Available energy fluxes drive a transition in the diversity, stability, and functional structure of microbial communities

Abstract

A fundamental goal of microbial ecology is to understand what determines the diversity, stability, and structure of microbial ecosystems. The microbial context poses special conceptual challenges because of the strong mutual influences between the microbes and their chemical environment through the consumption and production of metabolites. By analyzing a generalized consumer resource model that explicitly includes cross-feeding, stochastic colonization, and thermodynamics, we show that complex microbial communities generically exhibit a transition as a function of available energy fluxes from a “resource-limited” regime where community structure and stability is shaped by energetic and metabolic considerations to a diverse regime where the dominant force shaping microbial communities is the overlap between species’ consumption preferences. These two regimes have distinct species abundance patterns, different functional profiles, and respond differently to environmental perturbations. Our model reproduces large-scale ecological patterns observed across multiple experimental settings such as nestedness and differential beta diversity patterns along energy gradients. We discuss the experimental implications of our results and possible connections with disorder-induced phase transitions in statistical physics.

Author summary

The diversity, stability and functional structure of microbial communities have dramatic effects on the health of humans and of ecosystems. The complexity of these communities has so far precluded the development of a general predictive model that would capture the dependence of these features on environmental conditions. We confronted this challenge by constructing a flexible simulation framework, and randomly sampling parameters under a variety of modeling assumptions to identify generic patterns. We found two qualitatively distinct regimes of community structure, which reproduce observed patterns of biodiversity, and make new predictions about stability and function.