Species are commonly thought to be evolutionarily independent in a way that populations within a species are not. In recent years, studies that seek to identify evolutionarily independent lineages (i.e., to delimit species) using genetic data have typically adopted multispecies coalescent approaches that assume that evolutionary independence is formed by the differential sorting of ancestral alleles due to genetic drift. However, gene flow appears to be common among populations and nascent species, and while this process may inhibit lineage divergence (and thus independence), it is usually not explicitly considered when delimiting species. In this article, we apply Phylogeographic Inference using Approximate Likelihoods (PHRAPL), a recently described method for phylogeographic model selection, to species delimitation. We describe an approach to delimiting species using PHRAPL that attempts to account for both genetic drift and gene flow, and we compare the method's performance to that of a popular delimitation approach (BPP) using both simulated and empirical datasets. PHRAPL generally infers the correct demographic-delimitation model when the generating model includes gene flow between taxa, given a sufficient amount of data. When the generating model includes only isolation in the recent past, PHRAPL will in some cases fail to differentiate between gene flow and divergence, leading to model misspecification. Nevertheless, the explicit consideration of gene flow by PHRAPL is an important complement to existing delimitation approaches, particularly in systems where gene flow is likely important. [approximate likelihoods; coalescent simulations; genealogical divergence index; Homo sapiens; isolation-with-migration; multispecies coalescent; Sarracenia; Scincella.].

Empirical phylogeographic studies have progressively sampled greater numbers of loci over time, in part motivated by theoretical papers showing that estimates of key demographic parameters improve as the number of loci increases. Recently, next-generation sequencing has been applied to questions about organismal history, with the promise of revolutionizing the field. However, no systematic assessment of how phylogeographic data sets have changed over time with respect to overall size and information content has been performed. Here, we quantify the changing nature of these genetic data sets over the past 20 years, focusing on papers published in Molecular Ecology. We found that the number of independent loci, the total number of alleles sampled and the total number of single nucleotide polymorphisms (SNPs) per data set has improved over time, with particularly dramatic increases within the past 5 years. Interestingly, uniparentally inherited organellar markers (e.g. animal mitochondrial and plant chloroplast DNA) continue to represent an important component of phylogeographic data. Singlespecies studies (cf. comparative studies) that focus on vertebrates (particularly fish and to some extent, birds) represent the gold standard of phylogeographic data collection. Based on the current trajectory seen in our survey data, forecast modelling indicates that the median number of SNPs per data set for studies published by the end of the year 2016 may approach~20 000. This survey provides baseline information for understanding the evolution of phylogeographic data sets and underscores the fact that development of analytical methods for handling very large genetic data sets will be critical for facilitating growth of the field.Keywords: DNA sequences, information content, phylogeography, sampling, single nucleotide polymorphisms, temporal trends IntroductionPhylogeographers have been working to collect multilocus data ever since a series of theoretical papers pertinent to the discipline demonstrated that estimates of key demographic parameters improve as the number of loci increases (e.g. Edwards & Beerli 2000;Hey & Nielsen 2004;Felsenstein 2006;Carling & Brumfield 2007). Recent improvements in DNA sequencing technology have led to platforms with greater speed, resolution and/or output (e.g. Margulies et al. 2005;Bentley et al. 2008;Rothberg et al. 2011) when compared to the traditional Sanger method. These technological advances, together with the development of general-purpose protocols for discovering and screening many DNA sequence polymorphisms arrayed across a species' genome (e.g. Baird et al. 2008;Kerstens et al. 2009;Faircloth et al. 2012;Peterson et al. 2012), are transforming the field of phylogeography to one that is no longer data limited. Investigations concerned with reconstructing long-term population history generally require large numbers of sampled alleles (i.e. many individuals and populations), across multiple loci, to adequately characterize levels of diversity and spatial genetic structuring (McCor...

