Biology subjects

Revell, L. J.

Publications and source records attributed to Revell, L. J..

9 recordsLinked to original sources

bioRxiv2026

Unlocking a flexible set of phylogenetic models for discrete and continuous trait evolution using discretized stochastic diffusion

The practical utility of many modern phylogenetic comparative methods can depend on how accurately mathematical models capture the evolutionary process of traits. Boucher and Demery (2016) described a new quantitative trait model for testing hypotheses about constraint on phenotypic character evolution: Brownian motion with reflective limits. Since their analytic solution for the probability function under this bounded scenario was intractable for reasonably-sized trees, Boucher and Demery (2016) also identified a creative technique for computing the likelihood of their model. The basis of this method derives from the convergence of an equal-rates, symmetric, ordered Markov chain and continuous stochastic diffusion in the limit as the number of lattice states in the chain goes to{infty} (or, alternatively, as their widths decrease towards zero). We realized that this general approach had the potential to unlock a surprisingly large number of additional models for the phylogenetic comparative analysis of discrete and continuous trait data, and we explore several of these in the present article. Specifically, we examine application of this discretized diffusion approximation to the threshold model from evolutionary quantitative genetics, to a new "semi-threshold" trait evolution model, to a joint model where the rate of evolution for a continuous trait depends on the value of a co-evolving discrete character, along with a separate model where precisely the converse is true, and to a discrete-character-dependent multi-trend trended continuous trait evolution model. We conclude with some context for the origins of our article and discussion of other possible applications of this powerful approach.

evolutionary biology↗

bioRxiv2025

A semiparametric method to test for correlated evolution in a phylogenetic context

Phylogenetic comparative methods are a broad suite of approaches for studying trait and species diversification using evolutionary trees. In spite of their substantial growth in sophistication and complexity in recent years, among the most commonly-employed phylogenetic comparative method continues to be a simple measure of the evolutionary correlation between variables, while accounting for the statistical non-independence in our data that arises from common descent. The standard parametric phylogenetic approach for measuring the evolutionary correlation between continuously valued characters assumes a model called Brownian motion for the evolution of our traits. Here, we introduce a new semiparametric method that relaxes this assumption by testing for the evolutionary correlation between variables based on contrast ranks, and then obtains a null distribution on the test statistic via random permutation. We show that this approach has reasonable statistical properties: type I error close to the nominal level, and power that is similar to fully parametric methods. We conclude by comparing our new method to related approaches.

bioinformatics↗

bioRxiv2024

A discrete character evolution model for phylogenetic comparative biology with {Gamma}-distributed rate heterogeneity among branches of the tree

Phylogenetic comparative methods are now widely used to measure trait evolution on the tree of life. Often these methods involve fitting an explicit model of character evolution to trait data and then comparing the explanatory power of this model to alternative scenarios. In this article, we present a new model for discrete trait evolution in which the rate of character change in the tree varies from edge (i.e., "branch") to edge of the phylogeny according to a discretized {Gamma} distribution. When the edge-wise rates of evolution are, in fact, {Gamma}-distributed, we show via simulation that this model can be used to reliably estimate the shape parameter () of the distribution of rate variation among edges. We also describe how our model can be employed in ancestral state reconstruction, and demonstrate via simulation how doing so will tend to increase the accuracy of our estimated states when the generating edge rates are {Gamma}-distributed. We discuss how marginal edge rates are estimated under the model, and apply our method to a real dataset of digit number in squamate reptiles, modified from Brandley et al. (2008).

evolutionary biology↗

bioRxiv2023

phytools 2.0: An updated R ecosystem for phylogenetic comparative methods (and other things)

Phylogenetic comparative methods comprise the general endeavor of using an estimated phylogenetic tree (or set of trees) to make secondary inferences: about trait evolution, diversification dynamics, biogeography, community ecology, and a wide range of other phenomena or processes. Over the past ten years or so, the phytools R package (Revell 2012) has grown to become an important research tools for phylogenetic comparative analysis. phytools is a diverse contributed R library now consisting of hundreds of different functions covering a variety of methods and purposes in phylogenetic biology. As of the time of writing, phytools included functionality for fitting models of trait evolution, for reconstructing ancestral states, for studying diversification on trees, and for visualizing phylogenies, comparative data, and fitted models, as well numerous other tasks related to phylogenetic biology. Here, I describe some significant features of and recent updates to phytools, while also illustrating several popular workflows of the phytools computational software.

bioinformatics↗

bioRxiv2021

Testing for genetic assimilation with phylogenetic comparative analysis: Conceptual, methodological, and statistical considerations

Genetic assimilation is a process that leads to reduced phenotypic plasticity during adaptation to novel conditions, a potentially important phenomenon under global environmental change. Null expectations when testing for genetic assimilation, however, are not always clear. For instance, the statistical artifact of regression to the mean could bias us towards detecting genetic assimilation when it has not occurred. Likewise, the specific mechanism underlying plasticity expression may affect null expectations under neutral evolution. We used macroevolutionary numerical simulations to examine both of these important issues and their interaction, varying whether or not plasticity evolves, the evolutionary mechanism, trait measurement error, and experimental design. We also modified an existing reaction norm correction method to account for phylogenetic non-independence. We found: 1) regression to the mean is pervasive and can generate spurious support for genetic assimilation; 2) experimental design and post-hoc correction can minimize this spurious effect; and 3) neutral evolution can produce patterns consistent with genetic assimilation without constraint or selection, depending on the mechanism of plasticity expression. Additionally, we re-analyzed published macroevolutionary data supporting genetic assimilation, and found that support was lost after proper correction. Considerable caution is thus required whenever investigating genetic assimilation and reaction norm evolution at macroevolutionary scales.

