Modeling body size evolution in Felidae under alternative phylogenetic hypotheses

The use of phylogenetic comparative methods in ecological research has advanced during the last twenty years, mainly due to accurate phylogenetic reconstructions based on molecular data and computational and statistical advances. We used phylogenetic correlograms and phylogenetic eigenvector regression (PVR) to model body size evolution in 35 worldwide Felidae (Mammalia, Carnivora) species using two alternative phylogenies and published body size data. The purpose was not to contrast the phylogenetic hypotheses but to evaluate how analyses of body size evolution patterns can be affected by the phylogeny used for comparative analyses (CA). Both phylogenies produced a strong phylogenetic pattern, with closely related species having similar body sizes and the similarity decreasing with increasing distances in time. The PVR explained 65% to 67% of body size variation and all Moran's I values for the PVR residuals were non-significant, indicating that both these models explained phylogenetic structures in trait variation. Even though our results did not suggest that any phylogeny can be used for CA with the same power, or that "good" phylogenies are unnecessary for the correct interpretation of the evolutionary dynamics of ecological, biogeographical, physiological or behavioral patterns, it does suggest that developments in CA can, and indeed should, proceed without waiting for perfect and fully resolved phylogenies.     

A METHOD FOR ASSESSING PHYLOGENETIC LEAST SQUARES MODELS FOR SHAPE AND OTHER HIGH‐DIMENSIONAL MULTIVARIATE DATA

Studies of evolutionary correlations commonly use phylogenetic regression (i.e., independent contrasts and phylogenetic generalized least squares) to assess trait covariation in a phylogenetic context. However, while this approach is appropriate for evaluating trends in one or a few traits, it is incapable of assessing patterns in highly multivariate data, as the large number of variables relative to sample size prohibits parametric test statistics from being computed. This poses serious limitations for comparative biologists, who must either simplify how they quantify phenotypic traits, or alter the biological hypotheses they wish to examine. In this article, I propose a new statistical procedure for performing ANOVA and regression models in a phylogenetic context that can accommodate high‐dimensional datasets. The approach is derived from the statistical equivalency between parametric methods using covariance matrices and methods based on distance matrices. Using simulations under Brownian motion, I show that the method displays appropriate Type I error rates and statistical power, whereas standard parametric procedures have decreasing power as data dimensionality increases. As such, the new procedure provides a useful means of assessing trait covariation across a set of taxa related by a phylogeny, enabling macroevolutionary biologists to test hypotheses of adaptation, and phenotypic change in high‐dimensional datasets.     

PHYLOGENIES,SPATIAL AUTOREGRESSION,AND THE COMPARATIVE METHOD: A COMPUTER SIMULATION TEST

Brownian motion computer simulation was used to test the statistical properties of a spatial autoregressive method in estimating evolutionary correlations between two traits using interspecific comparative data. When applied with a phylogeny of 42 species, the method exhibited reasonable Type I and II error rates. Estimation abilities were comparable to those of independent contrasts and minimum evolution (parsimony) methods, and generally superior to a traditional nonphylogenetic approach (not taking phylogenies into account at all). However, the autoregressive method performed extremely poorly with a smaller phylogeny (15 species) and with nearly independent (“star”) phylogenies. In both of these situations, any phylogenetic autocorrelation present in the data was not detected by the method. Results show how diagnostic techniques (e.g., Moran's I) can be useful in detecting and avoiding such situations, but that such techniques should not be used as definitive evidence that phylogenetic correlation is not present in a set of comparative data. The correction factor (α) proposed by Gittleman and Kot (1990) for use in weighting phylogenetic information had little effect in most analyses of 15 or 42 species with incorrect phylogenetic information, and may require much larger sample sizes before significant improvement is shown. With the sample sizes tested in this study, however, the autoregressive method implemented with this correction factor and correct phylogenetic information led to downwardly biased estimates of the absolute magnitude of the evolutionary correlation between two traits. Cautions and recommendations for implemention of the spatial autoregressive method are given; computer programs to conduct the analyses are available on request.     

