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

Autor: Guo X; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China.; Institute for Environmental Genomics, University of Oklahoma, Norman, Oklahoma, USA.; Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA., Gao Q; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China.; Institute for Environmental Genomics, University of Oklahoma, Norman, Oklahoma, USA.; Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA., Yuan M; Department of Environmental Science, Policy, and Management, University of California, Berkeley, California, USA., Wang G; Institute for Environmental Genomics, University of Oklahoma, Norman, Oklahoma, USA.; Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA., Zhou X; Institute for Environmental Genomics, University of Oklahoma, Norman, Oklahoma, USA.; Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA.; School of Minerals Processing and Bioengineering, Central South University, Changsha, Hunan, China., Feng J; Institute for Environmental Genomics, University of Oklahoma, Norman, Oklahoma, USA.; Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA., Shi Z; Institute for Environmental Genomics, University of Oklahoma, Norman, Oklahoma, USA.; Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA., Hale L; Institute for Environmental Genomics, University of Oklahoma, Norman, Oklahoma, USA.; Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA., Wu L; Institute for Environmental Genomics, University of Oklahoma, Norman, Oklahoma, USA.; Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA., Zhou A; Institute for Environmental Genomics, University of Oklahoma, Norman, Oklahoma, USA.; Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA., Tian R; Institute for Environmental Genomics, University of Oklahoma, Norman, Oklahoma, USA.; Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA., Liu F; Institute for Environmental Genomics, University of Oklahoma, Norman, Oklahoma, USA.; Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA., Wu B; Institute for Environmental Genomics, University of Oklahoma, Norman, Oklahoma, USA.; Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA.; Environmental Microbiomics Research Center and School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou, China., Chen L; Institute for Environmental Genomics, University of Oklahoma, Norman, Oklahoma, USA., Jung CG; Center for Ecosystem Science and Society, Department of Biological Sciences, Northern Arizona University, Flagstaff, Arizona, USA., Niu S; Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.; University of Chinese Academy of Sciences, Beijing, China., Li D; Key Laboratory of Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, Hunan, China.; Huanjiang Observation and Research Station for Karst Ecosystem, Chinese Academy of Sciences, Huanjiang, Guangxi, China., Xu X; College of Biology and the Environment, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, China., Jiang L; Center for Ecosystem Science and Society, Department of Biological Sciences, Northern Arizona University, Flagstaff, Arizona, USA., Escalas A; Institute for Environmental Genomics, University of Oklahoma, Norman, Oklahoma, USA.; Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA., Wu L; Institute for Environmental Genomics, University of Oklahoma, Norman, Oklahoma, USA.; Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA., He Z; Institute for Environmental Genomics, University of Oklahoma, Norman, Oklahoma, USA.; Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA.; Environmental Microbiomics Research Center and School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou, China.; Southern Laboratory of Ocean Science and Engineering (Zhuhai), Zhuhai, China., Van Nostrand JD; Institute for Environmental Genomics, University of Oklahoma, Norman, Oklahoma, USA.; Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA., Ning D; Institute for Environmental Genomics, University of Oklahoma, Norman, Oklahoma, USA.; Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA., Liu X; School of Minerals Processing and Bioengineering, Central South University, Changsha, Hunan, China., Yang Y; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China., Schuur EAG; Center for Ecosystem Science and Society, Department of Biological Sciences, Northern Arizona University, Flagstaff, Arizona, USA., Konstantinidis KT; School of Civil and Environmental Engineering and School of Biological Science, Georgia Institute of Technology, Atlanta, Georgia, USA., Cole JR; Center for Microbial Ecology, Michigan State University, East Lansing, Michigan, USA., Penton CR; College of Letters and Sciences, Faculty of Science and Mathematics, Arizona State University, Mesa, AZ, USA.; Center for Fundamental and Applied Microbiomics, Biodesign Institute, Arizona State University, Tempe, AZ, USA., Luo Y; Center for Ecosystem Science and Society, Department of Biological Sciences, Northern Arizona University, Flagstaff, Arizona, USA., Tiedje JM; Center for Microbial Ecology, Michigan State University, East Lansing, Michigan, USA., Zhou J; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China. jzhou@ou.edu.; Institute for Environmental Genomics, University of Oklahoma, Norman, Oklahoma, USA. jzhou@ou.edu.; Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA. jzhou@ou.edu.; School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, Oklahoma, USA. jzhou@ou.edu.; Earth and Environmental Sciences, Lawrence Berkeley National Laboratory, Berkeley, California, USA. jzhou@ou.edu.
Jazyk: angličtina
Zdroj: Nature communications [Nat Commun] 2020 Sep 29; Vol. 11 (1), pp. 4897. Date of Electronic Publication: 2020 Sep 29.
DOI: 10.1038/s41467-020-18706-z
Abstrakt: 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 (Q 10 ) 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.
Databáze: MEDLINE