Untangling the dynamics of persistence and colonization in microbial communities.

ABSTRACT: A central goal of community ecology is to infer biotic interactions from observed distributions of co-occurring species. Evidence for biotic interactions, however, can be obscured by shared environmental requirements, posing a challenge for statistical inference. Here, we introduce a dynamic statistical model, based on probit regression, that quantifies the effects of spatial and temporal covariance in longitudinal co-occurrence data. We separate the fixed pairwise effects of species occurrences on persistence and colonization rates, a potential signal of direct interactions, from latent pairwise correlations in occurrence, a potential signal of shared environmental responses. We first validate our modeling framework with several simulation studies. Then, we apply the approach to a pressin

SUBMITTER: Ranjeva SL 

PROVIDER: S-EPMC6863904 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature