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      Phylogeographic analysis of the true lemurs (genus Eulemur) underlines the role of river catchments for the evolution of micro-endemism in Madagascar

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      1 , , 1 , 2
      Frontiers in Zoology
      BioMed Central
      Eulemur, Phylogeography, Madagascar, Centers of endemism, Biogeography

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          Abstract

          Introduction

          Due to its remarkable species diversity and micro-endemism, Madagascar has recently been suggested to serve as a biogeographic model region. However, hypothesis-based tests of various diversification mechanisms that have been proposed for the evolution of the island’s micro-endemic lineages are still limited. Here, we test the fit of several diversification hypotheses with new data on the broadly distributed genus Eulemur using coalescent-based phylogeographic analyses.

          Results

          Time-calibrated species tree analyses and population genetic clustering resolved the previously polytomic species relationships among eulemurs. The most recent common ancestor of eulemurs was estimated to have lived about 4.45 million years ago (mya). Divergence date estimates furthermore suggested a very recent diversification among the members of the “brown lemur complex”, i.e. former subspecies of E. fulvus, during the Pleistocene (0.33-1.43 mya). Phylogeographic model comparisons of past migration rates showed significant levels of gene flow between lineages of neighboring river catchments as well as between eastern and western populations of the redfronted lemur ( E. rufifrons).

          Conclusions

          Together, our results are concordant with the centers of endemism hypothesis (Wilmé et al. 2006, Science 312:1063–1065), highlight the importance of river catchments for the evolution of Madagascar’s micro-endemic biota, and they underline the usefulness of testing diversification mechanisms using coalescent-based phylogeographic methods.

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          Most cited references53

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          Speciation in amazonian forest birds.

          J Haffer (1969)
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            Inferring phylogeny despite incomplete lineage sorting.

            It is now well known that incomplete lineage sorting can cause serious difficulties for phylogenetic inference, but little attention has been paid to methods that attempt to overcome these difficulties by explicitly considering the processes that produce them. Here we explore approaches to phylogenetic inference designed to consider retention and sorting of ancestral polymorphism. We examine how the reconstructability of a species (or population) phylogeny is affected by (a) the number of loci used to estimate the phylogeny and (b) the number of individuals sampled per species. Even in difficult cases with considerable incomplete lineage sorting (times between divergences less than 1 N(e) generations), we found the reconstructed species trees matched the "true" species trees in at least three out of five partitions, as long as a reasonable number of individuals per species were sampled. We also studied the tradeoff between sampling more loci versus more individuals. Although increasing the number of loci gives more accurate trees for a given sampling effort with deeper species trees (e.g., total depth of 10 N(e) generations), sampling more individuals often gives better results than sampling more loci with shallower species trees (e.g., depth = 1 N(e)). Taken together, these results demonstrate that gene sequences retain enough signal to achieve an accurate estimate of phylogeny despite widespread incomplete lineage sorting. Continued improvement in our methods to reconstruct phylogeny near the species level will require a shift to a compound model that considers not only nucleotide or character state substitutions, but also the population genetics processes of lineage sorting. [Coalescence; divergence; population; speciation.].
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              Unified framework to evaluate panmixia and migration direction among multiple sampling locations.

              For many biological investigations, groups of individuals are genetically sampled from several geographic locations. These sampling locations often do not reflect the genetic population structure. We describe a framework using marginal likelihoods to compare and order structured population models, such as testing whether the sampling locations belong to the same randomly mating population or comparing unidirectional and multidirectional gene flow models. In the context of inferences employing Markov chain Monte Carlo methods, the accuracy of the marginal likelihoods depends heavily on the approximation method used to calculate the marginal likelihood. Two methods, modified thermodynamic integration and a stabilized harmonic mean estimator, are compared. With finite Markov chain Monte Carlo run lengths, the harmonic mean estimator may not be consistent. Thermodynamic integration, in contrast, delivers considerably better estimates of the marginal likelihood. The choice of prior distributions does not influence the order and choice of the better models when the marginal likelihood is estimated using thermodynamic integration, whereas with the harmonic mean estimator the influence of the prior is pronounced and the order of the models changes. The approximation of marginal likelihood using thermodynamic integration in MIGRATE allows the evaluation of complex population genetic models, not only of whether sampling locations belong to a single panmictic population, but also of competing complex structured population models.
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                Author and article information

                Journal
                Front Zool
                Front. Zool
                Frontiers in Zoology
                BioMed Central
                1742-9994
                2013
                14 November 2013
                : 10
                : 70
                Affiliations
                [1 ]Behavioral Ecology and Sociobiology Unit, German Primate Center, Kellnerweg 4, Göttingen 37077, Germany
                [2 ]Department of Sociobiology/Anthropology, University of Göttingen, Göttingen, Germany
                Article
                1742-9994-10-70
                10.1186/1742-9994-10-70
                3835867
                24228694
                cc473b36-6c9e-42e0-82f7-8645d66c1a09
                Copyright © 2013 Markolf and Kappeler; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 9 July 2013
                : 28 October 2013
                Categories
                Research

                Animal science & Zoology
                eulemur,phylogeography,madagascar,centers of endemism,biogeography
                Animal science & Zoology
                eulemur, phylogeography, madagascar, centers of endemism, biogeography

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