Phylogeographic Datasets Research Articles

Cycles of trans-Arctic dispersal and vicariance, and diversification of the amphi-boreal marine fauna.

The amphi-boreal faunal element comprises closely related species and conspecific populations with vicarious distributions in the North Atlantic and North Pacific basins. It originated from an initial trans-Arctic dispersal in the Pliocene after the first opening of the Bering Strait, and subsequent inter-oceanic vicariance through the Pleistocene when the passage through the Arctic was severed by glaciations and low sea levels. Opportunities for further trans-Arctic dispersal have risen at times, however, and molecular data now expose more complex patterns of inter-oceanic affinities and dispersal histories. For a general view on the trans-Arctic dynamics and of the roles of potential dispersal-vicariance cycles in generating systematic diversity, we produced new phylogeographic data sets for amphi-boreal taxa in 21 genera of invertebrates and vertebrates, and combined them with similar published data sets of mitochondrial coding gene variation, adding up to 89 inter-oceanic comparisons involving molluscs, crustaceans, echinoderms, polychaetes, fishes and mammals. Only 39% of the cases correspond to a simple history of Pliocene divergence; in most taxonomical groups, the range of divergence estimates implies connections through the entire Pliocene-Pleistocene-Holocene time frame. Repeated inter-oceanic exchange was inferred for 23 taxa, and the latest connection was usually post-glacial. Such repeated invasions have usually led to secondary contacts and occasionally to widespread hybridization between the different invasion waves. Late- or post-glacial exchange was inferred in 46% of the taxa, stressing the importance of the relatively recent invasions to the current diversity in the North Atlantic. Individual taxa also showed complex idiosyncratic patterns and histories, and several instances of cryptic speciation were recognized. In contrast to a simple inter-oceanic vicariance scenario underlying amphi-boreal speciation, the data expose complex patterns of reinvasion and reticulation that complicate the interpretation of taxon boundaries in the region.

Efficient summary statistics for detecting lineage fusion from phylogeographic datasets

AbstractAimLineage fusion (merging of two or more populations of a species resulting in a single panmictic group) is a special case of secondary contact. It has the potential to counteract diversification and speciation, or to facilitate it through creation of novel genotypes. Understanding the prevalence of lineage fusion in nature requires reliable detection of it, such that efficient summary statistics are needed. Here, we report on simulations that characterized the initial intensity and subsequent decay of signatures of past fusion for 17 summary statistics applicable to DNA sequence haplotype data.LocationGlobal.TaxaDiploid out‐crossing species.MethodsWe considered a range of scenarios that could reveal the impacts of different combinations of read length versus number of loci (arrangement of DNA sequence data), and whether or not pre‐fusion populations experienced bottlenecks coinciding with their divergence (historical context of fusion). Post‐fusion gene pools were sampled along 10 successive time points representing increasing lag times following merging of sister populations, and summary statistic values were recalculated at each.ResultsMany summary statistics were able to detect signatures of complete merging of populations after a sampling lag time of 1.5 Ne generations, but the most informative ones included two neutrality tests and four diversity metrics, with ZnS (a linkage disequilibrium‐based neutrality test) being particularly powerful. Correlation was relatively low among the two neutrality tests and two of the diversity metrics. There were clear benefits of many short (200‐bp × 200) loci over a handful of long (4‐kb × 10) loci. Also, only the latter genetic dataset type showed impacts of bottlenecks during divergence upon the number of informative summary statistics.Main conclusionsThis work contributes to identifying cases of lineage fusion, and advances phylogeography by enabling more nuanced reconstructions of how individual species, or multiple members of an ecological community, responded to past environmental change.

