Stability of characters and construction of phylogenetic trees.

Parsimony methods infer phylogenetic trees by minimizing number of character changes required to explain observed character states. From the perspective of applicability of parsimony methods, it is important to assess whether the characters used to infer phylogeny are likely to provide a correct tree. We introduce a graph theoretical characterization that helps to assess whether given set of characters is appropriate to use with parsimony methods. Given a set of characters and a set of taxa, we construct a network called character overlap graph. We show that the character overlap graph for characters that are appropriate to use in parsimony methods is characterized by significant under-representation of subnetworks known as holes, and provide a validation for this observation. This characterization explains success in constructing evolutionary trees using parsimony method for some characters (e.g., protein domains) and lack of such success for other characters (e.g., introns). In the latter case, the understanding of obstacles to applying parsimony methods in a direct way has lead us to a new approach for detecting inconsistent and/or noisy data. Namely, we introduce the concept of stable characters which is similar but less restrictive than the well known concept of pairwise compatible characters. Application of this approach to introns produces the evolutionary tree consistent with the Coelomata hypothesis.     

A comparative method for both discrete and continuous characters using the threshold model

The threshold model developed by Sewall Wright in 1934 can be used to model the evolution of two-state discrete characters along a phylogeny. The model assumes that there is a quantitative character, called liability, that is unobserved and that determines the discrete character according to whether the liability exceeds a threshold value. A Markov chain Monte Carlo algorithm is used to infer the evolutionary covariances of the liabilities for discrete characters, sampling liability values consistent with the phylogeny and with the observed data. The same approach can also be used for continuous characters by assuming that the tip species have values that have been observed. In this way, one can make a comparative-methods analysis that combines both discrete and continuous characters. Simulations are presented showing that the covariances of the liabilities are successfully estimated, although precision can be achieved only by using a large number of species, and we must always worry whether the covariances and the model apply throughout the group. An advantage of the threshold model is that the model can be straightforwardly extended to accommodate within-species phenotypic variation and allows an interface with quantitative-genetics models.     

Evolution of the insulin receptor family and receptor isoform expression in vertebrates

The molecular phylogeny of the vertebrate insulin receptor (IR) family was reconstructed under maximum likelihood (ML) to establish homologous relationships among its members. A sister group relationship between the orphan insulin-related receptor (IRR) and the insulin-like growth factor 1 receptor (IGF1R) to the exclusion of the IR obtained maximal bootstrap support. Although both IR and IGF1R were identified in all vertebrates, IRR could not be found in any teleost fish. The ancestral character states at each position of the receptor molecule were inferred for IR, IRR + IGF1R, and all 3 paralogous groups based on the recovered phylogeny using ML in order to determine those residues that could be important for the specific function of IR. For 18 residues, ancestral character state of IR was significantly distinct (probability >0.95) with respect to the corresponding inferred ancestral character states both of IRR + IGF1R and of all 3 vertebrate paralogs. Most of these IR distinct (shared derived) residues were located on the extracellular portion of the receptor (because this portion is larger and the rate of generation of IR shared derived sites is uniform along the receptor), suggesting that functional diversification during the evolutionary history of the family was largely generated modifying ligand affinity rather than signal transduction at the tyrosine kinase domain. In addition, 2 residues at positions 436 and 1095 of the human IR sequence were identified as radical cluster-specific sites in IRR + IGF1R. Both Ir and Irr have an extra exon (namely exon 11) with respect to Igf1r. We used the molecular phylogeny to infer the evolution of this additional exon. The Irr exon 11 can be traced back to amphibians, whereas we show that presence and alternative splicing of Ir exon 11 seems to be restricted exclusively to mammals. The highly divergent sequence of both exons and the reconstructed phylogeny of the vertebrate IR family strongly indicate that both exons were acquired independently by each paralog.     

