Guo, T., S. T. Marquart-Pyatt, and G. P. Robertson. 2023. Using three consecutive years of farmer survey data to identify prevailing conservation practices in four Midwestern US states. Renewable Agriculture and Food Systems 38:E44.
Granular temporal and spatial scale observations of conservation practices are essential for identifying changes in the production systems that improve soil health and water quality and inform long-term agricultural research and adaptive policy development. In this study, we demonstrate an innovative use of farmer practice survey data and what can be uniquely known from a detailed survey that targets specific farm groups with a regional focus over multiple consecutive years. Using three years of survey data (n = 3914 respondents), we describe prevailing crop rotation, tillage, and cover crop practice use in four Midwestern US states. Like national metrics, the results confirm dominant practices across the landscape, including corn-soybean rotation, little use of continuous no-till, and the limited use of cover crops. Our detailed regional survey further reveals differences by state for no-till and cover crop adoption rates that were not captured in federal datasets. For example, 66% of sampled acreage in the Midwest has corn and soybean rotation, with Illinois having the highest rate (72%) and Michigan the lowest (41%). In 2018, 20% of the corn acreage and 38% of the soybean acreage were in no-till, and 13% of the corn acres and 9% of the soybean acres were planted with a cover crop. Cover crop adoption rates fluctuate from year to year. Results demonstrate the value of a farmer survey at state scales over multiple years in complementing federal statistics and monitoring state and yearly differences in practice adoption. Agricultural policies and industry heavily depend on accurate and timely information that reflects spatial and temporal dynamics. We recommend building an agricultural information exchange and workforce that integrates diverse data sources with complementary strengths to provide a greater understanding of agricultural management practices that provide baseline data for prevailing practices.
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