A quantitative framework reveals ecological drivers of grassland microbial community assembly in response to warming
Unraveling the drivers controlling community assembly is a central issue in ecology. Although it is generally accepted that selection, dispersal, diversification and drift are major community assembly processes, defining their relative importance is very challenging. Here, we present a framework to...
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| Published in | Nature communications Vol. 11; no. 1; pp. 4717 - 12 |
|---|---|
| Main Authors | , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Nature Publishing Group UK
18.09.2020
Nature Publishing Group Nature Portfolio |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Unraveling the drivers controlling community assembly is a central issue in ecology. Although it is generally accepted that selection, dispersal, diversification and drift are major community assembly processes, defining their relative importance is very challenging. Here, we present a framework to quantitatively infer community assembly mechanisms by phylogenetic bin-based null model analysis (iCAMP). iCAMP shows high accuracy (0.93–0.99), precision (0.80–0.94), sensitivity (0.82–0.94), and specificity (0.95–0.98) on simulated communities, which are 10–160% higher than those from the entire community-based approach. Application of iCAMP to grassland microbial communities in response to experimental warming reveals dominant roles of homogeneous selection (38%) and ‘drift’ (59%). Interestingly, warming decreases ‘drift’ over time, and enhances homogeneous selection which is primarily imposed on Bacillales. In addition, homogeneous selection has higher correlations with drought and plant productivity under warming than control. iCAMP provides an effective and robust tool to quantify microbial assembly processes, and should also be useful for plant and animal ecology.
Studies of microbial community assembly mechanisms typically use metrics for turnover within the whole community. Here, the authors develop an alternative approach based on turnover within lineages and dissect mechanistic change in grassland bacterial assembly under experimental warming. |
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| AbstractList | Unraveling the drivers controlling community assembly is a central issue in ecology. Although it is generally accepted that selection, dispersal, diversification and drift are major community assembly processes, defining their relative importance is very challenging. Here, we present a framework to quantitatively infer community assembly mechanisms by phylogenetic bin-based null model analysis (iCAMP). iCAMP shows high accuracy (0.93–0.99), precision (0.80–0.94), sensitivity (0.82–0.94), and specificity (0.95–0.98) on simulated communities, which are 10–160% higher than those from the entire community-based approach. Application of iCAMP to grassland microbial communities in response to experimental warming reveals dominant roles of homogeneous selection (38%) and ‘drift’ (59%). Interestingly, warming decreases ‘drift’ over time, and enhances homogeneous selection which is primarily imposed on Bacillales. In addition, homogeneous selection has higher correlations with drought and plant productivity under warming than control. iCAMP provides an effective and robust tool to quantify microbial assembly processes, and should also be useful for plant and animal ecology.
Studies of microbial community assembly mechanisms typically use metrics for turnover within the whole community. Here, the authors develop an alternative approach based on turnover within lineages and dissect mechanistic change in grassland bacterial assembly under experimental warming. Unraveling the drivers controlling community assembly is a central issue in ecology. Although it is generally accepted that selection, dispersal, diversification and drift are major community assembly processes, defining their relative importance is very challenging. Here, we present a framework to quantitatively infer community assembly mechanisms by phylogenetic bin-based null model analysis (iCAMP). iCAMP shows high accuracy (0.93–0.99), precision (0.80–0.94), sensitivity (0.82–0.94), and specificity (0.95–0.98) on simulated communities, which are 10–160% higher than those from the entire community-based approach. Application of iCAMP to grassland microbial communities in response to experimental warming reveals dominant roles of homogeneous selection (38%) and ‘drift’ (59%). Interestingly, warming decreases ‘drift’ over time, and enhances homogeneous selection which is primarily imposed on Bacillales. In addition, homogeneous selection has higher correlations with drought and plant productivity under warming than control. iCAMP provides an effective and robust tool to quantify microbial assembly processes, and should also be useful for plant and animal ecology. Studies of microbial community assembly mechanisms typically use metrics for turnover within the whole community. Here, the authors develop an alternative approach based on turnover within lineages and dissect mechanistic change in grassland bacterial assembly under experimental warming. Unraveling the drivers controlling community assembly is a central issue in ecology. Although it is generally accepted that selection, dispersal, diversification and drift are major community assembly processes, defining their relative importance is very challenging. Here, we present a framework to quantitatively infer community assembly mechanisms by phylogenetic bin-based null model analysis (iCAMP). iCAMP shows high accuracy (0.93-0.99), precision (0.80-0.94), sensitivity (0.82-0.94), and specificity (0.95-0.98) on simulated communities, which are 10-160% higher than those from the entire community-based