From Haeckel’s phylogenetics and Hennig’s cladistics to the method of maximum likelihood: Advantages and limitations of modern and traditional approaches to phylogeny reconstruction

The maximum likelihood and Bayesian methods are based on parametric models of character evolution. They assume that if we know these models as well as distribution of character states in studied organisms, we can infer the probability of different phylogenetic trajectories leading from ancestors to modern forms. In fact, these methods are mathematized variants of the traditional Haeckel’s approach to phylogeny reconstruction. In contrast to classical and parsimonious cladistics, they infer phylogenies without such limitations as necessity of strictly dichotomous evolution, exclusion of plesiomorphic characters, and acceptance of only holophyletic taxa. They assume that evolution may be reticulated, any homologous characters—both apomorphic and plesiomorphic—can be used for inferring phylogenies, and interpretation of evolutionary lineages as taxa is optional. Thus, the main difference between the new and more traditional approaches to phylogeny reconstruction lies not in the characters used (molecular or morphological) but in the methodology of analysis. It must be admitted that a revolution began in phylogenetics 10–20 years ago. However, the fundamental changes in phylogenetics have been carried out so calmly and neatly by the people who started this revolution, that many systematists still do not realize their importance.     

PHYLOGENETIC ANALYSIS OF THE EVOLUTIONARY CORRELATION USING LIKELIHOOD

Many evolutionary processes can lead to a change in the correlation between continuous characters over time or on different branches of a phylogenetic tree. Shifts in genetic or functional constraint, in the selective regime, or in some combination thereof can influence both the evolution of continuous traits and their relation to each other. These changes can often be mapped on a phylogenetic tree to examine their influence on multivariate phenotypic diversification. We propose a new likelihood method to fit multiple evolutionary rate matrices (also called evolutionary variance–covariance matrices) to species data for two or more continuous characters and a phylogeny. The evolutionary rate matrix is a matrix containing the evolutionary rates for individual characters on its diagonal, and the covariances between characters (of which the evolutionary correlations are a function) elsewhere. To illustrate our approach, we apply the method to an empirical dataset consisting of two features of feeding morphology sampled from 28 centrarchid fish species, as well as to data generated via phylogenetic numerical simulations. We find that the method has appropriate type I error, power, and parameter estimation. The approach presented herein is the first to allow for the explicit testing of how and when the evolutionary covariances between characters have changed in the history of a group.     

FACTORS DETERMINING THE ACCURACY OF CLADOGRAM ESTIMATION: EVALUATION USING COMPUTER SIMULATION

We developed a simulation model of phylogenesis with which we generated a large number of phylogenies and associated data matrices. We examined the characteristics of these and evaluated the success of three taxonomic methods (Wagner parsimony, character compatibility, and UPGMA clustering) as estimators of phylogeny, paying particular attention to the consequences of changes in certain evolutionary assumptions: relative rate of evolution in three different evolutionary contexts (phyletic, parent lineage, and daughter lineage); relative rate of evolution in different directions (novel forward, convergent forward, or reverse); variation of evolutionary rates; and topology of the phylogenetic tree. Except for variation of evolutionary rates, all the evolutionary parameters that we controlled had significant effects on accuracy of phylogenetic reconstructions. Unexpectedly, the topology of the phylogeny was the most important single factor affecting accuracy; some phylogenies are more readily estimated than others for simply historical reasons. We conclude that none of the three estimation methods is very accurate, that the differences in accuracy among them are rather small, and that historical effects (the branching pattern of a phylogeny) may outweigh biological effects in determining the accuracy with which a phylogeny can be reconstructed.     

Morphological disparity and evolutionary rates of cranial and postcranial characters in sloths (Mammalia,Pilosa, Folivora)

Sloth morphological evolution has been widely studied qualitatively, with comparative anatomy and morpho-functional approaches, or through quantitative assessments of morphological variation using morphometrics. Only recently, however, have folivoran morphological disparity and evolutionary rates begun to be evaluated using discrete character data. Nonetheless, patterns of morphological evolution in separate character partitions have not been investigated, neither the relative influence of, on the one hand, phylogeny, and on the other, dietary and locomotory adaptations of sloths. Here we evaluate those patterns using a phylomorphospace approach, quantifying morphological disparity and evolutionary rates, and investigating possible drivers of morphological evolution for cranial and postcranial characters in Folivora. The evolution of the morphology in those partitions is associated with distinct patterns of disparity among clades and ecological groups, even though the two partitions do not differ substantially in overall evolutionary tempo. Historical processes shaped the morphological evolution of sloths more consistently than ecological ones, although changes in postcranial characters also seem to be associated with locomotory adaptations, in which morphological convergences were much more common. We also discuss important methodological trade-offs in investigations of partitioned datasets mostly composed of fossil taxa.     

