Agro-ecoregionalization of Iowa using multivariate geographical clustering

Agro-ecoregionalization is categorization of landscapes for use in crop suitability analysis, strategic agroeconomic development, risk analysis, and other purposes. Past agro-ecoregionalizations have been subjective, expert opinion driven, crop specific, and unsuitable for statistical extrapolation. Use of quantitative analytical methods provides an opportunity for delineation of agro-ecoregions in a more objective and reproducible manner, and with use of generalized crop-related environmental inputs offers an opportunity for delineation of regions with broader application. For this study, raster (cell-based) environmental data at 1 km scale were used in a multivariate geographic clustering process to delineate agroecozones. Environmental parameters included climatic, edaphic and topographic characteristics hypothesized to be generally relevant to many crops. Clustering was performed using five a priori grouping schemes of 5–25 agroecozones. Non-contiguous geographic zones were defined representing areas of similar crop-relevant environmental conditions. A red–green–blue color triplet was used for visualization of agroecozones as unique combinations of environmental factors. Concordance of the agroecozones with other widely used datasets was investigated using MapCurves, a quantitative goodness-of-fit method. The 5- and 25-agroecozone schemes had highest concordance with a map of major land resource areas and a map of major landform regions, with degree of fit judged to be good. The resulting agroecozones provide a framework for future rigorous hypothesis testing. Other applications include: quantitative evaluation of crop suitability at the landscape scale, environmental impact modeling and agricultural scenario building.