DISENTANGLING EVOLUTIONARY CAUSE‐EFFECT RELATIONSHIPS WITH PHYLOGENETIC CONFIRMATORY PATH ANALYSIS

Confirmatory path analysis is a statistical technique to build models of causal hypotheses among variables and test if the data conform with the causal model. However, classical path analysis techniques ignore the nonindependence of observations due to phylogenetic relatedness among species, possibly leading to spurious results. Here, we present a simple method to perform phylogenetic confirmatory path analysis (PPA). We analyzed simulated datasets with varying amounts of phylogenetic signal in the data and a known underlying causal structure linking the traits to estimate Type I error and power. Results show that Type I error for PPA appeared to be slightly anticonservative (range: 0.047–0.072) but path analysis models ignoring phylogenetic signal resulted in much higher Type I error rates, which were positively related to the amount of phylogenetic signal (range: 0.051 for λ= 0 to 0.916 for λ= 1). Further, the power of the test was not compromised when accounting for phylogeny. As an example of the application of PPA, we revisit a study on the correlates of aggressive broodmate competition across seven avian families. The use of PPA allowed us to gain greater insight into the plausible causal paths linking species traits to aggressive broodmate competition.     

Patterns of within-species body size variation of birds: strong evidence for Bergmann's rule

Aim The aim of this study is to test whether Bergmann's rule, a general intraspecific tendency towards larger body size in cooler areas and at higher latitudes, holds for birds throughout the world. Location This study includes information on species of birds from throughout the world. Methods I gathered data on body size variation from the literature and used two general meta‐analytical procedures to test the validity of Bergmann's rule in birds: a modified vote‐counting approach and calculation of overall effect sizes. Related species may show similar body size trends, thus I performed all analyses using nonphylogenetic and phylogenetic methods. I used tests of phylogenetic signal for each data set to decide which type of statistical analysis (nonphylogenetic or phylogenetic) was more appropriate. Results The majority of species of birds (76 of 100 species) are larger at higher latitudes, and in cooler areas (20 of 22 species). Birds show a grand mean correlation coefficient of +0.32 for body size and latitude, and ?0.81 for body size and temperature, both significant trends. Sedentary species show stronger body size trends in some, but not all, analyses. Neither males nor females consistently have stronger body size trends. Additionally, the strength of body size trends does not vary with latitude or body mass. Conclusions Bergmann's rule holds for birds throughout the world, regardless of whether temperature or latitude (as a proxy) is used. Previous studies have suggested that Bergmann's rule is stronger for sedentary than migratory species, males than females and temperate than tropical taxa. I did not find strong support for any of these as general themes for birds, although few studies of tropical taxa have been conducted. The processes responsible for Bergmann's rule remain somewhat of a black box; however, fasting endurance is probably a more important factor than the traditional hypothesis of heat conservation.     

Phylogeny and species traits predict bird detectability

Avian acoustic communication has resulted from evolutionary pressures and ecological constraints. We therefore expect that auditory detectability in birds might be predictable by species traits and phylogenetic relatedness. We evaluated the relationship between phylogeny, species traits, and field‐based estimates of the two processes that determine species detectability (singing rate and detection distance) for 141 bird species breeding in boreal North America. We used phylogenetic mixed models and cross‐validation to compare the relative merits of using trait data only, phylogeny only, or the combination of both to predict detectability. We found a strong phylogenetic signal in both singing rates and detection distances; however the strength of phylogenetic effects was less than expected under Brownian motion evolution. The evolution of behavioural traits that determine singing rates was found to be more labile, leaving more room for species to evolve independently, whereas detection distance was mostly determined by anatomy (i.e. body size) and thus the laws of physics. Our findings can help in disentangling how complex ecological and evolutionary mechanisms have shaped different aspects of detectability in boreal birds. Such information can greatly inform single‐ and multi‐species models but more work is required to better understand how to best correct possible biases in phylogenetic diversity and other community metrics.     

