CONDUCTING PHYLOGENETIC COMPARATIVE STUDIES WHEN THE PHYLOGENY IS NOT KNOWN

A method is proposed to conduct phylogenetic analyses of comparative or interspecific data when the true phylogeny is not known. Standard models of speciation and/or extinction or other methods are used to generate a sample from the set of all possible phylogenies for the measured species. The comparative data are then analyzed on each of the possible trees to obtain a distribution of possible evolutionary statistics for these data. The mean of this distribution is proposed as a reasonable estimate of the true evolutionary statistic of interest. Ways of obtaining confidence intervals and of developing hypothesis tests for this mean statistic are also proposed. The method can be used with any comparative method or phylogenetic analysis technique when phylogenetic relationships among species are not known or when branch lengths for a phylogeny in units of expected character change (as required by most methods) are not available. Computer programs to conduct the analyses are available on request.     

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.     

Recent developments in the analysis of comparative data

Comparative methods can be used to test ideas about adaptation by identifying cases of either parallel or convergent evolutionary change across taxa. Phylogenetic relationships must be known or inferred if comparative methods are to separate the cross-taxonomic covariation among traits associated with evolutionary change from that attributable to common ancestry. Only the former can be used to test ideas linking convergent or parallel evolutionary change to some aspect of the environment. The comparative methods that are currently available differ in how they manage the effects brought about by phylogenetic relationships. One method is applicable only to discrete data, and uses cladistic techniques to identify evolutionary events that depart from phylogenetic trends. Techniques for continuous variables attempt to control for phylogenetic effects in a variety of ways. One method examines the taxonomic distribution of variance to identify the taxa within which character variation is small. The method assumes that taxa with small amounts of variation are those in which little evolutionary change has occurred, and thus variation is unlikely to be independent of ancestral trends. Analyses are then concentrated among taxa that show more variation, on the assumption that greater evolutionary change in the character has taken place. Several methods estimate directly the extent to which ancestry can predict the observed variation of a character, and subtract the ancestral effect to reveal variation of phylogeny. Yet another can remove phylogenetic effects if the true phylogeny is known. One class of comparative methods controls for phylogenetic effects by searching for comparative trends within rather than across taxa. With current knowledge of phylogenies, there is a trade-off in the choice of a comparative method: those that control phylogenetic effects with greater certainty are either less applicable to real data, or they make restrictive or untestable assumptions. Those that rely on statistical patterns to infer phylogenetic effects may not control phylogeny as efficiently but are more readily applied to existing data sets.     

Advances in the use of DNA barcodes to build a community phylogeny for tropical trees in a Puerto Rican forest dynamics plot

Background

Species number, functional traits, and phylogenetic history all contribute to characterizing the biological diversity in plant communities. The phylogenetic component of diversity has been particularly difficult to quantify in species-rich tropical tree assemblages. The compilation of previously published (and often incomplete) data on evolutionary relationships of species into a composite phylogeny of the taxa in a forest, through such programs as Phylomatic, has proven useful in building community phylogenies although often of limited resolution. Recently, DNA barcodes have been used to construct a robust community phylogeny for nearly 300 tree species in a forest dynamics plot in Panama using a supermatrix method. In that study sequence data from three barcode loci were used to generate a well-resolved species-level phylogeny.

Methodology/Principal Findings

Here we expand upon this earlier investigation and present results on the use of a phylogenetic constraint tree to generate a community phylogeny for a diverse, tropical forest dynamics plot in Puerto Rico. This enhanced method of phylogenetic reconstruction insures the congruence of the barcode phylogeny with broadly accepted hypotheses on the phylogeny of flowering plants (i.e., APG III) regardless of the number and taxonomic breadth of the taxa sampled. We also compare maximum parsimony versus maximum likelihood estimates of community phylogenetic relationships as well as evaluate the effectiveness of one- versus two- versus three-gene barcodes in resolving community evolutionary history.

Conclusions/Significance

As first demonstrated in the Panamanian forest dynamics plot, the results for the Puerto Rican plot illustrate that highly resolved phylogenies derived from DNA barcode sequence data combined with a constraint tree based on APG III are particularly useful in comparative analysis of phylogenetic diversity and will enhance research on the interface between community ecology and evolution.     

