Language follows a distinct mode of extra-genomic evolution

As one of the most specific, yet most diverse of human behaviors, language is shaped by both genomic and extra-genomic evolution. Sharing methods and models between these modes of evolution has significantly advanced our understanding of language and inspired generalized theories of its evolution. Progress is hampered, however, by the fact that the extra-genomic evolution of languages, i.e. linguistic evolution, maps only partially to other forms of evolution. Contrasting it with the biological evolution of eukaryotes and the cultural evolution of technology as the best understood models, we show that linguistic evolution is special by yielding a stationary dynamic rather than stable solutions, and that this dynamic allows the use of language change for social differentiation while maintaining its global adaptiveness. Linguistic evolution furthermore differs from technological evolution by requiring vertical transmission, allowing the reconstruction of phylogenies; and it differs from eukaryotic biological evolution by foregoing a genotype vs phenotype distinction, allowing deliberate and biased change. Recognising these differences will improve our empirical tools and open new avenues for analyzing how linguistic, cultural, and biological evolution interacted with each other when language emerged in the hominin lineage. Importantly, our framework will help to cope with unprecedented scientific and ethical challenges that presently arise from how rapid cultural evolution impacts language, most urgently from interventional clinical tools for language disorders, potential epigenetic effects of technology on language, artificial intelligence and linguistic communicators, and global losses of linguistic diversity and identity. Beyond language, the distinctions made here allow identifying variation in other forms of biological and cultural evolution, developing new perspectives for empirical research.

Flower morphology as a predictor of pollination mode in a biotic to abiotic pollination continuum

BACKGROUND AND AIMS

Wind pollination has evolved repeatedly in flowering plants, yet the identification of a wind pollination syndrome as a set of integrated floral traits can be elusive. Thalictrum (Ranunculaceae) comprises temperate perennial herbs that have transitioned repeatedly from insect to wind pollination while also exhibiting mixed pollination, providing an ideal system to test for evolutionary correlation between floral morphology and pollination mode in a biotic to abiotic continuum. Moreover, the lack of floral organ fusion across this genus allows testing for specialization to pollination vectors in the absence of this feature.

METHODS

We expanded phylogenetic sampling in the genus from a previous study using six chloroplast loci, which allowed us to test whether species cluster into distinct pollination syndromes based on floral morphology. We then used multivariate analyses on floral traits followed by ancestral state reconstruction of the emerging flower morphotypes and determined whether these traits are evolutionarily correlated under a Bayesian framework with Brownian motion.

KEY RESULTS

Floral traits fell into five distinct clusters, which were reduced to three after considering phylogenetic relatedness and were largely consistent with flower morphotypes and associated pollination vectors. Multivariate evolutionary analyses found a positive correlation between the lengths of floral reproductive structures (styles, stigmas, filaments and anthers). Shorter reproductive structures tracked insect-pollinated species and clades in the phylogeny, whereas longer structures tracked wind-pollinated ones, consistent with selective pressures exerted by biotic vs. abiotic pollination vectors, respectively.

CONCLUSIONS

Although detectable suites of integrated floral traits across Thalictrum were correlated with wind or insect pollination at the extremes of the morphospace distribution, a presumed intermediate, mixed pollination mode morphospace was also detected. Thus, our data broadly support the existence of detectable flower morphotypes from convergent evolution underlying the evolution of pollination mode in Thalictrum, presumably via different paths from an ancestral mixed pollination state.

When can we reconstruct the ancestral state? Beyond Brownian motion

Reconstructing the ancestral state of a group of species helps answer many important questions in evolutionary biology. Therefore, it is crucial to understand when we can estimate the ancestral state accurately. Previous works provide a necessary and sufficient condition, called the big bang condition, for the existence of an accurate reconstruction method under discrete trait evolution models and the Brownian motion model. In this paper, we extend this result to a wide range of continuous trait evolution models. In particular, we consider a general setting where continuous traits evolve along the tree according to stochastic processes that satisfy some regularity conditions. We verify these conditions for popular continuous trait evolution models including Ornstein-Uhlenbeck, reflected Brownian Motion, bounded Brownian Motion, and Cox-Ingersoll-Ross.

