Drivers of diversity within and between microbial communities during stochastic assembly

Area of Science:

• Microbial Ecology
• Theoretical Ecology
• Mathematical Biology

Background:

• Microbial communities exhibit unique species richness and abundance profiles.
• Community assembly from a shared environmental pool generates diversity.
• Dispersal rates relative to division rates dictate community structure.

Purpose of the Study:

• To develop a minimal stochastic model for microbial community assembly.
• To quantitatively analyze the influence of dispersal and division rates on community structure.
• To identify robust metrics for predicting assembly regimes and microbial traits.

Main Methods:

• Development of a minimal stochastic model.
• Derivation of analytical expressions for abundance fluctuation distributions.
• Analysis of bimodality coefficient and mean relative abundance.

Main Results:

• The model recovers empirically observed assembly regimes (low, intermediate, high dispersal).
• The bimodality coefficient predicts community richness and dissimilarity.
• Mean relative abundance identifies differences in microbial traits.

Conclusions:

• Stochasticity, timescales, and microbial traits significantly influence microbial community assembly.
• The derived metrics are valuable for rapid identification of assembly regimes and trait asymmetries.
• This study enhances understanding of factors driving microbiome formation and variation.