SuperCRUNCH: A bioinformatics toolkit for creating and manipulating supermatrices and other large phylogenetic datasets

Abstract Phylogenies with extensive taxon sampling have become indispensable for many types of ecological and evolutionary studies. Many large‐scale trees are based on a ‘supermatrix’ approach, which involves amalgamating thousands of published sequences for a group. Constructing up‐to‐date supermatrices can be challenging, especially as new sequences may become available almost constantly. Additionally, genomic datasets (composed of thousands of loci) are becoming common in phylogenetics and phylogeography, and present novel challenges for constructing such datasets. Here we present SuperCRUNCH, a Python toolkit for assembling large phylogenetic datasets. It can be applied to GenBank sequences, unpublished sequences or combinations of GenBank and unpublished data. SuperCRUNCH constructs local databases and uses them to conduct rapid searches for user‐specified sets of taxa and loci. Sequences are parsed into putative loci and passed through rigorous filtering steps. A post‐filtering step allows for selection of one sequence per taxon (i.e. species‐level supermatrix) or retention of all sequences per taxon (i.e. population‐level dataset). Importantly, SuperCRUNCH can generate ‘vouchered’ population‐level datasets, in which voucher information is used to generate multi‐locus phylogeographic datasets. SuperCRUNCH offers many options for taxonomy resolution, similarity filtering, sequence selection, alignment and file manipulation. We demonstrate the range of features available in SuperCRUNCH by generating a variety of phylogenetic datasets. Output datasets include traditional species‐level supermatrices, large‐scale phylogenomic matrices and phylogeographic datasets. Finally, we briefly compare the ability of SuperCRUNCH to construct species‐level supermatrices relative to alternative approaches. SuperCRUNCH generated a large‐scale supermatrix (1,400 taxa and 66 loci) from 16 GB of GenBank data in ~1.5 hr, and generated population‐level datasets (<350 samples, <10 loci) in <1 min. It outperformed alternative methods for supermatrix construction in terms of taxa, loci and sequences recovered. SuperCRUNCH is a modular bioinformatics toolkit that can be used to assemble datasets for any taxonomic group and scale (kingdoms to individuals). It allows rapid construction of supermatrices, greatly simplifying the process of updating large phylogenies with new data. It is also designed to produce population‐level datasets. SuperCRUNCH streamlines the major tasks required to process phylogenetic data, including filtering, alignment, trimming and formatting. SuperCRUNCH is open‐source, documented and available at https://github.com/dportik/SuperCRUNCH.

Evolutionary Hotspots of Seed Plants in Subtropical China: A Comparison With Species Diversity Hotspots of Woody Seed Plants.

Genetic diversity is a fundamental level of biodiversity. However, it is frequently neglected in conservation prioritization because intraspecific genetic diversity is difficult to measure at large scales. In this study, we synthesized population genetic or phylogeographic datasets of 33 seed plants in subtropical China into multi-species genetic landscapes. The genetic landscapes identified 18 evolutionary hotspots with high within-population genetic diversity (WGD), and among-population genetic diversity (AGD), or both. The western subtropical China is rich in AGD (possessing four major AGD hotspots), deserving a high conservation priority. We found that WGD was positively correlated with longitude, with most WGD hotspots locating in east subtropical China. The results showed that the locations of 12 of 18 evolutionary hotspots corresponded approximately to those of previously identified species diversity (SD) hotspots, however, a positive and significant correlation existed only between AGD and SD, not between WGD and SD. Therefore, spatial patterns of species richness in plants in subtropical China cannot generally be used as surrogate for their intraspecific diversity. This study identified multi-species evolutionary hotspots and correlated multi-species genetic diversity with SD across subtropical China for the first time, providing profound implications for the conservation of biodiversity in this important ecoregion.

Targeted Sampling and Target Capture: Assessing Phylogeographic Concordance with Genome-wide Data.

Comparative phylogeography provides the necessary framework to examine the factors influencing population divergence, persistence, and change over time. Avise (2000) outlined four aspects of concordance that result when data exhibit significant phylogeographic signal: concordance among sites within a locus, among multiple loci within a species, among multiple species within a region, and between genetic patterns and established biogeographic provinces. To fully address each aspect of concordance, we combined target capture of a set of orthologous loci with targeted geographic sampling of multiple species, thus removing any variability introduced by using different genetic markers and heterogeneous sampling distributions. We used hybrid enrichment and high-throughput sequencing of four anuran species sampled from 36 congruent localities in the Southeastern United States Coastal Plain, a region that represents one of the classic systems in phylogeography. In total, we recovered > 375 of the same nuclear loci across species and assembled mitochondrial genomes, resulting in one of the most comprehensive comparative phylogeographic datasets in any region or taxon to date. We used these data to evaluate concordance, compare genetic structure across species, and test previously described biogeographic features in the region including major river drainages and suture zones. We then applied a recently-developed framework to quantify concordance across species using phylogeographic concordance factors. For the four species examined, which have higher dispersal and potentially limited structure compared to many amphibians, we found poor resolution in individual nuclear gene trees even with long (~ 1400 bp) nuclear sequences. The mitochondrial and multi-locus nuclear datasets, however, produced similar patterns within species, indicated high discordance among species, and suggested little correspondence of genetic patterns with putative biogeographic barriers. Variation in the phylogeographic structure detected may be related to differences in natural history, in that the two habitat generalists exhibited less structure. Our study demonstrates the utility of combining target capture, which is highly repeatable and produces comparable datasets, with a targeted sampling strategy to quantify phylogeographic concordance across diverse taxa in a region with a complex history.