CAGEE: Computational Analysis of Gene Expression Evolution

Despite the increasing abundance of whole transcriptome data, few methods are available to analyze global gene expression across phylogenies. Here, we present a new software package (Computational Analysis of Gene Expression Evolution [CAGEE]) for inferring patterns of increases and decreases in gene expression across a phylogenetic tree, as well as the rate at which these changes occur. In contrast to previous methods that treat each gene independently, CAGEE can calculate genome-wide rates of gene expression, along with ancestral states for each gene. The statistical approach developed here makes it possible to infer lineage-specific shifts in rates of evolution across the genome, in addition to possible differences in rates among multiple tissues sampled from the same species. We demonstrate the accuracy and robustness of our method on simulated data and apply it to a data set of ovule gene expression collected from multiple self-compatible and self-incompatible species in the genus Solanum to test hypotheses about the evolutionary forces acting during mating system shifts. These comparisons allow us to highlight the power of CAGEE, demonstrating its utility for use in any empirical system and for the analysis of most morphological traits. Our software is available at https://github.com/hahnlab/CAGEE/.

General statistical model shows that macroevolutionary patterns and processes are consistent with Darwinian gradualism

Macroevolution posed difficulties for Darwin and later theorists because species’ phenotypes frequently change abruptly, or experience long periods of stasis, both counter to the theory of incremental change or gradualism. We introduce a statistical model that accommodates this uneven evolutionary landscape by estimating two kinds of historical change: directional changes that shift the mean phenotype along the branches of a phylogenetic tree, and evolvability changes that alter a clade’s ability to explore its trait-space. In mammals, we find that both processes make substantial independent contributions to explaining macroevolution, and are rarely linked. ‘Watershed’ moments of increased evolvability greatly outnumber reductions in evolutionary potentials, and large or abrupt phenotypic shifts are explicable statistically as biased random walks, allowing macroevolutionary theory to engage with the language and concepts of gradualist microevolution. Our findings recast macroevolutionary phenomena, illustrating the necessity of accounting for a variety of evolutionary processes simultaneously.

‘Macroevolution posed difficulties for Darwin and later theorists because species frequently change abruptly, or experience long periods of stasis, both counter to the theory of incremental change or gradualism. Here, the authors propose a macroevolutionary statistical model that accommodates this uneven evolutionary landscape, and shows how even abrupt macroevolutionary changes are compatible with gradualist microevolutionary processes.’

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01234-1.

Trophic niche shifts and phenotypic trait evolution are largely decoupled in Australasian parrots

BACKGROUND

Trophic shifts from one dietary niche to another have played major roles in reshaping the evolutionary trajectories of a wide range of vertebrate groups, yet their consequences for morphological disparity and species diversity differ among groups.

METHODS

Here, we use phylogenetic comparative methods to examine whether the evolution of nectarivory and other trophic shifts have driven predictable evolutionary pathways in Australasian psittaculid parrots in terms of ecological traits such as body size, beak shape, and dispersal capacity.

RESULTS

We found no evidence for an 'early-burst' scenario of lineage or morphological diversification. The best-fitting models indicate that trait evolution in this group is characterized by abrupt phenotypic shifts (evolutionary jumps), with no sign of multiple phenotypic optima correlating with different trophic strategies. Thus, our results point to the existence of weak directional selection and suggest that lineages may be evolving randomly or slowly toward adaptive peaks they have not yet reached.

CONCLUSIONS

This study adds to a growing body of evidence indicating that the relationship between avian morphology and feeding ecology may be more complex than usually assumed and highlights the importance of adding more flexible models to the macroevolutionary toolbox.