Understanding Phenotypical Character Evolution in Parmelioid Lichenized Fungi (Parmeliaceae,Ascomycota)

Parmelioid lichens form a species-rich group of predominantly foliose and fruticose lichenized fungi encompassing a broad range of morphological and chemical diversity. Using a multilocus approach, we reconstructed a phylogeny including 323 OTUs of parmelioid lichens and employed ancestral character reconstruction methods to understand the phenotypical evolution within this speciose group of lichen-forming fungi. Specifically, we were interested in the evolution of growth form, epicortex structure, and cortical chemistry. Since previous studies have shown that results may differ depending on the reconstruction method used, here we employed both maximum-parsimony and maximum-likelihood approaches to reconstruct ancestral character states. We have also implemented binary and multistate coding of characters and performed parallel analyses with both coding types to assess for potential coding-based biases. We reconstructed the ancestral states for nine well-supported major clades in the parmelioid group, two higher-level sister groups and the ancestral character state for all parmelioid lichens. We found that different methods for coding phenotypical characters and different ancestral character state reconstruction methods mostly resulted in identical reconstructions but yield conflicting inferences of ancestral states, in some cases. However, we found support for the ancestor of parmelioid lichens having been a foliose lichen with a non-pored epicortex and pseudocyphellae. Our data suggest that some traits exhibit patterns of evolution consistent with adaptive radiation.     

A new phylogenetic method for identifying exceptional phenotypic diversification

Currently available phylogenetic methods for studying the rate of evolution in a continuously valued character assume that the rate is constant throughout the tree or that it changes along specific branches according to an a priori hypothesis of rate variation provided by the user. Herein, we describe a new method for studying evolutionary rate variation in continuously valued characters given an estimate of the phylogenetic history of the species in our study. According to this method, we propose no specific prior hypothesis for how the variation in evolutionary rate is structured throughout the history of the species in our study. Instead, we use a Bayesian Markov Chain Monte Carlo approach to estimate evolutionary rates and the shift point between rates on the tree. We do this by simultaneously sampling rates and shift points in proportion to their posterior probability, and then collapsing the posterior sample into an estimate of the parameters of interest. We use simulation to show that the method is quite successful at identifying the phylogenetic position of a shift in the rate of evolution, and that estimated rates are asymptotically unbiased. We also provide an empirical example of the method using data for Anolis lizards. [This article was published online on September 20, 2011. An error in a co‐author's name was subsequently identified. This notice is included in the online and print versions to indicate that both have been corrected September 21, 2011.]     

Maximum likelihood Jukes-Cantor triplets: analytic solutions

Maximum likelihood (ML) is a popular method for inferring a phylogenetic tree of the evolutionary relationship of a set of taxa, from observed homologous aligned genetic sequences of the taxa. Generally, the computation of the ML tree is based on numerical methods, which in a few cases, are known to converge to a local maximum on a tree, which is suboptimal. The extent of this problem is unknown, one approach is to attempt to derive algebraic equations for the likelihood equation and find the maximum points analytically. This approach has so far only been successful in the very simplest cases, of three or four taxa under the Neyman model of evolution of two-state characters. In this paper we extend this approach, for the first time, to four-state characters, the Jukes-Cantor model under a molecular clock, on a tree T on three taxa, a rooted triple. We employ spectral methods (Hadamard conjugation) to express the likelihood function parameterized by the path-length spectrum. Taking partial derivatives, we derive a set of polynomial equations whose simultaneous solution contains all critical points of the likelihood function. Using tools of algebraic geometry (the resultant of two polynomials) in the computer algebra packages (Maple), we are able to find all turning points analytically. We then employ this method on real sequence data and obtain realistic results on the primate-rodents divergence time.     

