Species abundance correlations carry limited information about microbial network interactions.

ABSTRACT: Unraveling the network of interactions in ecological communities is a daunting task. Common methods to infer interspecific interactions from cross-sectional data are based on co-occurrence measures. For instance, interactions in the human microbiome are often inferred from correlations between the abundances of bacterial phylogenetic groups across subjects. We tested whether such correlation-based methods are indeed reliable for inferring interaction networks. For this purpose, we simulated bacterial communities by means of the generalized Lotka-Volterra model, with variation in model parameters representing variability among hosts. Our results show that correlations can be indicative for presence of bacterial interactions, but only when measurement noise is low relative to the variation i

SUBMITTER: Pinto S 

PROVIDER: S-EPMC9518925 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature