Modeling interannual variability of global soil respiration from climate and soil properties
Modeling interannual variability of global soil respiration from climate and soil properties
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DOI：
10.1016/j.agrformet.2010.02.004
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发表时间：
2010-04-15
影响因子：
6.2
通讯作者：
Pan, Genxing
中科院分区：
文献类型：
--
作者：
Chen, Shutao;Huang, Yao;Pan, Genxing
为了建立一个描述土壤年呼吸作用对气候和土壤特性的依赖关系的模型，我们收集了657项已发表的土壤年呼吸作用（R - s）测量数据，这些数据来自全球147个地点，涵盖农田、草地、森林和苔原生态系统。然后，将这些土壤年呼吸作用的每一项数据与从地理参考数据集中获取的相应平均气温（T）和年降水量（P）数据以及从原始文献中收集的土壤特性数据进行汇总。偏相关分析表明，全球土壤年呼吸作用（R - s）与年平均气温、年降水量以及表层土壤（0 - 20厘米）有机碳（SOC）储量显著相关，而表层土壤总氮（SN）和pH值在不同生态系统中与R - s没有直接和明确的关系。虽然我们采用了利用温度和年降水量来全球预测土壤年呼吸作用的T&P模型，但它分别只能解释农田、草地和森林土壤呼吸作用变异性的41%、57%和31%。然而，对于农田和草地，残差与SOC显著相关。因此，我们开发了一个T&P&C模型，该模型将SOC作为土壤年呼吸作用（R - s）的一个额外预测因子。这个扩展但仍然简单的模型比T&P模型表现更好，它分别解释了农田、草地和森林土壤年呼吸作用（R - s）的年际和站点间变异性的69%、89%和47%，平均绝对误差分别为0.11、0.18和0.28千克碳/平方米·年。总体而言，T&P&C模型在不同生态系统中的建模效率接近60%。在全球范围内，农田、草地和森林的表层土壤碳平均周转时间（SOC/R - s）具有高度可比性，相当于6.1 - 6.3年。因此，通过由气候和土壤特性共同驱动的新模型，可以更好地估算全球土壤年呼吸作用。我们预计，如果在全球范围内的各个生态系统中广泛进行土壤呼吸作用与土壤特性和场地生产力相结合的测量，全球土壤年呼吸作用的预测将会有显著改进。（C）2010爱思唯尔公司。保留所有权利。
To develop a model describing the dependence of annual soil respiration on climate and soil properties, we compiled 657 published annual soil respiration (R-s) 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 R-s 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 R-s 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 R-s. This extended but still simple model performed better than the T&P-model and explained 69%, 89%, and 47% of the interannual and intersite variability of R-s with a mean absolute error of 0.11, 0.18 and 0.28 kg C m(-2) y(-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/R-s) 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. (C) 2010 Elsevier B.V. All rights reserved.