Abstract

Land management decisions need context about how landscapes will respond to different circumstances or actions. As ecologists’ understanding of nonlinear ecological dynamics has evolved into state-and-transition models (STMs), they have put more emphasis on defining and mapping the soil, geomorphological, and climate parameters that mediate these dynamics. The US Department of Agriculture Natural Resources Conservation Service ecological site descriptions (ESDs) have become the foremost system in classifying lands into ecological units based on STMs. However, an exhaustive inventory of ESDs has proved challenging to complete in the United States, and there have been questions about the consistency of detail in areas completed and the ability to objectively support some assertions made in existing ESDs. To address these issues, this study examines ESDs in the diverse Upper Colorado River region, where ESDs are only partially complete, to look at quantitative approaches to generalizing ecological site concepts based on unifying underlying soil, geomorphology, and climate patterns. Using existing ESDs and vegetation monitoring plot data, results show that a simple hierarchical soil geomorphic unit (SGU) framework based on topographic mediation of moisture, soil salinity, soil depth, slope, rock content, and soil texture can represent much of the ecological dynamics cataloged in ESDs. Analyses of reference plant production data, ecological state attribution, and regional monitoring data show that the new SGUs represent more variation than common climate parameters. This study also included predictively mapping SGUs at 30-m resolution (Kappa of 0.53, 74% agreement with top two predictions in validation). An optimized combination of SGUs with climate zones derived from an aridity index and maximum temperature of the hottest month resulted in an ecological site group framework that condensed over 826 unique ecological site records at various stages of completeness in the regional soil survey down to 35 intuitive and mappable ecological site groups.

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