Common molecular phylogenetic characteristics such as long branches and compositional heterogeneity can be problematic for phylogenetic reconstruction when using amino acid data. Recoding alignments to reduced alphabets before phylogenetic analysis has often been used both to explore and potentially decrease the effect of such problems. We tested the effectiveness of this strategy on topological accuracy using simulated data on four-taxon trees. We simulated alignments in phylogenetically challenging ways to test the phylogenetic accuracy of analyses using various recoding strategies together with commonly-used homogeneous models. We tested three recoding methods based on amino acid exchangeability, and another recoding method based on lowering the compositional heterogeneity among alignment sequences as measured by the Chi-squared statistic. Our simulation results show that on trees with long branches where sequences approach saturation, accuracy was not greatly affected by exchangeability-based recodings, but Chi-squared-based recoding decreased accuracy. We then simulated sequences with different kinds of compositional heterogeneity over the tree. Recoding often increased accuracy on such alignments. Exchangeability-based recoding was rarely worse than not recoding, and often considerably better. Recoding based on lowering the Chi-squared value improved accuracy in some cases but not in others, suggesting that low compositional heterogeneity by itself is not sufficient to increase accuracy in the analysis of these alignments. We also simulated alignments using site-specific amino acid profiles, making sequences that had compositional heterogeneity over alignment sites. Exchangeability-based recoding coupled with site-homogeneous models had poor accuracy for these datasets but Chi-squared-based recoding on these alignments increased accuracy. We then simulated datasets that were compositionally both site- and tree-heterogeneous, like many real datasets. The effect on accuracy of recoding such doubly problematic datasets varied widely, depending on the type of compositional tree-heterogeneity and on the recoding scheme. Interestingly, analysis of unrecoded compositionally heterogeneous alignments with the NDCH or CAT models was generally more accurate than homogeneous analysis, whether recoded or not. Overall, our results suggest that making trees for recoded amino acid datasets can be useful, but they need to be interpreted cautiously as part of a more comprehensive analysis. The use of better fitting models like NDCH and CAT, which directly account for the patterns in the data, may offer a more promising long-term solution for analysing empirical data.

If all nucleotide sites evolved at the same rate within molecules and throughout the history of lineages, if all nucleotides were in equal proportion, if any nucleotide or amino acid evolved to any other with equal probability, if all taxa could be sampled, if diversification happened at well-spaced intervals, and if all gene segments had the same history, then tree building would be easy. But of course, none of those conditions are true. Hence, the need for evaluating the information content and accuracy of phylogenetic trees. The symposium for which this historical essay and presentation were developed focused on the importance of phylogenetic support, specifically branch support for individual clades. Here, I present a timeline and review significant events in the history of systematics that set the stage for the development of the sophisticated measures of branch support and examinations of the information content of data highlighted in this symposium. [Bayes factors; bootstrap; branch support; concordance factors; internode certainty; posterior probabilities; spectral analysis; transfer bootstrap expectation.].

An unprecedented amount of evidence now illuminates the phylogeny of living mammals and birds on the Tree of Life. We use this tree to measure the phylogenetic value of data typically used in paleontology (bones and teeth) from six data sets derived from five published studies. We ask three interrelated questions: 1) Can these data adequately reconstruct known parts of the Tree of Life? 2) Is accuracy generally similar for studies using morphology, or do some morphological data sets perform better than others? 3) Does the loss of non-fossilizable data cause taxa to occur in misleadingly basal positions? Adding morphology to DNA data sets usually increases congruence of resulting topologies to the well-corroborated tree, but this varies among morphological data sets. Extant taxa with a high proportion of missing morphological characters can greatly reduce phylogenetic resolution when analyzed together with fossils. Attempts to ameliorate this by deleting extant taxa missing morphology are prone to decreased accuracy due to long-branch artifacts. We find no evidence that fossilization causes extinct taxa to incorrectly appear at or near topologically basal branches. Morphology comprises the evidence held in common by living taxa and fossils, and phylogenetic analysis of fossils greatly benefits from inclusion of molecular and morphological data sampled for living taxa, whatever methods are used for phylogeny estimation. [Concatenation; fossilization; morphology; parsimony; systematics; taphonomy; total-evidence.].

