Discriminating the effects of phylogenetic hypothesis,tree resolution and clade age estimates on phylogenetic signal measurements

Understanding how species traits evolved over time is the central question to comprehend assembly rules that govern the phylogenetic structure of communities. The measurement of phylogenetic signal (PS) in ecologically relevant traits is a first step to understand phylogenetically structured community patterns. The different methods available to estimate PS make it difficult to choose which is most appropriate. Furthermore, alternative phylogenetic tree hypotheses, node resolution and clade age estimates might influence PS measurements. In this study, we evaluated to what extent these parameters affect different methods of PS analysis, and discuss advantages and disadvantages when selecting which method to use. We measured fruit/seed traits and flowering/fruiting phenology of endozoochoric species occurring in Southern Brazilian Araucaria forests and evaluated their PS using Mantel regressions, phylogenetic eigenvector regressions (PVR) and K statistic. Mantel regressions always gave less significant results compared to PVR and K statistic in all combinations of phylogenetic trees constructed. Moreover, a better phylogenetic resolution affected PS, independently of the method used to estimate it. Morphological seed traits tended to show higher PS than diaspores traits, while PS in flowering/fruiting phenology depended mostly on the method used to estimate it. This study demonstrates that different PS estimates are obtained depending on the chosen method and the phylogenetic tree resolution. This finding has implications for inferences on phylogenetic niche conservatism or ecological processes determining phylogenetic community structure.     

POOR STATISTICAL PERFORMANCE OF THE MANTEL TEST IN PHYLOGENETIC COMPARATIVE ANALYSES

The Mantel test, based on comparisons of distance matrices, is commonly employed in comparative biology, but its statistical properties in this context are unknown. Here, we evaluate the performance of the Mantel test for two applications in comparative biology: testing for phylogenetic signal, and testing for an evolutionary correlation between two characters. We find that the Mantel test has poor performance compared to alternative methods, including low power and, under some circumstances, inflated type‐I error. We identify a remedy for the inflated type‐I error of three‐way Mantel tests using phylogenetic permutations; however, this test still has considerably lower power than independent contrasts. We recommend that use of the Mantel test should be restricted to cases in which data can only be expressed as pairwise distances among taxa.     

Evolutionary Models and Phylogenetic Signal Assessment via Mantel Test

Phylogenetically closely related species tend to be more similar to each other than to more distantly related ones, a pattern called phylogenetic signal. Appropriate tests to evaluate the association between phylogenetic relatedness and trait variation among species are employed in a myriad of eco-evolutionary studies. However, most tests available to date are only suitable for datasets describing continuous traits, and are most often applicable only for single trait analysis. The Mantel test is a useful method to measure phylogenetic signal for multiple (continuous, binary and/or categorical) traits. However, the classical Mantel test does not incorporate any evolutionary model (EM) in the analysis. Here, we describe a new analytical procedure, which incorporates explicitly an evolutionary model in the standard Mantel test (EM-Mantel). We run numerical simulations to evaluate its statistical properties, under different combinations of species pool size, trait type and number. Our results showed that EM-Mantel test has appropriate type I error and acceptable power, which increases with the strength of phylogenetic signal and with species pool size but depended on trait type. EM-Mantel test is a good alternative for measuring phylogenetic signal in binary and categorical traits and for datasets with multiple traits.     

TESTING FOR PHYLOGENETIC SIGNAL IN BIOLOGICAL TRAITS: THE UBIQUITY OF CROSS‐PRODUCT STATISTICS

To evaluate rates of evolution, to establish tests of correlation between two traits, or to investigate to what degree the phylogeny of a species assemblage is predictive of a trait value so‐called tests for phylogenetic signal are used. Being based on different approaches, these tests are generally thought to possess quite different statistical performances. In this article, we show that the Blomberg et al. K and K*, the Abouheif index, the Moran's I, and the Mantel correlation are all based on a cross‐product statistic, and are thus all related to each other when they are associated to a permutation test of phylogenetic signal. What changes is only the way phylogenetic and trait similarities (or dissimilarities) among the tips of a phylogeny are computed. The definitions of the phylogenetic and trait‐based (dis)similarities among tips thus determines the performance of the tests. We shortly discuss the biological and statistical consequences (in terms of power and type I error of the tests) of the observed relatedness among the statistics that allow tests for phylogenetic signal. Blomberg et al. K* statistic appears as one on the most efficient approaches to test for phylogenetic signal. When branch lengths are not available or not accurate, Abouheif's C_mean statistic is a powerful alternative to K*.     

