Inferring the ecological and evolutionary determinants of community genetic diversity

Understanding the relative contributions of ecological and evolutionary processes to the structuring of ecological communities is needed to improve our ability to predict how communities may respond to future changes in an increasingly human-modified world. Metabarcoding methods make it possible to gather population genetic data for all species within a community, unlocking a new axis of data to potentially unveil the origins and maintenance of biodiversity at local scales. Here, we present a new eco-evolutionary simulation model for investigating community assembly dynamics using metabarcoding data. The model makes joint predictions of species abundance, genetic variation, trait distributions and phylogenetic relationships under a wide range of parameter settings (e.g. high speciation/low dispersal or vice versa) and across a range of community states, from pristine and unmodified to heavily disturbed. We first demonstrate that parameters governing metacommunity and local community processes leave detectable signatures in simulated biodiversity data axes. Next, using a simulation-based machine learning approach we show that neutral and non-neutral models are distinguishable and that reasonable estimates of several model parameters within the local community can be obtained using only community-scale genetic data, while phylogenetic information is required to estimate those describing metacommunity dynamics. Finally, we apply the model to soil microarthropod metabarcoding data from the Troodos mountains of Cyprus, where we find that communities in widespread forest habitats are structured by neutral processes, while high-elevation and isolated habitats act as an abiotic filter generating non-neutral community structure. We implement our model within the ibiogen R package, a package dedicated to the investigation of island, and more generally community-scale, biodiversity using community-scale genetic data.

Importance of interindividual interactions in eco-evolutionary population dynamics: The rise of demo-genetic agent-based models

The study of eco-evolutionary dynamics, that is of the intertwinning between ecological and evolutionary processes when they occur at comparable time scales, is of growing interest in the current context of global change. However, many eco-evolutionary studies overlook the role of interindividual interactions, which are hard to predict and yet central to selective values. Here, we aimed at putting forward models that simulate interindividual interactions in an eco-evolutionary framework: the demo-genetic agent-based models (DG-ABMs). Being demo-genetic, DG-ABMs consider the feedback loop between ecological and evolutionary processes. Being agent-based, DG-ABMs follow populations of interacting individuals with sets of traits that vary among the individuals. We argue that the ability of DG-ABMs to take into account the genetic heterogeneity-that affects individual decisions/traits related to local and instantaneous conditions-differentiates them from analytical models, another type of model largely used by evolutionary biologists to investigate eco-evolutionary feedback loops. Based on the review of studies employing DG-ABMs and explicitly or implicitly accounting for competitive, cooperative or reproductive interactions, we illustrate that DG-ABMs are particularly relevant for the exploration of fundamental, yet pressing, questions in evolutionary ecology across various levels of organization. By jointly modelling the effects of management practices and other eco-evolutionary processes on interindividual interactions and population dynamics, DG-ABMs are also effective prospective and decision support tools to evaluate the short- and long-term evolutionary costs and benefits of management strategies and to assess potential trade-offs. Finally, we provide a list of the recent practical advances of the ABM community that should facilitate the development of DG-ABMs.

Feeding ecology has shaped the evolution of modern sharks

Sharks are iconic predators in today's oceans, yet their modern diversity has ancient origins. In particular, present hypotheses suggest that a combination of mass extinction, global climate change, and competition has regulated the community structure of dominant mackerel (Lamniformes) and ground (Carcharhiniformes) sharks over the last 66 million years. However, while these scenarios advocate an interplay of major abiotic and biotic events, the precise drivers remain obscure. Here, we focus on the role of feeding ecology using a geometric morphometric analysis of 3,837 fossil and extant shark teeth. Our results reveal that morphological segregation rather than competition has characterized lamniform and carcharhiniform evolution. Moreover, although lamniforms suffered a long-term disparity decline potentially linked to dietary "specialization," their recent disparity rivals that of "generalist" carcharhiniforms. We further confirm that low eustatic sea levels impacted lamniform disparity across the end-Cretaceous mass extinction. Adaptations to changing prey availability and the proliferation of coral reef habitats during the Paleogene also likely facilitated carcharhiniform dispersals and cladogenesis, underpinning their current taxonomic dominance. Ultimately, we posit that trophic partitioning and resource utilization shaped past shark ecology and represent critical determinants for their future species survivorship.

