bioRxivEcologyPreprint
Modeling assembly dynamics and stability of microbial communities
Abstract
Predicting the species composition of microbial communities is a problem that has proven surprisingly difficult, including in fully controlled microbial systems in a lab setting. Few organisms are able to establish themselves in an community with no others, even if nutrients are provided. At the same time some species are observed to be unable to stably coexist with certain other species. We here present a model attempting to reduce the dynamics of community assembly to its most basic components, while preserving its salient features. The model deals not with abundances or densities of bacterial populations or resources, but only with their presence or absence. Similarly, only three types of discrete relationships between species are considered: species excluding each other, and mutualistic dependence on and production of nutrients in the form of exometabolites. Despite these simplifications, the model system still exhibits rich dynamics, including extinction cascades and emerging stability against invasion. We derive conditions for these to occur and compare our results with existing knowledge of microbial communities. Our results provide a novel approach for the theoretical study of microbial communities and their stability. SignificanceUnderstanding the processes governing the community composition of microbial ecosystems is an as-yet unsolved problem. In this article, we propose a novel rule-based model for the assembly and stability of communities of microbial species. Despite its simplicity the model exhibits rich dynamics, including critical points and extinction cascades. It presupposes no knowledge of specific population parameters or exact resource or species abundances, but focuses on pairwise interactions between species and their metabolites. The framework may be useful for understanding how real microbial communities arise and what causes them to break down.
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- Microbial Community Ecology and Physiology
- Mathematical and Theoretical Epidemiology and Ecology Models
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