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This research project employs the Delphi method to systematically elicit expert-based expectations about the future of the agri-food system in the US, with a particular focus on policy, markets, technologies, and farm structure. The study is designed around two complementary Delphi surveys conducted with domain experts: a national survey focused on federal-level drivers and a state-level survey tailored to regional conditions in Ohio, Georgia, and Nebraska.
Combined with CMIP6 climate projections (SSP2-4.5, SSP3-7.0, and SSP5-8.5), expert projections of human-controlled variables generate forward-looking crop likelihood maps for 2041–2060.
The Delphi method is a structured, iterative process used to collect and synthesize expert judgments on complex and uncertain issues. Originally developed for forecasting purposes, the method is particularly useful in situations where empirical data may be limited or when future conditions are inherently uncertain — both of which apply to long-range projections of agricultural systems.
By aggregating the views of diverse, independent experts through multiple rounds of structured feedback, the Delphi method produces forecasts that reflect a broad consensus while preserving the nuance of individual expert reasoning.
Most future crop distribution models change only the climate, holding human factors fixed. Our Delphi framework explicitly projects how farming practices, policy environments, and market conditions are expected to evolve — producing more realistic and complete projections of future agricultural landscapes.
The national Delphi survey addressed a wide range of topics central to the US agri-sector, particularly those influenced by federal policy and national market dynamics. These topics reflect critical components of agri-policy and market systems that are expected to shape the future trajectory of US agriculture.
By focusing on these areas, the survey captures expert perspectives on how institutional programs and socio-market drivers may evolve over time and reshape the national agricultural landscape by mid-century.
The state-level surveys focused on issues that are region-specific but highly relevant to broader agri-food system transformations. Across Ohio, Georgia, and Nebraska, participants were asked about:
These topics reflect localized production realities, environmental conditions, and technological adoption patterns. For example, irrigation practices differ significantly across the three states due to climatic and hydrological differences, while emerging crop opportunities reflect distinct regional markets and agronomic conditions in each state.
Survey respondents were provided with graphical representations of trends over the past 15–20 years for each variable included in the Delphi questionnaires. These visualizations served as a baseline, helping participants anchor their expectations in observed patterns while still allowing room for forward-looking judgment.
Panelists then projected expected changes in each variable by 2050, expressed as directional shifts (increase, decrease, or remain stable) and, where possible, quantitative percentage-change estimates. These projections are applied as county-level adjustments to the historical predictor stack used in the random forest models.
Beyond quantitative forecasts, the survey design placed strong emphasis on collecting qualitative rationales. Respondents were asked to explain why they expected certain variables to increase, decrease, or remain stable. This qualitative component is crucial for understanding the mechanisms behind projected changes and for communicating model assumptions to non-technical audiences.
Analysis of responses across both national and state-level surveys reveals several major categories of drivers expected to shape future agricultural outcomes. Rather than being driven by a single factor, changes in key variables are expected to emerge from the interplay of multiple forces:
Shifting precipitation patterns, rising temperatures, and increased frequency of extreme events are expected to reshape what is agronomically viable in different regions.
Federal farm programs, conservation incentives, and climate policy will continue to shape the economic landscape within which farmers make planting decisions.
Corporate investment in agri-food infrastructure, input supply chains, and carbon markets will influence which crops are economically viable and where.
Advances in precision agriculture, genetic engineering, irrigation efficiency, and mechanization will expand the envelope of what is possible on American farms by 2050.
Farm consolidation, aging of the farm operator population, and the entry (or lack thereof) of beginning and young farmers will reshape the landscape of agricultural decision-making.
Shifts in consumer preferences — including demand for plant-based proteins, locally produced food, and sustainably grown commodities — will create new market signals that influence crop selection.
Across all responses, a central theme emerges: the future of the US agri-food system will be shaped by changes in climate and the evolving roles and interactions of actors and institutions. Our modeling framework is designed to capture this complexity rather than reduce it to climate alone.
Learn how Delphi projections are integrated into our modeling framework →