Biogeographical Modeling of Alien Worlds

In this article, we partially quantify the biological potential of an exoplanet. We employ a variety of biogeographical analyses, placing biological evolution in the context of the geological evolution of the planet as a whole. Terrestrial (as in Earthly) biodiversity is tightly constrained in terms of species richness by its environment. An organism's habitable environment may be considered its niche space or hypervolume in terms of the physical characteristics in which that organism can survive and reproduce. This fundamental niche forms the broader space in which the organism realizes its true niche in terms of its interactions with other species. Many of the physical characteristics can be determined from astrophysical constraints and are thus amenable for dissection. However, the geographical space that organisms occupy is driven by the geological evolution of a sizable telluric planet. In turn, this is driven by the progressive differentiation of its interior to produce increasingly felsic crust. Using a variety of available models, we can then constrain the available space that species can inhabit using species-area relationships. By considering a combination of astrophysical constraints and geographical space, we partially quantify the numbers of species that can inhabit the landscape that geology provides. Finally, we also identify a correlation between geomorphological scale and speciation, which, if validated, will allow further dissection of species diversity on alien worlds.

Distance metrics for ranked evolutionary trees

Genealogical tree modeling is essential for estimating evolutionary parameters in population genetics and phylogenetics. Recent mathematical results concerning ranked genealogies without leaf labels unlock opportunities in the analysis of evolutionary trees. In particular, comparisons between ranked genealogies facilitate the study of evolutionary processes of different organisms sampled at multiple time periods. We propose metrics on ranked tree shapes and ranked genealogies for lineages isochronously and heterochronously sampled. Our proposed tree metrics make it possible to conduct statistical analyses of ranked tree shapes and timed ranked tree shapes or ranked genealogies. Such analyses allow us to assess differences in tree distributions, quantify estimation uncertainty, and summarize tree distributions. We show the utility of our metrics via simulations and an application in infectious diseases.

Investigating Biotic Interactions in Deep Time

Recent renewed interest in using fossil data to understand how biotic interactions have shaped the evolution of life is challenging the widely held assumption that long-term climate changes are the primary drivers of biodiversity change. New approaches go beyond traditional richness and co-occurrence studies to explicitly model biotic interactions using data on fossil and modern biodiversity. Important developments in three primary areas of research include analysis of (i) macroevolutionary rates, (ii) the impacts of and recovery from extinction events, and (iii) how humans (Homo sapiens) affected interactions among non-human species. We present multiple lines of evidence for an important and measurable role of biotic interactions in shaping the evolution of communities and lineages on long timescales.

