Niche Theory as an Underutilized Resource for the Study of Adaptive Radiations.

Biologists are often stuck between two opposing questions: Why are there so many species and why are there not more? Although these questions apply to the maintenance of existing species, they equally apply to the formation of new ones. The more species specialize in terms of their niches, the more opportunities arise for new species to form and coexist in communities. What sets an upper limit to specialization, thus setting an upper limit to speciation? We propose that MacArthur's theories of species packing and resource minimization may hold answers. Specifically, resources and individuals are finite-as species become increasingly specialized, each individual has fewer resources it can access. Species can only be as specialized as is possible in a given resource environment while still meeting basic resource requirements. We propose that the upper limit to specialization lies below the threshold that causes populations to be so small that stochastic extinctions take over, and that this limit is likely rarely approached due to the sequential timing by which new lineages arrive.

Delimiting the rare, endangered and actively speciating.

Species delimitation is a contentious topic. The genomics revolution initially brought hope that identifying and classifying species would be easier through better methods and more data, but genomics has also brought complexity and controversy to delimitation. One solution can be to collect a larger sample of individuals at a finer geographic scale. But what if taxa are rare and collecting more samples is difficult or detrimental to the organisms at hand? In this issue of Molecular Ecology Resources, Opatova et al. (2023) tackle the ambiguity of species delimitation in rare and endangered trapdoor spiders (genus Cyclocosmia). The authors propose a framework for delimiting species when samples are hard to come by, such as in these rare and cryptic spiders. The authors combine extensive genomic sampling with statistical approaches that consider both the genetic distinctiveness of each population of spiders and how much gene flow occurs between these populations. Their proposed taxonomy balances two opposing signals, structure and gene flow, to count eight lineages of Cyclocosmia, and to point the way for future taxonomic studies of the rare or difficult to obtain.

Conceptual and empirical bridges between micro- and macroevolution.

Explaining broad molecular, phenotypic and species biodiversity patterns necessitates a unifying framework spanning multiple evolutionary scales. Here we argue that although substantial effort has been made to reconcile microevolution and macroevolution, much work remains to identify the links between biological processes at play. We highlight four major questions of evolutionary biology whose solutions require conceptual bridges between micro and macroevolution. We review potential avenues for future research to establish how mechanisms at one scale (drift, mutation, migration, selection) translate to processes at the other scale (speciation, extinction, biogeographic dispersal) and vice versa. We propose ways in which current comparative methods to infer molecular evolution, phenotypic evolution and species diversification could be improved to specifically address these questions. We conclude that researchers are in a better position than ever before to build a synthesis to understand how microevolutionary dynamics unfold over millions of years.

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].

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.

Frequent origins of traumatic insemination involve convergent shifts in sperm and genital morphology.

Traumatic insemination is a mating behavior during which the (sperm) donor uses a traumatic intromittent organ to inject an ejaculate through the epidermis of the (sperm) recipient, thereby frequently circumventing the female genitalia. Traumatic insemination occurs widely across animals, but the frequency of its evolution, the intermediate stages via which it originates, and the morphological changes that such shifts involve remain poorly understood. Based on observations in 145 species of the free-living flatworm genus Macrostomum, we identify at least nine independent evolutionary origins of traumatic insemination from reciprocal copulation, but no clear indication of reversals. These origins involve convergent shifts in multivariate morphospace of male and female reproductive traits, suggesting that traumatic insemination has a canalizing effect on morphology. We also observed sperm in both the sperm receiving organ and within the body tissue of two species. These species had intermediate trait values indicating that traumatic insemination evolves through initial internal wounding during copulation. Finally, signatures of male-female coevolution of genitalia across the genus indicate that sexual selection and sexual conflict drive the evolution of traumatic insemination, because it allows donors to bypass postcopulatory control mechanisms of recipients.

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.

Estimation of the strength of mate preference from mated pairs observed in the wild.

A number of key processes in evolution are driven by individuals preferring mates with particular phenotypes. However, despite long-standing interest, it is difficult to quantify the strength of mate preference from phenotypic observations in nature in a way that connects directly to key parameters in theoretical models. To bridge the gap between mathematical models and empirical data, we develop a novel maximum likelihood-based method to estimate the strength and form of mate preference, where preference depends on traits expressed in both males and females. Using simulated data, we demonstrate that our method accurately infers model parameters, including the strength of mate preference and the optimal offset match between trait values in mated pairs when model assumptions are satisfied. Applying our method to two previous studies of assortative mating in marine gastropods and the European common frog, we support previous findings, but also give additional insight into the role of mate preference in each system. Our method can be generalized to a variety of plant and animal taxa that exhibit mating preferences to facilitate the testing of evolutionary hypotheses and link empirical data to theoretical models of assortative mating, sexual selection, and speciation.

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.].

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.

A unified model of species abundance, genetic diversity, and functional diversity reveals the mechanisms structuring ecological communities.

