Optimal soil physical quality inferred through structural regression and parameter interactions

Soil physical quality (SPQ) is assessed by comparing values of "indicator" soil properties (e.g. bulk density, air capacity) to "ideal ranges" established in the literature. These ideal ranges may not be optimal for any particular soil or field site, however, as they are only "guidelines" based on broad soil types. The objective of this study was to determine if more relevant estimates of optimal indicator ranges can be obtained by using structural (Model II) regression to account for soil/site-specific indicator behaviour and interactions among the indicator parameters. The indicator parameters included relative water capacity (RWC), organic carbon content (OC), bulk density (BD), bulk soil air capacity (ACB), soil matrix air capacity (ACM), macroporosity (PORP), matrix porosity (PORM), field capacity (FC), plant-available water capacity (PAWC), and saturated hydraulic conductivity (KS). The indicators were determined using intact soil cores collected from the top 10 cm of a uniform, cool, humid clay loam soil under maize-soybean cropping, continuous bluegrass sod, and virgin soil. The structural regression analysis was applied by regressing RWC, OC, ACB, ACM, PORP, PORM, FC, PAWC and KS against BD using the "least squares bisector" method. Structural regression predicted soil/site-specific optimal ranges of 3 ≤ OC ≤ 4 wt.%, 1.10 ≤ BD ≤ 1.23 Mg m- 3, 0.16 ≤ ACB ≤ 0.22 m3 m- 3, 0.07 ≤ ACM ≤ 0.10 m3 m- 3, and 0.09 ≤ PORP ≤ 0.13 m3 m- 3, which are either narrower than the corresponding literature guidelines, or partially overlapping the guidelines. The regressions also provided information that is not currently available in the literature, including a possible optimal range for FC (0.30 ≤ FC ≤ 0.35 m3 m- 3), and plausible "upper limits" to the optimal ranges for ACB, ACM and PORP (see above). Optimal ranges were not obtainable for PORM and PAWC because they were effectively constant among the cropping and sod treatments. A questionably high optimal range was obtained for KS (8 × 10- 2 ≤ KS ≤ 7 × 10- 1 cm s- 1), and this was attributed to the perturbing effects of large, highly water-conductive macropores. The overall SPQ at the field site was judged by structural regression to be "poor" for maize-soybean cropping, "good" for bluegrass sod, and "fair" for virgin soil. It was concluded that structural regression is useful for determining soil/site-specific optimal ranges for SPQ indicators. Crown Copyright © 2008.