Bryan C. Carstens

Delimiting Species without Monophyletic Gene Trees

Genetic data are frequently used to delimit species, where species status is determined on the basis of an exclusivity criterium, such as reciprocal monophyly. Not only are there numerous empirical examples of incongruence between the boundaries inferred from such data compared to other sources like morphology -- especially with recently derived species, but population genetic theory also clearly shows that an inevitable bias in species status results because genetic thresholds do not explicitly take into account how the timing of speciation influences patterns of genetic differentiation. This study represents a fundamental shift in how genetic data might be used to delimit species. Rather than equating gene trees with a species tree or basing species status on some genetic threshold, the relationship between the gene trees and the species history is modeled probabilistically. Here we show that the same theory that is used to calculate the probability of reciprocal monophyly can also be used to delimit species despite widespread incomplete lineage sorting. The results from a preliminary simulation study suggest that very recently derived species can be accurately identified long before the requisite time for reciprocal monophyly to be achieved following speciation. The study also indicates the importance of sampling, both with regards to loci and individuals. Withstanding a thorough investigation into the conditions under which the coalescent-based approach will be effective, namely how the timing of divergence relative to the effective population size of species affects accurate species delimitation, the results are nevertheless consistent with other recent studies (aimed at inferring species relationships), showing that despite the lack of monophyletic gene trees, a signal of species divergence persists and can be extracted. Using an explicit model-based approach also avoids two primary problems with species delimitation that result when genetic thresholds are applied with genetic data -- the inherent biases in species detection arising from when and how speciation occurred, and failure to take into account the high stochastic variance of genetic processes. Both the utility and sensitivities of the coalescent-based approach outlined here are discussed; most notably, a model-based approach is essential for determining whether incompletely sorted gene lineages are (or are not) consistent with separate species lineages, and such inferences require accurate model parameterization (i.e., a range of realistic effective population sizes relative to potential times of divergence for the purported species). It is the goal (and motivation of this study) that genetic data might be used effectively as a source of complementation to other sources of data for diagnosing species, as opposed to the exclusion of other evidence for species delimitation, which will require an explicit consideration of the effects of the temporal dynamic of lineage splitting on genetic data.

How to fail at species delimitation

Species delimitation is the act of identifying species‐level biological diversity. In recent years, the field has witnessed a dramatic increase in the number of methods available for delimiting species. However, most recent investigations only utilize a handful (i.e. 2–3) of the available methods, often for unstated reasons. Because the parameter space that is potentially relevant to species delimitation far exceeds the parameterization of any existing method, a given method necessarily makes a number of simplifying assumptions, any one of which could be violated in a particular system. We suggest that researchers should apply a wide range of species delimitation analyses to their data and place their trust in delimitations that are congruent across methods. Incongruence across the results from different methods is evidence of either a difference in the power to detect cryptic lineages across one or more of the approaches used to delimit species and could indicate that assumptions of one or more of the methods have been violated. In either case, the inferences drawn from species delimitation studies should be conservative, for in most contexts it is better to fail to delimit species than it is to falsely delimit entities that do not represent actual evolutionary lineages.

STEM: species tree estimation using maximum likelihood for gene trees under coalescence

UNLABELLED STEM is a software package written in the C language to obtain maximum likelihood (ML) estimates for phylogenetic species trees given a sample of gene trees under the coalescent model. It includes options to compute the ML species tree, search the space of all species trees for the k trees of highest likelihood and compute ML branch lengths for a user-input species tree. AVAILABILITY The STEM package, including source code, is freely available at http://www.stat.osu.edu/~lkubatko/software/STEM/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Applications of next-generation sequencing to phylogeography and phylogenetics

This is a time of unprecedented transition in DNA sequencing technologies. Next-generation sequencing (NGS) clearly holds promise for fast and cost-effective generation of multilocus sequence data for phylogeography and phylogenetics. However, the focus on non-model organisms, in addition to uncertainty about which sample preparation methods and analyses are appropriate for different research questions and evolutionary timescales, have contributed to a lag in the application of NGS to these fields. Here, we outline some of the major obstacles specific to the application of NGS to phylogeography and phylogenetics, including the focus on non-model organisms, the necessity of obtaining orthologous loci in a cost-effective manner, and the predominate use of gene trees in these fields. We describe the most promising methods of sample preparation that address these challenges. Methods that reduce the genome by restriction digest and manual size selection are most appropriate for studies at the intraspecific level, whereas methods that target specific genomic regions (i.e., target enrichment or sequence capture) have wider applicability from the population level to deep-level phylogenomics. Additionally, we give an overview of how to analyze NGS data to arrive at data sets applicable to the standard toolkit of phylogeography and phylogenetics, including initial data processing to alignment and genotype calling (both SNPs and loci involving many SNPs). Even though whole-genome sequencing is likely to become affordable rather soon, because phylogeography and phylogenetics rely on analysis of hundreds of individuals in many cases, methods that reduce the genome to a subset of loci should remain more cost-effective for some time to come.

Estimating Species Phylogeny from Gene-Tree Probabilities Despite Incomplete Lineage Sorting: An Example from Melanoplus Grasshoppers

Estimating phylogenetic relationships among closely related species can be extremely difficult when there is incongruence among gene trees and between the gene trees and the species tree. Here we show that incorporating a model of the stochastic loss of gene lineages by genetic drift into the phylogenetic estimation procedure can provide a robust estimate of species relationships, despite widespread incomplete sorting of ancestral polymorphism. This approach is applied to a group of montane Melanoplus grasshoppers for which genealogical discordance among loci and incomplete lineage sorting obscures any obvious phylogenetic relationships among species. Unlike traditional treatments where gene trees estimated using standard phylogenetic methods are implicitly equated with the species tree, with the coalescent-based approach the species tree is modeled probabilistically from the estimated gene trees. The estimated species phylogeny (the ESP) is calculated for the grasshoppers from multiple gene trees reconstructed for nuclear loci and a mitochondrial gene. This empirical application is coupled with a simulation study to explore the performance of the coalescent-based approach. Specifically, we test the accuracy of the ESP given the data based on analyses of simulated data matching the multilocus data collected in Melanoplus (i.e., data were simulated for each locus with the same number of base pairs and locus-specific mutational models). The results of the study show that ESPs can be computed using the coalescent-based approach long before reciprocal monophyly has been achieved, and that these statistical estimates are accurate. This contrasts with analyses of the empirical data collected in Melanoplus and simulated data based on concatenation of multiple loci, for which the incomplete lineage sorting of recently diverged species posed significant problems. The strengths and potential challenges associated with incorporating an explicit model of gene-lineage coalescence into the phylogenetic procedure to obtain an ESP, as illustrated by application to Melanoplus, versus concatenation and consensus approaches are discussed. This study represents a fundamental shift in how species relationships are estimated - the relationship between the gene trees and the species phylogeny is modeled probabilistically rather than equating gene trees with a species tree.

INTEGRATING COALESCENT AND ECOLOGICAL NICHE MODELING IN COMPARATIVE PHYLOGEOGRAPHY

Abstract Understanding the factors that contribute to the formation of population genetic structure is a central goal of phylogeographic research, but achieving this goal can be complicated by the stochastic variance inherent to genetic processes. Statistical approaches to testing phylogeographic hypotheses accommodate this stochasticity by evaluating competing models of putative historical population structure, often by simulating null distributions of the expected variance. The effectiveness of these tests depends on the biological realism of the models. Information from the fossil record can aid in reconstructing the historical distributions of some taxa. However, for the majority of taxa, which lack sufficient fossils, paleodistributional modeling can provide valuable spatial-geographic data concerning ancestral distributions. Paleodistributional models are generated by projecting ecological niche models, which predict the current distribution of each species, onto a model of past climatic conditions. Here, we generate paleodistributional models describing the suitable habitat during the last glacial maximum for lineages from the mesic forests of the Pacific Northwest of North America, and use these models to generate alternative phylogeographic hypotheses. Coalescent simulations are then used to test these hypotheses to improve our understanding of the historical events that promoted the formation of population genetic structure in this ecosystem. Results from Pacific Northwest mesic forest organisms demonstrate the utility of these combined approaches. Paleodistribution models and population genetic structure are congruent across three amphibian lineages, suggesting that they have responded in a concerted manner to environmental change. Two other species, a willow and a water vole, despite being currently codistributed and having similar population genetic structure, were predicted by the paleodistributional model to have had markedly different distributions during the last glacial maximum. This suggests that congruent phylogeographic patterns can arise from incongruent ancestral distributions. Paleodistributional models introduce a much-needed spatial-geographic perspective to statistical phylogeography. In conjunction with coalescent models of population genetic structure, they have the potential to improve our understanding of the factors that promote population divergence and ultimately produce regional patterns of biodiversity.

Phylogenetic estimation error can decrease the accuracy of species delimitation: a Bayesian implementation of the general mixed Yule-coalescent model

