Microbial carbon use efficiency promotes global soil carbon storage

Feng Tao, Yuanyuan Huang, Bruce A. Hungate, Stefano Manzoni, Serita D. Frey, Michael W.I. Schmidt, Markus Reichstein, Nuno Carvalhais, Philippe Ciais, Lifen Jiang, Johannes Lehmann, Ying Ping Wang, Benjamin Z. Houlton, Bernhard Ahrens, Umakant Mishra, Gustaf Hugelius, Toby D. Hocking, Xingjie Lu, Zheng Shi, Kostiantyn ViatkinRonald Vargas, Yusuf Yigini, Christian Omuto, Ashish A. Malik, Guillermo Peralta, Rosa Cuevas-Corona, Luciano E. Di Paolo, Isabel Luotto, Cuijuan Liao, Yi Shuang Liang, Vinisa S. Saynes, Xiaomeng Huang*, Yiqi Luo*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Soils store more carbon than other terrestrial ecosystems1,2. How soil organic carbon (SOC) forms and persists remains uncertain1,3, which makes it challenging to understand how it will respond to climatic change3,4. It has been suggested that soil microorganisms play an important role in SOC formation, preservation and loss5–7. Although microorganisms affect the accumulation and loss of soil organic matter through many pathways4,6,8–11, microbial carbon use efficiency (CUE) is an integrative metric that can capture the balance of these processes12,13. Although CUE has the potential to act as a predictor of variation in SOC storage, the role of CUE in SOC persistence remains unresolved7,14,15. Here we examine the relationship between CUE and the preservation of SOC, and interactions with climate, vegetation and edaphic properties, using a combination of global-scale datasets, a microbial-process explicit model, data assimilation, deep learning and meta-analysis. We find that CUE is at least four times as important as other evaluated factors, such as carbon input, decomposition or vertical transport, in determining SOC storage and its spatial variation across the globe. In addition, CUE shows a positive correlation with SOC content. Our findings point to microbial CUE as a major determinant of global SOC storage. Understanding the microbial processes underlying CUE and their environmental dependence may help the prediction of SOC feedback to a changing climate.

Original languageEnglish
Pages (from-to)981-985
JournalNature
Volume618
Early online date24 May 2023
DOIs
Publication statusPublished - 29 Jun 2023

Bibliographical note

Funding Information:
We thank H. Yang, M. Schrumpf, T. Wutzler, R. Zheng and H. Ma for their comments and suggestions on this study. This work was supported by the National Natural Science Foundation of China (42125503) and the National Key Research and Development Program of China (2020YFA0608000, 2020YFA0607900 and 2021YFC3101600). F.T. was financially supported by China Scholarship Council during his visit at Food and Agricultural Organization of the United Nations (201906210489) and the Max-Planck Institute for Biogeochemistry (202006210289). The contributions of Y.L. were supported through US National Science Foundation DEB 1655499 and 2242034, subcontract CW39470 from Oak Ridge National Laboratory (ORNL) to Cornell University, DOE De-SC0023514, and the USDA National Institute of Food and Agriculture. S.M. has received funding from the ERC under the European Union’s H2020 Research and Innovation Programme (101001608). The contributions of U.M. were supported through a US Department of Energy grant to the Sandia National Laboratories, which is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International, Inc., for the US Department of Energy’s National Nuclear Security Administration under contract DE-NA-0003525. We thank the WoSIS database ( https://www.isric.org/explore/wosis ) for providing the publicly available global-scale SOC database used in this study.

Publisher Copyright:
© 2023, The Author(s).

Data Availability Statement

All the data that support the findings of this study are available at https://doi.org/10.5281/zenodo.7676632. The raw data for the SOC profiles from the WoSIS database can be accessed at https://www.isric.org/explore/wosis.

Code availability
All the code used in the analyses presented in this paper can be accessed at https://github.com/phxtao/PRODA_MIC.

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