approach. Application of iCAMP to grassland microbial communities in response to experimental warming reveals dominant roles of homogeneous selection (38%) and 'drift' (59%). Interestingly, warming decreases 'drift' over time, and enhances homogeneous selection which is primarily imposed on Bacillales. In addition, homogeneous selection has higher correlations with drought and plant productivity under warming than control. iCAMP provides an effective and robust tool to quantify microbial assembly processes, and should also be useful for plant and animal ecology.Unraveling the drivers controlling community assembly is a central issue in ecology. Although it is generally accepted that selection, dispersal, diversification and drift are major community assembly processes, defining their relative importance is very challenging. Here, we present a framework to quantitatively infer community assembly mechanisms by phylogenetic bin-based null model analysis (iCAMP). iCAMP shows high accuracy (0.93-0.99), precision (0.80-0.94), sensitivity (0.82-0.94), and specificity (0.95-0.98) on simulated communities, which are 10-160% higher than those from the entire community-based approach. Application of iCAMP to grassland microbial communities in response to experimental warming reveals dominant roles of homogeneous selection (38%) and 'drift' (59%). Interestingly, warming decreases 'drift' over time, and enhances homogeneous selection which is primarily imposed on Bacillales. In addition, homogeneous selection has higher correlations with drought and plant productivity under warming than control. iCAMP provides an effective and robust tool to quantify microbial assembly processes, and should also be useful for plant and animal ecology. |
| ArticleNumber | 4717 |
| Author | Guo, Xue Zhang, Ya Firestone, Mary K. Yang, Yunfeng Zhou, Jizhong Yuan, Mengting Ning, Daliang Arkin, Adam P. Zhou, Xishu Wu, Linwei |
| Author_xml | – sequence: 1 givenname: Daliang orcidid: 0000-0002-3368-5988 surname: Ning fullname: Ning, Daliang organization: Institute for Environmental Genomics and Department of Microbiology and Plant Biology, University of Oklahoma, State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University – sequence: 2 givenname: Mengting orcidid: 0000-0003-0017-3908 surname: Yuan fullname: Yuan, Mengting organization: Institute for Environmental Genomics and Department of Microbiology and Plant Biology, University of Oklahoma, Department of Environmental Science Policy and Management, University of California – sequence: 3 givenname: Linwei orcidid: 0000-0002-6649-5072 surname: Wu fullname: Wu, Linwei organization: Institute for Environmental Genomics and Department of Microbiology and Plant Biology, University of Oklahoma – sequence: 4 givenname: Ya surname: Zhang fullname: Zhang, Ya organization: Institute for Environmental Genomics and Department of Microbiology and Plant Biology, University of Oklahoma – sequence: 5 givenname: Xue orcidid: 0000-0002-4309-6140 surname: Guo fullname: Guo, Xue organization: Institute for Environmental Genomics and Department of Microbiology and Plant Biology, University of Oklahoma, State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University – sequence: 6 givenname: Xishu surname: Zhou fullname: Zhou, Xishu organization: Institute for Environmental Genomics and Department of Microbiology and Plant Biology, University of Oklahoma, School of Minerals Processing and Bioengineering, Central South University – sequence: 7 givenname: Yunfeng orcidid: 0000-0001-8274-6196 surname: Yang fullname: Yang, Yunfeng organization: State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University – sequence: 8 givenname: Adam P. surname: Arkin fullname: Arkin, Adam P. organization: Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Department of Bioengineering, University of California – sequence: 9 givenname: Mary K. surname: Firestone fullname: Firestone, Mary K. organization: Department of Environmental Science Policy and Management, University of California, Earth and Environmental Sciences, Lawrence Berkeley National Laboratory – sequence: 10 givenname: Jizhong orcidid: 0000-0003-2014-0564 surname: Zhou fullname: Zhou, Jizhong email: jzhou@ou.edu organization: Institute for Environmental Genomics and Department of Microbiology and Plant Biology, University of Oklahoma, State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Earth and Environmental Sciences, Lawrence Berkeley National Laboratory, School of Civil Engineering and Environmental Sciences, University of Oklahoma |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32948774$$D View this record in MEDLINE/PubMed https://www.osti.gov/servlets/purl/1706664$$D View this record in Osti.gov |
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| Snippet | Unraveling the drivers controlling community assembly is a central issue in ecology. Although it is generally accepted that selection, dispersal,... Studies of microbial community assembly mechanisms typically use metrics for turnover within the whole community. Here, the authors develop an alternative... |
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| SubjectTerms | 49/22 49/23 631/158/2453 631/326/2565 704/158/853 704/158/855 Animals Bacteria - classification BASIC BIOLOGICAL SCIENCES Biodiversity community ecology Droughts Ecology Global Warming Grassland grassland ecology Humanities and Social Sciences Microbial communities microbial ecology Microbiota Models, Biological multidisciplinary Phylogeny Science Science (multidisciplinary) Sensitivity and Specificity |
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| Title | A quantitative framework reveals ecological drivers of grassland microbial community assembly in response to warming |
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