Spatial patterns in temperature sensitivity of soil respiration in China: Estimation with inverse modeling

Temperature sensitivity of soil respiration (Q₁₀) is an important parameter in modeling the effects of global warming on ecosystem carbon release. Experimental studies of soil respiration have ubiquitously indicated that Q₁₀ has high spatial heterogeneity. However, most biogeochemical models still use a constant Q₁₀ in projecting future climate change and no spatial pattern of Q₁₀ values at large scales has been derived. In this study, we conducted an inverse modeling analysis to retrieve the spatial pattern of Q₁₀ in China at 8 km spatial resolution by assimilating data of soil organic carbon into a process-based terrestrial carbon model (CASA model). The results indicate that the optimized Q₁₀ values are spatially heterogeneous and consistent to the values derived from soil respiration observations. The mean Q₁₀ values of different soil types range from 1.09 to 2.38, with the highest value in volcanic soil, and the lowest value in cold brown calcic soil. The spatial pattern of Q₁₀ is related to environmental factors, especially precipitation and top soil organic carbon content. This study demonstrates that inverse modeling is a useful tool in deriving the spatial pattern of Q₁₀ at large scales, with which being incorporated into biogeochemical models, uncertainty in the projection of future carbon dynamics could be potentially reduced.