Euclidean nature of phylogenetic distance matrices

Phylogenies are fundamental to comparative biology as they help to identify independent events on which statistical tests rely. Two groups of phylogenetic comparative methods (PCMs) can be distinguished: those that take phylogenies into account by introducing explicit models of evolution and those that only consider phylogenies as a statistical constraint and aim at partitioning trait values into a phylogenetic component (phylogenetic inertia) and one or multiple specific components related to adaptive evolution. The way phylogenetic information is incorporated into the PCMs depends on the method used. For the first group of methods, phylogenies are converted into variance-covariance matrices of traits following a given model of evolution such as Brownian motion (BM). For the second group of methods, phylogenies are converted into distance matrices that are subsequently transformed into Euclidean distances to perform principal coordinate analyses. Here, we show that simply taking the elementwise square root of a distance matrix extracted from a phylogenetic tree ensures having a Euclidean distance matrix. This is true for any type of distances between species (patristic or nodal) and also for trees harboring multifurcating nodes. Moreover, we illustrate that this simple transformation using the square root imposes less geometric distortion than more complex transformations classically used in the literature such as the Cailliez method. Given the Euclidean nature of the elementwise square root of phylogenetic distance matrices, the positive semidefinitiveness of the phylogenetic variance-covariance matrix of a trait following a BM model, or related models of trait evolution, can be established. In that way, we build a bridge between the two groups of statistical methods widely used in comparative analysis. These results should be of great interest for ecologists and evolutionary biologists performing statistical analyses incorporating phylogenies.     

Hidden patterns of phylogenetic non‐stationarity overwhelm comparative analyses of niche conservatism and divergence

Aim Despite the importance of the niche concept in ecological and evolutionary theory, there are still many discussions about its definition and operational evaluation, especially when dealing with niche divergence and conservatism in an explicit phylogenetic context. Here we evaluate patterns of niche evolution in 67 New World Carnivora species, measured using Hellinger distances based on MAXENT models of species distribution. We show how inferences on niche conservatism or divergence depend on the way phylogenetic patterns are analysed using matrix comparison techniques. Innovation Initially we used the simplest approach of Mantel tests to compare Hellinger distances ( N ) derived from MAXENT and phylogenetic distances ( P ) among species. Then we extended the Mantel test to generate a multivariate correlogram, in which phylogenetic patterns are analysed at multiple levels in the phylogeny and can reveal nonlinearity in the relationship between divergence and time. Finally, we proposed a new approach to generate ‘local’ (or ‘specific’) leverages of components for Mantel correlation, evaluating the non‐stationarity in the relationship between N and P for each species. This new approach was used to show if some lineages are more prone to niche shift or conservatism than others. Main conclusions Standard Mantel tests indicated a poor correspondence between N and P matrices, discarding the idea of niche conservatism for Carnivora, but the correlogram supports that closely related species tend to be more similar than expected by chance. Moreover, the variance among Hellinger distances between pairs of closely phylogenetically related species is much larger than for the entire clade. Phylogenetic non‐stationarity analysis shows that in some Carnivora families the niche tends to divergence (Mustelidae and Canidae), whereas in others it tends to conservatism (Procyonidae and Mustelidae) at short phylogenetic distances. Our analyses clearly show that misleading results may appear if niche divergence is analysed only by simple matrix correlations not taking into account complex patterns of phylogenetic nonlinearity and non‐stationarity.     

Larger phylogenetic distances in litter mixtures: lower microbial biomass and higher C/N ratios but equal mass loss

Phylogenetic distances of coexisting species differ greatly within plant communities, but their consequences for decomposers and decomposition remain unknown. We hypothesized that large phylogenetic distance of leaf litter mixtures increases differences of their litter traits, which may, in turn, result in increased resource complementarity or decreased resource concentration for decomposers and hence increased or decreased chemical transformation and reduction of litter. We conducted a litter mixture experiment including 12 common temperate tree species (evolutionarily separated by up to 106 Myr), and sampled after seven months, at which average mass loss was more than 50%. We found no effect of increased phylogenetic distance on litter mass loss or on abundance and diversity of invertebrate decomposers. However, phylogenetic distance decreased microbial biomass and increased carbon/nitrogen (C/N) ratios of litter mixtures. Consistently, four litter traits showed (marginally) significant phylogenetic signal and in three of these traits increasing trait difference decreased microbial biomass and increased C/N. We suggest that phylogenetic proximity of litter favours microbial decomposers and chemical transformation of litter owing to a resource concentration effect. This leads to a new hypothesis: closely related plant species occurring in the same niche should promote and profit from increased nutrient availability.     

