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标题: Global soil carbon projections are improved by modelling microbial processes [打印本页]

作者: 雩风三日 时间: 2021-2-5 16:33
标题: Global soil carbon projections are improved by modelling microbial processes
Global soil carbon projections are improved by modelling microbial processes
通过模拟微生物过程可以改善全球土壤碳预测

Society relies on Earth system models (ESMs) to project future climate and carbon (C) cycle feedbacks. However, the soil C response to climate change is highly uncertain in these models1,2 and they omit key biogeochemical mechanisms3,4,5. Specifically, the traditional approach in ESMs lacks direct microbial control over soil C dynamics6,7,8. Thus, we tested a new model that explicitly represents microbial mechanisms of soil C cycling on the global scale. Compared with traditional models, the microbial model simulates soil C pools that more closely match contemporary observations. It also projects a much wider range of soil C responses to climate change over the twenty-first century. Global soils accumulate C if microbial growth efficiency declines with warming in the microbial model. If growth efficiency adapts to warming, the microbial model projects large soil C losses. By comparison, traditional models project modest soil C losses with global warming. Microbes also change the soil response to increased C inputs, as might occur with CO2 or nutrient fertilization. In the microbial model, microbes consume these additional inputs; whereas in traditional models, additional inputs lead to C storage. Our results indicate that ESMs should simulate microbial physiology to more accurately project climate change feedbacks.

社会依赖于地球系统模型(ESMs)来预测未来的气候和碳循环反馈。然而，在这些模型中，土壤碳对气候变化的响应具有高度不确定性，并且忽略了关键的生物地球化学机制。具体来说，ESMs中的传统方法缺乏对土壤C动态的微生物直接控制。因此，我们测试了一种新的模型，该模型明确地代表了全球范围内土壤碳循环的微生物机制。与传统模型相比，微生物模型模拟的土壤碳库更接近于当代观测结果。它还预测了21世纪土壤C对气候变化的更广泛的响应。在微生物模型中，如果微生物生长效率随着变暖而下降，全球土壤积累C。如果生长效率适应气候变暖，微生物模型将会造成大量土壤碳流失。相比之下，传统模型预测的全球变暖会导致适度的土壤C流失。微生物也会改变土壤对增加的碳输入的响应，就像CO2或养分施肥可能发生的那样。在微生物模型中，微生物消耗这些额外的输入;而在传统模型中，额外的输入导致C存储。我们的结果表明，ESMs应该模拟微生物生理，以更准确地预测气候变化反馈。

Global soil carbon projections are improved by modelling microbial processes.pdf

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