INTEGRATING FOSSILS WITH MOLECULAR PHYLOGENIES IMPROVES INFERENCE OF TRAIT EVOLUTION

Comparative biologists often attempt to draw inferences about tempo and mode in evolution by comparing the fit of evolutionary models to phylogenetic comparative data consisting of a molecular phylogeny with branch lengths and trait measurements from extant taxa. These kinds of approaches ignore historical evidence for evolutionary pattern and process contained in the fossil record. In this article, we show through simulation that incorporation of fossil information dramatically improves our ability to distinguish among models of quantitative trait evolution using comparative data. We further suggest a novel Bayesian approach that allows fossil information to be integrated even when explicit phylogenetic hypotheses are lacking for extinct representatives of extant clades. By applying this approach to a comparative dataset comprising body sizes for caniform carnivorans, we show that incorporation of fossil information not only improves ancestral state estimates relative to those derived from extant taxa alone, but also results in preference of a model of evolution with trend toward large body size over alternative models such as Brownian motion or Ornstein–Uhlenbeck processes. Our approach highlights the importance of considering fossil information when making macroevolutionary inference, and provides a way to integrate the kind of sparse fossil information that is available to most evolutionary biologists.     

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.     

Reanalysis of oviposition and development rates in the Phytoseiidae using a phylogenetic autoregressive method

Life history patterns are usually identified by comparisons of extant species. Because of inferences regarding phylogenetic constraints, comparative data are often not statistically independent. In order to remove phylogenetic patterns embedded in life history data completely, we adopted a phylogenetic autoregressive method to reanalyse a data set of the ovipositional and developmental rates of 45 Phytoseiidae species. We first calculated the phylogenetic correlation in relation to different taxonomic levels using Moran's I statistics. Significant and positive phylogenetic correlations were found at the subgenus and subfamily levels. This indicates that some variation in both of these life-history traits could be accounted for by phylogeny. Phylogenetic associations, therefore, were removed by a phylogenetic autoregressive method. Using corrected data from this method, the specific components of the ovipositional rate are positively correlated with the specific components of th e developmental rate. The method that we have used obtains the same conclusion as others but differs from the phylogenetic effect in the way that it influences the relationship between comparative data. Because of no data reduction in the phylogenetic autoregressive method, the specific components are more useful than the mean values derived from the higher taxonomic nodes for testing ecological and evolutionary hypotheses about life history patterns. © Rapid Science Ltd. 1998     

Factors influencing changes in trait correlations across species after using phylogenetic independent contrasts

Comparative interspecific data sets have been analyzed routinely by phylogenetic methods, generally using Felsenstein’s phylogenetic independent contrasts (PIC) method. However, some authors have suggested that it may not be always necessary to incorporate phylogenetic information into statistical analyses of comparative data due to the low influence of shared history on the distribution of␣character states. The main goal of this paper was to undertake a comparison of results from non-phylogenetic Pearson correlation of tip values (TIPs) and phylogenetic independent contrasts analyses (PICs), using 566 correlation coefficients derived from 65 published papers. From each study we collected the following data: taxonomic group, number of species, type of phylogeny, number of polytomies in the phylogenetic tree, if branch length was transformed or not, trait types, the original correlation coefficient between the traits (TIPs) and the correlation coefficient between the traits using the independent contrasts method (PICs). The slope estimated from a regression of PIC correlations on TIP correlations was lower than one, and a paired t-test showed that correlations from PIC are significantly smaller than those obtained by TIP. Thus, PIC analyses tend to decrease the correlation between traits and usually increases the P-value and, thus, favoring the acceptance of the null hypothesis. Multiple factors, including taxonomic group, trait type and use of branch length transformations affected the change in decision regarding the acceptance of the null hypotheses and differences between PIC and TIP results. Due to the variety of factors affecting the differences between results provided by these methods, we suggest that comparative methods should be applied as a conservative approach to cross-species studies. Despite difficulties in quantifying precisely why these factors affect the differences between PIC and TIP, we also suggest that a better evaluation of evolutionary models underlying trait evolution is still necessary in this context and might explain some of the observed patterns.     

Genome-based phylogeny of dsDNA viruses by a novel alignment-free method

Sequence alignment is not directly applicable to whole genome phylogeny since several events such as rearrangements make full length alignments impossible. Here, a novel alignment-free method derived from the standpoint of information theory is proposed and used to construct the whole-genome phylogeny for a population of viruses from 13 viral families comprising 218 dsDNA viruses. The method is based on information correlation (IC) and partial information correlation (PIC). We observe that (i) the IC-PIC tree segregates the population into clades, the membership of each is remarkably consistent with biologist's systematics only with little exceptions; (ii) the IC-PIC tree reveals potential evolutionary relationships among some viral families; and (iii) the IC-PIC tree predicts the taxonomic positions of certain “unclassified” viruses. Our approach provides a new way for recovering the phylogeny of viruses, and has practical applications in developing alignment-free methods for sequence classification.     