The effect of intraspecific sample size on type I and type II error rates in comparative studies

Comparative studies have increased greatly in number in recent years due to advances in statistical and phylogenetic methodologies. For these studies, a trade-off often exists between the number of species that can be included in any given study and the number of individuals examined per species. Here, we describe a simple simulation study examining the effect of intraspecific sample size on statistical error in comparative studies. We find that ignoring measurement error has no effect on type I error of nonphylogenetic analyses, but can lead to increased type I error under some circumstances when using independent contrasts. We suggest using ANOVA to evaluate the relative amounts of within- and between-species variation when considering a phylogenetic comparative study. If within-species variance is particularly large and intraspecific sample sizes small, then either larger sample sizes or comparative methods that account for measurement error are necessary.     

Incomplete lineage sorting impacts the inference of macroevolutionary regimes from molecular phylogenies when concatenation is employed: An analysis based on Cetacea

Interest in methods that estimate speciation and extinction rates from molecular phylogenies has increased over the last decade. The application of such methods requires reliable estimates of tree topology and node ages, which are frequently obtained using standard phylogenetic inference combining concatenated loci and molecular dating. However, this practice disregards population‐level processes that generate gene tree/species tree discordance. We evaluated the impact of employing concatenation and coalescent‐based phylogeny inference in recovering the correct macroevolutionary regime using simulated data based on the well‐established diversification rate shift of delphinids in Cetacea. We found that under scenarios of strong incomplete lineage sorting, macroevolutionary analysis of phylogenies inferred by concatenating loci failed to recover the delphinid diversification shift, while the coalescent‐based tree consistently retrieved the correct rate regime. We suggest that ignoring microevolutionary processes reduces the power of methods that estimate macroevolutionary regimes from molecular data.     

A phylogenetic comparative method for evaluating trait coevolution across two phylogenies for sets of interacting species

Evaluating trait correlations across species within a lineage via phylogenetic regression is fundamental to comparative evolutionary biology, but when traits of interest are derived from two sets of lineages that coevolve with one another, methods for evaluating such patterns in a dual‐phylogenetic context remain underdeveloped. Here, we extend multivariate permutation‐based phylogenetic regression to evaluate trait correlations in two sets of interacting species while accounting for their respective phylogenies. This extension is appropriate for both univariate and multivariate response data, and may use one or more independent variables, including environmental covariates. Imperfect correspondence between species in the interacting lineages can also be accommodated, such as when species in one lineage associate with multiple species in the other, or when there are unmatched taxa in one or both lineages. For both univariate and multivariate data, the method displays appropriate type I error, and statistical power increases with the strength of the trait covariation and the number of species in the phylogeny. These properties are retained even when there is not a 1:1 correspondence between lineages. Finally, we demonstrate the approach by evaluating the evolutionary correlation between traits in fig species and traits in their agaonid wasp pollinators. R computer code is provided.     

Is RAD‐seq suitable for phylogenetic inference? An in silico assessment and optimization

Inferring phylogenetic relationships between closely related taxa can be hindered by three factors: (1) the lack of informative molecular variation at short evolutionary timescale; (2) the lack of established markers in poorly studied taxa; and (3) the potential phylogenetic conflicts among different genomic regions due to incomplete lineage sorting or introgression. In this context, Restriction site Associated DNA sequencing (RAD‐seq) seems promising as this technique can generate sequence data from numerous DNA fragments scattered throughout the genome, from a large number of samples, and without preliminary knowledge on the taxa under study. However, divergence beyond the within‐species level will necessarily reduce the number of conserved and non‐duplicated restriction sites, and therefore the number of loci usable for phylogenetic inference. Here, we assess the suitability of RAD‐seq for phylogeny using a simulated experiment on the 12 Drosophila genomes, with divergence times ranging from 5 to 63 million years. These simulations show that RAD‐seq allows the recovery of the known Drosophila phylogeny with strong statistical support, even for relatively ancient nodes. Notably, this conclusion is robust to the potentially confounding effects of sequencing errors, heterozygosity, and low coverage. We further show that clustering RAD‐seq data using the BLASTN and SiLiX programs significantly improves the recovery of orthologous RAD loci compared with previously proposed approaches, especially for distantly related species. This study therefore validates the view that RAD sequencing is a powerful tool for phylogenetic inference.     