Emerging peak on the phylogeographic landscape of Mycobacterium tuberculosis in West Asia: Definitely smoke, likely fire

To date, a major attention was justly given to the global lineages of Mycobacterium tuberculosis. Here, we demonstrated an importance of the minor ones, on an example of intriguing and underestimated NEW-1 family that belongs to Euro-American lineage (lineage 4). Analysis of the global WGS/NGS datasets (5715 strains) identified 2235 strains of Lineage 4 and 66 strains of sublineage L4.5. This latter is marked with RD122 genomic deletion and includes NEW-1 family. Phylogenomic analysis confirmed a separate position of the NEW-1 family that we tentatively designate L4.5.1/Iran. We propose an evolution/migration scenario starting with origin of L4.5 1000–1300 ya in China, subsequent origin of the pre-NEW-1 intermediate genotype in Tibet, further migration to Xinjiang/Uyghur, and finally to Iran since 800 ya (origin of NEW-1), possibly, via expansion of the Mongol Yuan empire. Analysis of longitudinal phylogeographic datasets revealed a sharp increase in prevalence of NEW-1 strains in Iran and its eastwards neighbors in the last 20years; most alarmingly, it is accompanied with significant association with multidrug resistance (MDR). Ongoing migration, especially, Afghan refugees flows to developed countries emphasize a risk of the wider spread of the epidemic MDR subtype within NEW-1 family that we coin as emerging resistant clone of M. tuberculosis in West Asia.

Objective choice of phylogeographic models

Phylogeography seeks to discover the evolutionary processes that have given rise to organismal and genetic diversity. This requires explicit hypotheses (i.e., models) to be evaluated with genetic data in order to identify those hypotheses that best explain the data. In recent years, advancements in the model-based tools used to estimate phylogeographic parameters of interest such as gene flow, divergence time, and relationships among groups have been made. However, given the complexity of these models, available methods can typically only compare a handful of possible hypotheses, requiring researchers to specify in advance the small set of models to consider. Without formal quantitative approaches to model selection, researchers must rely on their intuition to formulate the model space to be explored.We explore the adequacy of intuitive choices made by researchers during the process of data analysis by reanalyzing 20 empirical phylogeographic datasets using PHRAPL, an objective tool for phylogeographic model selection. We show that the best models for most datasets include both gene flow and population divergence parameters, and that species tree methods (which do not consider gene flow) tend to be overly simplistic for many phylogeographic systems. Objective approaches to phylogeographic model selection offer an important complement to researcher intuition.

Demographic model selection using random forests and the site frequency spectrum.

Phylogeographic data sets have grown from tens to thousands of loci in recent years, but extant statistical methods do not take full advantage of these large data sets. For example, approximate Bayesian computation (ABC) is a commonly used method for the explicit comparison of alternate demographic histories, but it is limited by the "curse of dimensionality" and issues related to the simulation and summarization of data when applied to next-generation sequencing (NGS) data sets. We implement here several improvements to overcome these difficulties. We use a Random Forest (RF) classifier for model selection to circumvent the curse of dimensionality and apply a binned representation of the multidimensional site frequency spectrum (mSFS) to address issues related to the simulation and summarization of large SNP data sets. We evaluate the performance of these improvements using simulation and find low overall error rates (~7%). We then apply the approach to data from Haplotrema vancouverense, a land snail endemic to the Pacific Northwest of North America. Fifteen demographic models were compared, and our results support a model of recent dispersal from coastal to inland rainforests. Our results demonstrate that binning is an effective strategy for the construction of a mSFS and imply that the statistical power of RF when applied to demographic model selection is at least comparable to traditional ABC algorithms. Importantly, by combining these strategies, large sets of models with differing numbers of populations can be evaluated.

