Random sampling associated with microbial profiling leads to overestimated stochasticity inference in community assembly.

ABSTRACT: Revealing the mechanisms governing the complex community assembly over space and time is a central issue in ecology. Null models have been developed to quantitatively disentangle the relative importance of deterministic vs. stochastic processes in structuring the compositional variations of biological communities. Similar approaches have been recently extended to the field of microbial ecology. However, the profiling of highly diverse biological communities (e.g., microbial communities) is severely influenced by random sampling issues, leading to undersampled community profiles and overestimated β-diversity, which may further affect stochasticity inference in community assembly. By implementing simulated datasets, this study demonstrate that microbial stochasticity inference is also affect

SUBMITTER: Ma K 

PROVIDER: S-EPMC9598869 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature