A quantitative framework reveals ecological drivers of grassland microbial community assembly in response to warming

Daliang Ning(State Key Joint Laboratory of Environment Simulation and Pollution Control), Mengting Yuan(University of Oklahoma), Linwei Wu(University of Oklahoma), Ya Zhang(University of Oklahoma), Xue Guo(State Key Joint Laboratory of Environment Simulation and Pollution Control), Xishu Zhou(Central South University), Yunfeng Yang(State Key Joint Laboratory of Environment Simulation and Pollution Control), Adam P. Arkin(Lawrence Berkeley National Laboratory), Mary K. Firestone(Lawrence Berkeley National Laboratory), Jizhong Zhou(Lawrence Berkeley National Laboratory)
Nature Communications
September 18, 2020
Cited by 1,281Open Access
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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.


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