ARE PINNIPEDS FUNCTIONALLY DIFFERENT FROM FISSIPED CARNIVORES? THE IMPORTANCE OF PHYLOGENETIC COMPARATIVE ANALYSES

Abstract.— It is widely assumed that adaptations to an aquatic lifestyle are so profound as to produce only obvious differences between pinnipeds and the remaining, largely terrestrial carnivore species ("fissipeds"). Thus, comparative studies of the order Carnivora routinely examine these groups independently. This approach is invalid for two reasons. First, fissipeds are a paraphyletic assemblage, which raises the general issue of when it is appropriate to ignore monophyly as a criterion for inclusion in comparative studies. Second, the claim that most functional characters (beyond a few undoubted characteristic features) are different in pinnipeds and fissipeds has never been quantitatively examined, nor with phylogenetic comparative methods. We test for possible differences between these two groups in relation to 20 morphological, life-history, physiological, and ecological variables. Comparisons employed the method of independent contrasts based on a complete and dated species-level phylogeny of the extant Carnivora. Pinnipeds differ from fissipeds only through evolutionary grade shifts in a limited number of life-history traits: litter weight (vs. gestation length), birth weight, and age of eyes opening (both vs. size). Otherwise, pinnipeds display the same rate of evolution as phylogenetically equivalent fissiped taxa for all variables. Overall functional differences between pinnipeds and fissipeds appear to have been overstated and may be no greater than those among major fissiped groups. Recognition of this fact should lead to a more complete understanding of carnivore biology as a whole through more unified comparative tests. Comparative studies that do not include monophyletic groups for phylogenetically based comparative tests should be reconsidered.     

The phylogeny fallacy and the ontogeny fallacy

In 1990 Robert Lickliter and Thomas Berry identified the phylogeny fallacy, an empirically untenable dichotomy between proximate and evolutionary causation, which locates proximate causes in the decoding of ‘genetic programs’, and evolutionary causes in the historical events that shaped these programs. More recently, Lickliter and Hunter Honeycutt (Psychol Bull 129:819–835, 2003a) argued that Evolutionary Psychologists commit this fallacy, and they proposed an alternative research program for evolutionary psychology. For these authors the phylogeny fallacy is the proximate/evolutionary distinction itself, which they argue constitutes a misunderstanding of development, and its role in the evolutionary process. In this article I argue that the phylogeny fallacy should be relocated to an error of reasoning that this causal framework sustains: the conflation of proximate and evolutionary explanation. Having identified this empirically neutral form of the phylogeny fallacy, I identify its mirror image, the ontogeny fallacy. Through the lens of these fallacies I attempt to solve several outstanding problems in the debate that ensued from Lickliter and Honeycutt’s provocative article.     

Canonical phylogenetic ordination

A phylogenetic comparative method is proposed for estimating historical effects on comparative data using the partitions that compose a cladogram, i.e., its monophyletic groups. Two basic matrices, Y and X, are defined in the context of an ordinary linear model. Y contains the comparative data measured over t taxa. X consists of an initial tree matrix that contains all the xj monophyletic groups (each coded separately as a binary indicator variable) of the phylogenetic tree available for those taxa. The method seeks to define the subset of groups, i.e., a reduced tree matrix, that best explains the patterns in Y. This definition is accomplished via regression or canonical ordination (depending on the dimensionality of Y) coupled with Monte Carlo permutations. It is argued here that unrestricted permutations (i.e., under an equiprobable model) are valid for testing this specific kind of groupwise hypothesis. Phylogeny is either partialled out or, more properly, incorporated into the analysis in the form of component variation. Direct extensions allow for testing ecomorphological data controlled by phylogeny in a variation partitioning approach. Currently available statistical techniques make this method applicable under most univariate/multivariate models and metrics; two-way phylogenetic effects can be estimated as well. The simplest case (univariate Y), tested with simulations, yielded acceptable type I error rates. Applications presented include examples from evolutionary ethology, ecology, and ecomorphology. Results showed that the new technique detected previously overlooked variation clearly associated with phylogeny and that many phylogenetic effects on comparative data may occur at particular groups rather than across the entire tree.     

