title: Quantifying the mutational meltdown in diploid populations.
abstract: Mutational meltdown, in which demographic and genetic processes mutually reinforce one another to accelerate the extinction of small populations, has been poorly quantified despite its potential importance in conservation biology. Here we present a model-based framework to study and quantify the mutational meltdown in a finite diploid population that is evolving continuously in time and subject to resource competition. We model slightly deleterious mutations affecting the population demographic parameters and study how the rate of mutation fixation increases as the genetic load increases, a process that we investigate at two timescales: an ecological scale and a mutational scale. Unlike most previous studies, we treat population size as a random process in continuous time. We show that as deleterious mutations accumulate, the decrease in mean population size accelerates with time relative to a null model with a constant mean fixation time. We quantify this mutational meltdown via the change in the mean fixation time after each new mutation fixation, and we show that the meltdown appears less severe than predicted by earlier theoretical work. We also emphasize that mean population size alone can be a misleading index of the risk of population extinction, which could be better evaluated with additional information on demographic parameters.
authors.affiliation: Centre de Mathématiques Appliquées CMAP, École Polytechnique, CNRS, Route de Saclay, 91128 Palaiseau Cedex, France. coron@cmap.polytechnique.fr
authors.forename: Camille
authors.initials: C
authors.lastname: Coron
authors.forename: Sylvie
authors.initials: S
authors.lastname: Méléard
authors.forename: Emmanuelle
authors.initials: E
authors.lastname: Porcher
authors.forename: Alexandre
authors.initials: A
authors.lastname: Robert
mesh_terms: D004171:Diploidy; D019143:Evolution, Molecular; D053476:Extinction, Biological; D008957:Models, Genetic; D009154:Mutation; D011156:Population Density; D013269:Stochastic Processes