Modeling the Evolution of Rates of Continuous Trait Evolution.

Rates of phenotypic evolution vary markedly across the tree of life, from the accelerated evolution apparent in adaptive radiations to the remarkable evolutionary stasis exhibited by so-called "living fossils." Such rate variation has important consequences for large-scale evolutionary dynamics, generating vast disparities in phenotypic diversity across space, time, and taxa. Despite this, most methods for estimating trait evolution rates assume rates vary deterministically with respect to some variable of interest or change infrequently during a clade's history. These assumptions may cause underfitting of trait evolution models and mislead hypothesis testing. Here, we develop a new trait evolution model that allows rates to vary gradually and stochastically across a clade. Further, we extend this model to accommodate generally decreasing or increasing rates over time, allowing for flexible modeling of "early/late bursts" of trait evolution. We implement a Bayesian method, termed "evolving rates" (evorates for short), to efficiently fit this model to comparative data. Through simulation, we demonstrate that evorates can reliably infer both how and in which lineages trait evolution rates varied during a clade's history. We apply this method to body size evolution in cetaceans, recovering substantial support for an overall slowdown in body size evolution over time with recent bursts among some oceanic dolphins and relative stasis among beaked whales of the genus Mesoplodon. These results unify and expand on previous research, demonstrating the empirical utility of evorates. [cetacea; macroevolution; comparative methods; phenotypic diversity; disparity; early burst; late burst].

When adaptive radiations collide: Different evolutionary trajectories between and within island and mainland lizard clades.

Oceanic islands are known as test tubes of evolution. Isolated and colonized by relatively few species, islands are home to many of nature's most renowned radiations from the finches of the Galápagos to the silverswords of the Hawaiian Islands. Despite the evolutionary exuberance of insular life, island occupation has long been thought to be irreversible. In particular, the presumed much tougher competitive and predatory milieu in continental settings prevents colonization, much less evolutionary diversification, from islands back to mainlands. To test these predictions, we examined the ecological and morphological diversity of neotropical Anolis lizards, which originated in South America, colonized and radiated on various islands in the Caribbean, and then returned and diversified on the mainland. We focus in particular on what happens when mainland and island evolutionary radiations collide. We show that extensive continental radiations can result from island ancestors and that the incumbent and invading mainland clades achieve their ecological and morphological disparity in very different ways. Moreover, we show that when a mainland radiation derived from island ancestors comes into contact with an incumbent mainland radiation the ensuing interactions favor the island-derived clade.

Reconstructing Squamate Biogeography in Afro-Arabia Reveals the Influence of a Complex and Dynamic Geologic Past.

The geographic distribution of biodiversity is central to understanding evolutionary biology. Paleogeographic and paleoclimatic histories often help to explain how biogeographic patterns unfold through time. However, such patterns are also influenced by a variety of other factors, such as lineage diversification, that may affect the probability of certain types of biogeographic events. The complex and well-known geologic and climatic history of Afro-Arabia, together with the extensive research on reptile systematics in the region, makes Afro-Arabian squamate communities an ideal system to investigate biogeographic patterns and their drivers. Here, we reconstruct the phylogenetic relationships and the ancestral geographic distributions of several Afro-Arabian reptile clades (totaling 430 species) to estimate the number of dispersal, vicariance and range contraction events. We then compare the observed biogeographic history to a distribution of simulated biogeographic events based on the empirical phylogeny and the best-fit model. This allows us to identify periods in the past where the observed biogeographic history was likely shaped by forces beyond the ones included in the model. We find an increase in vicariance following the Oligocene, most likely caused by the fragmentation of the Afro-Arabian plate. In contrast, we did not find differences between observed and expected dispersal and range contraction levels. This is consistent with diversification enhanced by environmental processes and with the establishment of a dispersal corridor connecting Africa, Arabia and Eurasia since the middle Miocene. Finally, here we show that our novel approach is useful to pinpoint events in the evolutionary history of lineages that might reflect external forces not predicted by the underlying biogeographic model. [Dispersal; diversification; model adequacy; paleogeography; reptiles; simulations; vicariance.].

Mating behavior and reproductive morphology predict macroevolution of sex allocation in hermaphroditic flatworms.

