Assessing phylogenetic signal with measurement error: a comparison of mantel tests, blomberg et Al.'s k, and phylogenetic distograms

In macroevolutionary studies, different approaches are commonly used to measure phylogenetic signal-the tendency of related taxa to resemble one another-including the K statistic and the Mantel test. The latter was recently criticized for lacking statistical power. Using new simulations, we show that the power of the Mantel test depends on the metrics used to define trait distances and phylogenetic distances between species. Increasing power is obtained by lowering variance and increasing negative skewness in interspecific distances, as obtained using Euclidean trait distances and the complement of Abouheif proximity as a phylogenetic distance. We show realistic situations involving "measurement error" due to intraspecific variability where the Mantel test is more powerful to detect a phylogenetic signal than a permutation test based on the K statistic. We highlight limitations of the K-statistic (univariate measure) and show that its application should take into account measurement errors using repeated measures per species to avoid estimation bias. Finally, we argue that phylogenetic distograms representing Euclidean trait distance as a function of the square root of patristic distance provide an insightful representation of the phylogenetic signal that can be used to assess both the impact of measurement error and the departure from a Brownian evolution model.     

Assessing among‐lineage variability in phylogenetic imputation of functional trait datasets

Phylogenetic imputation has recently emerged as a potentially powerful tool for predicting missing data in functional traits datasets. As such, understanding the limitations of phylogenetic modelling in predicting trait values is critical if we are to use them in subsequent analyses. Previous studies have focused on the relationship between phylogenetic signal and clade‐level prediction accuracy, yet variability in prediction accuracy among individual tips of phylogenies remains largely unexplored. Here, we used simulations of trait evolution along the branches of phylogenetic trees to show how the accuracy of phylogenetic imputations is influenced by the combined effects of 1) the amount of phylogenetic signal in the traits and 2) the branch length of the tips to be imputed. Specifically, we conducted cross‐validation trials to estimate the variability in prediction accuracy among individual tips on the phylogenies (hereafter ‘tip‐level accuracy’). We found that under a Brownian motion model of evolution (BM, Pagel't λ = 1), tip‐level accuracy rapidly decreased with increasing tip branch‐lengths, and only tips of approximately 10% or less of the total height of the trees showed consistently accurate predictions (i.e. cross‐validation R‐squared >0.75). When phylogenetic signal was weak, the effect of tip branch‐length was reduced, becoming negligible for traits simulated with λ < 0.7, where accuracy was in any case low. Our study shows that variability in prediction accuracy among individual tips of the phylogeny should be considered when evaluating the reliability of phylogenetically imputed trait values. To address this challenge, we describe a Monte Carlo‐based method that allows one to estimate the expected tip‐level accuracy of phylogenetic predictions for continuous traits. Our approach identifies gaps in functional trait datasets for which phylogenetic imputation performs poorly, and will help ecologists to design more efficient trait collection campaigns by focusing resources on lineages whose trait values are more uncertain.     

phylosem: A fast and simple R package for phylogenetic inference and trait imputation using phylogenetic structural equation models

Phylogenetic comparative methods (PCMs) can be used to study evolutionary relationships and trade-offs among species traits. Analysts using PCM may want to (1) include latent variables, (2) estimate complex trait interdependencies, (3) predict missing trait values, (4) condition predicted traits upon phylogenetic correlations and (5) estimate relationships as slope parameters that can be compared with alternative regression methods. The Comprehensive R Archive Network (CRAN) includes well-documented software for phylogenetic linear models (phylolm), phylogenetic path analysis (phylopath), phylogenetic trait imputation (Rphylopars) and structural equation models (sem), but none of these can simultaneously accomplish all five analytical goals. We therefore introduce a new package phylosem for phylogenetic structural equation models (PSEM) and summarize features and interface. We also describe new analytical options, where users can specify any combination of Ornstein-Uhlenbeck, Pagel's-δ and Pagel's-λ transformations for species covariance. For the first time, we show that PSEM exactly reproduces estimates (and standard errors) for simplified cases that are feasible in sem, phylopath, phylolm and Rphylopars and demonstrate the approach by replicating a well-known case study involving trade-offs in plant energy budgets.     

