The sensitivity of soil respiration to soil temperature, moisture, and carbon supply at the global scale
The sensitivity of soil respiration to soil temperature, moisture, and carbon supply at the global scale
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DOI：
10.1111/gcb.13489
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发表时间：
2017-05-01
影响因子：
11.6
通讯作者：
Watts, Jennifer
中科院分区：
文献类型：
--
作者：
Hursh, Andrew;Ballantyne, Ashley;Watts, Jennifer
土壤呼吸(Rs)是生物圈中固定碳返回大气的主要途径，然而我们在全球范围内利用环境驱动因素预测呼吸速率的能力是有限的。虽然已知温度、水分、碳供应和其他地点特征在某些生物群落内的小区尺度上调节土壤呼吸速率，但评估这些因素在不同生物群落和全球尺度上的相对重要性的定量框架需要测试现场估计和全球气候数据之间的关系。这项研究通过将全球土壤水分、土壤温度、初级生产力和土壤碳估计的数据集与全球土壤呼吸数据库(SRDB)的年度Rs观测值联系起来，评估了在全球尺度上驱动Rs的因素。我们发现，采用抛物线土壤湿度函数对模型进行校正可以提高对年平均降水量具有渐近函数的类似模型的预报能力。土壤温度与以前报道的用于预测Rs的气温观测值相当，是全球模式中Rs的主要驱动因素；然而，在某些生物群落中，土壤湿度和土壤碳是Rs的主要预测因子。我们确定了典型的温度驱动响应进一步受到土壤水分、降水和碳供应的影响的地区，以及由于野外数据有限而难以确定高Rs值的环境控制的地区。由于土壤湿度综合了温度和降水动态，它可以更直接地限制Rs的异养成分，但全球尺度模型往往通过聚集增加生物群落内和跨生物群落水分变异性的因素来平滑其空间异质性。我们比较了统计模型和机械模型，这些模型提供了对全球R的独立估计，范围从83到108pgyr(-1)，但也强调了需要更多观测或难以约束环境控制的不确定区域。
Soil respiration (Rs) is a major pathway by which fixed carbon in the biosphere is returned to the atmosphere, yet there are limits to our ability to predict respiration rates using environmental drivers at the global scale. While temperature, moisture, carbon supply, and other site characteristics are known to regulate soil respiration rates at plot scales within certain biomes, quantitative frameworks for evaluating the relative importance of these factors across different biomes and at the global scale require tests of the relationships between field estimates and global climatic data. This study evaluates the factors driving Rs at the global scale by linking global datasets of soil moisture, soil temperature, primary productivity, and soil carbon estimates with observations of annual Rs from the Global Soil Respiration Database (SRDB). We find that calibrating models with parabolic soil moisture functions can improve predictive power over similar models with asymptotic functions of mean annual precipitation. Soil temperature is comparable with previously reported air temperature observations used in predicting Rs and is the dominant driver of Rs in global models; however, within certain biomes soil moisture and soil carbon emerge as dominant predictors of Rs. We identify regions where typical temperature-driven responses are further mediated by soil moisture, precipitation, and carbon supply and regions in which environmental controls on high Rs values are difficult to ascertain due to limited field data. Because soil moisture integrates temperature and precipitation dynamics, it can more directly constrain the heterotrophic component of Rs, but global-scale models tend to smooth its spatial heterogeneity by aggregating factors that increase moisture variability within and across biomes. We compare statistical and mechanistic models that provide independent estimates of global Rs ranging from 83 to 108 Pg yr(-1), but also highlight regions of uncertainty where more observations are required or environmental controls are hard to constrain.