Phylogenetically structured variance in felid bite force: the role of phylogeny in the evolution of biting performance

A key question in evolution is the degree to which morphofunctional complexes are constrained by phylogeny. We investigated the role of phylogeny in the evolution of biting performance, quantified as bite forces, using phylogenetic eigenvector regression. Results indicate that there are strong phylogenetic signals in both absolute and size‐adjusted bite forces, although it is weaker in the latter. This indicates that elimination of size influences reduces the level of phylogenetic inertia and that the majority of the phylogenetic constraint is a result of size. Tracing the evolution of bite force through phylogeny by character optimization also supports this notion, in that relative bite force is randomly distributed across phylogeny whereas absolute bite force diverges according to clade. The nonphylogenetically structured variance in bite force could not be sufficiently explained by species‐unique morphology or by ecology. This study demonstrates the difficulties in identifying causes of nonphylogenetically structured variance in morphofunctional character complexes.     

The utility of cranial ontogeny for phylogenetic inference: a case study in crocodylians using geometric morphometrics

The degree to which the ontogeny of organisms could facilitate our understanding of phylogenetic relationships has long been a subject of contention in evolutionary biology. The famed notion that ‘ontogeny recapitulates phylogeny’ has been largely discredited, but there remains an expectation that closely related organisms undergo similar morphological transformations throughout ontogeny. To test this assumption, we used three‐dimensional geometric morphometric methods to characterize the cranial morphology of 10 extant crocodylian species and construct allometric trajectories that model the post‐natal ontogenetic shape changes. Using time‐calibrated molecular and morphological trees, we employed a suite of comparative phylogenetic methods to assess the extent of phylogenetic signal in these trajectories. All analyses largely demonstrated a lack of significant phylogenetic signal, indicating that ontogenetic shape changes contain little phylogenetic information. Notably, some Mantel tests yielded marginally significant results when analysed with the morphological tree, which suggest that the underlying signal in these trajectories is correlated with similarities in the adult cranial morphology. However, despite these instances, all other analyses, including more powerful tests for phylogenetic signal, recovered statistical and visual evidence against the assumption that similarities in ontogenetic shape changes are commensurate with phylogenetic relatedness and thus bring into question the efficacy of using allometric trajectories for phylogenetic inference.     

