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Global soil carbon projections are improved by modelling microbial processes

Abstract

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.

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Figure 1: Diagram of the CLM microbial model.
Figure 2: Global distribution of soil C pools (0–100 cm) from observations19 and models.
Figure 3: Divergent model responses of global soil C pools in global change simulations.

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Acknowledgements

The National Center for Atmospheric Research is sponsored by the National Science Foundation. This work was supported by National Science Foundation grant AGS-1020767, the NSF Advancing Theory in Biology Program and the Office of Science (BER), US Department of Energy.

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W.R.W. and S.D.A. conceived the project and built the model. W.R.W. and G.B.B. assembled input and model evaluation data sets. W.R.W. conducted model runs. All authors contributed to writing the paper.

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Correspondence to William R. Wieder.

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The authors declare no competing financial interests.

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Wieder, W., Bonan, G. & Allison, S. Global soil carbon projections are improved by modelling microbial processes. Nature Clim Change 3, 909–912 (2013). https://doi.org/10.1038/nclimate1951

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