Jamie R. Oaks

A TIME-CALIBRATED SPECIES TREE OF CROCODYLIA REVEALS A RECENT RADIATION OF THE TRUE CROCODILES

True crocodiles (Crocodylus) are the most broadly distributed, ecologically diverse, and species‐rich crocodylian genus, comprising about half of extant crocodylian diversity and exhibiting a circumtropical distribution. Crocodylus traditionally has been viewed as an ancient group of morphologically conserved species that originated in Africa prior to continental breakup. In this study, these long‐held notions about the temporal and geographic origin of Crocodylus are tested using DNA sequence data of 10 loci from 76 individuals representing all 23 crocodylian species. I infer a time‐calibrated species tree of all Crocodylia and estimate the spatial pattern of diversification within Crocodylus. For the first time, a fully resolved phylogenetic estimate of all Crocodylia is well‐supported. The results overturn traditional views of the evolution of Crocodylus by demonstrating that the true crocodiles are not “living‐fossils” that originated in Africa. Rather, Crocodylus originated from an ancestor in the tropics of the Late Miocene Indo‐Pacific, and rapidly radiated and dispersed around the globe during a period marked by mass extinctions of fellow crocodylians. The findings also reveal more diversity within the genus than is recognized by current taxonomy.

Phylogeny and biogeography of Philippine bent-toed geckos (Gekkonidae: Cyrtodactylus) contradict a prevailing model of Pleistocene diversification.

In the Philippines, Pleistocene sea level oscillations repeatedly connected and isolated neighboring islands. Hence, an understanding of the island platforms adjoined during periods of low sea level has led biologists to a suite of expectations that, taken together, represent a paradigm for the process of recent diversification in southeast Asia. We employ statistical tests of phylogenetic topology and population genetic analyses of widespread species of bent-toed geckos (Cyrtodactylus) to ascertain whether patterns of inter- and intra-specific diversity can be explained by a Pleistocene aggregate island model of diversification. Contrary to many classic studies of Philippine vertebrates, we find complex patterns that are only partially explained by past island connectivity. In particular, we determine that some populations inhabiting previously united island groups show substantial genetic divergence and are inferred to be polyphyletic. Additionally, greater genetic diversity is found within islands, than between them. Among the topological patterns inconsistent with the Pleistocene model, we note some similarities with other lineages, but no obviously shared causal mechanisms are apparent. Finally, we infer well-supported discordance between the gene trees inferred from mitochondrial and nuclear DNA sequences of two species, which we suspect is the result of incomplete lineage sorting. This study contributes to a nascent body of literature suggesting that the current paradigm for Philippine biogeography is an oversimplification requiring revision.

EVIDENCE FOR CLIMATE‐DRIVEN DIVERSIFICATION? A CAUTION FOR INTERPRETING ABC INFERENCES OF SIMULTANEOUS HISTORICAL EVENTS

Approximate Bayesian computation (ABC) is rapidly gaining popularity in population genetics. One example, msBayes, infers the distribution of divergence times among pairs of taxa, allowing phylogeographers to test hypotheses about historical causes of diversification in co‐distributed groups of organisms. Using msBayes, we infer the distribution of divergence times among 22 pairs of populations of vertebrates distributed across the Philippine Archipelago. Our objective was to test whether sea‐level oscillations during the Pleistocene caused diversification across the islands. To guide interpretation of our results, we perform a suite of simulation‐based power analyses. Our empirical results strongly support a recent simultaneous divergence event for all 22 taxon pairs, consistent with the prediction of the Pleistocene‐driven diversification hypothesis. However, our empirical estimates are sensitive to changes in prior distributions, and our simulations reveal low power of the method to detect random variation in divergence times and bias toward supporting clustered divergences. Our results demonstrate that analyses exploring power and prior sensitivity should accompany ABC model selection inferences. The problems we identify are potentially mitigable with uniform priors over divergence models (rather than classes of models) and more flexible prior distributions on demographic and divergence‐time parameters.

Multilocus phylogeny and Bayesian estimates of species boundaries reveal hidden evolutionary relationships and cryptic diversity in Southeast Asian monitor lizards

Recent conceptual, technological and methodological advances in phylogenetics have enabled increasingly robust statistical species delimitation in studies of biodiversity. As the variety of evidence purporting species diversity has increased, so too have the kinds of tools and inferential power of methods for delimiting species. Here, we showcase an organismal system for a data‐rich, comparative molecular approach to evaluating strategies of species delimitation among monitor lizards of the genus Varanus. The water monitors (Varanus salvator Complex), a widespread group distributed throughout Southeast Asia and southern India, have been the subject of numerous taxonomic treatments, which have drawn recent attention due to the possibility of undocumented species diversity. To date, studies of this group have relied on purportedly diagnostic morphological characters, with no attention given to the genetic underpinnings of species diversity. Using a 5‐gene data set, we estimated phylogeny and used multilocus genetic networks, analysis of population structure and a Bayesian coalescent approach to infer species boundaries. Our results contradict previous systematic hypotheses, reveal surprising relationships between island and mainland lineages and uncover novel, cryptic evolutionary lineages (i.e. new putative species). Our study contributes to a growing body of literature suggesting that, used in concert with other sources of data (e.g. morphology, ecology, biogeography), multilocus genetic data can be highly informative to systematists and biodiversity specialists when attempting to estimate species diversity and identify conservation priorities. We recommend holding in abeyance taxonomic decisions until multiple, converging lines of evidence are available to best inform taxonomists, evolutionary biologists and conservationists.

