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Gene-informed decomposition model predicts lower soil carbon loss due to persistent microbial adaptation to warming
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 res...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7524716/ https://www.ncbi.nlm.nih.gov/pubmed/32994415 http://dx.doi.org/10.1038/s41467-020-18706-z |
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author | Guo, Xue Gao, Qun Yuan, Mengting Wang, Gangsheng Zhou, Xishu Feng, Jiajie Shi, Zhou Hale, Lauren Wu, Linwei Zhou, Aifen Tian, Renmao Liu, Feifei Wu, Bo Chen, Lijun Jung, Chang Gyo Niu, Shuli Li, Dejun Xu, Xia Jiang, Lifen Escalas, Arthur Wu, Liyou He, Zhili Van Nostrand, Joy D. Ning, Daliang Liu, Xueduan Yang, Yunfeng Schuur, Edward. A. G. Konstantinidis, Konstantinos T. Cole, James R. Penton, C. Ryan Luo, Yiqi Tiedje, James M. Zhou, Jizhong |
author_facet | Guo, Xue Gao, Qun Yuan, Mengting Wang, Gangsheng Zhou, Xishu Feng, Jiajie Shi, Zhou Hale, Lauren Wu, Linwei Zhou, Aifen Tian, Renmao Liu, Feifei Wu, Bo Chen, Lijun Jung, Chang Gyo Niu, Shuli Li, Dejun Xu, Xia Jiang, Lifen Escalas, Arthur Wu, Liyou He, Zhili Van Nostrand, Joy D. Ning, Daliang Liu, Xueduan Yang, Yunfeng Schuur, Edward. A. G. Konstantinidis, Konstantinos T. Cole, James R. Penton, C. Ryan Luo, Yiqi Tiedje, James M. Zhou, Jizhong |
author_sort | Guo, Xue |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7524716 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-75247162020-10-19 Gene-informed decomposition model predicts lower soil carbon loss due to persistent microbial adaptation to warming Guo, Xue Gao, Qun Yuan, Mengting Wang, Gangsheng Zhou, Xishu Feng, Jiajie Shi, Zhou Hale, Lauren Wu, Linwei Zhou, Aifen Tian, Renmao Liu, Feifei Wu, Bo Chen, Lijun Jung, Chang Gyo Niu, Shuli Li, Dejun Xu, Xia Jiang, Lifen Escalas, Arthur Wu, Liyou He, Zhili Van Nostrand, Joy D. Ning, Daliang Liu, Xueduan Yang, Yunfeng Schuur, Edward. A. G. Konstantinidis, Konstantinos T. Cole, James R. Penton, C. Ryan Luo, Yiqi Tiedje, James M. Zhou, Jizhong Nat Commun Article 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. Nature Publishing Group UK 2020-09-29 /pmc/articles/PMC7524716/ /pubmed/32994415 http://dx.doi.org/10.1038/s41467-020-18706-z Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Guo, Xue Gao, Qun Yuan, Mengting Wang, Gangsheng Zhou, Xishu Feng, Jiajie Shi, Zhou Hale, Lauren Wu, Linwei Zhou, Aifen Tian, Renmao Liu, Feifei Wu, Bo Chen, Lijun Jung, Chang Gyo Niu, Shuli Li, Dejun Xu, Xia Jiang, Lifen Escalas, Arthur Wu, Liyou He, Zhili Van Nostrand, Joy D. Ning, Daliang Liu, Xueduan Yang, Yunfeng Schuur, Edward. A. G. Konstantinidis, Konstantinos T. Cole, James R. Penton, C. Ryan Luo, Yiqi Tiedje, James M. Zhou, Jizhong Gene-informed decomposition model predicts lower soil carbon loss due to persistent microbial adaptation to warming |
title | Gene-informed decomposition model predicts lower soil carbon loss due to persistent microbial adaptation to warming |
title_full | Gene-informed decomposition model predicts lower soil carbon loss due to persistent microbial adaptation to warming |
title_fullStr | Gene-informed decomposition model predicts lower soil carbon loss due to persistent microbial adaptation to warming |
title_full_unstemmed | Gene-informed decomposition model predicts lower soil carbon loss due to persistent microbial adaptation to warming |
title_short | Gene-informed decomposition model predicts lower soil carbon loss due to persistent microbial adaptation to warming |
title_sort | gene-informed decomposition model predicts lower soil carbon loss due to persistent microbial adaptation to warming |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7524716/ https://www.ncbi.nlm.nih.gov/pubmed/32994415 http://dx.doi.org/10.1038/s41467-020-18706-z |
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