Multi-dice: r package for comparative population genomic inference under hierarchical co-demographic models of independent single-population size changes.

Population genetic data from multiple taxa can address comparative phylogeographic questions about community‐scale response to environmental shifts, and a useful strategy to this end is to employ hierarchical co‐demographic models that directly test multi‐taxa hypotheses within a single, unified analysis. This approach has been applied to classical phylogeographic data sets such as mitochondrial barcodes as well as reduced‐genome polymorphism data sets that can yield 10,000s of SNPs, produced by emergent technologies such as RAD‐seq and GBS. A strategy for the latter had been accomplished by adapting the site frequency spectrum to a novel summarization of population genomic data across multiple taxa called the aggregate site frequency spectrum (aSFS), which potentially can be deployed under various inferential frameworks including approximate Bayesian computation, random forest and composite likelihood optimization. Here, we introduce the r package multi‐dice, a wrapper program that exploits existing simulation software for flexible execution of hierarchical model‐based inference using the aSFS, which is derived from reduced genome data, as well as mitochondrial data. We validate several novel software features such as applying alternative inferential frameworks, enforcing a minimal threshold of time surrounding co‐demographic pulses and specifying flexible hyperprior distributions. In sum, multi‐dice provides comparative analysis within the familiar R environment while allowing a high degree of user customization, and will thus serve as a tool for comparative phylogeography and population genomics.

The evolution of phylogeographic data sets.

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. Single-species 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.

Emerging patterns and emerging challenges of comparative phylogeography

news and update ISSN 1948-6596 commentary Emerging patterns and emerging challenges of comparative phylogeography Biogeographic studies commonly amass distri- bution datasets for hundreds of species in an attempt to describe biogeographic patterns and their underlying processes (e.g., Keith et al. 2013). In contrast, phylogeographic studies are almost always limited to a small number of species and, while able to detect patterns at a population level, lack the replicative power of biogeography to describe those patterns in terms of relevant processes. This is particularly disadvantageous in phylogeographic studies of marine species, because the ocean contains few conspicuous geographic features that might explain population breaks (Horne 2014). Large, comparative phylogeographic datasets have long been the daydream of mo- lecular ecologists but have previously not been possible because the data didn't exist and rig- orous phylogeographic analyses do not scale well with large datasets (Andrew et al. 2013). For instance, coalescence-based phy- logeographic model fitting is able to accurately assess population patterns amid stochastic sig- nals and other noise in the data (Beaumont et al. 2010) but is computationally intensive and can become overwhelmingly time consuming as datasets grow larger and modelled scenarios become more complex. Even while data remain limited and coa- lescence analyses continue to be computation- ally burdensome, some research groups are expanding the boundaries of comparative phy- logeographic and population genetic research. Specifically, a recent paper, published earlier this year, by Selkoe and colleagues, jointly ana- lyzed population genetic patterns in 35 coral reef-associated species across the main and northwest Hawaiian islands. By biogeography standards this is a tiny dataset, but for a phy- logeographic study 35 species is impressive. Selkoe et al. (2014) did not include coa- lescence-based analyses, instead relying on multivariate analyses (principal components analysis and redundancy analysis) of popula- tion genetic summary statistics, k-means clus- ters, and ecological variables to assess four types of population structuring: long-term pan- mixia across the 2400-km-long archipelago, chaotic genetic heterogeneity, isolation-by- distance (IBD), and regional genetic structure. The multivariate approach used was based, in part, on another comparative study of 27 high- alpine plants (Miermans et al. 2011). Since we can probably expect more studies like these to arise in the future, it seems timely to comment on these comparative methods, their draw- backs and their merits. First, the entire approach rests upon a foundation of summary statistics (e.g., F ST ), which suffer from well-known shortcomings. For example, several of the datasets in Selkoe et al. did not have enough genetic polymor- phism to statistically reject a null hypothesis of panmixia using gene frequencies. At the other extreme, some of the datasets had too much polymorphism to reject panmixia, because if each individual has a unique genetic variant the maximum attainable F ST value is 0. Issues of polymorphism might be addressed with addi- tional sampling, which could uncover additional genetic signal (e.g., Horne et al. 2013). Alterna- tively, one could collect more loci. Regardless, insufficient data is the underlying problem. Ample amounts of genetic variation are the sine qua non of this method; a problem, considering that researchers are generally forced to rely on available datasets from past surveys, many of which were kept small by the costs of Sanger DNA sequencing. Furthermore, species that are too sparsely sampled, or con- tain too few individuals at each location, may not capture enough genetic variation. Selkoe et al. rightly point out that comparative studies demand substantial rigor in sampling coverage frontiers of biogeography 6.4, 2014 — © 2014 the authors; journal compilation © 2014 The International Biogeography Society

