Submitted to: Soil Science Society of America Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: June 2, 2004
Publication Date: November 1, 2004
Citation: Andrews, S.S., Karlen, D.L., Cambardella, C.A. 2004. The soil management assessment framework: a quantitative soil quality evaluation method with case studies. Soil Science Society of America Journal. 68:1945-1962. Interpretive Summary: Continued soil degradation through erosion, loss of soil organic matter, reduced fertility and productivity, or chemical and heavy metal contamination and the resultant degradation of air and water quality have sparked interest in the concept of soil quality and its assessment. During the past decade we have been among the leaders with regard to developing a useful and acceptable method for assessing soil quality based on the critical functions that soil resources must perform if they are to be maintained or improved in a sustainable condition. This manuscript provides a comprehensive description and examples of a soil management assessment framework (SMAF) developed as a tool that land managers, conservationists, and producers can use to better understand the multiple interactive effects that their soil management decisions are having on their soil resource. We recognize that the SMAF will require additional development, but based on the case studies conducted to date, we are confident that its use can lead to more sustainable soil management decisions.
Technical Abstract: Erosion rates and annual soil loss tolerance (T) values in evaluations of soil management practices have served as focal points for soil quality research and assessment programs for decades. Our objective is to enhance and extend current soil assessment efforts by presenting an evaluation framework that can be used to evaluate the impact of soil management practices on soil function. The tool consists of three steps: indicator selection, indicator interpretation, and integration into an index. Designed as a framework, this soil quality assessment tool allows researchers to continually update and refine the interpretations for many soils, climates, and land use practices. The framework was evaluated using data from case studies in GA, IA, CA, and the Pacific Northwest (WA, ID, OR). Applying decision rules based on management goals and other site-specific factors in the selection step successfully identified indicators that were present in the existing data sets. The interpretation step resulted in valid agronomic and site-specific differences in indicator scores. The efficacy of the indicator interpretation step was evaluated with stepwise regressions using scored and observed indicators as independent variables and outcome data as iterative dependent variables. Scored indicators usually had coefficients of determination (R2) that were similar or greater than those of the observed indicator values. In some cases, the R2 values for indicators and outcome regressions were higher when examined for individual treatments rather than the entire data set. This study demonstrates significant progress toward development of an assessment framework for adaptive soil resource management or monitoring that is transferable to a variety of climates, soil types, and soil management systems.