Dating the tree of life is central to understanding the evolution of life on Earth. Molecular clocks calibrated with fossils represent the state of the art for inferring the ages of major groups. Yet, other information on the timing of species diversification can be used to date the tree of life. For example, horizontal gene transfer events and ancient coevolutionary interactions such as (endo)symbioses occur between contemporaneous species and thus can imply temporal relationships between two nodes in a phylogeny. Temporal constraints from these alternative sources can be particularly helpful when the geological record is sparse, for example, for microorganisms, which represent the majority of extant and extinct biodiversity. Here, we present a new method to combine fossil calibrations and relative age constraints to estimate chronograms. We provide an implementation of relative age constraints in RevBayes that can be combined in a modular manner with the wide range of molecular dating methods available in the software. We use both realistic simulations and empirical datasets of 40 Cyanobacteria and 62 Archaea to evaluate our method. We show that the combination of relative age constraints with fossil calibrations significantly improves the estimation of node ages. [Archaea, Bayesian analysis, cyanobacteria, dating, endosymbiosis, lateral gene transfer, MCMC, molecular clock, phylogenetic dating, relaxed molecular clock, revbayes, tree of life.].

The scale of data sets used to infer phylogenies has grown dramatically in the last decades, providing researchers with an enormous amount of information with which to draw inferences about evolutionary history. However, standard approaches to assessing confidence in those inferences (e.g., nonparametric bootstrap proportions [BP] and Bayesian posterior probabilities [PPs]) are still deeply influenced by statistical procedures and frameworks that were developed when information was much more limited. These approaches largely quantify uncertainty caused by limited amounts of data, which is often vanishingly small with modern, genome-scale sequence data sets. As a consequence, today's phylogenomic studies routinely report near-complete confidence in their inferences, even when different studies reach strongly conflicting conclusions and the sites and loci in a single data set contain much more heterogeneity than our methods assume or can accommodate. Therefore, we argue that BPs and marginal PPs of bipartitions have outlived their utility as the primary means of measuring phylogenetic support for modern phylogenomic data sets with large numbers of sites relative to the number of taxa. Continuing to rely on these measures will hinder progress towards understanding remaining sources of uncertainty in the most challenging portions of the Tree of Life. Instead, we encourage researchers to examine the ideas and methods presented in this special issue of Systematic Biology and to explore the area further in their own work. The papers in this special issue outline strategies for assessing confidence and uncertainty in phylogenomic data sets that move beyond stochastic error due to limited data and offer promise for more productive dialogue about the challenges that we face in reaching our shared goal of understanding the history of life on Earth.[Big data; gene tree variation; genomic era; statistical bias.].

This article investigates a form of rank deficiency in phenotypic covariance matrices derived from geometric morphometric data, and its impact on measures of phenotypic integration. We first define a type of rank deficiency based on information theory then demonstrate that this deficiency impairs the performance of phenotypic integration metrics in a model system. Lastly, we propose methods to treat for this information rank deficiency. Our first goal is to establish how the rank of a typical geometric morphometric covariance matrix relates to the information entropy of its eigenvalue spectrum. This requires clear definitions of matrix rank, of which we define three: the full matrix rank (equal to the number of input variables), the mathematical rank (the number of nonzero eigenvalues), and the information rank or "effective rank" (equal to the number of nonredundant eigenvalues). We demonstrate that effective rank deficiency arises from a combination of methodological factors-Generalized Procrustes analysis, use of the correlation matrix, and insufficient sample size-as well as phenotypic covariance. Secondly, we use dire wolf jaws to document how differences in effective rank deficiency bias two metrics used to measure phenotypic integration. The eigenvalue variance characterizes the integration change incorrectly, and the standardized generalized variance lacks the sensitivity needed to detect subtle changes in integration. Both metrics are impacted by the inclusion of many small, but nonzero, eigenvalues arising from a lack of information in the covariance matrix, a problem that usually becomes more pronounced as the number of landmarks increases. We propose a new metric for phenotypic integration that combines the standardized generalized variance with information entropy. This metric is equivalent to the standardized generalized variance but calculated only from those eigenvalues that carry nonredundant information. It is the standardized generalized variance scaled to the effective rank of the eigenvalue spectrum. We demonstrate that this metric successfully detects the shift of integration in our dire wolf sample. Our third goal is to generalize the new metric to compare data sets with different sample sizes and numbers of variables. We develop a standardization for matrix information based on data permutation then demonstrate that Smilodon jaws are more integrated than dire wolf jaws. Finally, we describe how our information entropy-based measure allows phenotypic integration to be compared in dense semilandmark data sets without bias, allowing characterization of the information content of any given shape, a quantity we term "latent dispersion". [Canis dirus; Dire wolf; effective dispersion; effective rank; geometric morphometrics; information entropy; latent dispersion; modularity and integration; phenotypic integration; relative dispersion.].

As genomic sequence data become increasingly available, inferring the phylogeny of the species as that of concatenated genomic data can be enticing. However, this approach makes for a biased estimator of branch lengths and substitution rates and an inconsistent estimator of tree topology. Bayesian multispecies coalescent (MSC) methods address these issues. This is achieved by constraining a set of gene trees within a species tree and jointly inferring both under a Bayesian framework. However, this approach comes at the cost of increased computational demand. Here, we introduce StarBeast3-a software package for efficient Bayesian inference under the MSC model via Markov chain Monte Carlo. We gain efficiency by introducing cutting-edge proposal kernels and adaptive operators, and StarBeast3 is particularly efficient when a relaxed clock model is applied. Furthermore, gene-tree inference is parallelized, allowing the software to scale with the size of the problem. We validated our software and benchmarked its performance using three real and two synthetic data sets. Our results indicate that StarBeast3 is up to one-and-a-half orders of magnitude faster than StarBeast2, and therefore more than two orders faster than *BEAST, depending on the data set and on the parameter, and can achieve convergence on large data sets with hundreds of genes. StarBeast3 is open-source and is easy to set up with a friendly graphical user interface. [Adaptive; Bayesian inference; BEAST 2; effective population sizes; high performance; multispecies coalescent; parallelization; phylogenetics.].

A simple graphical device, the simplex plot of quartet concordance factors, is introduced to aid in the exploration of a collection of gene trees on a common set of taxa. A single plot summarizes all gene tree discord and allows for visual comparison to the expected discord from the multispecies coalescent model (MSC) of incomplete lineage sorting on a species tree. A formal statistical procedure is described that can quantify the deviation from expectation for each subset of four taxa, suggesting when the data are not in accord with the MSC, and thus that either gene tree inference error is substantial or a more complex model such as that on a network may be required. If the collection of gene trees is in accord with the MSC, the plots reveal when substantial incomplete lineage sorting is present. Applications to both simulated and empirical multilocus data sets illustrate the insights provided. [Gene tree discordance; hypothesis test; multispecies coalescent model; quartet concordance factor; simplex plot; species tree].

Genomic data have only sometimes brought resolution to the tree of life. Large phylogenomic studies can reach conflicting conclusions about important relationships, with mutually exclusive hypotheses receiving strong support. Reconciling such differences requires a detailed understanding of how phylogenetic signal varies among data sets. Two complementary strategies for better understanding phylogenomic conflicts are to examine support on a locus-by-locus basis and use support values that capture a larger range of variation in phylogenetic information, such as likelihood ratios. Likelihood ratios can be calculated using either maximum or marginal likelihoods. Despite being conceptually similar, differences in how these ratios are calculated and interpreted have not been closely examined in phylogenomics. Here, we compare the behavior of maximum and marginal likelihood ratios when evaluating alternate resolutions of recalcitrant relationships among major squamate lineages. We find that these ratios are broadly correlated between loci, but the correlation is driven by extreme values. As a consequence, the proportion of loci that support a hypothesis can change depending on which ratio is used and whether smaller values are discarded. In addition, maximum likelihood ratios frequently exhibit identical support for alternate hypotheses, making conflict resolution a challenge. We find surprising support for a sister relationship between snakes and iguanians across four different phylogenomic data sets in contrast to previous empirical studies. [Bayes factors; likelihood ratios; marginal likelihood; maximum likelihood; phylogenomics; squamates.].

An evolutionary process is reflected in the sequence of changes of any trait (e.g., morphological or molecular) through time. Yet, a better understanding of evolution would be procured by characterizing correlated evolution, or when two or more evolutionary processes interact. Previously developed parametric methods often require significant computing time as they rely on the estimation of many parameters. Here, we propose a minimal likelihood framework modeling the joint evolution of two traits on a known phylogenetic tree. The type and strength of correlated evolution are characterized by a few parameters tuning mutation rates of each trait and interdependencies between these rates. The framework can be applied to study any discrete trait or character ranging from nucleotide substitution to gain or loss of a biological function. More specifically, it can be used to 1) test for independence between two evolutionary processes, 2) identify the type of interaction between them, and 3) estimate parameter values of the most likely model of interaction. In the current implementation, the method takes as input a phylogenetic tree with discrete evolutionary events mapped on its branches. The method then maximizes the likelihood for one or several chosen scenarios. The strengths and limits of the method, as well as its relative power compared to a few other methods, are assessed using both simulations and data from 16S rRNA sequences in a sample of 54 $\gamma$-enterobacteria. We show that, even with data sets of fewer than 100 species, the method performs well in parameter estimation and in evolutionary model selection. [Correlated evolution; maximum likelihood; model.].