Australian Tropical and Subtropical Rain Forest Community Assembly: Phylogeny,Functional Biogeography,and Environmental Gradients

To compare community assemblage patterns in tropical northeastern and subtropical central eastern Australia across selected gradients and scales, we tested the relationship of species traits with phylogenetic structure, and niche breadth. We considered phylogenetic relationships across current‐day species in assemblages in relation to rain forest species pool sizes, and trait values along gradients including elevation and latitude. Trait values were quantified across scales for seed size, leaf area, wood density and maximum height at maturity for 1137 species and 596 assemblages using trait gradient analysis (TGA). Local assemblages of subtropical species had narrower trait ranges, and higher niche breadth values than corresponding assemblages of tropical species. Leaf size and seed size increased at low latitudes, and community phylogenetic structure was most strongly correlated with seed traits in the subtropics, reflecting dispersal and re‐colonization processes. Elevation accounted for little of the variance in community phylogenetic structure or trait variation across local and regional scales. Stable moist forest areas retained many species from ancestral rain forest lineages across a range of temporally conserved habitats; species within assemblages were less related; and rain forest assemblages had higher functional diversity, but lower niche breadth. This suggests that on average, assemblages of species in stable areas had greater trait variation and narrower distributions. Historic and recent rain forest contraction and re‐expansion can result in recolonized areas that are dominated by species that are more related (phylogenetically) than by chance, have smaller, widely dispersed seeds, and greater niche breadth (broader distributions).     

Trait similarity, shared ancestry and the structure of neighbourhood interactions in a subtropical wet forest: implications for community assembly

Ecology Letters (2010) 13: 1503-1514 ABSTRACT: The phylogenetic structure and distribution of functional traits in a community can provide insights into community assembly processes. However, these insights are sensitive to the spatial scale of analysis. Here, we use spatially explicit, neighbourhood models of tree growth and survival for 19 tree species, a highly resolved molecular phylogeny and information on eight functional traits to quantify the relative efficacy of functional similarity and shared ancestry in describing the effects of spatial interactions between tree species on demographic rates. We also assess the congruence of these results with observed phylogenetic and functional structure in the neighbourhoods of live and dead trees. We found strong support for models in which the effects of spatial neighbourhood interactions on tree growth and survival were scaled to species-specific mean functional trait values (e.g., wood specific gravity, leaf succulence and maximum height) but not to phylogenetic distance. The weak phylogenetic signal in functional trait data allowed us to independently interpret the static neighbourhood functional and phylogenetic patterns. We observed greater functional trait similarity in the neighbourhoods of live trees relative to those of dead trees suggesting that environmental filtering is the major force structuring this tree community at this scale while competitive interactions play a lesser role.     

The influence of variability in species trait data on community‐level ecological prediction and inference

Species trait data have been used to predict and infer ecological processes and the responses of biological communities to environmental changes. It has also been suggested that, in lieu of trait, data niche differences can be inferred from phylogenetic distance. It remains unclear how variation in trait data may influence the strength and character of ecological inference. Using species‐level trait data in community ecology assumes intraspecific variation is small in comparison with interspecific variation. Intraspecific variation across species ranges or within populations may lead to variability in trait data derived from different scales (i.e., local or regional) and methods (i.e., mean or maximum values). Variation in trait data across species can affect community‐level relationships. I examined variability in body size, a key trait often measured across taxa. I collected 12 metrics of fish species length (including common and maximum values) for 40 species from literature, online databases, museum collections, and field data. I then tested whether different metrics of fish length could consistently predict observed species range boundary shifts and the impacts of an introduced predator on inland lake fish communities across Ontario, Canada. I also investigated whether phylogenetic signal, an indicator of niche‐conservativism, changed among measures. I found strong correlations between length metrics and limited variation across metrics. Accordingly, length was a consistently significant predictor of the response of fish communities to environmental change. Additionally, I found significant evidence of phylogenetic signal in fish length across metrics. Limited variation in length across metrics (within species), in comparison with variation within metrics (across species), made fish species length a reliable predictor at a community‐level. When considering species‐level trait data from different sources, researchers should examine the potential influence of intraspecific trait variation on data derived by different metrics and at different scales.     

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.     

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.     

