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Reply to: Model uncertainty obscures major driver of soil carbon

Nature volume 627, pages E4–E6 (2024)Cite this article

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The Original Article was published on 06 March 2024

replying to: X. He et al. Nature https://doi.org/10.1038/s41586-023-06999-1 (2024).

In the accompanying Comment1, He et al. argue that Tao et al.2 overestimated the role of microbial carbon use efficiency (CUE) in global soil organic carbon (SOC) storage because carbon inputs were neglected in our data analysis. They also suggest that our big data analysis could be biased and model-dependent. Their argument is based on a different choice of independent variables in the data analysis and sensitivity analysis of two process-based models without being informed by observations other than that used in our study. We agree that both carbon inputs and outputs (as mediated by microbial processes) matter, and their influences on SOC could vary in models with different structures. By fusing big SOC data with models, the data-assimilation approach used by Tao et al.2 reconciles inter-model disagreements and reveals converging results in assessing the relative contributions of different processes to global SOC storage. Thus, the claims of He et al. need to be taken as an alternative, unproven hypothesis until empirical data support their specific parameterization. Here we show that another assessment of global data products does not support He et al.’s arguments and further study is essential.

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Fig. 1: Varying sensitivity of SOC storage to doubled NPP under different combinations of parameter values with the microbial model used by Tao et al.2.

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Author information

Authors and Affiliations

  1. Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA

    Feng Tao & Benjamin Z. Houlton

  2. Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Institute for Global Change Studies, Tsinghua University, Beijing, China

    Feng Tao, Cuijuan Liao, Yi-Shuang Liang & Xiaomeng Huang

  3. Department of Global Development, Cornell University, Ithaca, NY, USA

    Benjamin Z. Houlton

  4. Center for Soil Biogeochemistry and Microbial Ecology, Department of Natural Resources and the Environment, University of New Hampshire, Durham, NH, USA

    Serita D. Frey

  5. Soil and Crop Sciences Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, USA

    Johannes Lehmann, Lifen Jiang, Kostiantyn Viatkin & Yiqi Luo

  6. Department of Physical Geography and Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden

    Stefano Manzoni & Gustaf Hugelius

  7. Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

    Yuanyuan Huang

  8. Computational Biology & Biophysics, Sandia National Laboratories, Livermore, CA, USA

    Umakant Mishra

  9. Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, USA

    Umakant Mishra

  10. Center for Ecosystem Science and Society, Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA

    Bruce A. Hungate

  11. School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA

    Bruce A. Hungate & Toby D. Hocking

  12. Department of Geography, University of Zurich, Zurich, Switzerland

    Michael W. I. Schmidt

  13. Max Planck Institute for Biogeochemistry, Jena, Germany

    Markus Reichstein, Nuno Carvalhais & Bernhard Ahrens

  14. Departamento de Ciências e Engenharia do Ambiente, DCEA, Faculdade de Ciências e Tecnologia, FCT, Universidade Nova de Lisboa, Caparica, Portugal

    Nuno Carvalhais

  15. Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France

    Philippe Ciais

  16. CSIRO Environment, Clayton South, Victoria, Australia

    Ying-Ping Wang

  17. School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, China

    Xingjie Lu

  18. Institute for Environmental Genomics, University of Oklahoma, Norman, OK, USA

    Zheng Shi

  19. Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, USA

    Zheng Shi

  20. Food and Agriculture Organization of the United Nations, Rome, Italy

    Ronald Vargas, Yusuf Yigini, Christian Omuto, Guillermo Peralta, Rosa Cuevas-Corona, Luciano E. Di Paolo, Isabel Luotto & Vinisa S. Saynes

  21. School of Biological Sciences, University of Aberdeen, Aberdeen, UK

    Ashish A. Malik

Authors
  1. Feng Tao
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  32. Xiaomeng Huang
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  33. Yiqi Luo
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Contributions

F.T. and Y.L. drafted the reply. All authors contributed to the text and approved the final version.

Corresponding authors

Correspondence to Xiaomeng Huang or Yiqi Luo.

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The authors declare no competing interests.

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Tao, F., Houlton, B.Z., Frey, S.D. et al. Reply to: Model uncertainty obscures major driver of soil carbon. Nature 627, E4–E6 (2024). https://doi.org/10.1038/s41586-023-07000-9

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