Modeling Mito-nuclear Compatibility and Its Role in Species Identification

Mitochondrial genetic material (mtDNA) is widely used for phylogenetic reconstruction and as a barcode for species identification. The utility of mtDNA in these contexts derives from its particular molecular properties, including its high evolutionary rate, uniparental inheritance, and small size. But mtDNA may also play a fundamental role in speciation-as suggested by recent observations of coevolution with the nuclear DNA, along with the fact that respiration depends on coordination of genes from both sources. Here, we study how mito-nuclear interactions affect the accuracy of species identification by mtDNA, as well as the speciation process itself. We simulate the evolution of a population of individuals who carry a recombining nuclear genome and a mitochondrial genome inherited maternally. We compare a null model fitness landscape that lacks any mito-nuclear interaction against a scenario in which interactions influence fitness. Fitness is assigned to individuals according to their mito-nuclear compatibility, which drives the coevolution of the nuclear and mitochondrial genomes. Depending on the model parameters, the population breaks into distinct species and the model output then allows us to analyze the accuracy of mtDNA barcode for species identification. Remarkably, we find that species identification by mtDNA is equally accurate in the presence or absence of mito-nuclear coupling and that the success of the DNA barcode derives mainly from population geographical isolation during speciation. Nevertheless, selection imposed by mito-nuclear compatibility influences the diversification process and leaves signatures in the genetic content and spatial distribution of the populations, in three ways. First, speciation is delayed and the resulting phylogenetic trees are more balanced. Second, clades in the resulting phylogenetic tree correlate more strongly with the spatial distribution of species and clusters of more similar mtDNA's. Third, there is a substantial increase in the intraspecies mtDNA similarity, decreasing the number of alleles substitutions per locus and promoting the conservation of genetic information. We compare the evolutionary patterns observed in our model to empirical data from copepods (Tigriopus californicus). We find good qualitative agreement in the geographic patterns and the topology of the phylogenetic tree, provided the model includes selection based on mito-nuclear interactions. These results highlight the role of mito-nuclear compatibility in the speciation process and its reconstruction from genetic data.[Mito-nuclear coevolution; mtDNA barcode; parapatry; phylogeny.].

Species Selection Regime and Phylogenetic Tree Shape

Species selection, the effect of heritable traits in generating between-lineage diversification rate differences, provides a valuable conceptual framework for understanding the relationship between traits, diversification, and phylogenetic tree shape. An important challenge, however, is that the nature of real diversification landscapes—curves or surfaces which describe the propensity of species-level lineages to diversify as a function of one or more traits—remains poorly understood. Here, we present a novel, time-stratified extension of the QuaSSE model in which speciation/extinction rate is specified as a static or temporally shifting Gaussian or skewed-Gaussian function of the diversification trait. We then use simulations to show that the generally imbalanced nature of real phylogenetic trees, as well as their generally greater than expected frequency of deep branching events, are typical outcomes when diversification is treated as a dynamic, trait-dependent process. Focusing on four basic models (Gaussian-speciation with and without background extinction; skewed-speciation; Gaussian-extinction), we also show that particular features of the species selection regime produce distinct tree shape signatures and that, consequently, a combination of tree shape metrics has the potential to reveal the species selection regime under which a particular lineage diversified. We evaluate this idea empirically by comparing the phylogenetic trees of plant lineages diversifying within climatically and geologically stable environments of the Greater Cape Floristic Region, with those of lineages diversifying in environments that have experienced major change through the Late Miocene-Pliocene. Consistent with our expectations, the trees of lineages diversifying in a dynamic context are less balanced, show a greater concentration of branching events close to the present, and display stronger diversification rate-trait correlations. We suggest that species selection plays an important role in shaping phylogenetic trees but recognize the need for an explicit probabilistic framework within which to assess the likelihoods of alternative diversification scenarios as explanations of a particular tree shape. [Cape flora; diversification landscape; environmental change; gamma statistic; species selection; time-stratified QuaSSE model; trait-dependent diversification; tree imbalance.]

Incorporating alignment uncertainty into Felsenstein's phylogenetic bootstrap to improve its reliability

Motivation

Most evolutionary analyses are based on pre-estimated multiple sequence alignment. Wong et al. established the existence of an uncertainty induced by multiple sequence alignment when reconstructing phylogenies. They were able to show that in many cases different aligners produce different phylogenies, with no simple objective criterion sufficient to distinguish among these alternatives.

Results

We demonstrate that incorporating MSA induced uncertainty into bootstrap sampling can significantly increase correlation between clade correctness and its corresponding bootstrap value. Our procedure involves concatenating several alternative multiple sequence alignments of the same sequences, produced using different commonly used aligners. We then draw bootstrap replicates while favoring columns of the more unique aligner among the concatenated aligners. We named this concatenation and bootstrapping method, Weighted Partial Super Bootstrap (wpSBOOT). We show on three simulated datasets of 16, 32 and 64 tips that our method improves the predictive power of bootstrap values. We also used as a benchmark an empirical collection of 853 1-to-1 orthologous genes from seven yeast species and found wpSBOOT to significantly improve discrimination capacity between topologically correct and incorrect trees. Bootstrap values of wpSBOOT are comparable to similar readouts estimated using a single method. However, for reduced trees by 50% and 95% bootstrap thresholds, wpSBOOT comes out the lowest Type I error (less FP).

