Partitioning of Heterotrophic Soil Respiration in Corn and Switchgrass to Evaluate In Situ Soil Organic Matter Decomposition Dynamics
Tuesday, 16 December 2014
The vast majority of in situ soil carbon efflux studies measure total CO2 evolution (RS) from soil, which consists of both heterotrophic-(RH) and autotrophic-(RA) derived carbon sources. Because RA represents recently fixed carbon that is relatively transient within the plant-soil system, partitioning RH from RA is necessary for understanding organic matter decomposition and deriving ecosystem carbon balances. Management practices and vegetation type can influence RH through the effects of soil tillage, litter inputs, root turnover, root exudates, and soil microclimate. Yet, partitioning RH and RA in the field has proven notoriously challenging, and all current methods are subject to certain biases. The root exclusion method is the most common technique for estimating RH, but removing live roots from soil can alter physical conditions and thus may bias the RH estimate. Our objective was to derive and compare in situ estimates of RH in corn (Zea mays) and switchgrass (Panicum virgatum) temperate bioenergy cropping systems. We hypothesized that summer RH would be greater in corn compared to switchgrass due to tillage practices and generally warmer surface soil conditions in corn. Additionally, we hypothesized that the root exclusion method would provide relatively low estimates of RH, particularly during high precipitation periods when the root exclusions may hold excess moisture. We evaluated our hypotheses in July 2014 at the Great Lakes Bioenergy Research Center cropping systems trial in Arlington, WI, USA. Total RH averaged 50% greater in corn than in switchgrass, but the percent contribution of RH to RS was statistically similar between cropping systems at 24%. Following an abnormally wet June, RH estimates were 18% of RS, which is lower than most studies in similar cropping systems. However, as root exclusions dried out throughout July, RH gradually increased to 30% of RS. Continuing efforts will better constrain RH estimates using the root regression method and will additionally assess the effects of soil temperature and moisture on RH.