Ecological modelling approaches for predicting emergent properties in microbial communities

Recent studies have brought forward the critical role of emergent properties in shaping microbial communities and the ecosystems of which they are a part. Emergent properties—patterns or functions that cannot be deduced linearly from the properties of the constituent parts—underlie important ecological characteristics such as resilience, niche expansion and spatial self-organization. While it is clear that emergent properties are a consequence of interactions within the community, their non-linear nature makes mathematical modelling imperative for establishing the quantitative link between community structure and function. As the need for conservation and rational modulation of microbial ecosystems is increasingly apparent, so is the consideration of the benefits and limitations of the approaches to model emergent properties. Here we review ecosystem modelling approaches from the viewpoint of emergent properties. We consider the scope, advantages and limitations of Lotka–Volterra, consumer–resource, trait-based, individual-based and genome-scale metabolic models. Future efforts in this research area would benefit from capitalizing on the complementarity between these approaches towards enabling rational modulation of complex microbial ecosystems. As extremely large microbial community datasets have proliferated, numerous approaches to studying their ecological properties have emerged. In this Review, the authors offer a guide to five ecological modelling techniques used to study complex microbial communities.