Phylogenetic analyses may suffer from multiple sources of error leading to conflict between genes and methods of inference. The evolutionary history of the mollusc clade Vetigastropoda makes them susceptible to these conflicts, their higher level phylogeny remaining largely unresolved. Originating over 350 Ma, vetigastropods were the dominant marine snails in the Paleozoic. Multiple extinction events and new radiations have resulted in both very long and very short branches and a large extant diversity of over 4000 species. This is the perfect setting of a hard phylogenetic question in which sources of conflict can be explored. We present 41 new transcriptomes across the diversity of vetigastropods (62 terminals total), and provide the first genomic-scale phylogeny for the group. We find that deep divergences differ from previous studies in which long branch attraction was likely pervasive. Robust results leading to changes in taxonomy include the paraphyly of the order Lepetellida and the family Tegulidae. Tectinae subfam. nov. is designated for the clade comprising Tectus, Cittarium, and Rochia. For two early divergences, topologies disagreed between concatenated analyses using site heterogeneous models versus concatenated partitioned analyses and summary coalescent methods. We investigated rate and composition heterogeneity among genes, as well as missing data by locus and by taxon, none of which had an impact on the inferred topologies. We also found no evidence for ancient introgression throughout the phylogeny. We further tested whether uninformative genes and over-partitioning were responsible for this discordance by evaluating the phylogenetic signal of individual genes using likelihood mapping, and by analyzing the most informative genes with a full multispecies coalescent (MSC) model. We find that most genes are not informative at the two conflicting nodes, but neither this nor gene-wise partitioning are the cause of discordant results. New method implementations that simultaneously integrate amino acid profile mixture models and the MSC might be necessary to resolve these and other recalcitrant nodes in the Tree of Life. [Fissurellidae; Haliotidae; likelihood mapping; multispecies coalescent; phylogenetic signal; phylogenomic conflict; site heterogeneity; Trochoidea.].

Using time-reversible Markov models is a very common practice in phylogenetic analysis, because although we expect many of their assumptions to be violated by empirical data, they provide high computational efficiency. However, these models lack the ability to infer the root placement of the estimated phylogeny. In order to compensate for the inability of these models to root the tree, many researchers use external information such as using outgroup taxa or additional assumptions such as molecular clocks. In this study, we investigate the utility of nonreversible models to root empirical phylogenies and introduce a new bootstrap measure, the rootstrap, which provides information on the statistical support for any given root position. [Bootstrap; nonreversible models; phylogenetic inference; root estimation.].

Although convergence is often recognized as a ubiquitous feature across the Tree of Life, whether the underlying traits also exhibit similar evolutionary pathways towards convergent forms puzzles biologists. In carnivoran mammals, "elongate," "slender," and "long" are often used to describe and even to categorize mustelids (martens, polecats, and weasels), herpestids (mongooses), viverrids (civets and genets), and other carnivorans together. But just how similar these carnivorans are and whether there is convergence in the morphological component that contribute to elongation has never been assessed. Here, I found that these qualitatively described elongate carnivorans exhibited incomplete convergence towards elongate bodies compared to other terrestrial carnivorans. In contrast, the morphological components underlying body shape variation do not exhibit convergence despite evidence that these components are more elongate in elongate carnivorans compared to nonelongate carnivorans. Furthermore, these components also exhibited shorter but different phylogenetic half-lives towards more elongate adaptive peaks, indicating that different selective pressures can create multiple pathways to elongation. Incorporating the fossil record will facilitate further investigation of whether body elongation evolved adaptively or if it is simply a retained ancestral trait.[Axial skeleton; body elongation; convergent evolution; macroevolution; phylogenetic comparative methods; thoracolumbar vertebrae.].

