Phylogenetic biogeography inference using dynamic paleogeography models and explicit geographic ranges.

To model distribution ranges, the most popular methods of phylogenetic biogeography divide Earth into a handful of predefined areas. Other methods use explicit geographic ranges, but unfortunately, these methods assume a static Earth, ignoring the effects of plate tectonics and the changes in the landscape. To address this limitation, I propose a method that uses explicit geographic ranges and incorporates a plate motion model and a paleolandscape model directly derived from the models used by geologists in their tectonic and paleogeographic reconstructions. The underlying geographic model is a high-resolution pixelation of a spherical Earth. Biogeographic inference is based on diffusion, approximates the effects of the landscape, uses a time-stratified model to take into account the geographic changes, and directly integrates over all probable histories. By using a simplified stochastic mapping algorithm, it is possible to infer the ancestral locations as well as the distance traveled by the ancestral lineages. For illustration, I applied the method to an empirical phylogeny of the Sapindaceae plants. This example shows that methods based on explicit geographic data, coupled with high-resolution paleogeographic models, can provide detailed reconstructions of the ancestral areas but also include inferences about the probable dispersal paths and diffusion speed across the taxon history. The method is implemented in the program PhyGeo.

Historical biogeography of the Neotropical noctilionoid bats (Chiroptera: Noctilionoidea), revisited through a geographically explicit analysis.

Biogeographic studies have generally relied on methods that use a few, large predefined areas, which may overlook fine-scale patterns. Here we test previous hypotheses about the biogeographic history of a diverse bat clade regarding its association with major Neotropical geological formations, particularly the Antilles, the South American Dry Diagonal, the Andes and the Panamanian land bridge, by applying a recently available method that uses actual distributions instead of predefined areas. We compiled and curated spatially explicit, georeferenced data of 173 bat species (Mammalia: Chiroptera: Noctilionoidea) from the online database Global Biodiversity Information Facility. By taking a previous comprehensive phylogeny as an evolutionary framework, we performed computationally intensive analyses using the Geographically-explicit Event Model. This method uses the observed species distributions to reconstruct the ancestral areas and biogeographic events at each phylogeny node. We found that sympatric speciation was the most frequently reconstructed event, and involved mainly the Panamanian Isthmus and northern South America (SA), but all sympatry reconstructions were different and specific to each node. Allopatric events were important in the Andes; vicariance caused both west/east and north/south disjunctions that went unnoticed previously. Founder events indicated bidirectional dispersal between the mainland and the Antilles since the Miocene, and across the incomplete Panamanian bridge and the SA Dry Diagonal since the early Pliocene. Overall, we found support for previous hypotheses on the influence of major Neotropical paleogeographic events in the diversification of the group, but additionally revealed multi-scale patterns that are embedded within the mainland and were previously overlooked. Our results highlight a trans-isthmian centre of diversification in the biogeographic history of Noctilionoidea including the Panamanian Isthmus and Northern SA.

Likelihood approximations of implied weights parsimony can be selected over the Mk model by the Akaike information criterion.

A likelihood method that approximates the behaviour of implied weighting is described. This approach provides a likelihood perspective on several aspects of implied weighting, such as guidance for the choice of concavity values, a justification to use different concavities for different numbers of taxa, and a natural basis for extended implied weighting. In this approach, the number of free parameters in the estimation depends on C, the number of characters (in contrast to the standard Mk model, which estimates 2T-3 parameters for T taxa). Depending on the characteristics of the dataset, the likelihood obtained with this approach may in some cases be similar or superior to that of the Mk model, but with fewer parameters being adjusted. Because of that tradeoff, testing against the Mk model by means of the Akaike information criterion on a set of 182 morphological datasets indicated many cases (36) in which the likelihood approximation to implied weighting is the best method, from an information-theoretic point of view. Given that it is expected to produce (almost) the same results as this maximum-likelihood approximation, implied weighting can therefore be seen as a valid alternative to the Mk model often used for morphological datasets, on the basis of a criterion for model fit widely advocated by likelihoodists.

Weighted parsimony outperforms other methods of phylogenetic inference under models appropriate for morphology.

One of the lasting controversies in phylogenetic inference is the degree to which specific evolutionary models should influence the choice of methods. Model-based approaches to phylogenetic inference (likelihood, Bayesian) are defended on the premise that without explicit statistical models there is no science, and parsimony is defended on the grounds that it provides the best rationalization of the data, while refraining from assigning specific probabilities to trees or character-state reconstructions. Authors who favour model-based approaches often focus on the statistical properties of the methods and models themselves, but this is of only limited use in deciding the best method for phylogenetic inference-such decision also requires considering the conditions of evolution that prevail in nature. Another approach is to compare the performance of parsimony and model-based methods in simulations, which traditionally have been used to defend the use of models of evolution for DNA sequences. Some recent papers, however, have promoted the use of model-based approaches to phylogenetic inference for discrete morphological data as well. These papers simulated data under models already known to be unfavourable to parsimony, and modelled morphological evolution as if it evolved just like DNA, with probabilities of change for all characters changing in concert along tree branches. The present paper discusses these issues, showing that under reasonable and less restrictive models of evolution for discrete characters, equally weighted parsimony performs as well or better than model-based methods, and that parsimony under implied weights clearly outperforms all other methods.

Profile Parsimony (PP): an analysis under Implied Weights (IW).

Faith and Trueman [Syst. Biol. (2001) 331] recently proposed "Profile Parsimony" (PP) as a new form of phylogenetic analysis, but it is equivalent to the Implied Weights (IW) method when certain functions are used. The PP method cannot accommodate missing/inapplicable cells and/or multistate characters. Finally we demonstrate that, as defined, PP scores are not random, and there is no need to generate random trees as proposed by Faith and Trueman.