Causes and Consequences of Apparent Timescaling Across All Estimated Evolutionary Rates

Evolutionary rates play a central role in connecting micro- and macroevolution. All evolutionary rate estimates, including rates of molecular evolution, trait evolution, and lineage diversification, share a similar scaling pattern with time: The highest rates are those measured over the shortest time interval. This creates a disconnect between micro- and macroevolution, although the pattern is the opposite of what some might expect: Patterns of change over short timescales predict that evolution has tremendous potential to create variation and that potential is barely tapped by macroevolution. In this review, we discuss this shared scaling pattern across evolutionary rates. We break down possible explanations for scaling into two categories, estimation error and model misspecification, and discuss how both apply to each type of rate. We also discuss the consequences of this ubiquitous pattern, which can lead to unexpected results when comparing ratesover different timescales. Finally, after addressing purely statistical concerns, we explore a few possibilities for a shared unifying explanation across the three types of rates that results from a failure to fully understand and account for how biological processes scale over time.

Macroevolutionary history predicts flowering time but not phenological sensitivity to temperature in grasses

PREMISE

Long-term observations show that flowering phenology has shifted in many lineages in response to climate change. However, it remains unclear whether these results can be generalized to predict the presence, direction, or magnitude of responses in lineages for which we lack long time-series data. If phenological responses are phylogenetically conserved, we can extrapolate from species for which we have data to predict the responses of close relatives. While several studies have found that closely related species flower at similar times, fewer have evaluated whether phylogenetically proximal species respond to environmental change similarly.

METHODS

We paired flowering time data from 3161 manually scored herbarium specimens of 72 species of grasses (Poaceae) with historical climate data and analyzed the phylogenetic signal and phylogenetic half-life of phenological sensitivity. We also ran these analyses on a subset of species showing statistically significant sensitivities, in order to assess the role of sampling bias on phylogenetic signal.

RESULTS

Closely related grass species tend to flower at similar times, but flowering times respond to temperature changes in species-specific ways. We also show that only including species for which there is strong evidence of phenological shifts results in overestimating phylogenetic signal.

CONCLUSIONS

In agreement with other recent studies, our results suggest caution in extrapolating from evidence of phylogenetic similarity to predicting shared responses in this ecologically relevant trait. Future work is needed to better understand the discrepancy between the phylogenetic signal in observed phenological shifts and absence of such signal in sensitivity.

Exploring adaptive landscapes across deep time: A case study using echinoid body size

Adaptive landscapes are a common way of conceptualizing the phenotypic evolution of lineages across deep time. Although multiple approaches exist to implement this concept into operational models of trait evolution, inferring adaptive landscapes from comparative datasets remains challenging. Here, I explore the macroevolutionary dynamics of echinoid body size using data from over 5000 specimens and a phylogenetic framework incorporating a dense fossil sampling and spanning approximately 270 million years. Furthermore, I implement a novel approach of exploring alternative parameterizations of adaptive landscapes that succeeds in finding simpler, yet better-fitting models. Echinoid body size has been constrained to evolve within a single adaptive optimum for much of the clade's history. However, most of the morphological disparity of echinoids was generated by multiple regime shifts that drove the repeated evolution of miniaturized and gigantic forms. Events of body size innovation occurred predominantly in the Late Cretaceous and were followed by a drastic slowdown following the Cretaceous-Paleogene mass extinction. The discovery of these patterns is contingent upon directly sampling fossil taxa. The macroevolution of echinoid body size is therefore characterized by a late increase in disparity (likely linked to an expansion of ecospace), generated by active processes driving lineages toward extreme morphologies.

How should functional relationships be evaluated using phylogenetic comparative methods? A case study using metabolic rate and body temperature

Phylogenetic comparative methods are often used to test functional relationships between traits. However, million-year macroevolutionary observational datasets cannot definitively prove causal links between traits-correlation does not equal causation and experimental manipulation over such timescales is impossible. Although this caveat is widely understood, it is less appreciated that different phylogenetic approaches imply different causal assumptions about the functional relationships of traits. To make meaningful inferences, it is critical that our statistical methods make biologically reasonable assumptions. Here we illustrate the importance of causal reasoning in comparative biology by examining a recent study by Avaria-Llautureo et al (2019). that tested for the evolutionary coupling of metabolic rate and body temperature across endotherms and found that these traits were unlinked through evolutionary time and that body temperatures were, on average, higher in the early Cenozoic than they are today. We argue that the causal assumptions embedded into their models made it impossible for them to test the relevant functional and evolutionary hypotheses. We reanalyze their data using more biologically appropriate models and find support for the exact opposite conclusions, corroborating previous evidence from physiology and paleontology. We highlight the vital need for causal thinking, even when experiments are impossible.

