 2016, by 2040, highly developed areas and low-density residential areas will increase by 9.5 and 21 million acres, respectively. This increase would result in 18 million acres of agricultural land lost, fragmented, or compromised (~2% of total agricultural lands in 2016), with the remainder of projected development occurring on other types of natural and semi-natural lands. Of the affected agricultural lands, 6.2 million acres (34%) would be converted to uncultivable urban uses and 12 million acres (66%) to low-density residential uses. Agricultural land losses are projected to be greatest in fast-growing regions such as Texas, California, and the Southeast, and on the outskirts of metropolitan areas across the country, especially in the Midwest, where agricultural lands are more concentrated. The losses as a percentage of existing agricultural lands are projected to be highest along the East Coast, where many urban areas are forecasted to expand onto a limited remaining pool of cultivable lands. These findings can help guide the efforts of local, state, and federal policymakers to reduce land use competition between urban and agricultural systems and mitigate the impacts of projected urban expansion.

Suggested Citation

  • Yanhua Xie & Mitch Hunter & Ann Sorensen & Theresa Nogeire-McRae & Ryan Murphy & Justin P. Suraci & Stacy Lischka & Tyler J. Lark, 2023. "U.S. Farmland under Threat of Urbanization: Future Development Scenarios to 2040," Land, MDPI, vol. 12(3), pages 1-19, February.
  • Handle: RePEc:gam:jlands:v:12:y:2023:i:3:p:574-:d:1081815
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    References listed on IDEAS

    as
    1. Kaifang Shi & Yun Chen & Bailang Yu & Tingbao Xu & Linyi Li & Chang Huang & Rui Liu & Zuoqi Chen & Jianping Wu, 2016. "Urban Expansion and Agricultural Land Loss in China: A Multiscale Perspective," Sustainability, MDPI, vol. 8(8), pages 1-16, August.
    2. Sohl, Terry L. & Wimberly, Michael C. & Radeloff, Volker C. & Theobald, David M. & Sleeter, Benjamin M., 2016. "Divergent projections of future land use in the United States arising from different models and scenarios," Ecological Modelling, Elsevier, vol. 337(C), pages 281-297.
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