An improved approximate-Bayesian model-choice method for estimating shared evolutionary history

BackgroundTo understand biological diversification, it is important to account for large-scale processes that affect the evolutionary history of groups of co-distributed populations of organisms. Such events predict temporally clustered divergences times, a pattern that can be estimated using genetic data from co-distributed species. I introduce a new approximate-Bayesian method for comparative phylogeographical model-choice that estimates the temporal distribution of divergences across taxa from multi-locus DNA sequence data. The model is an extension of that implemented in msBayes.ResultsBy reparameterizing the model, introducing more flexible priors on demographic and divergence-time parameters, and implementing a non-parametric Dirichlet-process prior over divergence models, I improved the robustness, accuracy, and power of the method for estimating shared evolutionary history across taxa.ConclusionsThe results demonstrate the improved performance of the new method is due to (1) more appropriate priors on divergence-time and demographic parameters that avoid prohibitively small marginal likelihoods for models with more divergence events, and (2) the Dirichlet-process providing a flexible prior on divergence histories that does not strongly disfavor models with intermediate numbers of divergence events. The new method yields more robust estimates of posterior uncertainty, and thus greatly reduces the tendency to incorrectly estimate models of shared evolutionary history with strong support.

The roles of history and ecology in chloroplast phylogeographic patterns of the bird-dispersed plant parasite Phoradendron californicum (Viscaceae) in the Sonoran Desert

UNLABELLED • PREMISE OF THE STUDY A recurrent explanation for phylogeographic discontinuities in the Baja California Peninsula and the Sonoran Desert Region has been the association of vicariant events with Pliocene and Pleistocene seaway breaks. Nevertheless, despite its relevance for plant dispersal, other explanations such as ecological and paleoclimatic factors have received little attention. Here, we analyzed the role of several of these factors to describe the phylogeographic patterns of the desert mistletoe, Phoradendron californicum.• METHODS Using noncoding chloroplast regions, we assess the marginal probability of 19 a priori hypotheses related to geological and ecological factors to predict the cpDNA variation in P. californicum using a Bayesian coalescent framework. Complementarily, we used the macrofossil record and niche model projections on Last Glacial Maximum climatic conditions for hosts, mistletoe, and a bird specialist to interpret phylogeographic patterns.• KEY RESULTS Genealogical reconstructions revealed five clades, which suggest a combination of cryptic divergence, long-distance seed dispersal, and isolating postdivergence events. Bayesian hypothesis test favored a series of Pliocene and Pleistocene geological events related to the formation of the Baja California Peninsula and seaways across the peninsula as the most supported explanation for this genealogical pattern. However, age estimates, niche projections, and fossil records show dynamic host-mistletoe interactions and evidence of host races, indicating that ecological and geological factors have been interacting during the formation and structuring of phylogeographic divergence.• CONCLUSIONS Variation in cpDNA across the species range results from the interplay of vicariant events, past climatic oscillations, and more dynamic factors related to ecological processes at finer temporal and spatial scales.

Implications of uniformly distributed, empirically informed priors for phylogeographical model selection: A reply to Hickerson et al.

Establishing that a set of population‐splitting events occurred at the same time can be a potentially persuasive argument that a common process affected the populations. Recently, Oaks et al. ( ) assessed the ability of an approximate‐Bayesian model‐choice method (msBayes) to estimate such a pattern of simultaneous divergence across taxa, to which Hickerson et al. ( ) responded. Both papers agree that the primary inference enabled by the method is very sensitive to prior assumptions and often erroneously supports shared divergences across taxa when prior uncertainty about divergence times is represented by a uniform distribution. However, the papers differ about the best explanation and solution for this problem. Oaks et al. ( ) suggested the methods behavior was caused by the strong weight of uniformly distributed priors on divergence times leading to smaller marginal likelihoods (and thus smaller posterior probabilities) of models with more divergence‐time parameters (Hypothesis 1); they proposed alternative prior probability distributions to avoid such strongly weighted posteriors. Hickerson et al. ( ) suggested numerical‐approximation error causes msBayes analyses to be biased toward models of clustered divergences because the methods rejection algorithm is unable to adequately sample the parameter space of richer models within reasonable computational limits when using broad uniform priors on divergence times (Hypothesis 2). As a potential solution, they proposed a model‐averaging approach that uses narrow, empirically informed uniform priors. Here, we use analyses of simulated and empirical data to demonstrate that the approach of Hickerson et al. ( ) does not mitigate the methods tendency to erroneously support models of highly clustered divergences, and is dangerous in the sense that the empirically derived uniform priors often exclude from consideration the true values of the divergence‐time parameters. Our results also show that the tendency of msBayes analyses to support models of shared divergences is primarily due to Hypothesis 1, whereas Hypothesis 2 is an untenable explanation for the bias. Overall, this series of papers demonstrates that if our prior assumptions place too much weight in unlikely regions of parameter space such that the exact posterior supports the wrong model of evolutionary history, no amount of computation can rescue our inference. Fortunately, as predicted by fundamental principles of Bayesian model choice, more flexible distributions that accommodate prior uncertainty about parameters without placing excessive weight in vast regions of parameter space with low likelihood increase the methods robustness and power to detect temporal variation in divergences.