Gene-informed decomposition model predicts lower soil carbon loss due to persistent microbial adaptation to warming
文献类型:期刊论文
作者 | Guo, Xue3,12; Gao, Qun3,12; Yuan, Mengting4; Wang, Gangsheng3; Zhou, Xishu3,5; Feng, Jiajie3; Shi, Zhou3; Hale, Lauren3; Wu, Linwei3; Zhou, Aifen3 |
刊名 | NATURE COMMUNICATIONS
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出版日期 | 2020-09-29 |
卷号 | 11期号:1页码:12 |
ISSN号 | 2041-1723 |
DOI | 10.1038/s41467-020-18706-z |
英文摘要 | 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 12.03.7% 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. |
WOS关键词 | TEMPERATURE SENSITIVITY ; ORGANIC-MATTER ; CYCLE FEEDBACK ; RESPIRATION ; PRECIPITATION ; AVAILABILITY ; PRODUCTIVITY ; ACCLIMATION ; COMPONENTS ; RESPONSES |
资助项目 | US Department of Energy, Office of Science, Genomic Science Program[DE-SC0004601] ; US Department of Energy, Office of Science, Genomic Science Program[DE-SC0010715] ; Office of the Vice President for Research at the University of Oklahoma ; China Scholarship Council (CSC) |
WOS研究方向 | Science & Technology - Other Topics |
语种 | 英语 |
WOS记录号 | WOS:000577262800008 |
出版者 | NATURE RESEARCH |
资助机构 | US Department of Energy, Office of Science, Genomic Science Program ; Office of the Vice President for Research at the University of Oklahoma ; China Scholarship Council (CSC) |
源URL | [http://ir.igsnrr.ac.cn/handle/311030/157123] ![]() |
专题 | 生态系统网络观测与模拟院重点实验室_外文论文 |
作者单位 | 1.Chinese Acad Sci, Huanjiang Observat & Res Stn Karst Ecosyst, Huanjiang, Guangxi, Peoples R China 2.Univ Oklahoma, Inst Environm Genom, Norman, OK 73019 USA 3.Univ Oklahoma, Dept Microbiol & Plant Biol, Norman, OK 73019 USA 4.Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA 94720 USA 5.Cent South Univ, Sch Minerals Proc & Bioeng, Changsha, Hunan, Peoples R China 6.Sun Yat Sen Univ, Environm Microbi Res Ctr, Guangzhou, Peoples R China 7.Sun Yat Sen Univ, Sch Environm Sci & Engn, Guangzhou, Peoples R China 8.No Arizona Univ, Dept Biol Sci, Ctr Ecosyst Sci & Soc, Flagstaff, AZ 86011 USA 9.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China 10.Univ Chinese Acad Sci, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Guo, Xue,Gao, Qun,Yuan, Mengting,et al. Gene-informed decomposition model predicts lower soil carbon loss due to persistent microbial adaptation to warming[J]. NATURE COMMUNICATIONS,2020,11(1):12. |
APA | Guo, Xue.,Gao, Qun.,Yuan, Mengting.,Wang, Gangsheng.,Zhou, Xishu.,...&Zhou, Jizhong.(2020).Gene-informed decomposition model predicts lower soil carbon loss due to persistent microbial adaptation to warming.NATURE COMMUNICATIONS,11(1),12. |
MLA | Guo, Xue,et al."Gene-informed decomposition model predicts lower soil carbon loss due to persistent microbial adaptation to warming".NATURE COMMUNICATIONS 11.1(2020):12. |
入库方式: OAI收割
来源:地理科学与资源研究所
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