Rphylopars: fast multivariate phylogenetic comparative methods for missing data and within-species variation

Over the past several years, phylogenetic comparative studies have increasingly approached trait evolution in a multivariate context, with a number of taxa that continues to rise dramatically. Recent methods for phylogenetic comparative studies have provided ways to incorporate measurement error and to address computational challenges. However, missing data remain a particularly common problem, in which data are unavailable for some but not all traits of interest for a given species (or individual), leaving researchers with the choice between omitting observations or utilizing imputation-based approaches. Here, we introduce an r implementation of PhyloPars, a tool for phylogenetic imputation of missing data and estimation of trait covariance across species (phylogenetic covariance) and within species (phenotypic covariance). Rphylopars provides expanded capabilities over the original PhyloPars interface including a fast linear-time algorithm, thus allowing for extremely large data sets (which were previously computationally infeasible) to be analysed in seconds or minutes rather than hours. In addition to providing fast and computationally efficient implementations, we introduce in Rphylopars methods to estimate macroevolutionary parameters under alternative evolutionary models (e.g. Early-Burst, multivariate Ornstein-Uhlenbeck). By providing fast and computationally efficient methods with flexible options for various phylogenetic comparative approaches, Rphylopars expands the possibilities for researchers to analyse large and complex data with missing observations, within-species variation and deviations from Brownian motion

The role of diet in shaping the chemical signal design of Lacertid lizards

Lizards communicate with others via chemical signals, the composition of which may vary among species. Although the selective pressures and constraints affecting chemical signal diversity at the species level remain poorly understood, the possible role of diet has been largely neglected. The chemical signals of many lizards originate from the femoral glands that exude a mixture of semiochemicals, and may be used in a variety of contexts. We analyzed the lipophilic fraction of the glandular secretions of 45 species of lacertid lizard species by gas chromatography/mass spectrometry. The proportions of nine major chemical classes (alcohols, aldehydes, fatty acids, furanones, ketones, steroids, terpenoids, tocopherols and waxy esters), the relative contributions of these different classes (‘chemical diversity’), and the total number of different lipophilic compounds (‘chemical richness’) varied greatly among species. We examined whether interspecific differences in these chemical variables could be coupled to interspecific variation in diet using data from the literature. In addition, we compared chemical signal composition among species that almost never, occasionally, or often eat plant material. We found little support for the hypothesis that the chemical profile of a given species’ secretion depends on the type of food consumed. Diet breadth did not correlate with chemical diversity or richness. The amount of plants or ants consumed did not affect the relative contribution of any of the nine major chemical classes to the secretion. Chemical diversity did not differ among lizards with different levels of plant consumption; however, chemical richness was low in species with an exclusive arthropod diet, suggesting that incorporating plants in the diet enables lizards to increase the number of compounds allocated to secretions, likely because a (partly) herbivorous diet allows them to include compounds of plant origin that are unavailable in animal prey. Still, overall, diet appears a relatively poor predictor of interspecific differences in the broad chemical profiles of secretions of lacertid lizards.Financial support to JM and RGR was provided by the Spanish’s Ministerio de Economía y Competitividad projects MICIIN-CGL2011- 24150/BOS and MINECO CGL2014-53523-P.Peer Reviewe