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Modeling interannual variability of global soil respiration from climate and soil properties

发布时间:2010-10-08 点击次数:

期刊:Agricultural and Forest Meteorology 150 (2010) 590–605
作者:Shutao Chen , Yao Huang , Jianwen Zou *, Qirong Shen , Zhenghua Hua,
Yanmei Qin , Haishan Chen , Genxing Pan
摘要:To develop a model describing the dependence of annual soil respiration on climate and soil properties, we compiled 657 published annual soil respiration (Rs) measurements that were assembled from 147 sites globally, representing croplands, grasslands, forests and tundra ecosystems. Each of these annual soil respiration data was then aggregated with the appropriate mean air temperature (T) and annual
precipitation (P) data derived from geographically referenced datasets and with soil properties gathered from the original literature. Partial correlation analyses showed that global annual Rs significantly related to annual mean temperature, annual precipitation, and topsoil (0–20 cm) organic carbon (SOC) storage, while topsoil total nitrogen (SN) and pH did not show a direct and clear relationship with Rs across ecosystems. While we employed the T&P-model that used temperature and annual precipitation to globally predict annual soil respiration, it was able to explain 41%, 57%, and 31% of the variability of soil respiration for croplands, grasslands and forests, respectively. However, the residuals were significantly related to SOC for croplands and grasslands. Thus, we developed a T&P&C-model that includes SOC as an additional predictor of annual Rs. This extended but still simple model performed better than the T&Pmodel and explained 69%, 89%, and 47% of the interannual and intersite variability of Rs with a mean absolute error of 0.11, 0.18 and 0.28 kg C m_2 yr_1 for croplands, grasslands and forests, respectively. Overall, the modeling efficiency of the T&P&C-model was nearly 60% across ecosystems. Globally, the mean turnover time of topsoil carbon (SOC/Rs) was highly comparable among croplands, grasslands and forests, equivalent to 6.1–6.3 years. Therefore, better estimates of global annual soil respiration would be obtained with the new model driven by climate and soil properties together. We expect significant improvements of global annual soil respiration predictions given that measurements of soil respiration coupling with soil properties and site productivities are widely taken across ecosystems over the world.



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