Gene tree conflict is common and finding methods to analyze and alleviate the negative effects that conflict has on species tree analysis is a crucial part of phylogenomics. This study aims to expand the discussion of inferring species trees and molecular branch lengths when conflict is present. Conflict is typically examined in two ways: inferring its prevalence and inferring the influence of the individual genes (how strongly one gene supports any given topology compared to an alternative topology). Here, we examine a procedure for incorporating both conflict and the influence of genes in order to infer evolutionary relationships. All supported relationships in the gene trees are analyzed and the likelihood of the genes constrained to these relationships is summed to provide a likelihood for the relationship. Consensus tree assembly is conducted based on the sum of likelihoods for a given relationship and choosing relationships based on the most likely relationship assuming it does not conflict with a relationship that has a higher likelihood score. If it is not possible for all most likely relationships to be combined into a single bifurcating tree then multiple trees are produced and a consensus tree with a polytomy is created. This procedure allows for more influential genes to have a greater influence on an inferred relationship, does not assume conflict has arisen from any one source and does not force the data set to produce a single bifurcating tree. Using this approach, on three empirical data sets, we examine and discuss the relationship between influence and prevalence of gene tree conflict. We find that in one of the data sets, assembling a bifurcating consensus tree solely composed of the most likely relationships is impossible. To account for conflict in molecular rate analysis we also introduce a concordance-based approach to the summary and estimation of branch lengths suitable for downstream comparative analyses. We demonstrate through simulation that even under high levels of stochastic conflict, the mean and median of the concordant rates recapitulate the true molecular rate better than using a supermatrix approach. Using a large phylogenomic data set, we examine rate heterogeneity across concordant genes with a focus on the branch subtending crown angiosperms. Notably, we find highly variable rates of evolution along the branch subtending crown angiosperms. The approaches outlined here have several limitations, but they also represent some alternative methods for harnessing the complexity of phylogenomic data sets and enrich our inferences of both species relationships and evolutionary processes.[Branch length estimation; consensus tree; gene tree conflict; gene tree filtering; phylogenetics; phylogenomics.].

Many phylogeographic studies on species with large ranges have found genetic-geographic structure associated with changes in habitat and physical barriers preventing or reducing gene flow. These interactions with geographic space, contemporary and historical climate, and biogeographic barriers have complex effects on contemporary population genetic structure and processes of speciation. While allopatric speciation at biogeographic barriers is considered the primary mechanism for generating species, more recently it has been shown that parapatric modes of divergence may be equally or even more common. With genomic data and better modeling capabilities, we can more clearly define causes of speciation in relation to biogeography and migration between lineages, the location of hybrid zones with respect to the ecology of parental lineages, and differential introgression of genes between taxa. Here, we examine the origins of three Nearctic milksnakes (Lampropeltis elapsoides, Lampropeltis triangulum and Lampropeltis gentilis) using genome-scale data to better understand species diversification. Results from artificial neural networks show that a mix of a strong biogeographic barrier, environmental changes, and physical space has affected genetic structure in these taxa. These results underscore conspicuous environmental changes that occur as the sister taxa L. triangulum and L. gentilis diverged near the Great Plains into the forested regions of the Eastern Nearctic. This area has been recognized as a region for turnover for many vertebrate species, but as we show here the contemporary boundary does not isolate these sister species. These two species likely formed in the mid-Pleistocene and have remained partially reproductively isolated over much of this time, showing differential introgression of loci. We also demonstrate that when L. triangulum and L. gentilis are each in contact with the much older L. elapsoides, some limited gene flow has occurred. Given the strong agreement between nuclear and mtDNA genomes, along with estimates of ecological niche, we suggest that all three lineages should continue to be recognized as unique species. Furthermore, this work emphasizes the importance of considering complex modes of divergence and differential allelic introgression over a complex landscape when testing mechanisms of speciation. [Cline; delimitation; Eastern Nearctic; Great Plains; hybrids; introgression; speciation.].