Availability

The automated generation of replicates has been implemented in the T-Coffee package, which is available as open source freeware available from www.tcoffee.org.

Supplementary information

Supplementary data are available at Bioinformatics online.

Signatures of Microevolutionary Processes in Phylogenetic Patterns

Phylogenetic trees are representations of evolutionary relationships among species and contain signatures of the processes responsible for the speciation events they display. Inferring processes from tree properties, however, is challenging. To address this problem, we analyzed a spatially-explicit model of speciation where genome size and mating range can be controlled. We simulated parapatric and sympatric (narrow and wide mating range, respectively) radiations and constructed their phylogenetic trees, computing structural properties such as tree balance and speed of diversification. We showed that parapatric and sympatric speciation are well separated by these structural tree properties. Balanced trees with constant rates of diversification only originate in sympatry and genome size affected both the balance and the speed of diversification of the simulated trees. Comparison with empirical data showed that most of the evolutionary radiations considered to have developed in parapatry or sympatry are in good agreement with model predictions. Even though additional forces other than spatial restriction of gene flow, genome size, and genetic incompatibilities, do play a role in the evolution of species formation, the microevolutionary processes modeled here capture signatures of the diversification pattern of evolutionary radiations, regarding the symmetry and speed of diversification of lineages.

The Species Problem from the Modeler's Point of View

How to define a partition of individuals into species is a long-standing question called the species problem in systematics. Here, we focus on this problem in the thought experiment where individuals reproduce clonally and both the differentiation process and the population genealogies are explicitly known. We specify three desirable properties of species partitions: (A) Heterotypy between species, (B) Homotypy within species and (M) Genealogical monophyly of each species. We then ask: How and when is it possible to delineate species in a way satisfying these properties? We point out that the three desirable properties cannot in general be satisfied simultaneously, but that any two of them can. We mathematically prove the existence of the finest partition satisfying (A) and (M) and the coarsest partition satisfying (B) and (M). For each of them, we propose a simple algorithm to build the associated phylogeny out of the genealogy. The ways we propose to phrase the species problem shed new light on the interaction between the genealogical and phylogenetic scales in modeling work. The two definitions centered on the monophyly property can readily be used at a higher taxonomic level as well, e.g., to cluster species into monophyletic genera.

The influence of ecological and geographic limits on the evolution of species distributions and diversity

The role of ecological limits in regulating the distribution and diversification of species remains controversial. Although such limits must ultimately arise from constraints on local species coexistence, this spatial context is missing from most macroevolutionary models. Here, we develop a stochastic, spatially explicit model of species diversification to explore the phylogenetic and biogeographic patterns expected when local diversity is bounded. We show how local ecological limits, by regulating opportunities for range expansion and thus rates of speciation and extinction, lead to temporal slowdowns in diversification and predictable differences in equilibrium diversity between regions. However, our models also show that even when regions have identical diversity limits, the dynamics of diversification and total number of species supported at equilibrium can vary dramatically depending on the relative size of geographic and local ecological niche space. Our model predicts that small regions with higher local ecological limits support a higher standing diversity and more balanced phylogenetic trees than large geographic areas with more stringent constraints on local coexistence. Our findings highlight how considering the spatial context of diversification can provide new insights into the role of ecological limits in driving variation in biodiversity across space, time, and clades.