BACKGROUND: Sex allocation is the distribution of resources to male or female reproduction. In hermaphrodites, this concerns an individual's resource allocation to, for example, the production of male or female gametes. Macroevolutionary studies across hermaphroditic plants have revealed that the self-pollination rate and the pollination mode are strong predictors of sex allocation. Consequently, we expect similar factors such as the selfing rate and aspects of the reproductive biology, like the mating behaviour and the intensity of postcopulatory sexual selection, to predict sex allocation in hermaphroditic animals. However, comparative work on hermaphroditic animals is limited. Here, we study sex allocation in 120 species of the hermaphroditic free-living flatworm genus Macrostomum. We ask how hypodermic insemination, a convergently evolved mating behaviour where sperm are traumatically injected through the partner's epidermis, affects the evolution of sex allocation. We also test the commonly-made assumption that investment into male and female reproduction should trade-off. Finally, we ask if morphological indicators of the intensity of postcopulatory sexual selection (female genital complexity, male copulatory organ length, and sperm length) can predict sex allocation. RESULTS: We find that the repeated evolution of hypodermic insemination predicts a more female-biased sex allocation (i.e., a relative shift towards female allocation). Moreover, transcriptome-based estimates of heterozygosity reveal reduced heterozygosity in hypodermically mating species, indicating that this mating behavior is linked to increased selfing or biparental inbreeding. Therefore, hypodermic insemination could represent a selfing syndrome. Furthermore, across the genus, allocation to male and female gametes is negatively related, and larger species have a more female-biased sex allocation. Finally, increased female genital complexity, longer sperm, and a longer male copulatory organ predict a more male-biased sex allocation. CONCLUSIONS: Selfing syndromes have repeatedly originated in plants. Remarkably, this macroevolutionary pattern is replicated in Macrostomum flatworms and linked to repeated shifts in reproductive behavior. We also find a trade-off between male and female reproduction, a fundamental assumption of most theories of sex allocation. Beyond that, no theory predicts a more female-biased allocation in larger species, suggesting avenues for future work. Finally, morphological indicators of more intense postcopulatory sexual selection appear to predict more intense sperm competition.

Uncovering Cryptic Coevolution.

AbstractStudies of coevolution in the wild have largely focused on reciprocally specialized species pairs with striking and exaggerated phenotypes. Textbook examples include interactions between toxic newts and their garter snake predators, long-tongued flies and the flowers they pollinate, and weevils with elongated rostra used to bore through the defensive pericarp of their host plants. Although these studies have laid a foundation for understanding coevolution in the wild, they have also contributed to the widespread impression that coevolution is a rare and quirky sideshow to the day-to-day grind of ecology and evolution. In this perspective, we argue that the focus of coevolution has been biased toward the obvious and ignored the cryptic. We have focused on the obvious-studies of reciprocally specialized species pairs with exaggerated phenotypes-mainly because we have lacked the statistical tools required to study coevolution in more generalized and phenotypically mundane systems. Building from well-established coevolutionary theory, we illustrate how model-based approaches can be used to remove this barrier and begin estimating the strength of coevolutionary selection indirectly using routinely collected data, thus uncovering cryptic coevolution in more typical communities. By allowing the distribution of coevolutionary selection to be estimated across genomes, phylogenies, and communities and over deep timescales, these novel approaches have the potential to revolutionize the way we study coevolution. As we develop a road map to these next-generation approaches, we highlight recent studies making notable progress in this direction.

Macroevolutionary diversification rates show time dependency.

For centuries, biologists have been captivated by the vast disparity in species richness between different groups of organisms. Variation in diversity is widely attributed to differences between groups in how fast they speciate or go extinct. Such macroevolutionary rates have been estimated for thousands of groups and have been correlated with an incredible variety of organismal traits. Here we analyze a large collection of phylogenetic trees and fossil time series and describe a hidden generality among these seemingly idiosyncratic results: speciation and extinction rates follow a scaling law in which both depend on the age of the group in which they are measured, with the fastest rates in the youngest clades. Using a series of simulations and sensitivity analyses, we demonstrate that the time dependency is unlikely to be a result of simple statistical artifacts. As such, this time scaling is likely a genuine feature of the tree of life, hinting that the dynamics of biodiversity over deep time may be driven in part by surprisingly simple and general principles.

A white noise approach to evolutionary ecology.