On the Effect of Asymmetrical Trait Inheritance on Models of Trait Evolution

Current phylogenetic comparative methods modeling quantitative trait evolution generally assume that, during speciation, phenotypes are inherited identically between the two daughter species. This, however, neglects the fact that species consist of a set of individuals, each bearing its own trait value. Indeed, because descendent populations after speciation are samples of a parent population, we can expect their mean phenotypes to randomly differ from one another potentially generating a "jump" of mean phenotypes due to asymmetrical trait inheritance at cladogenesis. Here, we aim to clarify the effect of asymmetrical trait inheritance at speciation on macroevolutionary analyses, focusing on model testing and parameter estimation using some of the most common models of quantitative trait evolution. We developed an individual-based simulation framework in which the evolution of phenotypes is determined by trait changes at the individual level accumulating across generations, and cladogenesis occurs then by separation of subsets of the individuals into new lineages. Through simulations, we assess the magnitude of phenotypic jumps at cladogenesis under different modes of trait inheritance at speciation. We show that even small jumps can strongly alter both the results of model selection and parameter estimations, potentially affecting the biological interpretation of the estimated mode of evolution of a trait. Our results call for caution when interpreting analyses of trait evolution, while highlighting the importance of testing a wide range of alternative models. In the light of our findings, we propose that future methodological advances in comparative methods should more explicitly model the intraspecific variability around species mean phenotypes and how it is inherited at speciation.

The macroevolutionary landscape of short-necked plesiosaurians

Throughout their evolution, tetrapods have repeatedly colonised a series of ecological niches in marine ecosystems, producing textbook examples of convergent evolution. However, this evolutionary phenomenon has typically been assessed qualitatively and in broad-brush frameworks that imply simplistic macroevolutionary landscapes. We establish a protocol to visualize the density of trait space occupancy and thoroughly test for the existence of macroevolutionary landscapes. We apply this protocol to a new phenotypic dataset describing the morphology of short-necked plesiosaurians, a major component of the Mesozoic marine food webs (ca. 201 to 66 Mya). Plesiosaurians evolved this body plan multiple times during their 135-million-year history, making them an ideal test case for the existence of macroevolutionary landscapes. We find ample evidence for a bimodal craniodental macroevolutionary landscape separating latirostrines from longirostrine taxa, providing the first phylogenetically-explicit quantitative assessment of trophic diversity in extinct marine reptiles. This bimodal pattern was established as early as the Middle Jurassic and was maintained in evolutionary patterns of short-necked plesiosaurians until a Late Cretaceous (Turonian) collapse to a unimodal landscape comprising longirostrine forms with novel morphologies. This study highlights the potential of severe environmental perturbations to profoundly alter the macroevolutionary dynamics of animals occupying the top of food chains.