Clade diversification dynamics and the biotic and abiotic controls of speciation and extinction rates

How ecological interactions, genetic processes, and environmental variability jointly shape the evolution of species diversity remains a challenging problem in biology. We developed an individual-based model of clade diversification to predict macroevolutionary dynamics when resource competition, genetic differentiation, and landscape fluctuations interact. Diversification begins with a phase of geographic adaptive radiation. Extinction rates rise sharply at the onset of the next phase. In this phase of niche self-structuring, speciation and extinction processes, albeit driven by biotic mechanisms (competition and hybridization), have essentially constant rates, determined primarily by the abiotic pace of landscape dynamics. The final phase of diversification begins when intense competition prevents dispersing individuals from establishing new populations. Species’ ranges shrink, causing negative diversity-dependence of speciation rates. These results show how ecological and microevolutionary processes shape macroevolutionary dynamics and rates; they caution against the notion of ecological limits to diversity, and suggest new directions for the phylogenetic analysis of diversification.

The history and patterns of species diversity are shaped by a variety of ecological and evolutionary factors. Here, the authors develop a computational model to predict clade diversification dynamics and rates of speciation and extinction under the influences of resource competition, genetic differentiation, and random landscape fluctuation.

Species notions that combine phylogenetic trees and phenotypic partitions

A recent paper (Manceau and Lambert in bioRxiv, 2017. https://doi.org/10.1101/075580 ) developed a novel approach for describing two well-defined notions of 'species' based on a phylogenetic tree and a phenotypic partition. In this paper, we explore some further combinatorial properties of this approach and describe an extension that allows an arbitrary number of phenotypic partitions to be combined with a phylogenetic tree for these two species notions.

Assessing species saturation: conceptual and methodological challenges

Is there a maximum number of species that can coexist? Intuitively, we assume an upper limit to the number of species in a given assemblage, or that a lineage can produce, but defining and testing this limit has proven problematic. Herein, we first outline seven general challenges of studies on species saturation, most of which are independent of the actual method used to assess saturation. Among these are the challenge of defining saturation conceptually and operationally, the importance of setting an appropriate referential system, and the need to discriminate among patterns, processes and mechanisms. Second, we list and discuss the methodological approaches that have been used to study species saturation. These approaches vary in time and spatial scales, and in the variables and assumptions needed to assess saturation. We argue that assessing species saturation is possible, but that many studies conducted to date have conceptual and methodological flaws that prevent us from currently attaining a good idea of the occurrence of species saturation.

Comparing spatial diversification and meta-population models in the Indo-Australian Archipelago

Reconstructing the processes that have shaped the emergence of biodiversity gradients is critical to understand the dynamics of diversification of life on Earth. Islands have traditionally been used as model systems to unravel the processes shaping biological diversity. MacArthur and Wilson's island biogeographic model predicts diversity to be based on dynamic interactions between colonization and extinction rates, while treating islands themselves as geologically static entities. The current spatial configuration of islands should influence meta-population dynamics, but long-term geological changes within archipelagos are also expected to have shaped island biodiversity, in part by driving diversification. Here, we compare two mechanistic models providing inferences on species richness at a biogeographic scale: a mechanistic spatial-temporal model of species diversification and a spatial meta-population model. While the meta-population model operates over a static landscape, the diversification model is driven by changes in the size and spatial configuration of islands through time. We compare the inferences of both models to floristic diversity patterns among land patches of the Indo-Australian Archipelago. Simulation results from the diversification model better matched observed diversity than a meta-population model constrained only by the contemporary landscape. The diversification model suggests that the dynamic re-positioning of islands promoting land disconnection and reconnection induced an accumulation of particularly high species diversity on Borneo, which is central within the island network. By contrast, the meta-population model predicts a higher diversity on the mainlands, which is less compatible with empirical data. Our analyses highlight that, by comparing models with contrasting assumptions, we can pinpoint the processes that are most compatible with extant biodiversity patterns.

