Dispersal homogenizes communities via immigration even at low rates in a simplified synthetic bacterial metacommunity

Stylianos Fodelianakis, ALEXANDER LORZ, Adriana Valenzuela Cuevas, Alan Barozzi, Jenny Marie Booth, Daniele Daffonchio

Research output: Contribution to journalArticlepeer-review

45 Scopus citations


Selection and dispersal are ecological processes that have contrasting roles in the assembly of communities. Variable selection diversifies and strong dispersal homogenizes them. However, we do not know whether dispersal homogenizes communities directly via immigration or indirectly via weakening selection across habitats due to physical transfer of material, e.g., water mixing in aquatic ecosystems. Here we examine how dispersal homogenizes a simplified synthetic bacterial metacommunity, using a sequencing-independent approach based on flow cytometry and mathematical modeling. We show that dispersal homogenizes the metacommunity via immigration, not via weakening selection, and even when immigration is four times slower than growth. This finding challenges the current view that dispersal homogenizes communities only at high rates and explains why communities are homogeneous at small spatial scales. It also offers a benchmark for sequence-based studies in natural microbial communities where immigration rates can be inferred solely by using neutral models.
Original languageEnglish (US)
JournalNature Communications
Issue number1
StatePublished - Mar 21 2019

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): OSR-2018-CARF-1973
Acknowledgements: This publication is based upon work supported by the King Abdullah University of Science and Technology (KAUST) to D.D. under the baseline funding and the Office of Sponsored Research (OSR) Award No. OSR-2018-CARF-1973 to the Red Sea Research Center. The authors would like to thank Dr. Frederik Hammes and Dr. Jay Lennon for their constructive comments on a previous version of the manuscript, as well as Dr. Marco Fusi and Adam Bouchaala for their advice regarding statistical analyses and MATLAB coding, respectively.


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