Eco-evolutionary extinction and recolonization dynamics reduce genetic load and increase time to extinction in highly inbred populations

Anders Poulsen Charmouh* (Corresponding Author), Jane Reid, Greta Bocedi, Trine Bilde

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


Understanding how genetic and ecological effects can interact to shape genetic loads within and across local populations is key to understanding ongoing persistence of systems that should otherwise be susceptible to extinction through mutational meltdown. Classic theory predicts short persistence times for metapopulations comprising small local populations with low connectivity, due to accumulation of deleterious mutations. Yet, some such systems have persisted over evolutionary time, implying the existence of mechanisms that allow metapopulations to avoid mutational meltdown. We first hypothesize a mechanism by which the combination of stochasticity in the numbers and types of mutations arising locally (genetic stochasticity), resulting local extinction, and recolonization through evolving dispersal, facilitates metapopulation persistence. We then test this mechanism using a spatially and genetically explicit individual-based model. We show that genetic stochasticity in highly structured metapopulations can result in local extinctions, which can favour increased dispersal, thus allowing recolonization of empty habitat patches. This causes fluctuations in metapopulation size and transient gene flow, which reduces genetic load and increases metapopulation persistence over evolutionary time. Our suggested mechanism and simulation results provide an explanation for the conundrum presented by the continued persistence of highly structured populations with inbreeding mating systems which occur in diverse taxa.
Original languageEnglish
Pages (from-to)2482-2497
Number of pages16
Issue number11
Early online date28 Sept 2022
Publication statusPublished - 1 Nov 2022

Bibliographical note

We thank Maximilian Tschol, Lana Dunan and Justin M. J. Travis for useful discussions and comments on the initial results. All simulations were performed using the Maxwell computing cluster at the University of Aberdeen. APC was supported by the University of Aberdeen. GB was supported by a Royal Society University Research Fellowship (UF160614). JMR was supported by NTNU and the Centre for Biodiversity Dynamics (NFR grant 223257).

Data Availability Statement

The model is implemented in C++ and the full source code is available at []. Summary data for plots is available at


  • Genetic load
  • metapopulation dynamics
  • inbreeding
  • dispersal
  • genetic stochasticity
  • mutational meltdown


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