Wagner and Dollo: a stochastic duet by composing two parsimonious solos

New contributions toward generalizing evolutionary models expand greatly our ability to analyze complex evolutionary characters and advance phylogeny reconstruction. In this article, we extend the binary stochastic Dollo model to allow for multi-state characters. In doing so, we align previously incompatible Wagner and Dollo parsimony principles under a common probabilistic framework by embedding arbitrary continuous-time Markov chains into the binary stochastic Dollo model. This approach enables us to analyze character traits that exhibit both Dollo and Wagner characteristics throughout their evolutionary histories. Utilizing Bayesian inference, we apply our novel model to analyze intron conservation patterns and the evolution of alternatively spliced exons. The generalized framework we develop demonstrates potential in distinguishing between phylogenetic hypotheses and providing robust estimates of evolutionary rates. Moreover, for the two applications analyzed here, our framework is the first to provide an adequate stochastic process for the data. We discuss possible extensions to the framework from both theoretical and applied perspectives.     

Calculating the evolutionary rates of different genes: a fast, accurate estimator with applications to maximum likelihood phylogenetic analysis

In phylogenetic analyses with combined multigene or multiprotein data sets, accounting for differing evolutionary dynamics at different loci is essential for accurate tree prediction. Existing maximum likelihood (ML) and Bayesian approaches are computationally intensive. We present an alternative approach that is orders of magnitude faster. The method, Distance Rates (DistR), estimates rates based upon distances derived from gene/protein sequence data. Simulation studies indicate that this technique is accurate compared with other methods and robust to missing sequence data. The DistR method was applied to a fungal mitochondrial data set, and the rate estimates compared well to those obtained using existing ML and Bayesian approaches. Inclusion of the protein rates estimated from the DistR method into the ML calculation of trees as a branch length multiplier resulted in a significantly improved fit as measured by the Akaike Information Criterion (AIC). Furthermore, bootstrap support for the ML topology was significantly greater when protein rates were used, and some evident errors in the concatenated ML tree topology (i.e., without protein rates) were corrected. [Bayesian credible intervals; DistR method; multigene phylogeny; PHYML; rate heterogeneity.].     

Phylogenetic interpretation of ontogenetic change: sorting out the actual and artefactual in an empirical case study of centrarchid fishes

Hypothesized relationships between ontogenetic and phylogenetic change in morphological characters were empirically tested in centrarchid fishes by comparing observed patterns of character development with patterns of character evolution as inferred from a representative phylogenetic hypothesis. This phylogeny was based on 56–61 morphological characters that were polarized by outgroup comparison. Through these comparisons, evolutionary changes in character ontogeny were categorized in one of eight classes (terminal addition, terminal deletion, terminal substitution, non-terminal addition, non-terminal deletion, non-terminal substitution, ontogenetic reversal and substitution). The relative frequencies of each of these classes provided an empirical basis from which assumptions underlying hypothesized relationships between ontogeny and phylogeny were tested. In order to test hypothesized relationships between ontogeny and phylogeny that involve assumptions about the relative frequencies of terminal change (e.g. the use of ontogeny as a homology criterion), two additional phylogenies were generated in which terminal addition and terminal deletion were maximized and minimized for all characters. Character state change interpreted from these phylogenies thus represents the maxima and minima of the frequency range of terminal addition and terminal deletion for the 8.7 × 10³⁶ trees possible for centrarchids. It was found for these data that terminal change accounts for c. 75% of the character state change. This suggests either that early ontogeny is conserved in evolution or that interpretation and classification of evolutionary changes in ontogeny is biased in part by the way that characters are recognized, delimited and coded. It was found that ontogenetic interpretation is influenced by two levels of homology decision: an initial decision involving delimitation of the character (the ontogenetic sequence), and the subsequent recognition of homologous components of developmental sequences. Recognition of phylogenetic homology among individual components of developmental sequences is necessary for interpretation of evolutionary changes in ontogeny as either terminal or non-terminal. If development is the primary criterion applied in recognizing individual homologies among parts of ontogenetic sequences, the only possible interpretation of phylogenetic differences is that of terminal change. If homologies of the components cannot be ascertained, recognition of the homology of the developmental sequence as a whole will result in the interpretation of evolutionary differences as substitutions. Particularly when the objective of a study is to discover how ontogeny has evolved, criteria in addition to ontogeny must be used to recognize homology. Interpretation is also dependent upon delimitation within an ontogenetic sequence. This is in part a function of the way that an investigator ‘sees’ and codes characters. Binary and multistate characters influence interpretation differently and predictably. The use of ontogeny for determining phylogenetic polarity as previously proposed rests on the assumptions that ancestral ontogenies are conserved and that character evolution occurs predominantly through terminal addition. It was found for these data that terminal addition may comprise a maximum of 51.9% of the total character state change. It is concluded that the ontogenetic criterion is not a reliable indicator of phylogenetic polarity. Process and pattern data are collected simultaneously by those engaged in comparative morphological studies of development. The set of alternative explanatory processes is limited in the process of observing development. These form necessary starting points for the research of developmental biologists. Separating ‘empirical’ results from interpretational influences requires awareness of potential biases in the course of character selection, coding and interpretation. Consideration of the interpretational problems involved in identifying and classifying phylogenetic changes in ontogeny leads to a re-evaluation of the purpose, usefulness and information conveyed by the current classification system. It is recommended that alternative classification schemes be pursued.     