Although the evolutionary response to random genetic drift is classically modelled as a sampling process for populations with fixed abundance, the abundances of populations in the wild fluctuate over time. Furthermore, since wild populations exhibit demographic stochasticity and since random genetic drift is in part due to demographic stochasticity, theoretical approaches are needed to understand the role of demographic stochasticity in eco-evolutionary dynamics. Here we close this gap for quantitative characters evolving in continuously reproducing populations by providing a framework to track the stochastic dynamics of abundance density across phenotypic space using stochastic partial differential equations. In the process we develop a set of heuristics to operationalize the powerful, but abstract theory of white noise and diffusion-limits of individual-based models. Applying these heuristics, we obtain stochastic ordinary differential equations that generalize classical expressions of ecological quantitative genetics. In particular, by supplying growth rate and reproductive variance as functions of abundance densities and trait values, these equations track population size, mean trait and additive genetic variance responding to mutation, demographic stochasticity, random genetic drift, deterministic selection and noise-induced selection. We demonstrate the utility of our approach by formulating a model of diffuse coevolution mediated by exploitative competition for a continuum of resources. In addition to trait and abundance distributions, this model predicts interaction networks defined by niche-overlap, competition coefficients, or selection gradients. Using a high-richness approximation, we find linear selection gradients and competition coefficients are uncorrelated, but magnitudes of linear selection gradients and quadratic selection gradients are both positively correlated with competition coefficients. Hence, competing species that strongly affect each other's abundance tend to also impose selection on one another, but the directionality is not predicted. This approach contributes to the development of a synthetic theory of evolutionary ecology by formalizing first principle derivations of stochastic models tracking feedbacks of biological processes and the patterns of diversity they produce.

Comparing Adaptive Radiations Across Space, Time, and Taxa.

Adaptive radiation plays a fundamental role in our understanding of the evolutionary process. However, the concept has provoked strong and differing opinions concerning its definition and nature among researchers studying a wide diversity of systems. Here, we take a broad view of what constitutes an adaptive radiation, and seek to find commonalities among disparate examples, ranging from plants to invertebrate and vertebrate animals, and remote islands to lakes and continents, to better understand processes shared across adaptive radiations. We surveyed many groups to evaluate factors considered important in a large variety of species radiations. In each of these studies, ecological opportunity of some form is identified as a prerequisite for adaptive radiation. However, evolvability, which can be enhanced by hybridization between distantly related species, may play a role in seeding entire radiations. Within radiations, the processes that lead to speciation depend largely on (1) whether the primary drivers of ecological shifts are (a) external to the membership of the radiation itself (mostly divergent or disruptive ecological selection) or (b) due to competition within the radiation membership (interactions among members) subsequent to reproductive isolation in similar environments, and (2) the extent and timing of admixture. These differences translate into different patterns of species accumulation and subsequent patterns of diversity across an adaptive radiation. Adaptive radiations occur in an extraordinary diversity of different ways, and continue to provide rich data for a better understanding of the diversification of life.

Detecting the macroevolutionary signal of species interactions.

Species interactions lie at the heart of many theories of macroevolution, from adaptive radiation to the Red Queen. Although some theories describe the imprint that interactions will have over long timescales, we are still missing a comprehensive understanding of the effects of interactions on macroevolution. Current research shows strong evidence for the impact of interactions on macroevolutionary patterns of trait evolution and diversification, yet many macroevolutionary studies have only a tenuous relationship to ecological studies of interactions over shorter timescales. We review current research in this area, highlighting approaches that explicitly model species interactions and connect them to broad-scale macroevolutionary patterns. We also suggest that progress has been made by taking an integrative interdisciplinary look at individual clades. We focus on African cichlids as a case study of how this approach can be fruitful. Overall, although the evidence for species interactions shaping macroevolution is strong, further work using integrative and model-based approaches is needed to spur progress towards understanding the complex dynamics that structure communities over time and space.

A General Model for Estimating Macroevolutionary Landscapes.

The evolution of quantitative characters over long timescales is often studied using stochastic diffusion models. The current toolbox available to students of macroevolution is however limited to two main models: Brownian motion and the Ornstein-Uhlenbeck process, plus some of their extensions. Here, we present a very general model for inferring the dynamics of quantitative characters evolving under both random diffusion and deterministic forces of any possible shape and strength, which can accommodate interesting evolutionary scenarios like directional trends, disruptive selection, or macroevolutionary landscapes with multiple peaks. This model is based on a general partial differential equation widely used in statistical mechanics: the Fokker-Planck equation, also known in population genetics as the Kolmogorov forward equation. We thus call the model FPK, for Fokker-Planck-Kolmogorov. We first explain how this model can be used to describe macroevolutionary landscapes over which quantitative traits evolve and, more importantly, we detail how it can be fitted to empirical data. Using simulations, we show that the model has good behavior both in terms of discrimination from alternative models and in terms of parameter inference. We provide R code to fit the model to empirical data using either maximum-likelihood or Bayesian estimation, and illustrate the use of this code with two empirical examples of body mass evolution in mammals. FPK should greatly expand the set of macroevolutionary scenarios that can be studied since it opens the way to estimating macroevolutionary landscapes of any conceivable shape. [Adaptation; bounds; diffusion; FPK model; macroevolution; maximum-likelihood estimation; MCMC methods; phylogenetic comparative data; selection.].

