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Data Sheet 1_Environmental outcomes of landscape-scale agricultural transitions in the Upper Midwestern U.S..docx

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NIAID Data Ecosystem2026-05-02 收录
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https://figshare.com/articles/dataset/Data_Sheet_1_Environmental_outcomes_of_landscape-scale_agricultural_transitions_in_the_Upper_Midwestern_U_S_docx/29134229
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The United States (U.S.) Corn Belt leads North America in row crop production, yet this high productivity comes at an environmental cost in terms of nitrate loss, soil erosion, and greenhouse gas emissions. In this study, we focus on the Upper Mississippi River basin within the U.S. Corn Belt, which represents a landscape scale for agricultural transformation. We outline a methodology to assess a suite of environmental outcomes associated with the transition from summer annual maize/soybean systems to incorporation of continuous living cover systems. We use and expand publicly available tools alongside empirical data to assess nitrate loss, soil erosion, and greenhouse gas emissions for four potential agricultural transition scenarios in the region, on an annual basis compared to a business-as-usual maize/soybean rotation. We consider the following four scenarios: incorporating (1) winter annual cover crops or (2) winter annual oilseeds into 50% of maize and soybean hectares in the region, or converting 50% of marginally productive maize and soybean hectares to (3) agroforestry or (4) pastured livestock systems. Our results indicate that all four systems are likely to reduce topsoil loss when compared to maize and soybean systems, and that the more transformative systems—agroforestry and pastured livestock—have the greatest potential to reduce nitrate loss. Yet, our results suggest that among these transitions, there are tradeoffs in environmental outcomes. For example, pastured livestock and winter annual oilseeds could potentially increase greenhouse gas emissions relative to maize/soybean systems. Our results illustrate that continuous living cover could improve environmental outcomes in the Upper Midwest, but there is tremendous uncertainty and variability surrounding those outcomes.
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2025-05-23
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