Detecting concerted demographic response across community assemblages using hierarchical approximate Bayesian computation.

Methods that integrate population-level sampling from multiple taxa into a single community-level analysis are an essential addition to the comparative phylogeographic toolkit. Detecting how species within communities have demographically tracked each other in space and time is important for understanding the effects of future climate and landscape changes and the resulting acceleration of extinctions, biological invasions, and potential surges in adaptive evolution. Here, we present a statistical framework for such an analysis based on hierarchical approximate Bayesian computation (hABC) with the goal of detecting concerted demographic histories across an ecological assemblage. Our method combines population genetic data sets from multiple taxa into a single analysis to estimate: 1) the proportion of a community sample that demographically expanded in a temporally clustered pulse and 2) when the pulse occurred. To validate the accuracy and utility of this new approach, we use simulation cross-validation experiments and subsequently analyze an empirical data set of 32 avian populations from Australia that are hypothesized to have expanded from smaller refugia populations in the late Pleistocene. The method can accommodate data set heterogeneity such as variability in effective population size, mutation rates, and sample sizes across species and exploits the statistical strength from the simultaneous analysis of multiple species. This hABC framework used in a multitaxa demographic context can increase our understanding of the impact of historical climate change by determining what proportion of the community responded in concert or independently and can be used with a wide variety of comparative phylogeographic data sets as biota-wide DNA barcoding data sets accumulate.

Biogeography: Where do we go from here?

AbstractBiogeography is a multidisciplinary science concerned with how and why organisms are distributed as they are on Earth. It links fields such as systematics, ecology, paleontology, and climatology, and occupies a central position in evolutionary biology, being fundamental to the study of processes such as speciation and adaptive radiation. Here we provide a brief overview of some particularly dynamic areas of inquiry and offer some perspectives on future directions for the field. We hope that some historical debates, such as those over the importance of dispersal, or the validity of molecular dating, are finally being put to rest. Over the last decade, biogeography has become increasingly integrative, and has benefited from advances in statistical methods for inferring geographic range dynamics in a phylogenetic context, molecular estimation of lineage divergence times, and modeling lineage birth and death. These are enabling greater insights into patterns of organismal diversification in time and space. In the next decade, analytical challenges are emerging on several fronts. For example, phylogenies are increasing in size and taxonomic breadth and new sequencing technologies enabling phylogenetic and phylogeographic datasets are increasingly genomic in depth. In addition, geographic occurrence data are accumulating in online repositories, yet tools for data mining and synthetic analysis are lacking for comparative multi‐lineage studies. Biogeography is thus entering an era characterized by phylogenomic datasets, increasingly comprehensive sampling of clades, and interdisciplinary synthesis. We anticipate continued progress in our understanding of biodiversity patterns at regional and global scales, but this will likely require greater collaboration with specialists in bioinformatics and computational science. Finally, it is clear that biogeography has an increasingly important role to play in the discovery and conservation of biodiversity. Lessons learned from biogeographic studies of islands are being applied to better understand extinction dynamics as continental ecosystems become more fragmented, and phylogeography and ecological niche modeling offer innovative paths toward the discovery of previously unknown species distributions and priority areas for conservation. The future of biogeography is bright and filled with exciting challenges and opportunities.