Biodiversity accumulates hierarchically by means of ecological and evolutionary processes and feedbacks. Within ecological communities drift, dispersal, speciation, and selection operate simultaneously to shape patterns of biodiversity. Reconciling the relative importance of these is hindered by current models and inference methods, which tend to focus on a subset of processes and their resulting predictions. Here we introduce massive ecoevolutionary synthesis simulations (MESS), a unified mechanistic model of community assembly, rooted in classic island biogeography theory, which makes temporally explicit joint predictions across three biodiversity data axes: (i) species richness and abundances, (ii) population genetic diversities, and (iii) trait variation in a phylogenetic context. Using simulations we demonstrate that each data axis captures information at different timescales, and that integrating these axes enables discriminating among previously unidentifiable community assembly models. MESS is unique in generating predictions of community-scale genetic diversity, and in characterizing joint patterns of genetic diversity, abundance, and trait values. MESS unlocks the full potential for investigation of biodiversity processes using multidimensional community data including a genetic component, such as might be produced by contemporary eDNA or metabarcoding studies. We combine MESS with supervised machine learning to fit the parameters of the model to real data and infer processes underlying how biodiversity accumulates, using communities of tropical trees, arthropods, and gastropods as case studies that span a range of data availability scenarios, and spatial and taxonomic scales.

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.

Insights From Experiments With Rigor in an EvoBio Design Study.

Design study is an established approach of conducting problem-driven visualization research. The academic visualization community has produced a large body of work for reporting on design studies, informed by a handful of theoretical frameworks, and applied to a broad range of application areas. The result is an abundance of reported insights into visualization design, with an emphasis on novel visualization techniques and systems as the primary contribution of these studies. In recent work we proposed a new, interpretivist perspective on design study and six companion criteria for rigor that highlight the opportunities for researchers to contribute knowledge that extends beyond visualization idioms and software. In this work we conducted a year-long collaboration with evolutionary biologists to develop an interactive tool for visual exploration of multivariate datasets and phylogenetic trees. During this design study we experimented with methods to support three of the rigor criteria: ABUNDANT, REFLEXIVE, and TRANSPARENT. As a result we contribute two novel visualization techniques for the analysis of multivariate phylogenetic datasets, three methodological recommendations for conducting design studies drawn from reflections over our process of experimentation, and two writing devices for reporting interpretivist design study. We offer this work as an example for implementing the rigor criteria to produce a diverse range of knowledge contributions.

Hybridizing salamanders experience accelerated diversification.

Whether hybridization generates or erodes species diversity has long been debated, but to date most studies have been conducted at small taxonomic scales. Salamanders (order Caudata) represent a taxonomic order in which hybridization plays a prevalent ecological and evolutionary role. We employed a recently developed model of trait-dependent diversification to test the hypothesis that hybridization impacts the diversification dynamics of species that are currently hybridizing. We find strong evidence supporting this hypothesis, showing that hybridizing salamander lineages have significantly greater net-diversification rates than non-hybridizing lineages. This pattern is driven by concurrently increased speciation rates and decreased extinction rates in hybridizing lineages. Our results support the hypothesis that hybridization can act as a generative force in macroevolutionary diversification.

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.

Identifying models of trait-mediated community assembly using random forests and approximate Bayesian computation.

Ecologists often use dispersion metrics and statistical hypothesis testing to infer processes of community formation such as environmental filtering, competitive exclusion, and neutral species assembly. These metrics have limited power in inferring assembly models because they rely on often-violated assumptions. Here, we adapt a model of phenotypic similarity and repulsion to simulate the process of community assembly via environmental filtering and competitive exclusion, all while parameterizing the strength of the respective ecological processes. We then use random forests and approximate Bayesian computation to distinguish between these models given the simulated data. We find that our approach is more accurate than using dispersion metrics and accounts for uncertainty in model selection. We also demonstrate that the parameter determining the strength of the assembly processes can be accurately estimated. This approach is available in the R package CAMI; Community Assembly Model Inference. We demonstrate the effectiveness of CAMI using an example of plant communities living on lava flow islands.

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.

The choice of tree prior and molecular clock does not substantially affect phylogenetic inferences of diversification rates.

Comparative methods allow researchers to make inferences about evolutionary processes and patterns from phylogenetic trees. In Bayesian phylogenetics, estimating a phylogeny requires specifying priors on parameters characterizing the branching process and rates of substitution among lineages, in addition to others. Accordingly, characterizing the effect of prior selection on phylogenies is an active area of research. The choice of priors may systematically bias phylogenetic reconstruction and, subsequently, affect conclusions drawn from the resulting phylogeny. Here, we focus on the impact of priors in Bayesian phylogenetic inference and evaluate how they affect the estimation of parameters in macroevolutionary models of lineage diversification. Specifically, we simulate trees under combinations of tree priors and molecular clocks, simulate sequence data, estimate trees, and estimate diversification parameters (e.g., speciation and extinction rates) from these trees. When substitution rate heterogeneity is large, diversification rate estimates deviate substantially from those estimated under the simulation conditions when not captured by an appropriate choice of relaxed molecular clock. However, in general, we find that the choice of tree prior and molecular clock has relatively little impact on the estimation of diversification rates insofar as the sequence data are sufficiently informative and substitution rate heterogeneity among lineages is low-to-moderate.

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.