Adaptive constraints and the phylogenetic comparative method: a computer simulation test

Recently, the utility of modern phylogenetic comparative methods (PCMs) has been questioned because of the seemingly restrictive assumptions required by these methods. Although most comparative analyses involve traits thought to be undergoing natural or sexual selection, most PCMs require an assumption that the traits be evolving by less directed random processes, such as Brownian motion (BM). In this study, we use computer simulation to generate data under more realistic evolutionary scenarios and consider the statistical abilities of a variety of PCMs to estimate correlation coefficients from these data. We found that correlations estimated without taking phylogeny into account were often quite poor and never substantially better than those produced by the other tested methods. In contrast, most PCMs performed quite well even when their assumptions were violated. Felsenstein's independent contrasts (FIC) method gave the best performance in many cases, even when weak constraints had been acting throughout phenotypic evolution. When strong constraints acted in opposition to variance-generating (i.e., BM) forces, however, FIC correlation coefficients were biased in the direction of those BM forces. In most cases, all other PCMs tested (phylogenetic generalized least squares, phylogenetic mixed model, spatial autoregression, and phylogenetic eigenvector regression) yielded good statistical performance, regardless of the details of the evolutionary model used to generate the data. Actual parameter estimates given by different PCMs for each dataset, however, were occasionally very different from one another, suggesting that the choice among them should depend on the types of traits and evolutionary processes being considered.     

SIMULATION‐BASED LIKELIHOOD APPROACH FOR EVOLUTIONARY MODELS OF PHENOTYPIC TRAITS ON PHYLOGENY

Phylogenetic comparative methods (PCMs) have been used to test evolutionary hypotheses at phenotypic levels. The evolutionary modes commonly included in PCMs are Brownian motion (genetic drift) and the Ornstein–Uhlenbeck process (stabilizing selection), whose likelihood functions are mathematically tractable. More complicated models of evolutionary modes, such as branch‐specific directional selection, have not been used because calculations of likelihood and parameter estimates in the maximum‐likelihood framework are not straightforward. To solve this problem, we introduced a population genetics framework into a PCM, and here, we present a flexible and comprehensive framework for estimating evolutionary parameters through simulation‐based likelihood computations. The method does not require analytic likelihood computations, and evolutionary models can be used as long as simulation is possible. Our approach has many advantages: it incorporates different evolutionary modes for phenotypes into phylogeny, it takes intraspecific variation into account, it evaluates full likelihood instead of using summary statistics, and it can be used to estimate ancestral traits. We present a successful application of the method to the evolution of brain size in primates. Our method can be easily implemented in more computationally effective frameworks such as approximate Bayesian computation (ABC), which will enhance the use of computationally intensive methods in the study of phenotypic evolution.     

Novel Relationships Among Ten Fish Model Species Revealed Based on a Phylogenomic Analysis Using ESTs

The power of comparative phylogenomic analyses also depends on the amount of data that are included in such studies. We used expressed sequence tags (ESTs) from fish model species as a proof of principle approach in order to test the reliability of using ESTs for phylogenetic inference. As expected, the robustness increases with the amount of sequences. Although some progress has been made in the elucidation of the phylogeny of teleosts, relationships among the main lineages of the derived fish (Euteleostei) remain poorly defined and are still debated. We performed a phylogenomic analysis of a set of 42 of orthologous genes from 10 available fish model systems from seven different orders (Salmoniformes, Siluriformes, Cypriniformes, Tetraodontiformes, Cyprinodontiformes, Beloniformes, and Perciformes) of euteleostean fish to estimate divergence times and evolutionary relationships among those lineages. All 10 fish species serve as models for developmental, aquaculture, genomic, and comparative genetic studies. The phylogenetic signal and the strength of the contribution of each of the 42 orthologous genes were estimated with randomly chosen data subsets. Our study revealed a molecular phylogeny of higher-level relationships of derived teleosts, which indicates that the use of multiple genes produces robust phylogenies, a finding that is expected to apply to other phylogenetic issues among distantly related taxa. Our phylogenomic analyses confirm that the euteleostean superorders Ostariophysi and Acanthopterygii are monophyletic and the Protacanthopterygii and Ostariophysi are sister clades. In addition, and contrary to the traditional phylogenetic hypothesis, our analyses determine that killifish (Cyprinodontiformes), medaka (Beloniformes), and cichlids (Perciformes) appear to be more closely related to each other than either of them is to pufferfish (Tetraodontiformes). All 10 lineages split before or during the fragmentation of the supercontinent Pangea in the Jurassic. [Reviewing Editor: Dr. Rafael Zardoya]     