Although phylogeny estimation is notoriously difficult in radiations that occurred several hundred million years ago, phylogenomic approaches offer new ways to examine relationships among ancient lineages and evaluate hypotheses that are key to evolutionary biology. Here, we reconstruct the deep-rooted relationships of one of the oldest living arthropod clades, the branchiopod crustaceans, using a kaleidoscopic approach. We use concatenation and coalescent tree-building methods to analyze a large multigene data set at the nucleotide and amino acid level and examine gene tree versus species tree discordance. We unequivocally resolve long-debated relationships among extant orders of the Cladocera, the waterfleas, an ecologically relevant zooplankton group in global aquatic and marine ecosystems that is famous for its model systems in ecology and evolution. To build the data set, we assembled eight de novo genomes of key taxa including representatives of all extant cladoceran orders and suborders. Our phylogenetic analysis focused on a BUSCO-based set of 823 conserved single-copy orthologs shared among 23 representative taxa spanning all living branchiopod orders, including 11 cladoceran families. Our analysis supports the monophyly of the Cladocera and reveals remarkable homoplasy in their body plans. We found large phylogenetic distances between lineages with similar ecological specializations, indicating independent evolution in major body plans, such as in the pelagic predatory orders Haplopoda and Onychopoda (the "Gymnomera"). In addition, we assessed rapid cladogenesis by estimating relative timings of divergence in major lineages using reliable fossil-calibrated priors on eight nodes in the branchiopod tree, suggesting a Paleozoic origin around 325 Ma for the cladoceran ancestor and an ancient rapid radiation around 252 Ma at the Perm/Triassic boundary. These findings raise new questions about the roles of homoplasy and rapid radiation in the diversification of the cladocerans and help examine trait evolution from a genomic perspective in a functionally well understood, ancient arthropod group. [Cladocera; Daphnia; evolution; homoplasy; molecular clock; phylogenomics; systematics; waterfleas.].

One of the key objectives in biological research is understanding how evolutionary processes have produced Earth's diversity. A critical step toward revealing these processes is an investigation of evolutionary tradeoffs-that is, the opposing pressures of multiple selective forces. For millennia, nocturnal moths have had to balance successful flight, as they search for mates or host plants, with evading bat predators. However, the potential for evolutionary trade-offs between wing shape and body size are poorly understood. In this study, we used phylogenomics and geometric morphometrics to examine the evolution of wing shape in the wild silkmoth subfamily Arsenurinae (Saturniidae) and evaluate potential evolutionary relationships between body size and wing shape. The phylogeny was inferred based on 782 loci from target capture data of 42 arsenurine species representing all 10 recognized genera. After detecting in our data one of the most vexing problems in phylogenetic inference-a region of a tree that possesses short branches and no "support" for relationships (i.e., a polytomy), we looked for hidden phylogenomic signal (i.e., inspecting differing phylogenetic inferences, alternative support values, quartets, and phylogenetic networks) to better illuminate the most probable generic relationships within the subfamily. We found there are putative evolutionary trade-offs between wing shape, body size, and the interaction of fore- and hindwing (HW) shape. Namely, body size tends to decrease with increasing HW length but increases as forewing (FW) shape becomes more complex. Additionally, the type of HW (i.e., tail or no tail) a lineage possesses has a significant effect on the complexity of FW shape. We outline possible selective forces driving the complex HW shapes that make Arsenurinae, and silkmoths as a whole, so charismatic. [Anchored hybrid enrichment; Arsenurinae; geometric morphometrics; Lepidoptera; phylogenomics; Saturniidae.].

Generally, the species is considered to be the only naturally occurring taxon. However, species recognized and defined using different species delimitation criteria cannot readily be compared, impacting studies of biodiversity through Deep Time. This comparability issue is particularly marked when comparing extant with extinct species because the only available data for species delimitation in fossils are derived from their preserved morphology, which is generally restricted to osteology in vertebrates. Here, we quantify intraspecific, intrageneric, and intergeneric osteological variability in extant species of lacertid lizards using pairwise dissimilarity scores based on a data set of 253 discrete osteological characters for 99 specimens referred to 24 species. Variability is always significantly lower intraspecifically than between individuals belonging to distinct species of a single genus, which is in turn significantly lower than intergeneric variability. Average values of intraspecific variability and associated standard deviations are consistent (with few exceptions), with an overall average within a species of 0.208 changes per character scored. Application of the same methods to six extinct lacertid species (represented by 40 fossil specimens) revealed that intraspecific osteological variability is inconsistent, which can at least in part be attributed to different researchers having unequal expectations of the skeletal dissimilarity within species units. Such a divergent interpretation of intraspecific and interspecific variability among extant and extinct species reinforces the incomparability of the species unit. Lacertidae is an example where extant species recognized and defined based on a number of delimitation criteria show comparable and consistent intraspecific osteological variability. Here, as well as in equivalent cases, application of those skeletal dissimilarity values to paleontological species delimitation potentially provides a way to ameliorate inconsistencies created by the use of morphology to define species. [Intraspecific variation; Lacertidae; morphological disparity; osteology; species delimitation; taxonomic bias.].