The demographic history of most species is complex, with multiple evolutionary processes combining to shape the observed patterns of genetic diversity. To infer this history, the discipline of phylogeography has (to date) used models that simplify the historical demography of the focal organism, for example by assuming or ignoring ongoing gene flow between populations or by requiring a priori specification of divergence history. Since no single model incorporates every possible evolutionary process, researchers rely on intuition to choose the models that they use to analyze their data. Here, we describe an approximate likelihood approach that reduces this reliance on intuition. PHRAPL allows users to calculate the probability of a large number of complex demographic histories given a set of gene trees, enabling them to identify the most likely underlying model and estimate parameters for a given system. Available model parameters include coalescence time among populations or species, gene flow, and population size. We describe the method and test its performance in model selection and parameter estimation using simulated data. We also compare model probabilities estimated using our approximate likelihood method to those obtained using standard analytical likelihood. The method performs well under a wide range of scenarios, although this is sometimes contingent on sampling many loci. In most scenarios, as long as there are enough loci and if divergence among populations is sufficiently deep, PHRAPL can return the true model in nearly all simulated replicates. Parameter estimates from the method are also generally accurate in most cases. PHRAPL is a valuable new method for phylogeographic model selection and will be particularly useful as a tool to more extensively explore demographic model space than is typically done or to estimate parameters for complex models that are not readily implemented using current methods. Estimating relevant parameters using the most appropriate demographic model can help to sharpen our understanding of the evolutionary processes giving rise to phylogeographic patterns. [AIC; grid search; isolation-with-migration; migration rate; multispecies coalescent; parameter optimization; population genetics; tree topologies.].

Growing evidence supports the idea that species can diverge in the presence of gene flow. However, most methods of phylogeny estimation do not consider this process, despite the fact that ignoring gene flow is known to bias phylogenetic inference. Furthermore, studies that do consider divergence-with-gene-flow typically do so by estimating rates of gene flow using a isolation-with-migration model (IM), rather than evaluating scenarios of gene flow (such as divergence-with-gene flow or secondary contact) that represent very different types of diversification. In this investigation, we aim to infer the recent phylogenetic history of a clade of western long-eared bats while evaluating a number of different models that parameterize gene flow in a variety of ways. We utilize PHRAPL, a new tool for phylogeographic model selection, to compare the fit of a broad set of demographic models that include divergence, migration, or both among Myotis evotis, $M$. thysanodes and M. keenii. A genomic data set consisting of 808 loci of ultraconserved elements was used to explore such models in three steps using an incremental design where each successive set was informed by, and thus more focused than, the previous set of models. Specifically, the three steps were to (i) assess whether gene flow should be modeled and identify the best topologies, (ii) infer directionality of migration using the best topologies, and (iii) estimate the timing of gene flow. The best model (AIC model weight ${\sim}0.98$) included two divergence events (($M$. evotis, $M$. thysanodes), M. keenii) accompanied by gene flow at the initial stages of divergence. These results provide a striking example of speciation-with-gene-flow in an evolutionary lineage. [Myotis bats; PHRAPL; P2C2M; phylogeographic model selection; speciation with gene flow.].

Adaptive radiations are defined as rapid diversification with phenotypic innovation led by colonization to new environments. Notably, adaptive radiations can occur in parallel when habitats with similar selective pressures are accessible promoting convergent adaptions. Although convergent evolution appears to be a common process, it is unclear what are the main drivers leading the reappearance of morphologies or ecological roles. We explore this question in Myotis bats, the only Chiropteran genus with a worldwide distribution. Three foraging strategies—gleaning, trawling, and aerial netting—repeatedly evolved in several regions of the world, each linked to characteristic morphologies recognized as ecomorphs. Phylogenomic, morphometric, and comparative approaches were adopted to investigate convergence of such foraging strategies and skull morphology as well as factors that explain diversification rates. Genomic and morphometric data were analyzed from ∼80% extant taxa. Results confirm that the ecomorphs evolved multiple times, with trawling evolving more often and foliage gleaning most recently. Skull morphology does not reflect common ancestry and evolves convergently with foraging strategy. Although diversification rates have been roughly constant across the genus, speciation rates are area‐dependent and higher in taxa with temperate distributions. Results suggest that in this species‐rich group of bats, first, stochastic processes have led divergence into multiple lineages. Then, natural selection in similar niches has promoted repeated adaptation of phenotypes and foraging strategies. Myotis bats are thus a remarkable case of ecomorphological convergence and an emerging model system for investigating the genomic basis of parallel adaptive radiation.