Drivers of diversity within and between microbialcommunities during stochastic assembly

No two microbial communities share the same species richness and abundance. Experiments have shown that the assembly of new microbial communities from the same environmental pool is sufficient to generate diversity within and between communities. To identify the mechanisms behind these experimental results, we build a stochastic model that considers both the dispersal of microbes from a pool to communities and microbial division. By analyzing timescales, we identify distinct assembly regimes. Specifically, if dispersal is slower than division, microbial communities show low diversity within communities but high diversity between communities. Conversely, if dispersal is faster than division, microbial communities exhibit high diversity within communities but low diversity between them. We validate these predictions both numerically, using Gillespie simulations, and analytically, by deriving equations for species richness and abundance distributions. Our derivations pinpoint two key metrics, the bimodality coefficient and mean relative abundance, which identify the assembly regime and quantify trait differences. We apply these metrics to reanalyze an experimental data set, demonstrating their practical application. Overall, our study provides general predictions on how stochasticity, timescales, and traits impact diversity within and between communities during the assembly of new microbial communities, allowing for a better understanding of variation in microbiome formation.