成对比较
微观世界
群落结构
简单(哲学)
预测能力
生态学
微生物种群生物学
生物
环境资源管理
进化生物学
计算机科学
微生物群
细菌
社区
数据科学
生态系统
人工智能
环境科学
哲学
认识论
遗传学
作者
Jonathan Friedman,Logan M. Higgins,Jeff Gore
标识
DOI:10.1038/s41559-017-0109
摘要
Microorganisms typically form diverse communities of interacting species, whose activities have tremendous impact on the plants, animals and humans they associate with. The ability to predict the structure of these complex communities is crucial to understanding and managing them. Here, we propose a simple, qualitative assembly rule that predicts community structure from the outcomes of competitions between small sets of species, and experimentally assess its predictive power using synthetic microbial communities composed of up to eight soil bacterial species. Nearly all competitions resulted in a unique, stable community, whose composition was independent of the initial species fractions. Survival in three-species competitions was predicted by the pairwise outcomes with an accuracy of ~90%. Obtaining a similar level of accuracy in competitions between sets of seven or all eight species required incorporating additional information regarding the outcomes of the three-species competitions. Our results demonstrate experimentally the ability of a simple bottom-up approach to predict community structure. Such an approach is key for anticipating the response of communities to changing environments, designing interventions to steer existing communities to more desirable states and, ultimately, rationally designing communities de novo. Survival of competing microbial species pairs predicts competition outcome between a greater number of species: species that coexist with each other in pairs will survive, species that are excluded by any of the surviving species will go extinct.
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