How to identify (as opposed to define) a homoplasy: examples from fossil and living great apes

There is much debate on the definitions of homoplasy and homology, and on how to spot them among character states used in a phylogenetic analysis. Many advocate what I call a "processual approach," in which information on genetics, development, function, or other criteria help a priori in identifying two character states as homologous or homoplastic. I argue that the processes represented by these criteria are insufficiently known for most organisms and most characters to be reliably used to identify homoplasies and homologies. Instead, while not foolproof, phylogeny should be the ultimate test for homology. Character states are assumed to be homologous a priori because this is falsifiable and because their initial inclusion in the character-state analysis is based on the assumption that they may be phylogenetically informative. If they fall out as symplesiomorphies or synapomorphies in a phylogenetic analysis, their status as homologies remains unfalsified. If they fall out as homoplasies, having evolved independently in more than one clade, their status as homologous is falsified, and a homoplasy is identified. The character-state transformation series, functional morphology, finer levels of morphological comparison, and the distribution and correlation of characters all help to explain the presence of homoplasies in a given phylogeny. Explaining these homoplasies, and not ignoring them as "noise," should be as much a goal of phylogenetic analysis as the production of a phylogeny. Examples from the fossil record of Miocene hominoids are given to illustrate the advantages of a process-informs-pattern-recognition-after-the-fact approach to understanding the evolution of character states.     

EVOLUTIONARY CHARACTER ANALYSIS: TRACING CHARACTER CHANGE ON A CLADOGRAM

Abstract— There has been little formal discussion concerning character analysis in cladistics, even though characters and their character state trees are central to phylogenetic analyses. We refer to this field as Evolutionary Character Analysis. This paper defines the components of evolutionary character analysis: character state trees, transmodal characters, cladogram characters, attribute and character phylogenies; and the use of these components in phylogenetic inference and evolutionary studies. Character state trees and their effect on cladogram construction are discussed. A new method for numerically coding complex character state trees is described that further reduces the number of variables required to describe them. This method, ordinal coding, reduces the size of data matrices, and facilitates retrieval of state codes. This paper advocates the use of both biological evidence and evidence internal to the cladogram itself to construct character state trees (CSTs). We discuss general models of character evolution (morphocline analysis, Fitch minimum mutation model, etc.) and their role in forming CSTs. Character state trees formed with theories of character evolution are referred to as transmodal characters. These transmodal characters are contrasted with cladogram characters (Mickevich, 1982), and the place of each in a phylogenetic analysis is discussed. The method for determining cladogram characters is detailed with more complicated examples than found in previous publications. We advocate testing transmodal characters by comparing them with the resultant cladogram characters. This comparison involves transformation series analysis (TSA; Mickevich, 1982) which is viewed as an extension of reciprocal illumination. The TSA procedure and its place in hypothesis testing are reviewed. Tracing the evolution of characters interests both systematists and non-systematists alike. When character state trees (transmodal characters) are optimized on pre-existing phylogenies, character phylogenies and attribute phylogenies result. Attributes are defined as a feature that may or may not be homologous (i.e., ecological categories, plant hosts, etc.). We provide two illustrations of this approach, one involving the evolution of the anuran ear and another involving the coevolution of the butterfly Heliconius and its hostplants. Finally, the components of phylogenetic character analysis can be used to test more general evolutionary theories such as the biogenetic law and vicariance biogeography.     