AN EIGENVECTOR METHOD FOR ESTIMATING PHYLOGENETIC INERTIA

We propose a new method to estimate and correct for phylogenetic inertia in comparative data analysis. The method, called phylogenetic eigenvector regression (PVR) starts by performing a principal coordinate analysis on a pairwise phylogenetic distance matrix between species. Traits under analysis are regressed on eigenvectors retained by a broken-stick model in such a way that estimated values express phylogenetic trends in data and residuals express independent evolution of each species. This partitioning is similar to that realized by the spatial autoregressive method, but the method proposed here overcomes the problem of low statistical performance that occurs with autoregressive method when phylogenetic correlation is low or when sample size is too small to detect it. Also, PVR is easier to perform with large samples because it is based on well-known techniques of multivariate and regression analyses. We evaluated the performance of PVR and compared it with the autoregressive method using real datasets and simulations. A detailed worked example using body size evolution of Carnivora mammals indicated that phylogenetic inertia in this trait is elevated and similarly estimated by both methods. In this example, Type I error at α = 0.05 of PVR was equal to 0.048, but an increase in the number of eigenvectors used in the regression increases the error. Also, similarity between PVR and the autoregressive method, defined by correlation between their residuals, decreased by overestimating the number of eigenvalues necessary to express the phylogenetic distance matrix. To evaluate the influence of cladogram topology on the distribution of eigenvalues extracted from the double-centered phylogenetic distance matrix, we analyzed 100 randomly generated cladograms (up to 100 species). Multiple linear regression of log transformed variables indicated that the number of eigenvalues extracted by the broken-stick model can be fully explained by cladogram topology. Therefore, the broken-stick model is an adequate criterion for determining the correct number of eigenvectors to be used by PVR. We also simulated distinct levels of phylogenetic inertia by producing a trend across 10, 25, and 50 species arranged in “comblike” cladograms and then adding random vectors with increased residual variances around this trend. In doing so, we provide an evaluation of the performance of both methods with data generated under different evolutionary models than tested previously. The results showed that both PVR and autoregressive method are efficient in detecting inertia in data when sample size is relatively high (more than 25 species) and when phylogenetic inertia is high. However, PVR is more efficient at smaller sample sizes and when level of phylogenetic inertia is low. These conclusions were also supported by the analysis of 10 real datasets regarding body size evolution in different animal clades. We concluded that PVR can be a useful alternative to an autoregressive method in comparative data analysis.     

Using phylogeny and functional traits for assessing community assembly along environmental gradients: A deterministic process driven by elevation

Community assembly processes is the primary focus of community ecology. Using phylogenetic‐based and functional trait‐based methods jointly to explore these processes along environmental gradients are useful ways to explain the change of assembly mechanisms under changing world. Our study combined these methods to test assembly processes in wide range gradients of elevation and other habitat environmental factors. We collected our data at 40 plots in Taibai Mountain, China, with more than 2,300 m altitude difference in study area and then measured traits and environmental factors. Variance partitioning was used to distinguish the main environment factors leading to phylogeny and traits change among 40 plots. Principal component analysis (PCA) was applied to colligate other environment factors. Community assembly patterns along environmental gradients based on phylogenetic and functional methods were studied for exploring assembly mechanisms. Phylogenetic signal was calculated for each community along environmental gradients in order to detect the variation of trait performance on phylogeny. Elevation showed a better explanatory power than other environment factors for phylogenetic and most traits’ variance. Phylogenetic and several functional structure clustered at high elevation while some conserved traits overdispersed. Convergent tendency which might be caused by filtering or competition along elevation was detected based on functional traits. Leaf dry matter content (LDMC) and leaf nitrogen content along PCA 1 axis showed conflicting patterns comparing to patterns showed on elevation. LDMC exhibited the strongest phylogenetic signal. Only the phylogenetic signal of maximum plant height showed explicable change along environmental gradients. Synthesis. Elevation is the best environment factors for predicting phylogeny and traits change. Plant's phylogenetic and some functional structures show environmental filtering in alpine region while it shows different assembly processes in middle‐ and low‐altitude region by different trait/phylogeny. The results highlight deterministic processes dominate community assembly in large‐scale environmental gradients. Performance of phylogeny and traits along gradients may be independent with each other. The novel method for calculating functional structure which we used in this study and the focus of phylogenetic signal change along gradients may provide more useful ways to detect community assembly mechanisms.     