Graph hierarchies for phylogeography

Bayesian phylogeographic methods simultaneously integrate geographical and evolutionary modelling, and have demonstrated value in assessing spatial spread patterns of measurably evolving organisms. We improve on existing phylogeographic methods by combining information from multiple phylogeographic datasets in a hierarchical setting. Consider N exchangeable datasets or strata consisting of viral sequences and locations, each evolving along its own phylogenetic tree and according to a conditionally independent geographical process. At the hierarchical level, a random graph summarizes the overall dispersion process by informing which migration rates between sampling locations are likely to be relevant in the strata. This approach provides an efficient and improved framework for analysing inherently hierarchical datasets. We first examine the evolutionary history of multiple serotypes of dengue virus in the Americas to showcase our method. Additionally, we explore an application to intrahost HIV evolution across multiple patients.

Methodological framework for projecting the potential loss of intraspecific genetic diversity due to global climate change.

BackgroundWhile research on the impact of global climate change (GCC) on ecosystems and species is flourishing, a fundamental component of biodiversity – molecular variation – has not yet received its due attention in such studies. Here we present a methodological framework for projecting the loss of intraspecific genetic diversity due to GCC.MethodsThe framework consists of multiple steps that combines 1) hierarchical genetic clustering methods to define comparable units of inference, 2) species accumulation curves (SAC) to infer sampling completeness, and 3) species distribution modelling (SDM) to project the genetic diversity loss under GCC. We suggest procedures for existing data sets as well as specifically designed studies. We illustrate the approach with two worked examples from a land snail (Trochulus villosus) and a caddisfly (Smicridea (S.) mucronata).ResultsSampling completeness was diagnosed on the third coarsest haplotype clade level for T. villosus and the second coarsest for S. mucronata. For both species, a substantial species range loss was projected under the chosen climate scenario. However, despite substantial differences in data set quality concerning spatial sampling and sampling depth, no loss of haplotype clades due to GCC was predicted for either species.ConclusionsThe suggested approach presents a feasible method to tap the rich resources of existing phylogeographic data sets and guide the design and analysis of studies explicitly designed to estimate the impact of GCC on a currently still neglected level of biodiversity.

Lizards as model organisms for linking phylogeographic and speciation studies

Lizards have been model organisms for ecological and evolutionary studies from individual to community levels at multiple spatial and temporal scales. Here we highlight lizards as models for phylogeographic studies, review the published population genetics/phylogeography literature to summarize general patterns and trends and describe some studies that have contributed to conceptual advances. Our review includes 426 references and 452 case studies: this literature reflects a general trend of exponential growth associated with the theoretical and empirical expansions of the discipline. We describe recent lizard studies that have contributed to advances in understanding of several aspects of phylogeography, emphasize some linkages between phylogeography and speciation and suggest ways to expand phylogeographic studies to test alternative pattern-based modes of speciation. Allopatric speciation patterns can be tested by phylogeographic approaches if these are designed to discriminate among four alternatives based on the role of selection in driving divergence between populations, including: (i) passive divergence by genetic drift; (ii) adaptive divergence by natural selection (niche conservatism or ecological speciation); and (iii) socially-mediated speciation. Here we propose an expanded approach to compare patterns of variation in phylogeographic data sets that, when coupled with morphological and environmental data, can be used to to discriminate among these alternative speciation patterns. [Correction made after online publication (28/07/2010): (minor deletion in the last line of the abstract)].

Testing comparative phylogeographic models of marine vicariance and dispersal using a hierarchical Bayesian approach.

