Microbial communities and their functions are shaped by complex networks of interactions among microbes and with their environment. While the critical roles microbial communities play in numerous environments have become increasingly appreciated, we have a very limited understanding of their interactions and how these interactions combine to generate community-level behaviors. This knowledge gap hinders our ability to predict community responses to perturbations and to design interventions that manipulate these communities to our benefit. Dynamic models are promising tools to address these questions. We review existing modeling techniques to construct dynamic models of microbial communities at different scales and suggest ways to leverage multiple types of models and data to facilitate our understanding and engineering of microbial communities.

微生物群落及其功能是由微生物之间及其与环境相互作用的复杂网络决定的。尽管微生物群落在众多环境中发挥的关键作用越来越受到重视，但我们对它们的相互作用以及这些相互作用如何结合起来产生群落水平的行为的了解非常有限。这种知识差距阻碍了我们预测社区对扰动的反应以及设计干预措施以操纵这些社区为我们谋利的能力。动态模型是解决这些问题的有前途的工具。我们回顾了现有的建模技术来构建不同尺度的微生物群落的动态模型，并提出了利用多种类型的模型和数据来促进我们对微生物群落的理解和工程的方法。