SCRAPP: A tool to assess the diversity of microbial samples from phylogenetic placements

Microbial ecology research is currently driven by the continuously decreasing cost of DNA sequencing and the improving accuracy of data analysis methods. One such analysis method is phylogenetic placement, which establishes the phylogenetic identity of the anonymous environmental sequences in a sample by means of a given phylogenetic reference tree. However, assessing the diversity of a sample remains challenging, as traditional methods do not scale well with the increasing data volumes and/or do not leverage the phylogenetic placement information. Here, we present scrapp , a highly parallel and scalable tool that uses a molecular species delimitation algorithm to quantify the diversity distribution over the reference phylogeny for a given phylogenetic placement of the sample. scrapp employs a novel approach to cluster phylogenetic placements, called placement space clustering, to efficiently perform dimensionality reduction, so as to scale on large data volumes. Furthermore, it uses the phylogeny‐aware molecular species delimitation method mPTP to quantify diversity. We evaluated scrapp using both, simulated and empirical data sets. We use simulated data to verify our approach. Tests on an empirical data set show that scrapp ‐derived metrics can classify samples by their diversity‐correlated features equally well or better than existing, commonly used approaches. scrapp is available at https://github.com/pbdas/scrapp .     

Phylogenetic targeting of research effort in evolutionary biology

Many questions in comparative biology require that new data be collected, either to build a comparative database for the first time or to augment existing data. Given resource limitations in collecting data, the question arises as to which species should be studied to increase the size of comparative data sets. By taking hypotheses, existing data relevant to the hypotheses, and a phylogeny, we show that a method of “phylogenetic targeting” can systematically guide data collection while taking into account potentially confounding variables and competing hypotheses. Phylogenetic targeting selects potential candidates for future data collection, using a flexible scoring system based on differences in pairwise comparisons. We used simulations to assess the performance of phylogenetic targeting, as compared with the less systematic approach of randomly selecting species (as might occur when data have been collected without regard to phylogeny and variation in the traits of interest). The simulations revealed that phylogenetic targeting increased the statistical power to detect correlations and that power increased with the number of species in the tree, even when the number of species studied was held constant. We also developed a Web‐based computer program called PhyloTargeting to implement the approach ( http://phylotargeting.fas.harvard.edu ).     

Nonindependence and sensitivity analyses in ecological and evolutionary meta‐analyses

Meta‐analysis is an important tool for synthesizing research on a variety of topics in ecology and evolution, including molecular ecology, but can be susceptible to nonindependence. Nonindependence can affect two major interrelated components of a meta‐analysis: (i) the calculation of effect size statistics and (ii) the estimation of overall meta‐analytic estimates and their uncertainty. While some solutions to nonindependence exist at the statistical analysis stages, there is little advice on what to do when complex analyses are not possible, or when studies with nonindependent experimental designs exist in the data. Here we argue that exploring the effects of procedural decisions in a meta‐analysis (e.g. inclusion of different quality data, choice of effect size) and statistical assumptions (e.g. assuming no phylogenetic covariance) using sensitivity analyses are extremely important in assessing the impact of nonindependence. Sensitivity analyses can provide greater confidence in results and highlight important limitations of empirical work (e.g. impact of study design on overall effects). Despite their importance, sensitivity analyses are seldom applied to problems of nonindependence. To encourage better practice for dealing with nonindependence in meta‐analytic studies, we present accessible examples demonstrating the impact that ignoring nonindependence can have on meta‐analytic estimates. We also provide pragmatic solutions for dealing with nonindependent study designs, and for analysing dependent effect sizes. Additionally, we offer reporting guidelines that will facilitate disclosure of the sources of nonindependence in meta‐analyses, leading to greater transparency and more robust conclusions.     

Effects of sample size and intraspecific variation in phylogenetic comparative studies: a meta‐analytic review