evolutionary biology↗

bioRxiv2021

Testing for heterogeneous rates of discrete character evolution on phylogenies

Many hypotheses in the field of phylogenetic comparative biology involve specific changes in the rate or process of trait evolution. We present a method designed to test whether the rate of evolution of a discrete character has changed in one or more clades, lineages, or time periods. This method differs from other related approaches (such as the covarion model) in that the regimes in which the rate or process is postulated to have changed are specified a priori by the user, rather than inferred from the data. Similarly, it differs from methods designed to model a correlation between two binary traits in that the regimes mapped onto the tree are fixed. We apply our method to investigate the rate of dewlap color and/or caudal vertebra number evolution in Caribbean and mainland clades of the diverse lizard genus Anolis. We find little evidence to support any difference between mainland and island evolution in either character. We also examine the statistical properties of the method more generally and show that it has acceptable type I error, parameter estimation, and power. Finally, we discuss the relationship of our method to existing models of heterogeneity in the rate of discrete character evolution on phylogenies.

evolutionary biology↗

bioRxiv2021

A simple hierarchical model for heterogeneity in the evolutionary correlation on a phylogenetic tree

Numerous questions in phylogenetic comparative biology revolve around the correlated evolution of two or more phenotypic traits on a phylogeny. In many cases, it may be sufficient to assume a constant value for the evolutionary correlation between characters across all the clades and branches of the tree. Under other circumstances, however, it is desirable or necessary to account for the possibility that the evolutionary correlation differs through time or in different sections of the phylogeny. Here, we present a method designed to fit a hierarchical series of models for heterogeneity in the evolutionary rates and correlation of two quantitative traits on a phylogenetic tree. We apply the method to two datasets: one for different attributes of the buccal morphology in sunfishes (Centrarchidae); and a second for overall body length and relative body depth in rock- and non-rock-dwelling South American iguanian lizards. We also examine the performance of the method for parameter estimation and model selection using a small set of numerical simulations.

evolutionary biology↗

bioRxiv2021

A variable-rate quantitative trait evolution model using penalized-likelihood

In recent years it has become increasingly popular to use phylogenetic comparative methods to investigate heterogeneity in the rate or process of quantitative trait evolution across the branches or clades of a phylogenetic tree. Here, I present a new method for modeling variability in the rate of evolution of a continuously-valued character trait on a reconstructed phylogeny. The underlying model of evolution is stochastic diffusion (Brownian motion), but in which the instantaneous diffusion rate ({sigma}2) also evolves by Brownian motion on a logarithmic scale. Unfortunately, its not possible to simultaneously estimate the rates of evolution along each edge of the tree and the rate of evolution of{sigma} 2 itself using Maximum Likelihood. As such, I propose a penalized-likelihood method in which the penalty term is equal to the log-transformed probability density of the rates under a Brownian model, multiplied by a smoothing coefficient,{lambda} , selected by the user.{lambda} determines the magnitude of penalty thats applied to rate variation between edges. Lower values of{lambda} penalize rate variation relatively little; whereas larger{lambda} values result in minimal rate variation among edges of the tree in the fitted model, eventually converging on a single value of{sigma} 2 for all of the branches of the tree. In addition to presenting this model here, I have also implemented it as part of my phytools R package in the function multirateBM. Using different values of the penalty coefficient,{lambda} , I fit the model to simulated data with: Brownian rate variation among edges (the model assumption); uncorrelated rate variation; rate changes that occur in discrete places on the tree; and no rate variation at all among the branches of the phylogeny. I then compare the estimated values of{sigma} 2 to their known true values. In addition, I use the method to analyze a simple empirical dataset of body mass evolution in mammals. Finally, I discuss the relationship between the method of this article and other models from the phylogenetic comparative methods and finance literature, as well as some applications and limitations of the approach.

evolutionary biology↗

bioRxiv2021

Molecular phylogeny of Puerto Rico Bank dwarf geckos (Squamata: Sphaerodactylidae: Sphaerodactylus)

AO_SCPLOWBSTRACTC_SCPLOWThe genus Sphaerodactylus is a very species-rich assemblage of sphaerodactylid lizards that has undergone a level of speciation in parallel to that of the well-known Anolis lizards. Nevertheless, molecular phylogenetic research on this group consists of a handful of smaller studies of regional focus (e.g., western Puerto Rico, the Lesser Antilles) or large-scale analyses based on relatively limited sequence data. Few medium-scale multi-locus studies exist-- for example, studies that encompass an entire radiation on an island group. Building upon previous work done in Puerto Rican Sphaerodactylus, we performed multi-locus sampling of Sphaerodactylus geckos from across the Puerto Rico Bank. We then used these data for phylogeny estimation with near-complete taxon sampling. We focused on sampling the widespread nominal species S. macrolepis and in so doing, we uncovered a highly divergent and morphologically distinct lineage of Sphaerodactylus macrolepis from Puerto Rico, Culebra, and Vieques islands, which we recognize as S. grandisquamis (Stejneger, 1904) on the basis of molecular and morphological characters. S. grandisquamis co-occurs with S. macrolepis only on Culebra Island but is highly genetically differentiated and morphologically distinct. Sphaerodactylus macrolepis is now restricted to the eastern Puerto Rico Bank, from Culebra east through the Virgin Islands and including the topotypic population on St. Croix. We include additional discussion of the evolutionary history and historical biogeography of the Sphaerodactylus of the Puerto Rican Bank in the context of these new discoveries.

evolutionary biology↗