Finding our way through phenotypes.

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility.

Ecological opportunity and sexual selection together predict adaptive radiation.

A fundamental challenge to our understanding of biodiversity is to explain why some groups of species undergo adaptive radiations, diversifying extensively into many and varied species, whereas others do not. Both extrinsic environmental factors (for example, resource availability, climate) and intrinsic lineage-specific traits (for example, behavioural or morphological traits, genetic architecture) influence diversification, but few studies have addressed how such factors interact. Radiations of cichlid fishes in the African Great Lakes provide some of the most dramatic cases of species diversification. However, most cichlid lineages in African lakes have not undergone adaptive radiations. Here we compile data on cichlid colonization and diversification in 46 African lakes, along with lake environmental features and information about the traits of colonizing cichlid lineages, to investigate why adaptive radiation does and does not occur. We find that extrinsic environmental factors related to ecological opportunity and intrinsic lineage-specific traits related to sexual selection both strongly influence whether cichlids radiate. Cichlids are more likely to radiate in deep lakes, in regions with more incident solar radiation and in lakes where there has been more time for diversification. Weak or negative associations between diversification and lake surface area indicate that cichlid speciation is not constrained by area, in contrast to diversification in many terrestrial taxa. Among the suite of intrinsic traits that we investigate, sexual dichromatism, a surrogate for the intensity of sexual selection, is consistently positively associated with diversification. Thus, for cichlids, it is the coincidence between ecological opportunity and sexual selection that best predicts whether adaptive radiation will occur. These findings suggest that adaptive radiation is predictable, but only when species traits and environmental factors are jointly considered.

Radiating despite a Lack of Character: Ecological Divergence among Closely Related, Morphologically Similar Honeyeaters (Aves: Meliphagidae) Co-occurring in Arid Australian Environments.

Quantifying the relationship between form and function can inform use of morphology as a surrogate for ecology. How the strength of this relationship varies continentally can inform understanding of evolutionary radiations; for example, does the relationship break down when certain lineages invade and diversify in novel habitats? The 75 species of Australian honeyeaters (Meliphagidae) are morphologically and ecologically diverse, with species feeding on nectar, insects, fruit, and other resources. We investigated Meliphagidae ecomorphology and community structure by (1) quantifying the concordance between morphology and ecology (foraging behavior), (2) estimating rates of trait evolution in relation to the packing of ecological space, and (3) comparing phylogenetic and trait community structure across the broad environmental gradients of the continent. We found that morphology explained 37% of the variance in ecology (and 62% vice versa), and we uncovered well-known bivariate relationships among the multivariate ecomorphological data. Ecological trait diversity declined less rapidly than phylogenetic diversity along a gradient of decreasing precipitation. We employ a new method (trait fields) and extend another (phylogenetic fields) to show that while species in phylogenetically clustered, arid-environment assemblages are similar morphologically, they are as varied in foraging behavior as those from more diverse assemblages. Thus, although closely related and similar morphologically, these arid-adapted species have diverged in ecological space to a similar degree as their mesic counterparts.

Long-term morphological stasis maintained by a plant-pollinator mutualism.

Many major branches in the Tree of Life are marked by stereotyped body plans that have been maintained over long periods of time. One possible explanation for this stasis is that there are genetic or developmental constraints that restrict the origin of novel body plans. An alternative is that basic body plans are potentially quite labile, but are actively maintained by natural selection. We present evidence that the conserved floral morphology of a species-rich flowering plant clade, Malpighiaceae, has been actively maintained for tens of millions of years via stabilizing selection imposed by their specialist New World oil-bee pollinators. Nine clades that have lost their primary oil-bee pollinators show major evolutionary shifts in specific floral traits associated with oil-bee pollination, demonstrating that developmental constraint is not the primary cause of morphological stasis in Malpighiaceae. Interestingly, Malpighiaceae show a burst in species diversification coinciding with the origin of this plant-pollinator mutualism. One hypothesis to account for radiation despite morphological stasis is that although selection on pollinator efficiency explains the origin of this unique and conserved floral morphology, tight pollinator specificity subsequently permitted greatly enhanced diversification in this system.