Functional Tradeoffs Carry Phenotypes Across the Valley of the Shadow of Death

Functional tradeoffs are often viewed as constraints on phenotypic evolution, but they can also facilitate evolution across the suboptimal valleys separating performance peaks. I explore this process by reviewing a previously published model of how disruptive selection from competing functional demands defines an intermediate performance optimum for morphological systems that cannot simultaneously be optimized for all of the functional roles they must play. Because of the inherent tradeoffs in such a system, its optimal morphology in any particular environmental context will usually be intermediate between the performance peaks of the competing functions. The proportional contribution of each functional demand can be estimated by maximum likelihood from empirically observed morphologies, including complex ones measured with multivariate geometric morphometrics, using this model. The resulting tradeoff weight can be mapped onto a phylogenetic tree to study how the performance optimum has shifted across a functional landscape circumscribed by the function-specific performance peaks. This model of tradeoff evolution is sharply different from one in which a multipeak Ornstein-Uhlenbeck (OU) model is applied to a set of morphologies and a phylogenetic tree to estimate how many separate performance optima exist. The multi-peak OU approach assumes that each branch is pushed toward one of two or more performance peaks that exist simultaneously and are separated by valleys of poor performance, whereas the model discussed here assumes that each branch tracks a single optimal performance peak that wanders through morphospace as the balance of functional demands shifts. That the movements of this net performance peak emerge from changing frequencies of selection events from opposing functional demands are illustrated using a series of computational simulations. These simulations show how functional tradeoffs can carry evolution across putative performance valleys: even though intermediate morphologies may not perform optimally for any one function, they may represent the optimal solution in any environment in which an organism experiences competing functional demands.

Diversification in evolutionary arenas-Assessment and synthesis

Understanding how and why rates of evolutionary diversification vary is a key issue in evolutionary biology, ecology, and biogeography. Evolutionary rates are the net result of interacting processes summarized under concepts such as adaptive radiation and evolutionary stasis. Here, we review the central concepts in the evolutionary diversification literature and synthesize these into a simple, general framework for studying rates of diversification and quantifying their underlying dynamics, which can be applied across clades and regions, and across spatial and temporal scales. Our framework describes the diversification rate (d) as a function of the abiotic environment (a), the biotic environment (b), and clade-specific phenotypes or traits (c); thus, d ~ a,b,c. We refer to the four components (a-d) and their interactions collectively as the "Evolutionary Arena." We outline analytical approaches to this framework and present a case study on conifers, for which we parameterize the general model. We also discuss three conceptual examples: the Lupinus radiation in the Andes in the context of emerging ecological opportunity and fluctuating connectivity due to climatic oscillations; oceanic island radiations in the context of island formation and erosion; and biotically driven radiations of the Mediterranean orchid genus Ophrys. The results of the conifer case study are consistent with the long-standing scenario that low competition and high rates of niche evolution promote diversification. The conceptual examples illustrate how using the synthetic Evolutionary Arena framework helps to identify and structure future directions for research on evolutionary radiations. In this way, the Evolutionary Arena framework promotes a more general understanding of variation in evolutionary rates by making quantitative results comparable between case studies, thereby allowing new syntheses of evolutionary and ecological processes to emerge.

Diversification rate vs. diversification density: Decoupled consequences of plant height for diversification of Alooideae in time and space

While biodiversity hotspots are typically identified on the basis of species number per unit area, their exceptional richness is often attributed, either implicitly or explicitly, to high diversification rates. High species concentrations, however, need not reflect rapid diversification, with the diversity of some hotspots accumulating at modest rates over long timespans. Here we explore the relationship between diversification in time vs. diversification in space and develop the concept of diversification density to describe the spatial scale of species accumulation in a clade. We investigate how plant height is associated with both aspects of diversification in Alooideae, a large plant subfamily with its center of diversity in the Greater Cape Floristic Region. We first reconstruct a time-calibrated phylogeny for Alooideae and demonstrate an evolutionary tendency towards reduced plant height. While plant height does not correlate with diversification rate across Alooideae it does so with diversification per unit space: clades of small plants tend to have the highest diversification densities. Furthermore, we find that diversification in time vs. space are uncorrelated. Our results show that diversification rate and density can be decoupled, and suggest that while some biodiversity hotspots might have been generated by high diversification rates, others are the product of high diversification density.

