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Modeling soil respiration and variations in source components using a multi-factor global climate change experiment

机译：使用多因素全球气候变化实验模拟土壤呼吸和源成分的变化

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Soil respiration is an important component of the global carbon cycle and is highly responsive to changes in soil temperature and moisture. Accurate prediction of soil respiration and its changes under future climatic conditions requires a clear understanding of the processes involved. Most current empirical soil respiration models incorporate just few of the underlying mechanisms that may influence its response. In this study, a new partially process-based component model that separately treated several source components of soil respiration was tested with data from a climate change experiment that manipulated atmospheric [CO2], air temperature and soil moisture. Results from this model were compared to results from other widely used models with the parameters fitted using experimental data. Using the component model, we were able to estimate the relative proportions of heterotrophic and autotrophic respiration in total soil respiration for each of the different treatments. The value of the Q 10 parameters for temperature response component of all of the models showed sensitivity to soil moisture. Estimated Q 10 parameters were higher for wet treatments and lower for dry treatments compared to the values estimated using either the data from all treatments or from only the control treatments. Our results suggest that process-based models provide a better understanding of soil respiration dynamics under changing environmental conditions, but the extent and contribution of different source components need to be included in mechanistic and process-based soil respiration models at corresponding scales.
机译：土壤呼吸是全球碳循环的重要组成部分，对土壤温度和湿度的变化高度敏感。要准确预测土壤呼吸作用及其在未来气候条件下的变化，需要对所涉及的过程有清楚的了解。当前大多数经验性土壤呼吸模型都只包含一些可能影响其响应的潜在机制。在这项研究中，使用来自控制大气[CO 2 ]，空气温度和土壤湿度的气候变化实验的数据，测试了一种新的基于部分过程的成分模型，该模型分别处理了土壤呼吸的几种源成分。 。将来自该模型的结果与使用实验数据拟合参数的其他广泛使用的模型的结果进行比较。使用分量模型，我们能够估算出每种不同处理方法在总土壤呼吸中异养和自养呼吸的相对比例。所有模型的温度响应分量的Q 10 参数值均显示对土壤水分敏感。与使用所有处理的数据或仅使用对照处理的数据估算的值相比，湿处理的估算Q 10 参数较高，而干处理则较低。我们的结果表明，基于过程的模型可以更好地理解不断变化的环境条件下的土壤呼吸动力学，但是在相应规模的机械和基于过程的土壤呼吸模型中，必须包括不同来源组分的范围和贡献。

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