PHYLOGENETIC ANALYSES OF THE CORRELATED EVOLUTION OF CONTINUOUS CHARACTERS: A SIMULATION STUDY

We use computer simulation to compare the statistical properties of several methods that have been proposed for estimating the evolutionary correlation between two continuous traits, and define alternative evolutionary correlations that may be of interest. We focus on Felsenstein's (1985) method and some variations of it and on several “minimum evolution” methods (of which the procedure of Huey and Bennett [1987] is a special case), as compared with a nonphylogenetic correlation. The last, a simple correlation of trait values across the tips of a phylogeny, virtually always yields inflated Type I error rates, relatively low power, and relatively poor estimates of evolutionary correlations. We therefore cannot recommend its use. In contrast, Felsenstein's (1985) method yields acceptable significance tests, high power, and good estimates of what we term the input correlation and the standardized realized evolutionary correlation, given complete phylogenetic information and knowledge of the rate and mode of character change (e.g., gradual and proportional to time [“Brownian motion”] or punctuational, with change only at speciation events). Inaccurate branch length information may affect any method adversely, but only rarely does it cause Felsenstein's (1985) method to perform worse than do the others tested. Other proposed methods generally yield inflated Type I error rates and have lower power. However, certain minimum evolution methods (although not the specific procedure used by Huey and Bennett [1987]) often provide more accurate estimates of what we term the unstandardized realized evolutionary correlation, and their use is recommended when estimation of this correlation is desired. We also demonstrate how correct Type I error rates can be obtained for any method by reference to an empirical null distribution derived from computer simulations, and provide practical suggestions on choosing an analytical method, based both on the evolutionary correlation of interest and on the availability of branch lengths and knowledge of the model of evolutionary change appropriate for the characters being analyzed. Computer programs that implement the various methods and that will simulate (correlated) character evolution along a known phylogeny are available from the authors on request. These programs can be used to test the effectiveness of any new methods that might be proposed, and to check the generality of our conclusions with regard to other phylogenies.     

Evolutionary history shapes patterns of mutualistic benefit in Acacia–rhizobial interactions

The ecological and evolutionary factors that drive the emergence and maintenance of variation in mutualistic benefit (i.e., the benefits provided by one partner to another) in mutualistic symbioses are not well understood. In this study, we evaluated the role that host and symbiont phylogeny might play in determining patterns of mutualistic benefit for interactions among nine species of Acacia and 31 strains of nitrogen‐fixing rhizobial bacteria. Using phylogenetic comparative methods we compared patterns of variation in mutualistic benefit (host response to inoculation) to rhizobial phylogenies constructed from housekeeping and symbiosis genes; and a multigene host phylogeny. We found widespread genotype‐by‐genotype variation in patterns of plant growth. A relatively large component of this variation (21–28%) was strongly influenced by the interacting evolutionary histories of both partners, such that phylogenetically similar host species had similar growth responses when inoculated with phylogenetically similar rhizobia. We also found a relatively large nonphylogenetic effect for the average mutualistic benefit provided by rhizobia to plants, such that phylogenetic relatedness did not predict the overall benefit provided by rhizobia across all hosts. We conclude that phylogenetic relatedness should frequently predict patterns of mutualistic benefit in acacia‐rhizobial mutualistic interactions; but that some mutualistic traits also evolve independently of the phylogenies.     

Seed mass and germination in an alpine meadow on the eastern Tsinghai–Tibet plateau

In this study, we built up a database of 570 species from an alpine meadow on the eastern Tsinghai–Tibet plateau. We examined the correlation of seed mass and germination with phylogeny, habitat and altitude, and the relationship between seed mass and germination. We found that: habitats had no significant effects on seed mass and germinability, which was in accord with the former studies; there was a significant negative correlation between seed mass and altitude, as well as between germinability and altitude, which was opposite to most of the former studies; there was a significant negative correlation between seed mass and germinability, which was in contrast with other studies that have found a positive relationship, and seed mass could explain 24.1% of total variation in germinability; in GLM, family and genus accounted for 43.9% and 83.9% of total variation in seed mass, and 34.1% and 65.4% in germinability, respectively, thus, it was evident that seed mass and germinability were strongly related to phylogeny. We considered that seed mass and germination might be the result of both selective pressures over long-term ecological time and the constraints over long-standing evolutionary history of the taxonomic membership. We suggest that correlates of ecology and phylogeny should be taken into account in comparative studies on seed mass and germination among species.