Abstract
Genetic estimates of effective population size (Ne) are an established means to develop informed conservation policies. Another key goal to pursue the conservation of endangered species is keeping the connectivity across fragmented environments, to which genetic inferences of gene flow and dispersal greatly contribute. Most current statistical tools for estimating such population demographic parameters are based on Kingman's coalescent (KC). However, KC is inappropriate for taxa displaying skewed reproductive variance, a property widely observed in natural species. Coalescent models that consider skewed reproductive success-called multiple merger coalescents (MMCs)-have been shown to substantially improve estimates of Ne when the distribution of offspring per capita is highly skewed. MMCs predictions of standard population genetic parameters, including the rate of loss of genetic variation and the fixation probability of strongly selected alleles, substantially depart from KC predictions. These extended models also allow studying gene genealogies in a spatial continuum, providing a novel theoretical framework to investigate spatial connectivity. Therefore, development of statistical tools based on MMCs should substantially improve estimates of population demographic parameters with major conservation implications.