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...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 proc-ess-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.展开更多
基金Supported by the National Natural Science Foundation of China(Grant Nos.40671173,40425008,30590384 and 40401028)the Free Research Foundation of State Key Laboratory of Earth Surface Processes and Resource Ecology(Grant No.070105)
文摘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 proc-ess-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.
