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.     

The island rule: made to be broken?

The island rule is a hypothesis whereby small mammals evolve larger size on islands while large insular mammals dwarf. The rule is believed to emanate from small mammals growing larger to control more resources and enhance metabolic efficiency, while large mammals evolve smaller size to reduce resource requirements and increase reproductive output. We show that there is no evidence for the existence of the island rule when phylogenetic comparative methods are applied to a large, high-quality dataset. Rather, there are just a few clade-specific patterns: carnivores; heteromyid rodents; and artiodactyls typically evolve smaller size on islands whereas murid rodents usually grow larger. The island rule is probably an artefact of comparing distantly related groups showing clade-specific responses to insularity. Instead of a rule, size evolution on islands is likely to be governed by the biotic and abiotic characteristics of different islands, the biology of the species in question and contingency.     

Phylogenetic comparative approaches for studying niche conservatism

Analyses of phylogenetic niche conservatism (PNC) are becoming increasingly common. However, each analysis makes subtly different assumptions about the evolutionary mechanism that generates patterns of niche conservatism. To understand PNC, analyses should be conducted with reference to a clear underlying model, using appropriate methods. Here, we outline five macroevolutionary models that may underlie patterns of PNC (drift, niche retention, phylogenetic inertia, niche filling/shifting and evolutionary rates) and link these to published phylogenetic comparative methods. For each model, we give recent examples from the literature and suggest how the methods can be practically applied. We hope that this will help clarify the niche conservatism literature and encourage people to think about the evolutionary models underlying niche conservatism in their study group.     

Comparing phylogenetic signal in intraspecific and interspecific body size datasets

Phylogenetic comparative methods have become a standard statistical approach for analysing interspecific data, under the assumption that traits of species are more similar than expected by chance (i.e. phylogenetic signal is present). Here I test for phylogenetic signal in intraspecific body size datasets to evaluate whether intraspecific datasets may require phylogenetic analysis. I also compare amounts of phylogenetic signal in intraspecific and interspecific body size datasets. Some intraspecific body size datasets contain significant phylogenetic signal. Detection of significant phylogenetic signal was dependant upon the number of populations (n) and the amount of phylogenetic signal (K) for a given dataset. Amounts of phylogenetic signal do not differ between intraspecific and interspecific datasets. Further, relationships between significance of phylogenetic signal and sample size and amount of phylogenetic signal are similar for intraspecific and interspecific datasets. Thus, intraspecific body size datasets are similar to interspecific body size datasets with respect to phylogenetic signal. Whether these results are general for all characters requires further study.     

The evolution of signal–reward correlations in bee- and hummingbird-pollinated species of Salvia

Within-individual variation in floral advertising and reward traits is a feature experienced by pollinators that visit different flowers of the same plant. Pollinators can use advertising traits to gather information about the quality and amount of rewards, leading to the evolution of signal–reward correlations. As long as plants differ in the reliability of their signals and pollinators base their foraging decisions on this information, natural selection should act on within-individual correlations between signals and rewards. Because birds and bees differ in their cognitive capabilities, and use different floral traits as signals, we tested the occurrence of adaptive divergence of the within-individual signal–reward correlations among Salvia species that are pollinated either by bees or by hummingbirds. They are expected to use different floral advertising traits: frontal traits in the case of bees and side traits in the case of hummingbirds. We confirmed this expectation as bee- and hummingbird-pollinated species differed in which specific traits are predominantly associated with nectar reward at the within-individual level. Our findings highlight the adaptive value of within-individual variation and covariation patterns, commonly disregarded as ‘environmental noise’, and are consistent with the hypothesis that pollinator-mediated selection affects the correlation pattern among floral traits.