Microbial communities are capable of performing diverse functions with important bioindustrial and medical applications. One approach to improving a community function is to breed new communities by artificially selecting for those displaying high community function (‘community selection’). Importantly, community selection can improve the function of interest without needing to understand how the function arises, just like in classical artificial selection of individuals. However, experimental studies of community selection have had varied and largely limited success. Here, we review a conceptual framework to help foster an understanding of community selection and its associated challenges, and provide broad insights for designing effective selection strategies.

微生物群落能够在重要的生物工业和医学应用中发挥多种功能。改善群落功能的一种方法是通过人为选择那些表现出高群落功能的群落来培育新的群落（“群落选择”）。重要的是，群体选择可以改善兴趣功能，而无需了解该功能是如何产生的，就像经典的个体人工选择一样。然而，群落选择的实验研究取得了不同的成果，而且在很大程度上取得了有限的成功。在这里，我们回顾了一个概念框架，以帮助促进对社区选择及其相关挑战的理解，并为设计有效的选择策略提供广泛的见解。