Summary data for plots in: Eco-evolutionary extinction and recolonization dynamics reduce genetic load and increase time to extinction in highly inbred populations

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 in 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 that occur in diverse taxa.Data files can be opened using Notepad, or opened as dataframes using R.Funding provided by: University of AberdeenCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100000882Award Number:The data was produced by an individual-based simulation model implemented in C++ (full source code available at https://github.com/r02ap19/InbredMetapops/tree/master) and processed using R