Phylogenetic signal, evolutionary process, and rate

A recent advance in the phylogenetic comparative analysis of continuous traits has been explicit, model-based measurement of "phylogenetic signal" in data sets composed of observations collected from species related by a phylogenetic tree. Phylogenetic signal is a measure of the statistical dependence among species' trait values due to their phylogenetic relationships. Although phylogenetic signal is a measure of pattern (statistical dependence), there has nonetheless been a widespread propensity in the literature to attribute this pattern to aspects of the evolutionary process or rate. This may be due, in part, to the perception that high evolutionary rate necessarily results in low phylogenetic signal; and, conversely, that low evolutionary rate or stabilizing selection results in high phylogenetic signal (due to the resulting high resemblance between related species). In this study, we use individual-based numerical simulations on stochastic phylogenetic trees to clarify the relationship between phylogenetic signal, rate, and evolutionary process. Under the simplest model for quantitative trait evolution, homogeneous rate genetic drift, there is no relation between evolutionary rate and phylogenetic signal. For other circumstances, such as functional constraint, fluctuating selection, niche conservatism, and evolutionary heterogeneity, the relationship between process, rate, and phylogenetic signal is complex. For these reasons, we recommend against interpretations of evolutionary process or rate based on estimates of phylogenetic signal.     

Phylogenetic limiting similarity and competitive exclusion

One of the oldest ecological hypotheses, proposed by Darwin, suggests that the struggle for existence is stronger between more closely related species. Despite its long history, the validity of this phylogenetic limiting similarity hypothesis has rarely been examined. Here we provided a formal experimental test of the hypothesis using pairs of bacterivorous protist species in a multigenerational experiment. Consistent with the hypothesis, both the frequency and tempo of competitive exclusion, and the reduction in the abundance of inferior competitors, increased with increasing phylogenetic relatedness of the competing species. These results were linked to protist mouth size, a trait potentially related to resource use, exhibiting a significant phylogenetic signal. The likelihood of coexistence, however, was better predicted by phylogenetic relatedness than trait similarity of the competing species. Our results support phylogenetic relatedness as a useful predictor of the outcomes of competitive interactions in ecological communities.     

A phylogenetic analysis of macroevolutionary patterns in fermentative yeasts

When novel sources of ecological opportunity are available, physiological innovations can trigger adaptive radiations. This could be the case of yeasts (Saccharomycotina), in which an evolutionary novelty is represented by the capacity to exploit simple sugars from fruits (fermentation). During adaptive radiations, diversification and morphological evolution are predicted to slow‐down after early bursts of diversification. Here, we performed the first comparative phylogenetic analysis in yeasts, testing the “early burst” prediction on species diversification and also on traits of putative ecological relevance (cell‐size and fermentation versatility). We found that speciation rates are constant during the time‐range we considered (ca., 150 millions of years). Phylogenetic signal of both traits was significant (but lower for cell‐size), suggesting that lineages resemble each other in trait‐values. Disparity analysis suggested accelerated evolution (diversification in trait values above Brownian Motion expectations) in cell‐size. We also found a significant phylogenetic regression between cell‐size and fermentation versatility (R² = 0.10), which suggests correlated evolution between both traits. Overall, our results do not support the early burst prediction both in species and traits, but suggest a number of interesting evolutionary patterns, that warrant further exploration. For instance, we show that the Whole Genomic Duplication that affected a whole clade of yeasts, does not seems to have a statistically detectable phenotypic effect at our level of analysis. In this regard, further studies of fermentation under common‐garden conditions combined with comparative analyses are warranted.     

What factors potentially influence the ability of phylogenetic distance to predict trait dispersion in a temperate forest?

Although phylogenetic‐based approaches have been frequently used to infer ecological processes, they have been increasingly criticized in recent years. To date, the factors that affect phylogenetic signals and further the ability of phylogenetic distance to predict trait dispersion have been assumed but not empirically tested. Therefore, we investigate which factors potentially influence the ability of phylogenetic distance to predict trait dispersion. We quantified the phylogenetic and trait dispersions across size classes and spatial scales in a 9‐ha old‐growth temperate forest dynamics plot in northeastern China. Phylogenetic signals at the community level were generally lower than those at the species pool level, and phylogenetically clustered communities showed lower phylogenetic signals than did overdispersed communities. This pattern might explain the other three findings of our study. First, phylogenetically overdispersed communities performed better at predicting trait dispersion than did clustered communities. Second, the mean pairwise distance (MPD)‐based metric exhibited a stronger correlation with trait dispersion than did the mean nearest taxon distance (MNTD)‐based metric. Finally, the MNTD‐based metric showed that the prediction accuracy for trait dispersion decreased with increasing spatial scales, whereas its effects were weak on the MPD‐based metric. In addition, phylogeny could not determine the dispersions of all functional axes but was able to predict certain traits depending on whether they were evolutionarily conserved. These results were conserved when we removed the effects of space and environment. Our findings highlighted that using phylogenetic distance as a proxy of trait similarity might work in a temperate forest depending on the species in local communities sampled from total pool as well as the traits measured. Utilizing these rules, we should rethink the conclusions of previous studies that were based on phylogenetic‐based approaches.     

