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Divergent projections of future land use in the United States arising from different models and scenarios

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  • Sohl, Terry L.
  • Wimberly, Michael C.
  • Radeloff, Volker C.
  • Theobald, David M.
  • Sleeter, Benjamin M.

Abstract

A variety of land-use and land-cover (LULC) models operating at scales from local to global have been developed in recent years, including a number of models that provide spatially explicit, multi-class LULC projections for the conterminous United States. This diversity of modeling approaches raises the question: how consistent are their projections of future land use? We compared projections from six LULC modeling applications for the United States and assessed quantitative, spatial, and conceptual inconsistencies. Each set of projections provided multiple scenarios covering a period from roughly 2000 to 2050. Given the unique spatial, thematic, and temporal characteristics of each set of projections, individual projections were aggregated to a common set of basic, generalized LULC classes (i.e., cropland, pasture, forest, range, and urban) and summarized at the county level across the conterminous United States. We found very little agreement in projected future LULC trends and patterns among the different models. Variability among scenarios for a given model was generally lower than variability among different models, in terms of both trends in the amounts of basic LULC classes and their projected spatial patterns. Even when different models assessed the same purported scenario, model projections varied substantially. Projections of agricultural trends were often far above the maximum historical amounts, raising concerns about the realism of the projections. Comparisons among models were hindered by major discrepancies in categorical definitions, and suggest a need for standardization of historical LULC data sources. To capture a broader range of uncertainties, ensemble modeling approaches are also recommended. However, the vast inconsistencies among LULC models raise questions about the theoretical and conceptual underpinnings of current modeling approaches. Given the substantial effects that land-use change can have on ecological and societal processes, there is a need for improvement in LULC theory and modeling capabilities to improve acceptance and use of regional- to national-scale LULC projections for the United States and elsewhere.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ecomod:v:337:y:2016:i:c:p:281-297
    DOI: 10.1016/j.ecolmodel.2016.07.016
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    Cited by:

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    2. Jordan Dornbierer & Steve Wika & Charles Robison & Gregory Rouze & Terry Sohl, 2021. "Prototyping a Methodology for Long-Term (1680–2100) Historical-to-Future Landscape Modeling for the Conterminous United States," Land, MDPI, vol. 10(5), pages 1-31, May.
    3. Yee, Susan H. & Paulukonis, E. & Simmons, C. & Russell, M. & Fulford, R. & Harwell, L. & Smith, L.M., 2021. "Projecting effects of land use change on human well-being through changes in ecosystem services," Ecological Modelling, Elsevier, vol. 440(C).
    4. Behnoosh Abbasnezhad & Jesse B. Abrams & Jeffrey Hepinstall-Cymerman, 2023. "Incorporating Social and Policy Drivers into Land-Use and Land-Cover Projection," Sustainability, MDPI, vol. 15(19), pages 1-18, September.
    5. 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.
    6. Hui Xiang & Yinhua Ma & Rongrong Zhang & Hongji Chen & Qingyuan Yang, 2022. "Spatio-Temporal Evolution and Future Simulation of Agricultural Land Use in Xiangxi, Central China," Land, MDPI, vol. 11(4), pages 1-16, April.
    7. Peizhi Tian & Binyang Jian & Jianrui Li & Xitian Cai & Jiangfeng Wei & Guo Zhang, 2023. "Land-Use-Change-Induced Cooling and Precipitation Reduction in China: Insights from CMIP6 Models," Sustainability, MDPI, vol. 15(16), pages 1-24, August.

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