Modeling observed animal performance using the Weibull distribution.

To understand how organisms adapt, researchers must link performance and microhabitat. However, measuring performance, especially maximum performance, can sometimes be difficult. Here, we describe an improvement over previous techniques that only consider the largest observed values as maxima. Instead, we model expected performance observations via the Weibull distribution, a statistical approach that reduces the impact of rare observations. After calculating group-level weighted averages and variances by treating individuals separately to reduce pseudoreplication, our approach resulted in high statistical power despite small sample sizes. We fitted lizard adhesive performance and bite force data to the Weibull distribution and found that it closely estimated maximum performance in both cases, illustrating the generality of our approach. Using the Weibull distribution to estimate observed performance greatly improves upon previous techniques by facilitating power analyses and error estimations around robustly estimated maximum values.

Predicting rates of interspecific interaction from phylogenetic trees.

Integrating phylogenetic information can potentially improve our ability to explain species' traits, patterns of community assembly, the network structure of communities, and ecosystem function. In this study, we use mathematical models to explore the ecological and evolutionary factors that modulate the explanatory power of phylogenetic information for communities of species that interact within a single trophic level. We find that phylogenetic relationships among species can influence trait evolution and rates of interaction among species, but only under particular models of species interaction. For example, when interactions within communities are mediated by a mechanism of phenotype matching, phylogenetic trees make specific predictions about trait evolution and rates of interaction. In contrast, if interactions within a community depend on a mechanism of phenotype differences, phylogenetic information has little, if any, predictive power for trait evolution and interaction rate. Together, these results make clear and testable predictions for when and how evolutionary history is expected to influence contemporary rates of species interaction.

Unifying ecology and macroevolution with individual-based theory.

A contemporary goal in both ecology and evolutionary biology is to develop theory that transcends the boundary between the two disciplines, to understand phenomena that cannot be explained by either field in isolation. This is challenging because macroevolution typically uses lineage-based models, whereas ecology often focuses on individual organisms. Here, we develop a new parsimonious individual-based theory by adding mild selection to the neutral theory of biodiversity. We show that this model generates realistic phylogenies showing a slowdown in diversification and also improves on the ecological predictions of neutral theory by explaining the occurrence of very common species. Moreover, we find the distribution of individual fitness changes over time, with average fitness increasing at a pace that depends positively on community size. Consequently, large communities tend to produce fitter species than smaller communities. These findings have broad implications beyond biodiversity theory, potentially impacting, for example, invasion biology and paleontology.

Species diversity is dynamic and unbounded at local and continental scales.

We argue that biotas at scales from local communities to entire continents are nearly always open to new species and that their diversities are far from any ecological limits. We show that the fossil, phylogenetic, and morphological evidence that has been used to suggest that ecological processes set limits to diversity in evolutionary time is weak and inconsistent. At the same time, ecological evidence from biological invasions, experiments, and diversity analyses strongly supports the openness of communities to new species. We urge evolutionary biologists to recognize that ecology has largely moved beyond simple notions of equilibrium at a carrying capacity and toward a richer view of communities as highly dynamic in space and time.

Model Adequacy and the Macroevolution of Angiosperm Functional Traits.

Making meaningful inferences from phylogenetic comparative data requires a meaningful model of trait evolution. It is thus important to determine whether the model is appropriate for the data and the question being addressed. One way to assess this is to ask whether the model provides a good statistical explanation for the variation in the data. To date, researchers have focused primarily on the explanatory power of a model relative to alternative models. Methods have been developed to assess the adequacy, or absolute explanatory power, of phylogenetic trait models, but these have been restricted to specific models or questions. Here we present a general statistical framework for assessing the adequacy of phylogenetic trait models. We use our approach to evaluate the statistical performance of commonly used trait models on 337 comparative data sets covering three key angiosperm functional traits. In general, the models we tested often provided poor statistical explanations for the evolution of these traits. This was true for many different groups and at many different scales. Whether such statistical inadequacy will qualitatively alter inferences drawn from comparative data sets will depend on the context. Regardless, assessing model adequacy can provide interesting biological insights-how and why a model fails to describe variation in a data set give us clues about what evolutionary processes may have driven trait evolution across time.