BackgroundMarine allopatric speciation is an enigma because pelagic larval dispersal can potentially connect disjunct populations thereby preventing reproductive and morphological divergence. Here we present a new hierarchical approximate Bayesian computation model (HABC) that tests two hypotheses of marine allopatric speciation: 1.) "soft vicariance", where a speciation involves fragmentation of a large widespread ancestral species range that was previously connected by long distance gene flow; and 2.) peripatric colonization, where speciations in peripheral archipelagos emerge from sweepstakes colonizations from central source regions. The HABC approach analyzes all the phylogeographic datasets at once in order to make across taxon-pair inferences about biogeographic processes while explicitly allowing for uncertainty in the demographic differences within each taxon-pair. Our method uses comparative phylogeographic data that consists of single locus mtDNA sequences from multiple co-distributed taxa containing pairs of central and peripheral populations. We use the method on two comparative phylogeographic data sets consisting of cowrie gastropod endemics co-distributed in the Hawaiian (11 taxon-pairs) and Marquesan archipelagos (7 taxon-pairs).ResultsGiven the Marquesan data, we find strong evidence of simultaneous colonization across all seven cowrie gastropod endemics co-distributed in the Marquesas. In contrast, the lower sample sizes in the Hawaiian data lead to greater uncertainty associated with the Hawaiian estimates. Although, the hyper-parameter estimates point to soft vicariance in a subset of the 11 Hawaiian taxon-pairs, the hyper-prior and hyper-posterior are too similar to make a definitive conclusion. Both results are not inconsistent with what is known about the geologic history of the archipelagos. Simulations verify that our method can successfully distinguish these two histories across a wide range of conditions given sufficient sampling.ConclusionAlthough soft vicariance and colonization are likely to produce similar genetic patterns when a single taxon-pair is used, our hierarchical Bayesian model can potentially detect if either history is a dominant process across co-distributed taxon-pairs. As comparative phylogeographic datasets grow to include > 100 co-distributed taxon-pairs, the HABC approach will be well suited to dissect temporal patterns in community assembly and evolution, thereby providing a bridge linking comparative phylogeography with community ecology.

The coup de grâce for the nested clade phylogeographic analysis?

Nested clade phylogeographic analysis (NCPA) has become a popular method for reconstructing the history of populations across species ranges. Ever since its invention in 1995, criticisms have been formulated, but the method, which has been regularly updated, continues to attract investigators. Molecular Ecology has published a large fraction of the literature on the topic--both pro and con. A recent study by Panchal and Beaumont (2007) finally allows a precise evaluation of the method by developing software that automates the somewhat complicated NCPA procedure. Using simulations of random-mating populations, Panchal and Beaumont find a high frequency of false-positives with their automated NCPA procedure (over 75%). These findings, which echo and amplify earlier warnings, appear serious enough to suggest to researchers to await further evaluation of the method. Although no other all-encompassing method such as the NCAP currently exists to evaluate phylogeographic data sets, researchers have many alternative methods to test ever more refined hypotheses.

Comparative phylogeographic summary statistics for testing simultaneous vicariance

Testing for simultaneous vicariance across comparative phylogeographic data sets is a notoriously difficult problem hindered by mutational variance, the coalescent variance, and variability across pairs of sister taxa in parameters that affect genetic divergence. We simulate vicariance to characterize the behaviour of several commonly used summary statistics across a range of divergence times, and to characterize this behaviour in comparative phylogeographic datasets having multiple taxon-pairs. We found Tajima's D to be relatively uncorrelated with other summary statistics across divergence times, and using simple hypothesis testing of simultaneous vicariance given variable population sizes, we counter-intuitively found that the variance across taxon pairs in Nei and Li's net nucleotide divergence (pi(net)), a common measure of population divergence, is often inferior to using the variance in Tajima's D across taxon pairs as a test statistic to distinguish ancient simultaneous vicariance from variable vicariance histories. The opposite and more intuitive pattern is found for testing more recent simultaneous vicariance, and overall we found that depending on the timing of vicariance, one of these two test statistics can achieve high statistical power for rejecting simultaneous vicariance, given a reasonable number of intron loci (> 5 loci, 400 bp) and a range of conditions. These results suggest that components of these two composite summary statistics should be used in future simulation-based methods which can simultaneously use a pool of summary statistics to test comparative the phylogeographic hypotheses we consider here.

Congruence, Consensus, and the Comparative Phylogeography of Codistributed Species in California

Comparative phylogeography has emerged as a means of understanding the spatial patterns of genetic divergence of codistributed species. However, researchers are often frustrated because of the lack of appropriate statistical tests to assess concordancy of multiple phylogeographic trees. We develop a method for testing congruence across multiple species and synthesizing the data into a regional supertree. Nine phylogeographic data sets of species with different life histories and ecologies were statistically compared using maximum agreement subtrees (MAST) and showed a high degree of concordancy. A supertree combining the different phylogeographic trees was then computed using matrix representation with parsimony, and the groups defined by this supertree were tested against climatic data to investigate a potential mechanism driving divergence. Our data suggest that species and genetic lineages in California are shaped by climatic regimes. The supertree method in combination with MAST represents a new approach to test congruence hypotheses and detect common geographic signals in comparative phylogeography.