Phylogenetic patterns of trait and trait plasticity evolution: Insights from amphibian embryos

Environmental variation favors the evolution of phenotypic plasticity. For many species, we understand the costs and benefits of different phenotypes, but we lack a broad understanding of how plastic traits evolve across large clades. Using identical experiments conducted across North America, we examined prey responses to predator cues. We quantified five life‐history traits and the magnitude of their plasticity for 23 amphibian species/populations (spanning three families and five genera) when exposed to no cues, crushed‐egg cues, and predatory crayfish cues. Embryonic responses varied considerably among species and phylogenetic signal was common among the traits, whereas phylogenetic signal was rare for trait plasticities. Among trait‐evolution models, the Ornstein–Uhlenbeck (OU) model provided the best fit or was essentially tied with Brownian motion. Using the best fitting model, evolutionary rates for plasticities were higher than traits for three life‐history traits and lower for two. These data suggest that the evolution of life‐history traits in amphibian embryos is more constrained by a species’ position in the phylogeny than is the evolution of life history plasticities. The fact that an OU model of trait evolution was often a good fit to patterns of trait variation may indicate adaptive optima for traits and their plasticities.     

Phylogenetic imputation of plant functional trait databases

Continental‐scale maps of plant functional diversity are a fundamental piece of data of interest to ecosystem modelers and ecologists, yet such maps have been exceedingly hard to generate. The large effort to compile global plant functional trait databases largely for the purpose of mapping and analyzing the spatial distribution of function has resulted in very sparse data matrices thereby limiting progress. Identifying robust methodologies to gap fill or impute trait values in these databases is an important objective. Here I argue that existing statistical tools from phylogenetic comparative methods can be used to rapidly impute values into global plant functional trait databases due to the large amount of phylogenetic signal often in trait data. In particular, statistical models of phylogenetic signal in traits can be generated from existing data and used to predict missing values of closely related species often with a high degree of accuracy thereby facilitating the continental‐scale mapping of plant function. Despite the promise of this approach, I also discuss potential pitfalls and future challenges that will need to be addressed.     

Neutral lipid fatty acid composition as trait and constraint in Collembola evolution

Functional traits determine the occurrence of species along environmental gradients and their coexistence with other species. Understanding how traits evolved among coexisting species helps to infer community assembly processes. We propose fatty acid composition in consumer tissue as a functional trait related to both food resources and physiological functions of species. We measured phylogenetic signal in fatty acid profiles of 13 field‐sampled Collembola (springtail) species and then combined the data with published fatty acid profiles of another 24 species. Collembola fatty acid profiles generally showed phylogenetic signal, with related species resembling each other. Long‐chain polyunsaturated fatty acids, related to physiological functions, demonstrated phylogenetic signal. In contrast, most food resource biomarker fatty acids and the ratios between bacterial, fungal, and plant biomarker fatty acids exhibited no phylogenetic signal. Presumably, fatty acids related to physiological functions have been constrained during Collembola evolutionary history: Species with close phylogenetic affinity experienced similar environments during divergence, while niche partitioning in food resources among closely related species favored species coexistence. Measuring phylogenetic signal in ecologically relevant traits of coexisting species provides an evolutionary perspective to contemporary assembly processes of ecological communities. Integrating phylogenetic comparative methods with community phylogenetic and trait‐based approaches may compensate for the limitations of each method when used alone and improve understanding of processes driving and maintaining assembly patterns.     

A new bayesian method for fitting evolutionary models to comparative data with intraspecific variation

Phylogenetic comparative methods that incorporate intraspecific variability are relatively new and, so far, not especially widely used in empirical studies. In the present short article we will describe a new Bayesian method for fitting evolutionary models to comparative data that incorporates intraspecific variability. This method differs from an existing likelihood-based approach in that it requires no a priori inference about species means and variances; rather it takes phenotypic values from individuals and a phylogenetic tree as input, and then samples species means and variances, along with the parameters of the evolutionary model, from their joint posterior probability distribution. One of the most novel and intriguing attributes of this approach is that jointly sampling the species means with the evolutionary model parameters means that the model and tree can influence our estimates of species mean trait values, not just the reverse. In the present implementation, we first apply this method to the most widely used evolutionary model for continuously valued phenotypic trait data (Brownian motion). However, the general approach has broad applicability, which we illustrate by also fitting the λ model, another simple model for quantitative trait evolution on a phylogeny. We test our approach via simulation and by analyzing two empirical datasets obtained from the literature. Finally, we have implemented the methods described herein in a new function for the R statistical computing environment, and this function will be distributed as part of the 'phytools' R library.     

