Phylogenetic comparative methods and the geographic range size – body size relationship in new world terrestrial carnivora

Most recent papers avoid describing macroecological relationships and interpreting then without a previous control of non-independence in data caused by phylogenetic patterns in data. In this paper, we analyzed the geographic range size – body size relationship for 70 species of New World terrestrial Carnivora (fissipeds) using various phylogenetic comparative methods and simulation procedures to assess their statistical performance. Autocorrelation analyses suggested a strong phylogenetic pattern for body size, but not for geographic range size. The correlation between the two traits was estimated using standard Pearson correlation across species (TIPS) and four different comparative methods: Felsenstein's independent contrasts (PIC), autoregressive method (ARM), phylogenetic eigenvector regression (PVR) and phylogenetic generalized least-squares (PGLS). The correlation between the two variables was significant for all methods, except PIC, in such a way that ecological mechanisms (i.e., minimum viable population or environmental heterogeneity- physiological homeostasis), could be valid explanations for the relationship. Simulations using different O-U processes for each trait were run in order to estimate true Type I errors of each method. Type I errors at 5% were similar for all phylogenetic methods (always lower than 8%), but equal to 13.1% for TIPS. PIC usually performs better than all other methods under Brownian motion evolution, but not in this case using a more complex combination of evolutionary models. So, recent claims that using independent contrasts in ecological research can be too conservative are correct but, on the other hand, using simple across-species correlation is too liberal even under the more complex evolutionary models exhibited by the traits analyzed here.     

Disentangling determinants of egg size in the Geometridae (Lepidoptera) using an advanced phylogenetic comparative method

We present a phylogenetic comparative study assessing the evolutionary determinants of egg size in the moth family Geometridae. These moths were found to show a strong negative allometric relationship between egg size and maternal body size. Using recently developed comparative methods based on an Ornstein-Uhlenbeck process, we show that maternal body size explains over half the variation in egg size. However, other determinants are less clear: ecological factors, previously hypothesized to affect egg size, were not found to have a considerable influence in the Geometridae. The limited role of such third factors suggests a direct causal link between egg size and body size rather than an indirect correlation mediated by some ecological factors. Notably, no large geometrid species lay small eggs. This pattern suggests that maternal body size poses a physical constraint on egg size, but within these limits, there appears to be a rather invariable selection for larger eggs.     

Exploring macroevolution using modern and fossil data

Macroevolution, encompassing the deep-time patterns of the origins of modern biodiversity, has been discussed in many contexts. Non-Darwinian models such as macromutations have been proposed as a means of bridging seemingly large gaps in knowledge, or as a means to explain the origin of exquisitely adapted body plans. However, such gaps can be spanned by new fossil finds, and complex, integrated organisms can be shown to have evolved piecemeal. For example, the fossil record between dinosaurs and Archaeopteryx has now filled up with astonishing fossil intermediates that show how the unique plexus of avian adaptations emerged step by step over 60 Myr. New numerical approaches to morphometrics and phylogenetic comparative methods allow palaeontologists and biologists to work together on deep-time questions of evolution, to explore how diversity, morphology and function have changed through time. Patterns are more complex than sometimes expected, with frequent decoupling of species diversity and morphological diversity, pointing to the need for some new generalizations about the processes that lie behind such patterns.     

The best of both worlds: Phylogenetic eigenvector regression and mapping

Eigenfunction analyses have been widely used to model patterns of autocorrelation in time, space and phylogeny. In a phylogenetic context, Diniz-Filho et al. (1998) proposed what they called Phylogenetic Eigenvector Regression (PVR), in which pairwise phylogenetic distances among species are submitted to a Principal Coordinate Analysis, and eigenvectors are then used as explanatory variables in regression, correlation or ANOVAs. More recently, a new approach called Phylogenetic Eigenvector Mapping (PEM) was proposed, with the main advantage of explicitly incorporating a model-based warping in phylogenetic distance in which an Ornstein-Uhlenbeck (O-U) process is fitted to data before eigenvector extraction. Here we compared PVR and PEM in respect to estimated phylogenetic signal, correlated evolution under alternative evolutionary models and phylogenetic imputation, using simulated data. Despite similarity between the two approaches, PEM has a slightly higher prediction ability and is more general than the original PVR. Even so, in a conceptual sense, PEM may provide a technique in the best of both worlds, combining the flexibility of data-driven and empirical eigenfunction analyses and the sounding insights provided by evolutionary models well known in comparative analyses.