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.     

phylosignal: an R package to measure,test, and explore the phylogenetic signal

Phylogenetic signal is the tendency for closely related species to display similar trait values as a consequence of their phylogenetic proximity. Ecologists and evolutionary biologists are becoming increasingly interested in studying the phylogenetic signal and the processes which drive patterns of trait values in the phylogeny. Here, we present a new R package, phylosignal which provides a collection of tools to explore the phylogenetic signal for continuous biological traits. These tools are mainly based on the concept of autocorrelation and have been first developed in the field of spatial statistics. To illustrate the use of the package, we analyze the phylogenetic signal in pollution sensitivity for 17 species of diatoms.     

Testing for phylogenetic signal in phenotypic traits: new matrices of phylogenetic proximities

Abouheif adapted a test for serial independence to detect a phylogenetic signal in phenotypic traits. We provide the exact analytic value of this test, revealing that it uses Moran's I statistic with a new matrix of phylogenetic proximities. We introduce then two new matrices of phylogenetic proximities highlighting their mathematical properties: matrix A which is used in Abouheif test and matrix M which is related to A and biodiversity studies. Matrix A unifies the tests developed by Abouheif, Moran and Geary. We discuss the advantages of matrices A and M over three widely used phylogenetic proximity matrices through simulations evaluating power and type-I error of tests for phylogenetic autocorrelation. We conclude that A enhances the power of Moran's test and is useful for unresolved trees. Data sets and routines are freely available in an online package and explained in an online supplementary file.     

Correlation analysis of dissimilarity matrices

Distance-based methods have been a valuable tool for ecologists for decades. Indirectly, distance-based ordination and cluster analysis, in particular, have been widely practiced as they allow the visualization of a multivariate data set in a few dimensions. The explicitly distance-based Mantel test and multiple regression on distance matrices (MRM) add hypothesis testing to the toolbox. One concern for ecologists wishing to use these methods lies in deciding whether to combine data vectors into a compound multivariate dissimilarity to analyze them individually. For Euclidean distances on scaled data, the correlation of a pair of multivariate distance matrices can be calculated from the correlations between the two sets of individual distance matrices if one set is orthogonal, demonstrating a clear link between individual and compound distances. The choice between Mantel and MRM should be driven by ecological hypotheses rather than mathematical concerns. The relationship between individual and compound distance matrices also provides a means for calculating the maximum possible value of the Mantel statistic, which can be considerably less than 1 for a given analysis. These relationships are demonstrated with simulated data. Although these mathematical relationships are only strictly true for Euclidean distances when one set of variables is orthogonal, simulations show that they are approximately true for weakly correlated variables and Bray–Curtis dissimilarities.     

Disentangling niche and neutral influences on community assembly: assessing the performance of community phylogenetic structure tests

Patterns of phylogenetic relatedness within communities have been widely used to infer the importance of different ecological and evolutionary processes during community assembly, but little is known about the relative ability of community phylogenetics methods and null models to detect the signature of processes such as dispersal, competition and filtering under different models of trait evolution. Using a metacommunity simulation incorporating quantitative models of trait evolution and community assembly, I assessed the performance of different tests that have been used to measure community phylogenetic structure. All tests were sensitive to the relative phylogenetic signal in species metacommunity abundances and traits; methods that were most sensitive to the effects of niche-based processes on community structure were also more likely to find non-random patterns of community phylogenetic structure under dispersal assembly. When used with a null model that maintained species occurrence frequency in random communities, several metrics could detect niche-based assembly when there was strong phylogenetic signal in species traits, when multiple traits were involved in community assembly, and in the presence of environmental heterogeneity. Interpretations of the causes of community phylogenetic structure should be modified to account for the influence of dispersal.     

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.     

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.     