Character evolution in Hydrozoa (phylum Cnidaria)

The diversity of hydrozoan life cycles, as manifested in the wide range of polyp, colony, and medusa morphologies, has been appreciated for centuries. Unraveling the complex history of characters involved in this diversity is critical for understanding the processes driving hydrozoan evolution. In this study, we use a phylogenetic approach to investigate the evolution of morphological characters in Hydrozoa. A molecular phylogeny is reconstructed using ribosomal DNA sequence data. Several characters involving polyp, colony, and medusa morphology are coded in the terminal taxa. These characters are mapped onto the phylogeny and then the ancestral character states are reconstructed. This study confirms the complex evolutionary history of hydrozoan morphological characters. Many of the characters involving polyp, colony, and medusa morphology appear as synapomorphies for major hydrozoan clades, yet homoplasy is commonplace.     

The phylogeny of land plants inferred from 18S rDNA sequences: pushing the limits of rDNA signal?

Previous studies of the phylogeny of land plants based on analysis of 18S ribosomal DNA (rDNA) sequences have generally found weak support for the relationships recovered and at least some obviously spurious relationships, resulting in equivocal inferences of land plant phylogeny. We hypothesized that greater sampling of both characters and taxa would improve inferences of land plant phylogeny based on 18S rDNA sequences. We therefore conducted a phylogenetic analysis of complete (or nearly complete) 18S rDNA sequences for 93 species of land plants and 7 green algal relatives. Parsimony analyses with equal weighting of characters and characters state changes and parsimony analyses weighting (1) stem bases half as much as loop bases and (2) transitions half as much as transversions did not produce substantially different topologies. Although the general structure of the shortest trees is consistent with most hypotheses of land plant phylogeny, several relationships, particularly among major groups of land plants, appear spurious. Increased character and taxon sampling did not substantially improve the performance of 18S rDNA in phylogenetic analyses of land plants, nor did analyses designed to accommodate variation in evolutionary rates among sites. The rate and pattern of 18S rDNA evolution across land plants may limit the usefulness of this gene for phylogeny reconstruction at deep levels of plant phylogeny. We conclude that the mosaic structure of 18S rDNA, consisting of highly conserved and highly variable regions, may contain historical signal at two levels. Rapidly evolving regions are informative for relatively recent divergences (e.g., within angiosperms, seed plants, and ferns), but homoplasy at these sites makes it difficult to resolve relationships among these groups. At deeper levels, changes in the highly conserved regions of small-subunit rDNAs provide signal across all of life. Because constraints imposed by the secondary structure of the rRNA may affect the phylogenetic information content of 18S rDNA, we suggest that 18S rDNA sequences be combined with other data and that methods of analysis be employed to accommodate these differences in evolutionary patterns, particularly across deep divergences in the tree of life.     

Robustness of maximum likelihood tree estimation against different patterns of base substitutions

Summary In the maximum likelihood (ML) method for estimating a molecular phylogenetic tree, the pattern of nucleotide substitutions for computing likelihood values is assumed to be simpler than that of the actual evolutionary process, simply because the process, considered to be quite devious, is unknown. The problem, however, is that there has been no guarantee to endorse the simplification.To study this problem, we first evaluated the robustness of the ML method in the estimation of molecular trees against different nucleotide substitution patterns, including Jukes and Cantor's, the simplest ever proposed. Namely, we conducted computer simulations in which we could set up various evolutionary models of a hypothetical gene, and define a true tree to which an estimated tree by the ML method was to be compared. The results show that topology estimation by the ML method is considerably robust against different ratios of transitions to transversions and different GC contents, but branch length estimation is not so. The ML tree estimation based on Jukes and Cantor's model is also revealed to be resistant to GC content, but rather sensitive to the ratio of transitions to transversions.We then applied the ML method with different substitution patterns to nucleotide sequence data ontax gene from T-cell leukemia viruses whose evolutionary process must have been more complicated than that of the hypothetical gene. The results are in accordance with those from the simulation study, showing that Jukes and Cantor's model is as useful as a more complicated one for making inferences about molecular phylogeny of the viruses.     

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.