Common Ancestry Is a Poor Predictor of Competitive Traits in Freshwater Green Algae

Phytoplankton species traits have been used to successfully predict the outcome of competition, but these traits are notoriously laborious to measure. If these traits display a phylogenetic signal, phylogenetic distance (PD) can be used as a proxy for trait variation. We provide the first investigation of the degree of phylogenetic signal in traits related to competition in freshwater green phytoplankton. We measured 17 traits related to competition and tested whether they displayed a phylogenetic signal across a molecular phylogeny of 59 species of green algae. We also assessed the fit of five models of trait evolution to trait variation across the phylogeny. There was no significant phylogenetic signal for 13 out of 17 ecological traits. For 7 traits, a non-phylogenetic model provided the best fit. For another 7 traits, a phylogenetic model was selected, but parameter values indicated that trait variation evolved recently, diminishing the importance of common ancestry. This study suggests that traits related to competition in freshwater green algae are not generally well-predicted by patterns of common ancestry. We discuss the mechanisms by which the link between phylogenetic distance and phenotypic differentiation may be broken.     

cati: an R package using functional traits to detect and quantify multi‐level community assembly processes

Community ecologists are active in describing species by their functional traits, quantifying the functional structure of plant and animal assemblages and inferring community assembly processes with null‐model analyses of trait distribution and functional diversity indices. Intraspecific variation in traits and effects of spatial scale are potentially important in these analyses. Here, we introduce the R package cati (Community Assembly by Traits: Individuals and beyond) available on CRAN, for the analysis of community assembly with functional traits. cati builds on a recent approach to community assembly that explicitly incorporates individual differences in community assembly analyses and decomposes phenotypic variations across scales and organizational levels, based on three phenotypic variance ratios, termed the T‐statistics. More generally, the cati package 1) calculates a variety of single‐trait and multi‐trait indices from interspecific and intraspecific trait measures; 2) it partitions functional trait variation among spatial and taxonomic levels; 3) it implements a palette of flexible null models for detecting non‐random patterns of functional traits. These patterns can be used to draw inferences about hypotheses of community assembly such as environmental filtering and species interactions. The basic input for cati is a data frame in which columns are traits, rows are species or individuals, and entries are the measured trait values. The cati package can also incorporate a square distance matrix into analyses, which could include phylogenetic or genetic distances among individuals or species. Users select from a variety of functional trait metrics and analyze these relative to a null model that specifies trait distributions in a regional source pool.     

PHYLOGENETIC CONSTRAINTS IN KEY FUNCTIONAL TRAITS BEHIND SPECIES’ CLIMATE NICHES: PATTERNS OF DESICCATION AND COLD RESISTANCE ACROSS 95 DROSOPHILA SPECIES

Species distributions are often constrained by climatic tolerances that are ultimately determined by evolutionary history and/or adaptive capacity, but these factors have rarely been partitioned. Here, we experimentally determined two key climatic niche traits (desiccation and cold resistance) for 92–95 Drosophila species and assessed their importance for geographic distributions, while controlling for acclimation, phylogeny, and spatial autocorrelation. Employing an array of phylogenetic analyses, we documented moderate‐to‐strong phylogenetic signal in both desiccation and cold resistance. Desiccation and cold resistance were clearly linked to species distributions because significant associations between traits and climatic variables persisted even after controlling for phylogeny. We used different methods to untangle whether phylogenetic signal reflected phylogenetically related species adapted to similar environments or alternatively phylogenetic inertia. For desiccation resistance, weak phylogenetic inertia was detected; ancestral trait reconstruction, however, revealed a deep divergence that could be traced back to the genus level. Despite drosophilids’ high evolutionary potential related to short generation times and high population sizes, cold resistance was found to have a moderate‐to‐high level of phylogenetic inertia, suggesting that evolutionary responses are likely to be slow. Together these findings suggest species distributions are governed by evolutionarily conservative climate responses, with limited scope for rapid adaptive responses to future climate change.     

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.