Environment differentially affects the functional and phylogenetic structures of plant communities in a dry evergreen Afromontane tropical forest

Testing how local environmental conditions influence plant community assembly is important to understand the underlying mechanisms that promote and/or maintain biodiversity. Functional traits are used to find the broad spectrum of resource use strategies that plants use to respond to environmental variation. The patterns and drivers of plant community assembly through the lens of traits and phylogeny; however, remain to be studied in a uniquely biodiversity rich but poorly known fragmented dry Afromontane forest of Ethiopia. Here, we combined trait and community phylogenetic data from thirty sampling plots of 20 × 20 m size to determine the functional and phylogenetic structures and their drivers in a fragmented, human-dominated dry evergreen Afromontane forest. We found phylogenetic and functional clustering of plants in which the effect of environment was found to be trait specific. A weak phylogenetic signal for traits was detected suggesting that species resource use strategies may not be inferred using species phylogenetic distance. Additionally, we found functional traits to be weak in predicting species abundance distribution. Overall, while this study shows a non-random community assembly pattern, it also highlights the importance of deterministic processes being trait specific.     

Predicting rates of interspecific interaction from phylogenetic trees

Integrating phylogenetic information can potentially improve our ability to explain species' traits, patterns of community assembly, the network structure of communities, and ecosystem function. In this study, we use mathematical models to explore the ecological and evolutionary factors that modulate the explanatory power of phylogenetic information for communities of species that interact within a single trophic level. We find that phylogenetic relationships among species can influence trait evolution and rates of interaction among species, but only under particular models of species interaction. For example, when interactions within communities are mediated by a mechanism of phenotype matching, phylogenetic trees make specific predictions about trait evolution and rates of interaction. In contrast, if interactions within a community depend on a mechanism of phenotype differences, phylogenetic information has little, if any, predictive power for trait evolution and interaction rate. Together, these results make clear and testable predictions for when and how evolutionary history is expected to influence contemporary rates of species interaction.     

Sharing is caring? Measurement error and the issues arising from combining 3D morphometric datasets

Geometric morphometrics is routinely used in ecology and evolution and morphometric datasets are increasingly shared among researchers, allowing for more comprehensive studies and higher statistical power (as a consequence of increased sample size). However, sharing of morphometric data opens up the question of how much nonbiologically relevant variation (i.e., measurement error) is introduced in the resulting datasets and how this variation affects analyses. We perform a set of analyses based on an empirical 3D geometric morphometric dataset. In particular, we quantify the amount of error associated with combining data from multiple devices and digitized by multiple operators and test for the presence of bias. We also extend these analyses to a dataset obtained with a recently developed automated method, which does not require human‐digitized landmarks. Further, we analyze how measurement error affects estimates of phylogenetic signal and how its effect compares with the effect of phylogenetic uncertainty. We show that measurement error can be substantial when combining surface models produced by different devices and even more among landmarks digitized by different operators. We also document the presence of small, but significant, amounts of nonrandom error (i.e., bias). Measurement error is heavily reduced by excluding landmarks that are difficult to digitize. The automated method we tested had low levels of error, if used in combination with a procedure for dimensionality reduction. Estimates of phylogenetic signal can be more affected by measurement error than by phylogenetic uncertainty. Our results generally highlight the importance of landmark choice and the usefulness of estimating measurement error. Further, measurement error may limit comparisons of estimates of phylogenetic signal across studies if these have been performed using different devices or by different operators. Finally, we also show how widely held assumptions do not always hold true, particularly that measurement error affects inference more at a shallower phylogenetic scale and that automated methods perform worse than human digitization.     

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.     

Phylogenetic niche conservatism, phylogenetic signal and the relationship between phylogenetic relatedness and ecological similarity among species

Ecologists are increasingly adopting an evolutionary perspective, and in recent years, the idea that closely related species are ecologically similar has become widespread. In this regard, phylogenetic signal must be distinguished from phylogenetic niche conservatism. Phylogenetic niche conservatism results when closely related species are more ecologically similar that would be expected based on their phylogenetic relationships; its occurrence suggests that some process is constraining divergence among closely related species. In contrast, phylogenetic signal refers to the situation in which ecological similarity between species is related to phylogenetic relatedness; this is the expected outcome of Brownian motion divergence and thus is necessary, but not sufficient, evidence for the existence of phylogenetic niche conservatism. Although many workers consider phylogenetic niche conservatism to be common, a review of case studies indicates that ecological and phylogenetic similarities often are not related. Consequently, ecologists should not assume that phylogenetic niche conservatism exists, but rather should empirically examine the extent to which it occurs.