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Assessing drivers and tradeoffs of landscape diversification within U.S. agricultural systems

Authors: Kaitlyn Spangler*, Utah State University, Emily Burchfield, Emory University, Britta Schumacher, Utah State University
Topics: Agricultural Geography, Landscape, Food Systems
Keywords: agriculture, crop diversification, data integration, sustainable systems
Session Type: Paper
Presentation File: No File Uploaded

Within a growing concern over the simplification of agricultural landscapes across the U.S., this research aims to more deeply assess the possibilities and tradeoffs associated with on-farm and landscape diversification as adaptation strategies. Through secondary data analysis and fieldwork during 2019 in Magic Valley, Idaho, we integrate large-scale quantitative and in-depth qualitative data in the context of sustainable agricultural transitions. First, we utilized open-source national datasets to assess past and current trends in agricultural land use and the federal policy structure. This data-driven inquiry provides a broad understanding of the system within which farmers make decisions and adapt to current challenges. We also used a hierarchical Bayesian model linking agricultural land use diversity and yield of corn, soy, and wheat at the county scale to isolate regions that exhibit both high diversity and high yields. Several counties within the Magic Valley meet these criteria, and we seek to understand tradeoffs of farmer decision-making within this diverse and productive context. Thus, we conducted in-depth interviews, focus group discussions, and participant observation with twenty-three stakeholders to contextualize secondary data analyses. Informants represent a broad range of expertise: farmers, extension agents, academic researchers, and private industry personnel. We find that on-farm and landscape diversification in this area presents an array of social, ecological, and economic tradeoffs that are intertwined with the viability of diversification as adaptation. These findings inform a framework of integrating multiscale data to identify critical contextual factors to move U.S. production systems toward increased sustainability.

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