生态学
生物扩散
同种类的
空模式
草原
生态系统
选择(遗传算法)
环境科学
气候变化
社区
生物
计算机科学
数学
机器学习
组合数学
社会学
人口学
人口
作者
Daliang Ning,Mengting Yuan,Linwei Wu,Ya Zhang,Xue Guo,Xishu Zhou,Yunfeng Yang,Adam P. Arkin,Mary K. Firestone,Jizhong Zhou
标识
DOI:10.1038/s41467-020-18560-z
摘要
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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