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Gene-informed decomposition model predicts lower soil carbon loss due to persistent microbial adaptation to warming

Author

Listed:
  • Xue Guo

    (Tsinghua University
    University of Oklahoma
    University of Oklahoma)

  • Qun Gao

    (Tsinghua University
    University of Oklahoma
    University of Oklahoma)

  • Mengting Yuan

    (University of California)

  • Gangsheng Wang

    (University of Oklahoma
    University of Oklahoma)

  • Xishu Zhou

    (University of Oklahoma
    University of Oklahoma
    Central South University)

  • Jiajie Feng

    (University of Oklahoma
    University of Oklahoma)

  • Zhou Shi

    (University of Oklahoma
    University of Oklahoma)

  • Lauren Hale

    (University of Oklahoma
    University of Oklahoma)

  • Linwei Wu

    (University of Oklahoma
    University of Oklahoma)

  • Aifen Zhou

    (University of Oklahoma
    University of Oklahoma)

  • Renmao Tian

    (University of Oklahoma
    University of Oklahoma)

  • Feifei Liu

    (University of Oklahoma
    University of Oklahoma)

  • Bo Wu

    (University of Oklahoma
    University of Oklahoma
    Sun Yat-sen University)

  • Lijun Chen

    (University of Oklahoma)

  • Chang Gyo Jung

    (Northern Arizona University)

  • Shuli Niu

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Dejun Li

    (Key Laboratory of Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences
    Huanjiang Observation and Research Station for Karst Ecosystem, Chinese Academy of Sciences)

  • Xia Xu

    (Nanjing Forestry University)

  • Lifen Jiang

    (Northern Arizona University)

  • Arthur Escalas

    (University of Oklahoma
    University of Oklahoma)

  • Liyou Wu

    (University of Oklahoma
    University of Oklahoma)

  • Zhili He

    (University of Oklahoma
    University of Oklahoma
    Sun Yat-sen University
    Southern Laboratory of Ocean Science and Engineering (Zhuhai))

  • Joy D. Van Nostrand

    (University of Oklahoma
    University of Oklahoma)

  • Daliang Ning

    (University of Oklahoma
    University of Oklahoma)

  • Xueduan Liu

    (Central South University)

  • Yunfeng Yang

    (Tsinghua University)

  • Edward. A. G. Schuur

    (Northern Arizona University)

  • Konstantinos T. Konstantinidis

    (School of Civil and Environmental Engineering and School of Biological Science, Georgia Institute of Technology)

  • James R. Cole

    (Michigan State University)

  • C. Ryan Penton

    (Arizona State University
    Arizona State University)

  • Yiqi Luo

    (Northern Arizona University)

  • James M. Tiedje

    (Michigan State University)

  • Jizhong Zhou

    (Tsinghua University
    University of Oklahoma
    University of Oklahoma
    University of Oklahoma)

Abstract

Soil microbial respiration is an important source of uncertainty in projecting future climate and carbon (C) cycle feedbacks. However, its feedbacks to climate warming and underlying microbial mechanisms are still poorly understood. Here we show that the temperature sensitivity of soil microbial respiration (Q10) in a temperate grassland ecosystem persistently decreases by 12.0 ± 3.7% across 7 years of warming. Also, the shifts of microbial communities play critical roles in regulating thermal adaptation of soil respiration. Incorporating microbial functional gene abundance data into a microbially-enabled ecosystem model significantly improves the modeling performance of soil microbial respiration by 5–19%, and reduces model parametric uncertainty by 55–71%. In addition, modeling analyses show that the microbial thermal adaptation can lead to considerably less heterotrophic respiration (11.6 ± 7.5%), and hence less soil C loss. If such microbially mediated dampening effects occur generally across different spatial and temporal scales, the potential positive feedback of soil microbial respiration in response to climate warming may be less than previously predicted.

Suggested Citation

  • Xue Guo & Qun Gao & Mengting Yuan & Gangsheng Wang & Xishu Zhou & Jiajie Feng & Zhou Shi & Lauren Hale & Linwei Wu & Aifen Zhou & Renmao Tian & Feifei Liu & Bo Wu & Lijun Chen & Chang Gyo Jung & Shuli, 2020. "Gene-informed decomposition model predicts lower soil carbon loss due to persistent microbial adaptation to warming," Nature Communications, Nature, vol. 11(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-18706-z
    DOI: 10.1038/s41467-020-18706-z
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    Cited by:

    1. Xuanyu Tao & Zhifeng Yang & Jiajie Feng & Siyang Jian & Yunfeng Yang & Colin T. Bates & Gangsheng Wang & Xue Guo & Daliang Ning & Megan L. Kempher & Xiao Jun A. Liu & Yang Ouyang & Shun Han & Linwei W, 2024. "Experimental warming accelerates positive soil priming in a temperate grassland ecosystem," Nature Communications, Nature, vol. 15(1), pages 1-18, December.

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