Characterizing and Comparing Phylogenetic Trait Data from Their Normalized Laplacian Spectrum

The dissection of the mode and tempo of phenotypic evolution is integral to our understanding of global biodiversity. Our ability to infer patterns of phenotypes across phylogenetic clades is essential to how we infer the macroevolutionary processes governing those patterns. Many methods are already available for fitting models of phenotypic evolution to data. However, there is currently no comprehensive nonparametric framework for characterizing and comparing patterns of phenotypic evolution. Here, we build on a recently introduced approach for using the phylogenetic spectral density profile (SDP) to compare and characterize patterns of phylogenetic diversification, in order to provide a framework for nonparametric analysis of phylogenetic trait data. We show how to construct the SDP of trait data on a phylogenetic tree from the normalized graph Laplacian. We demonstrate on simulated data the utility of the SDP to successfully cluster phylogenetic trait data into meaningful groups and to characterize the phenotypic patterning within those groups. We furthermore demonstrate how the SDP is a powerful tool for visualizing phenotypic space across traits and for assessing whether distinct trait evolution models are distinguishable on a given empirical phylogeny. We illustrate the approach in two empirical data sets: a comprehensive data set of traits involved in song, plumage, and resource-use in tanagers, and a high-dimensional data set of endocranial landmarks in New World monkeys. Considering the proliferation of morphometric and molecular data collected across the tree of life, we expect this approach will benefit big data analyses requiring a comprehensive and intuitive framework.

Dietary niche and the evolution of cranial morphology in birds

Cranial morphology in birds is thought to be shaped by adaptive evolution for foraging performance. This understanding of ecomorphological evolution is supported by observations of avian island radiations, such as Darwin's finches, which display rapid evolution of skull shape in response to food resource availability and a strong fit between cranial phenotype and trophic ecology. However, a recent analysis of larger clades has suggested that diet is not necessarily a primary driver of cranial shape and that phylogeny and allometry are more significant factors in skull evolution. We use phenome-scale morphometric data across the breadth of extant bird diversity to test the influence of diet and foraging behaviour in shaping cranial evolution. We demonstrate that these trophic characters are significant but very weak predictors of cranial form at this scale. However, dietary groups exhibit significantly different rates of morphological evolution across multiple cranial regions. Granivores and nectarivores exhibit the highest rates of evolution in the face and cranial vault, whereas terrestrial carnivores evolve the slowest. The basisphenoid, occipital, and jaw joint regions have less extreme differences among dietary groups. These patterns demonstrate that dietary niche shapes the tempo and mode of phenotypic evolution in deep time, despite a weaker than expected form–function relationship across large clades.

Beyond Brownian Motion and the Ornstein-Uhlenbeck Process: Stochastic Diffusion Models for the Evolution of Quantitative Characters

Gaussian processes, such as Brownian motion and the Ornstein-Uhlenbeck process, have been popular models for the evolution of quantitative traits and are widely used in phylogenetic comparative methods. However, they have drawbacks that limit their utility. Here we describe new, non-Gaussian stochastic differential equation (diffusion) models of quantitative trait evolution. We present general methods for deriving new diffusion models and develop new software for fitting non-Gaussian evolutionary models to trait data. The theory of stochastic processes provides a mathematical framework for understanding the properties of current and future phylogenetic comparative methods. Attention to the mathematical details of models of trait evolution and diversification may help avoid some pitfalls when using stochastic processes to model macroevolution.

Linking micro and macroevolution in the presence of migration

Understanding macroevolutionary patterns is central to evolutionary biology. This involves the process of divergence within a species, which starts at the microevolutionary level, for instance, when two subpopulations evolve towards different phenotypic optima. The speed at which these optima are reached is controlled by the degree of stabilising selection, which pushes the mean trait towards different optima in the different subpopulations, and ongoing migration that pulls the mean phenotype away from that optimum. Traditionally, macro phenotypic evolution is modelled by directional selection processes, but these models usually ignore the role of migration within species. Here, our goal is to reconcile the processes of micro and macroevolution by modelling migration as part of the speciation process. More precisely, we introduce an Ornstein-Uhlenbeck (OU) model where migration happens between two subpopulations within a branch of a phylogeny and this migration decreases over time as it happens during speciation. We then use this model to study the evolution of trait means along a phylogeny, as well as the way phenotypic disparity between species changes with successive epochs. We show that ignoring the effect of migration in sampled time-series data biases significantly the estimation of the selective forces acting upon it. We also show that migration decreases the expected phenotypic disparity between species and we analyse the effect of migration in the particular case of niche filling. We further introduce a method to jointly estimate selection and migration from time-series data. Our model extends traditional quantitative genetics results of selection and migration from a microevolutionary time frame to multiple speciation events at a macroevolutionary scale. Our results further support that not accounting for gene flow has important consequences in inferences at both the micro and macroevolutionary scale.

