Direct quantification of ecological drift at the population level in synthetic bacterial communities

In community ecology, drift refers to random births and deaths in a population. In microbial ecology, drift is estimated indirectly via community snapshots but in this way, it is almost impossible to distinguish the effect of drift from the effect of other ecological processes. Controlled experiments where drift is quantified in isolation from other processes are still missing. Here we isolate and quantify drift in a series of controlled experiments on simplified and tractable bacterial communities. We detect drift arising randomly in the populations within the communities and resulting in a 1.4–2% increase in their growth rate variability on average. We further use our experimental findings to simulate complex microbial communities under various conditions of selection and dispersal. We find that the importance of drift increases under high selection and low dispersal, where it can lead to ~5% of species loss and to ~15% increase in β-diversity. The species extinct by drift are mainly rare, but they become increasingly less rare when selection increases, and dispersal decreases. Our results provide quantitative insights regarding the properties of drift in bacterial communities and suggest that it accounts for a consistent fraction of the observed stochasticity in natural surveys.

Fodelianakis, S., Valenzuela-Cuevas, A., Barozzi, A., & Daffonchio, D. (2020). Direct quantification of ecological drift at the population level in synthetic bacterial communities. The ISME Journal. doi:10.1038/s41396-020-00754-4

We would like to thank Ms. Sadaf Umer for her support in organizing the laboratory work and Prof. Tom Battin, Prof. Emmanuel Ladoukakis, Dr. Alex Wasburne, and Dr. Athanasios Kousathanas for their valuable comments on a previous version of the manuscript. DD acknowledges the financial support of King Abdullah University and Technology (KAUST) through the baseline research fund and the Office of Sponsored Research (OSR) Award No. OSR-2018-CARF-1973 to the Red Sea Research Center.

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