BackgroundSpecies are considered the fundamental unit in many ecological and evolutionary analyses, yet accurate, complete, accessible taxonomic frameworks with which to identify them are often unavailable to researchers. In such cases DNA sequence-based species delimitation has been proposed as a means of estimating species boundaries for further analysis. Several methods have been proposed to accomplish this. Here we present a Bayesian implementation of an evolutionary model-based method, the general mixed Yule-coalescent model (GMYC). Our implementation integrates over the parameters of the model and uncertainty in phylogenetic relationships using the output of widely available phylogenetic models and Markov-Chain Monte Carlo (MCMC) simulation in order to produce marginal probabilities of species identities.ResultsWe conducted simulations testing the effects of species evolutionary history, levels of intraspecific sampling and number of nucleotides sequenced. We also re-analyze the dataset used to introduce the original GMYC model. We found that the model results are improved with addition of DNA sequence and increased sampling, although these improvements have limits. The most important factor in the success of the model is the underlying phylogenetic history of the species under consideration. Recent and rapid divergences result in higher amounts of uncertainty in the model and eventually cause the model to fail to accurately assess uncertainty in species limits.ConclusionOur results suggest that the GMYC model can be useful under a wide variety of circumstances, particularly in cases where divergences are deeper, or taxon sampling is incomplete, as in many studies of ecological communities, but that, in accordance with expectations from coalescent theory, rapid, recent radiations may yield inaccurate results. Our implementation differs from existing ones in two ways: it allows for the accounting for important sources of uncertainty in the model (phylogenetic and in parameters specific to the model) and in the specification of informative prior distributions that can increase the precision of the model. We have incorporated this model into a user-friendly R package available on the authors’ websites.

INVESTIGATING THE EVOLUTIONARY HISTORY OF THE PACIFIC NORTHWEST MESIC FOREST ECOSYSTEM: HYPOTHESIS TESTING WITHIN A COMPARATIVE PHYLOGEOGRAPHIC FRAMEWORK

Abstract We examine the evolution of mesic forest ecosystems in the Pacific Northwest of North America using a statistical phylogeography approach in four animal and two plant lineages. Three a priori hypotheses, which explain the disjunction in the mesic forest ecosystem with either recent dispersal or ancient vicariance, are tested with phylogenetic and coalescent methods. We find strong support in three amphibian lineages (Ascaphus spp., and Dicampton spp., and Plethodon vandykei and P. idahoensis) for deep divergence between coastal and inland populations, as predicted by the ancient vicariance hypothesis. Unlike the amphibians, the disjunction in other Pacific Northwest lineages is likely due to recent dispersal along a northern route. Topological and population divergence tests support the northern dispersal hypothesis in the water vole (Microtus richardsoni) and northern dispersal has some support in both the dusky willow (Salix melanopsis) and whitebark pine (Pinus albicaulis). These analyses demonstrate that genetic data sampled from across an ecosystem can provide insight into the evolution of ecological communities and suggest that the advantages of a statistical phylogeographic approach are most pronounced in comparisons across multiple taxa in a particular ecosystem. Genetic patterns in organisms as diverse as willows and salamanders can be used to test general regional hypotheses, providing a consistent metric for comparison among members of an ecosystem with disparate life‐history traits.

Shifting distributions and speciation: species divergence during rapid climate change

Questions about how shifting distributions contribute to species diversification remain virtually without answer, even though rapid climate change during the Pleistocene clearly impacted genetic variation within many species. One factor that has prevented this question from being adequately addressed is the lack of precision associated with estimates of species divergence made from a single genetic locus and without incorporating processes that are biologically important as populations diverge. Analysis of DNA sequences from multiple variable loci in a coalescent framework that (i) corrects for gene divergence pre‐dating speciation, and (ii) derives divergence‐time estimates without making a priori assumptions about the processes underlying patterns of incomplete lineage sorting between species (i.e. allows for the possibility of gene flow during speciation), is critical to overcoming the inherent logistical and analytical difficulties of inferring the timing and mode of speciation during the dynamic Pleistocene. Estimates of species divergence that ignore these processes, use single locus data, or do both can dramatically overestimate species divergence. For example, using a coalescent approach with data from six loci, the divergence between two species of montane Melanoplus grasshoppers is estimated at between 200 000 and 300 000 years before present, far more recently than divergence estimates made using single‐locus data or without the incorporation of population‐level processes. Melanoplus grasshoppers radiated in the sky islands of the Rocky Mountains, and the analysis of divergence between these species suggests that the isolation of populations in multiple glacial refugia was an important factor in promoting speciation. Furthermore, the low estimates of gene flow between the species indicate that reproductive isolation must have evolved rapidly for the incipient species boundaries to be maintained through the subsequent glacial periods and shifts in species distributions.

SpedeSTEM: a rapid and accurate method for species delimitation

We describe a software package (SpedeSTEM) that allows researchers to conduct a species delimitation analysis using intraspecific genetic data. Our method operates under the assumption that a priori information regarding group membership is available, for example that samples are drawn from some number of described subspecies, races or distinct morphotypes. SpedeSTEM proceeds by calculating the maximum likelihood species tree from all hierarchical arrangements of the sampled alleles and uses information theory to quantify the model probability of each permutation. SpedeSTEM is tested here against empirical and simulated data; results indicate that evolutionary lineages that diverged as few as 0.5N generations in the past can be validated as distinct using sequence data from little as five loci. This work enables speciation investigations to identify lineages that are evolutionarily distinct and thus have the potential to form new species before these lineages acquire secondary characteristics such as reproductive isolation or morphological differentiation that are commonly used to define species.