Barrier Displacement on a Neutral Landscape: Toward a Theory of Continental Biogeography

Macroevolutionary theory posits three processes leading to lineage diversification and the formation of regional biotas: dispersal (species geographic range expansion), speciation (species lineage splitting), and extinction (species lineage termination). The Theory of Island Biogeography (TIB) predicts species richness values using just two of these processes; dispersal and extinction. Yet most species on Earth live on continents or continental shelves, and the dynamics of evolutionary diversification at regional and continental scales are qualitatively different from those that govern the formation of species richness on biogeographic islands. Certain geomorphological processes operating perennially on continental platforms displace barriers to gene flow and organismal dispersal, and affect all three terms of macroevolutionary diversification. For example, uplift of a dissected landscape and river capture both merge and separate portions of adjacent areas, allowing dispersal and larger geographic ranges, vicariant speciation and smaller geographic ranges, and extinction when range sizes are subdivided below a minimum persistence threshold. The TIB also does not predict many biogeographic and phylogenetic patterns widely observed in continentally distributed taxa, including: (i) power function-like species-area relationships; (ii) log-normal distribution of species geographic range sizes, in which most species have restricted ranges (are endemic) and few species have broad ranges (are cosmopolitan); (iii) mid-domain effects with more species toward the geographic center, and more early-branching, species-poor clades toward the geographic periphery; (iv) exponential rates of net diversification with log-linear accumulation of lineages through geological time; and (v) power function-like relationships between species-richness and clade diversity, in which most clades are species-poor and few clades are species-rich. Current theory does not provide a robust mechanistic framework to connect these seemingly disparate patterns. Here we present SEAMLESS (Spatially Explicit Area Model of Landscape Evolution by SimulationS) that generates clade diversification by moving geographic barriers on a continuous, neutral landscape. SEAMLESS is a neutral Landscape Evolution Model (LEM) that treats species and barriers as functionally equivalent with respect to model parameters. SEAMLESS differs from other model-based biogeographic methods (e.g., Lagrange, GeoSSE, BayArea, and BioGeoBEARS) by modeling properties of dispersal barriers rather than areas, and by modeling the evolution of species lineages on a continuous landscape, rather than the evolution of geographic ranges along branches of a phylogeny. SEAMLESS shows how dispersal is required to maintain species richness and avoid clade-wide extinction, demonstrates that ancestral range size does not predict species richness, and provides a unified explanation for the suite of commonly observed biogeographic and phylogenetic patterns listed above. SEAMLESS explains how a simple barrier-displacement mechanism affects lineage diversification under neutral conditions, and is advanced here toward the formulation of a general theory of continental biogeography. [Diversification, extinction, geodispersal, macroevolution, river capture, vicariance.].

Inferring epidemiological parameters from phylogenies using regression-ABC: A comparative study

Inferring epidemiological parameters such as the R₀ from time-scaled phylogenies is a timely challenge. Most current approaches rely on likelihood functions, which raise specific issues that range from computing these functions to finding their maxima numerically. Here, we present a new regression-based Approximate Bayesian Computation (ABC) approach, which we base on a large variety of summary statistics intended to capture the information contained in the phylogeny and its corresponding lineage-through-time plot. The regression step involves the Least Absolute Shrinkage and Selection Operator (LASSO) method, which is a robust machine learning technique. It allows us to readily deal with the large number of summary statistics, while avoiding resorting to Markov Chain Monte Carlo (MCMC) techniques. To compare our approach to existing ones, we simulated target trees under a variety of epidemiological models and settings, and inferred parameters of interest using the same priors. We found that, for large phylogenies, the accuracy of our regression-ABC is comparable to that of likelihood-based approaches involving birth-death processes implemented in BEAST2. Our approach even outperformed these when inferring the host population size with a Susceptible-Infected-Removed epidemiological model. It also clearly outperformed a recent kernel-ABC approach when assuming a Susceptible-Infected epidemiological model with two host types. Lastly, by re-analyzing data from the early stages of the recent Ebola epidemic in Sierra Leone, we showed that regression-ABC provides more realistic estimates for the duration parameters (latency and infectiousness) than the likelihood-based method. Overall, ABC based on a large variety of summary statistics and a regression method able to perform variable selection and avoid overfitting is a promising approach to analyze large phylogenies.

