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Cover crop residue decomposition in no-till cropping systems: Insights from multi-state on-farm litter bag studies
Agriculture, Ecosystems & Environment  (IF5.567),  Pub Date : 2021-12-12, DOI: 10.1016/j.agee.2021.107823
Resham Thapa, Katherine L. Tully, Chris Reberg-Horton, Miguel Cabrera, Brian W. Davis, David Fleisher, Julia Gaskin, Richard Hitchcock, Aurelie Poncet, Harry H. Schomberg, Sarah A. Seehaver, Dennis Timlin, Steven B. Mirsky

Cover crop (CC) residue decomposition influences the provisioning of agroecosystem services. While several laboratory and field studies have investigated processes and mechanisms of CC residue decomposition at specific point or plot scales, regional assessment of factors controlling decomposition rates (i.e., k-values) in no-till corn (Zea mays L.) systems are currently lacking. Here, we conducted the first multi-state on-farm litter bag studies over 105 site-years in the mid-Atlantic and Southeastern US states to determine the independent and combined effect of factors intrinsic to the field (soil and weather) and extrinsic or management factors (CC quantity and quality) on k-values. In the coastal plain regions, the k-values decreased as the underlying soils became sandier. Among weather variables, mean daily air relative humidity (RH) and number of rainy days showed stronger control on k-values than cumulative rainfall. This suggests faster decomposition of CC residues in humid environments and in site-years with frequent rain-events. Among extrinsic factors, the k-values decreased with higher CC biomass, C:N, residue holo-cellulose concentrations, and lignin:N, but increased with higher residue carbohydrate concentrations. The combination of CC residue quality (C:N and holo-cellulose) and weather (RH and rainy days) variables accounted in total for 69% of the variability in k-values with CC residue quality having a greater control over k-values than does weather in the mid-Atlantic and Southeastern US states. Therefore, our study emphasizes the necessity to update current process-based decomposition models to explicitly consider both CC residue quality (C:N, holo-cellulose) and weather factors (RH, rainy days), when predicting CC residue decomposition in no-till cropping systems.