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Abstract Many hypotheses in the field of phylogenetic comparative biology involve specific changes in the rate or process of trait evolution. This is particularly true of approaches designed to connect macroevolutionary pattern to microevolutionary process. 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 in the evolutionary process between mainland and island evolution for 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 some general issues of frequentist hypothesis testing and model adequacy, as well as the relationship of our method to existing models of heterogeneity in the rate of discrete character evolution on phylogenies. 

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, thephytoolsR package has grown to become an important research tool for phylogenetic comparative analysis.phytoolsis 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,phytoolsincluded 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 tophytools, while also illustrating several popular workflows of thephytoolscomputational software. 

Urbanization drastically transforms landscapes, resulting in fragmentation, degradation, and the loss of local biodiversity. Yet, urban environments also offer opportunities to observe rapid evolutionary change in wild populations that survive and even thrive in these novel habitats. In many ways, cities represent replicated “natural experiments” in which geographically separated populations adaptively respond to similar selection pressures over rapid evolutionary timescales. Little is known, however, about the genetic basis of adaptive phenotypic differentiation in urban populations nor the extent to which phenotypic parallelism is reflected at the genomic level with signatures of parallel selection. Here, we analyzed the genomic underpinnings of parallel urban-associated phenotypic change in Anolis cristatellus , a small-bodied neotropical lizard found abundantly in both urbanized and forested environments. We show that phenotypic parallelism in response to parallel urban environmental change is underlain by genomic parallelism and identify candidate loci across the Anolis genome associated with this adaptive morphological divergence. Our findings point to polygenic selection on standing genetic variation as a key process to effectuate rapid morphological adaptation. Identified candidate loci represent several functions associated with skeletomuscular development, morphology, and human disease. Taken together, these results shed light on the genomic basis of complex morphological adaptations, provide insight into the role of contingency and determinism in adaptation to novel environments, and underscore the value of urban environments to address fundamental evolutionary questions. 

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. 

Determining whether and how evolution is predictable is an important goal, particularly as anthropogenic disturbances lead to novel species interactions that could modify selective pres- sures. Here, we use a multigeneration field experiment with brown anole lizards (Anolis sagrei) to test hypotheses about the predictabil- ity of evolution. We manipulated the presence/absence of predators and competitors of A. sagrei across 16 islands in the Bahamas that had preexisting brown anole populations. Before the experiment and again after roughly five generations, we measured traits related to locomotor performance and habitat use by brown anoles and used double-digest restriction enzyme–associated DNA sequencing to estimate genome-wide changes in allele frequencies. Although previous work showed that predators and competitors had characteristic effects on brown anole behavior, diet, and population sizes, we found that evolutionary change at both phenotypic and genomic levels was difficult to forecast. Phenotypic changes were contingent on sex and hab- itat use, whereas genetic change was unpredictable and not measur- ably correlated with phenotypic changes, experimental treatments, or other environmental factors. Our work shows how differences in ecological context can alter evolutionary outcomes over short timescales and underscores the difficulty of forecasting evolutionary responses to multispecies interactions in natural conditions, even in a well-studied system with ample supporting ecological information. 

Appearing at the end of 2019, a novel virus (later identified as SARS-CoV-2) was characterized in the city of Wuhan in Hubei Province, China. As of the time of writing, the disease caused by this virus (known as COVID-19) has already resulted in over three million deaths worldwide. SARS-CoV-2 infections and deaths, however, have been highly unevenly distributed among age groups, sexes, countries, and jurisdictions over the course of the pandemic. Herein, I present a tool (the covid19.Explorer R package and web application) that has been designed to explore and analyze publicly available United States COVID-19 infection and death data from the 2020/21 U.S. SARS-CoV-2 pandemic. The analyses and visualizations that this R package and web application facilitate can help users better comprehend the geographic progress of the pandemic, the effectiveness of non-pharmaceutical interventions (such as lockdowns and other measures, which have varied widely among U.S. states), and the relative risks posed by COVID-19 to different age groups within the U.S. population. The end result is an interactive tool that will help its users develop an improved understanding of the temporal and geographic dynamics of the SARS-CoV-2 pandemic, accessible to lay people and scientists alike. 

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 (σ 2 ) also evolves by Brownian motion on a logarithmic scale. Unfortunately, it’s not possible to simultaneously estimate the rates of evolution along each edge of the tree and the rate of evolution of σ 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, λ, selected by the user. λ determines the magnitude of penalty that’s applied to rate variation between edges. Lower values of λ penalize rate variation relatively little; whereas larger λ values result in minimal rate variation among edges of the tree in the fitted model, eventually converging on a single value of σ 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, λ, 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 σ 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. 

Body sizes of marine amniotes span six orders of magnitude, yet the factors that governed the evolution of this diversity are largely unknown. High primary production of modern oceans is considered a prerequisite for the emergence of cetacean giants, but that condition cannot explain gigantism in Triassic ichthyosaurs. We describe the new giant ichthyosaur Cymbospondylus youngorum sp. nov. with a 2-meter-long skull from the Middle Triassic Fossil Hill Fauna of Nevada, USA, underscoring rapid size evolution despite the absence of many modern primary producers. Surprisingly, the Fossil Hill Fauna rivaled the composition of modern marine mammal faunas in terms of size range, and energy-flux models suggest that Middle Triassic marine food webs were able to support several large-bodied ichthyosaurs at high trophic levels, shortly after ichthyosaur origins.