INTEGRATION OF MULTIPLE SOIL PARAMETERS TO EVALUATE SOIL QUALITY - A FIELD EXAMPLE

Development of a method to assess and monitor soil quality is critical to soil resource management and policy formation. To be useful, a met hod for assessing soil quality must be able to integrate many differen t kinds of data, allow evaluation of soil quality based on alternative uses or definitions and estimate soil quality for unsampled locations . In the present study we used one such method, based on non-parametri c geostatistics. We evaluated soil quality from the integration of six soil variables measured at 220 locations in an agricultural field in southeastern Washington State. We converted the continous data values for each soil variable at each location to a binary variable indicator transform based on thresholds. We then combined indicator transformed data for individual soil variables into a single integrative indicato r of soil quality termed a multiple variable indicator transform (MVIT ). We observed that soil chemical variables, pools of soil resources, populations of microorgansims, and soil enzymes covaried spatially acr oss the landscape. These ensembles of soil variables were not randomly distributed, but rather were systematically patterned. Soil quality m aps calculated by kriging showed that the joint probabilities of meeti ng specific MVIT selection were influenced by the critical threshold v alues used to transform each individual soil quality variable and the MVIT selection criteria. If MVIT criteria adequately reflect soil qual ity then the kriging can produce maps of the probabilty of a soil bein g of good or poor quality.