Performance Surface Analysis Identifies Consistent Functional Patterns across 10 Morphologically Divergent Terrestrial Turtle Lineages

Newly-developed methods for utilizing performance surfaces—multivariate representations of the relationship between phenotype and functional performance—allow researchers to test hypotheses about adaptive landscapes and evolutionary diversification with explicit attention to functional factors. Here, information from performance surfaces of three turtle shell functions—shell strength, hydrodynamics, and self-righting—is used to test the hypothesis that turtle lineages transitioning from aquatic to terrestrial habitats show patterns of shell shape evolution consistent with decreased importance of hydrodynamic performance. Turtle shells are excellent model systems for evolutionary functional analysis. The evolution of terrestriality is an interesting test case for the efficacy of these methods because terrestrial turtles do not show a straightforward pattern of morphological convergence in shell shape: many terrestrial lineages show increased shell height, typically assumed to decrease hydrodynamic performance, but there are also several lineages where the evolution of terrestriality was accompanied by shell flattening. Performance surface analyses allow exploration of these complex patterns and explicit quantitative analysis of the functional implications of changes in shell shape. Ten lineages were examined. Nearly all terrestrial lineages, including those which experienced decreased shell height, are associated with morphological changes consistent with a decrease in the importance of shell hydrodynamics. This implies a common selective pattern across lineages showing divergent morphological patterns. Performance studies such as these hold great potential for integrating adaptive and performance data in macroevolutionary studies.

Performance in three shell functions predicts the phenotypic distribution of hard-shelled turtles

Adaptive landscapes have served as fruitful guides to evolutionary research for nearly a century. Current methods guided by landscape frameworks mostly utilize evolutionary modeling (e.g., fitting data to Ornstein-Uhlenbeck models) to make inferences about adaptive peaks. Recent alternative methods utilize known relationships between phenotypes and functional performance to derive information about adaptive landscapes; this information can then help explain the distribution of species in phenotypic space and help infer the relative importance of various functions for guiding diversification. Here, data on performance for three turtle shell functions-strength, hydrodynamic efficiency, and self-righting ability-are used to develop a set of predicted performance optima in shell shape space. The distribution of performance optima shows significant similarity to the distribution of existing turtle species and helps explain the absence of shells in otherwise anomalously empty regions of morphospace. The method outperforms a modeling-based approach in inferring the location of reasonable adaptive peaks and in explaining the shape of the phenotypic distributions of turtle shells. Performance surface-based methods allow researchers to more directly connect functional performance with macroevolutionary diversification, and to explain the distribution of species (including presences and absences) across phenotypic space.

Functional biogeography of angiosperms: life at the extremes

Nonlinear relationships between species and their environments are believed common in ecology and evolution, including during angiosperms' rise to dominance. Early angiosperms are thought of as woody evergreens restricted to warm, wet habitats. They have since expanded into numerous cold and dry places. This expansion may have included transitions across important environmental thresholds. To understand linear and nonlinear relationships between angiosperm structure and biogeographic distributions, we integrated large datasets of growth habits, conduit sizes, leaf phenologies, evolutionary histories, and environmental limits. We consider current-day patterns and develop a new evolutionary model to investigate processes that created them. The macroecological pattern was clear: herbs had lower minimum temperature and precipitation limits. In woody species, conduit sizes were smaller in evergreens and related to species' minimum temperatures. Across evolutionary timescales, our new modeling approach found conduit sizes in deciduous species decreased linearly with minimum temperature limits. By contrast, evergreen species had a sigmoidal relationship with minimum temperature limits and an inflection overlapping freezing. These results suggest freezing represented an important threshold for evergreen but not deciduous woody angiosperms. Global success of angiosperms appears tied to a small set of alternative solutions when faced with a novel environmental threshold.