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

Science china(Life Sciences) 2009年第10期52卷 982-989页

作者： zhou tao1,2. shi peijun1,2. {2. {2. luo yiqi4 1 state key Laboratory of earth surface processes and resource {12., beijing Normal University, beijing 100875, china 2.Academy of Disaster Reduction and Emergency Management, Ministry of Civil Affairs & Ministry of Education, beijing 100875, china 3.Department of Biological Sciences, Tennessee state University, Nashville, TN 3.2.9, USA 4 Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73.19, USA 1. state key Laboratory of {2. {3. processes and resource ecology Beijing Normal University Beijing 100875 China 2. Academy of Disaster Reduction and Emergency Management Ministry of Civil Affairs & Ministry of Education Beijing 100875 China 3. Department of Biological Sciences Tennessee State University Nashville TN 37209 USA 4. Department of Botany and Microbiology University of Oklahoma Norman OK 73019 USA

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 2.3., 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.

关键词： temperature sensitivity Q10 soil respiration global warming inverse analysis

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