Testing for Genetic Evidence of Population Expansion and Contraction: An Empirical Analysis of Microsatellite Dna Variation Using a Hierarchical Bayesian Model

Abstract

The role of past climatic change in shaping the distributions of tropical rain forest vertebrates is central to long‐standing hypotheses about the legacy of the Quaternary ice ages. One approach to testing such hypotheses is to use genetic data to infer the demographic history of codistributed species. Population genetic theory that relates the structure of allelic genealogies to historical changes in effective population size can be used to detect a past history of demographic expansion or contraction. The fruit bats Cynopterus sphinx and C. brachyotis (Chiroptera: Pteropodidae) exhibit markedly different distribution patterns across the Indomalayan region and therefore represent an exemplary species pair to use for such tests. The purpose of this study was to test alternative hypotheses about historical patterns of demographic expansion and contraction in C. sphinx and C. brachyotis using a coalescent‐based analysis of microsatellite variation. Specifically, we used a hierarchical Bayesian model based on Markov chain Monte Carlo simulations to estimate the posterior distribution of genealogical and demographic parameters. The results revealed strong evidence for population contraction in both species. Evidence for a population contraction in C. brachyotis was expected on the basis of biogeographic considerations. However, similar evidence for population contraction in C. sphinx does not support the hypothesis that this species underwent a pronounced range expansion during the late Quaternary. Genetic evidence for population decline may reflect the consequences of habitat destruction on a more recent time scale.

Contrasted levels of genetic diversity in a benthic Mediterranean octocoral: Consequences of different demographic histories?

“…Values of the multivariate Gelman and Rubin's convergence diagnostic between 1.0 and 1.1 indicate reasonable convergence, whereas values >1.1 indicate poor convergence. In this regard, the last 10 000 output lines of each chain were retained to make a combined consensus chain of 40 000 data points for each region, which was assumed to summarize the posterior distribution of N anc and N curr (Storz & Beaumont, 2002). The output of MSVAR was analyzed by focusing on the detection and on the direction of demographic changes (expansion or contraction).…”

MTML-msBayes: Approximate Bayesian comparative phylogeographic inference from multiple taxa and multiple loci with rate heterogeneity

“…The use of a hierarchical Bayesian framework within the context of ABC has been described elsewhere [10-12,22,23]. As in the single locus msBayes [24], our hierarchical Bayesian model includes taxon-specific demographic parameters and locus-specific mutation parameters ( Φ ) that are conditional on demographic and mutational "hyper-parameters" ( ϕ ) which quantify the variability of Φ among the different taxon-pairs and loci.…”

Genetic evidence of reproductive isolation in a remote enclave of Quercus pubescens in the presence of cross-fertile species

“…We used the basic method as implemented in version 0.4.2 of the software (available at http://www.rubic.rdg.ac.uk/*mab/stuff/), which assumes common demographic parameters for all loci. Although data exploitation might be suboptimal in this way (Storz and Beaumont 2002;Girod et al 2011), the basic method has an advantage as it requires priors on the scaled demographic parameters (i.e. r and t f ), which in our case can be proposed much more easily than priors for the natural demographic parameters (i.e.…”

“…N 0 , N 1 and T a ; as in version 1.3) (see ''Discussion'' in Girod et al 2011). The analysis was conducted assuming the exponential growth model, with rectangular priors for log(r), log(t f ) and log(h) bounded on -5 and 5 (as in Storz and Beaumont 2002). The Markov chain was run for 3 9 10 9 steps (keeping every 30,000 update), disregarding the first 3 9 10 8 updates to avoid dependence of final estimates on initial settings.…”