Using microbial information to inform global climate change models
- Date:
- September 29, 2020
- Source:
- University of Oklahoma
- Summary:
- Researchers have tackled a problem that has challenged scientists for more than a decade. The findings from which may have important implications for understanding and predicting the ecological consequences of climate warming.
- Share:
Jizhong Zhou, the Director of the Institute for Environmental Genomics, a George Lynn Cross Research Professor in the OU College of Arts and Sciences and the lead for the study, tackles a problem that has challenged scientists for more than a decade.
"Soil microbial respiration, which is the carbon dioxide flux from the soil to the atmosphere, is an important source of uncertainty in projecting future climate and carbon cycle feedbacks," said Zhou. "Our study illustrates that warming-induced respiratory adaptation is subject to the adaptive changes in microbial community functional structure, so that the positive feedback of soil microbial respiration in response to climate warming may be less than previously expected."
He adds that this study is also unique in its approach to integrate omics data, the term for the comprehensive approach for analysis of complete genetic profiles of organisms and communities, into ecosystem models for better predictions.
"Integrating microbial omics information to inform global climate change models is extremely challenging," Zhou said. "The findings from this study have important implications for understanding and predicting the ecological consequences of climate warming."
Story Source:
Materials provided by University of Oklahoma. Note: Content may be edited for style and length.
Journal Reference:
- 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 Niu, Dejun Li, Xia Xu, Lifen Jiang, Arthur Escalas, Liyou Wu, Zhili He, Joy D. Van Nostrand, Daliang Ning, Xueduan Liu, Yunfeng Yang, Edward. A. G. Schuur, Konstantinos T. Konstantinidis, James R. Cole, C. Ryan Penton, Yiqi Luo, James M. Tiedje, Jizhong Zhou. Gene-informed decomposition model predicts lower soil carbon loss due to persistent microbial adaptation to warming. Nature Communications, 2020; 11 (1) DOI: 10.1038/s41467-020-18706-z
Cite This Page: