Spatiotemporal Patterns for Agroforestry Tree Crops in the U.S. Corn Belt for USDA Census of Agriculture Periods 2012–2022 - Andria Caruthers; Justin Dijak; Robin Rotman (Agriculture)
Within the U.S., there is a growing need to integrate environmentally friendly practices into conventional agriculture. Agroforestry enhances environmental and resource stewardship in agricultural landscapes while offering potential economic benefits to farmers. Despite rising interest, limited information on its application in the U.S. hinders development efforts. A spatiotemporal analysis of current farm operations can provide crucial insights. This study examined patterns of agroforestry and tree crop adoption in the U.S. Corn Belt using USDA Census data (2012, 2017, and 2022) and spatial tools (Global Moran’s I, Local Moran’s I, and Moran scatterplots). The tree crops included in the analysis were chestnut (Castanea spp.), hazelnut (Corylus spp.), improved northern pecan (Carya illinoinensis), elderberry (Sambucus spp.), and pawpaw (Asimina triloba). The results showed increasing farm operations with agroforestry and tree crops over time for all census periods. Agroforestry had the strongest spatial cluster patterns, with Local Moran’s I revealing R2 values rising from 0.30 to 0.35 between 2017 and 2022. Chestnut, hazelnut, and improved pecan had clustered spatial patterns, but had decreasing spatial autocorrelations from 2012 to 2022, while elderberry clustered in 2017 but not 2022. This study reveals an upward trend in agroforestry adoption and the spatial expansion of certain tree crops in the U.S. Corn Belt, highlighting potential for region-specific agroforestry development. The findings offer insights to guide strategies and programs supporting sustainable agricultural practices.