Agro-ecoregionalization of Iowa using multivariate geographical clustering

  • Authors: Williams, Carol L.; Hargrove, William W.; Leibman, Matt; James, David E.
  • Publication Year: 2008
  • Publication Series: Miscellaneous Publication
  • Source: Agriculture, Ecosystems and Environment, Vol. 123: 161-174

Abstract

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.

  • Citation: Williams, Carol L.; Hargrove, William W.; Leibman, Matt; James, David E. 2008. Agro-ecoregionalization of Iowa using multivariate geographical clustering. Agriculture, Ecosystems and Environment, Vol. 123: 161-174
  • Keywords: agroecopause, agroecozone, mapcurves, multivariate geographic clustering
  • Posted Date: November 27, 2007
  • Modified Date: November 29, 2007
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