Comparative analyses aim to explain interspecific variation in phenotype among taxa. In this context, phylogenetic approaches are generally applied to control for similarity due to common descent, because such phylogenetic relationships can produce spurious similarity in phenotypes (known as phylogenetic inertia or bias). On the other hand, these analyses largely ignore potential biases due to within‐species variation. Phylogenetic comparative studies inherently assume that species‐specific means from intraspecific samples of modest sample size are biologically meaningful. However, within‐species variation is often significant, because measurement errors, within‐ and between‐individual variation, seasonal fluctuations, and differences among populations can all reduce the repeatability of a trait. Although simulations revealed that low repeatability can increase the type I error in a phylogenetic study, researchers only exercise great care in accounting for similarity in phenotype due to common phylogenetic descent, while problems posed by intraspecific variation are usually neglected. A meta‐analysis of 194 comparative analyses all adjusting for similarity due to common phylogenetic descent revealed that only a few studies reported intraspecific repeatabilities, and hardly any considered or partially dealt with errors arising from intraspecific variation. This is intriguing, because the meta‐analytic data suggest that the effect of heterogeneous sampling can be as important as phylogenetic bias, and thus they should be equally controlled in comparative studies. We provide recommendations about how to handle such effects of heterogeneous sampling.     

HOW LIZARDS TURN INTO SNAKES: A PHYLOGENETIC ANALYSIS OF BODY-FORM EVOLUTION IN ANGUID LIZARDS

Abstract One of the most striking morphological transformations in vertebrate evolution is the transition from a lizardlike body form to an elongate, limbless (snakelike) body form. Despite its dramatic nature, this transition has occurred repeatedly among closely related species (especially in squamate reptiles), making it an excellent system for studying macroevolutionary transformations in body plan. In this paper, we examine the evolution of body form in the lizard family Anguidae, a clade in which multiple independent losses of limbs have occurred. We combine a molecular phylogeny for 27 species, our morphometric data, and phylogenetic comparative methods to provide the first statistical phylogenetic tests of several long‐standing hypotheses for the evolution of snakelike body form. Our results confirm the hypothesized relationships between body elongation and limb reduction and between limb reduction and digit reduction. However, we find no support for the hypothesized sequence going from body elongation to limb reduction to digit loss, and we show that a burrowing lifestyle is not a necessary correlate of limb loss. We also show that similar degrees of overall body elongation are achieved in two different ways in anguids, that these different modes of elongation are associated with different habitat preferences, and that this dichotomy in body plan and ecology is widespread in limb‐reduced squamates. Finally, a recent developmental study has proposed that the transition from lizardlike to snakelike body form involves changes in the expression domains of midbody Hox genes, changes that would link elongation and limb loss and might cause sudden transformations in body form. Our results reject this developmental model and suggest that this transition involves gradual changes occurring over relatively long time scales.     

Scale‐dependence of phylogenetic signal in ecological traits of ectoparasites

The non‐independence of traits among closely related species is a well‐documented phenomenon underpinning modern methods for comparative analyses or prediction of trait values in new species. Surprisingly such studies have mainly focused on life‐history or morphological traits of free‐living organisms, ignoring ecological attributes of parasite species in spite of the fact that they are critical for conservation and human health. We tested for a phylogenetic signal acting on two ecological traits, abundance and host specificity, using data for 218 flea species parasitic on small mammals in 19 regions of the Palaearctic and Nearctic, and a phylogenetic tree for these species. We tested for the presence of a phylogenetic signal at both regional and continental scales using three measures (Abouheif/Moran's I, Pagel's λ, and Blomberg et al.'s K). Our results show 1) a consistent positive phylogenetic signal for flea abundance, but only a weaker and erratic signal for host specificity, and 2) a clear dependence on scale, with the signals being stronger at the continental scale and relatively weaker or inconsistent at the regional scale. Whenever values of Blomberg et al.'s K were found significant, they were <1 suggesting that the effects of phylogeny on the evolution of abundance and host specificity in fleas are weaker than expected from a Brownian motion model. The most striking finding is that, within a continental fauna, closely‐related flea species are characterized by similar levels of abundance, though this pattern is weaker within local assemblages, possibly eroded by local biotic or abiotic conditions. We discuss the link between history (represented by phylogeny) and pattern of variation among species in morphological and ecological traits, and use comparisons between the Palaearctic and Nearctic to infer a role of historical events in the probability of detecting phylogenetic signals.