Given the rapid evolution of many pathogens, analysing their genomes by means of phylogenies can inform us about how they spread. This is the focus of the field known as “phylodynamics”. Most existing methods inferring epidemiological parameters from virus phylogenies are limited by the difficulty of handling complex likelihood functions, which commonly incorporate latent variables. Here, we use an alternative method known as regression-based Approximate Bayesian Computation (ABC), which circumvents this problem by using simulations and dataset comparisons. Since phylogenies are difficult to compare to one another, we introduce many summary statistics to describe them and take advantage of current machine learning techniques able to perform variable selection. We show that the accuracy we reach is comparable to that of existing methods. This accuracy increases with phylogeny size and can even be higher than that of existing methods for some parameters. Overall, regression-based ABC opens new perspectives to infer epidemiological parameters from large phylogenies.

Evolution in a Community Context: On Integrating Ecological Interactions and Macroevolution

Despite a conceptual understanding that evolution and species interactions are inextricably linked, it remains challenging to study ecological and evolutionary dynamics together over long temporal scales. In this review, we argue that, despite inherent challenges associated with reconstructing historical processes, the interplay of ecology and evolution is central to our understanding of macroevolution and community coexistence, and cannot be safely ignored in community and comparative phylogenetic studies. We highlight new research avenues that foster greater consideration of both ecological and evolutionary dynamics as processes that occur along branches of phylogenetic trees. By promoting new ways forward using this perspective, we hope to inspire further integration that creatively co-utilizes phylogenies and ecological data to study eco-evolutionary dynamics over time and space.

Towards a mechanistic foundation of evolutionary theory

Most evolutionary thinking is based on the notion of fitness and related ideas such as fitness landscapes and evolutionary optima. Nevertheless, it is often unclear what fitness actually is, and its meaning often depends on the context. Here we argue that fitness should not be a basal ingredient in verbal or mathematical descriptions of evolution. Instead, we propose that evolutionary birth-death processes, in which individuals give birth and die at ever-changing rates, should be the basis of evolutionary theory, because such processes capture the fundamental events that generate evolutionary dynamics. In evolutionary birth-death processes, fitness is at best a derived quantity, and owing to the potential complexity of such processes, there is no guarantee that there is a simple scalar, such as fitness, that would describe long-term evolutionary outcomes. We discuss how evolutionary birth-death processes can provide useful perspectives on a number of central issues in evolution.

DOI:http://dx.doi.org/10.7554/eLife.23804.001

Understanding how biodiversity unfolds through time under neutral theory

Theoretical predictions for biodiversity patterns are typically derived under the assumption that ecological systems have reached a dynamic equilibrium. Yet, there is increasing evidence that various aspects of ecological systems, including (but not limited to) species richness, are not at equilibrium. Here, we use simulations to analyse how biodiversity patterns unfold through time. In particular, we focus on the relative time required for various biodiversity patterns (macroecological or phylogenetic) to reach equilibrium. We simulate spatially explicit metacommunities according to the Neutral Theory of Biodiversity (NTB) under three modes of speciation, which differ in how evenly a parent species is split between its two daughter species. We find that species richness stabilizes first, followed by species area relationships (SAR) and finally species abundance distributions (SAD). The difference in timing of equilibrium between these different macroecological patterns is the largest when the split of individuals between sibling species at speciation is the most uneven. Phylogenetic patterns of biodiversity take even longer to stabilize (tens to hundreds of times longer than species richness) so that equilibrium predictions from neutral theory for these patterns are unlikely to be relevant. Our results suggest that it may be unwise to assume that biodiversity patterns are at equilibrium and provide a first step in studying how these patterns unfold through time.

Diversity and Coevolutionary Dynamics in High-Dimensional Phenotype Spaces

We study macroevolutionary dynamics by extending microevolutionary competition models to long timescales. It has been shown that for a general class of competition models, gradual evolutionary change in continuous phenotypes (evolutionary dynamics) can be nonstationary and even chaotic when the dimension of the phenotype space in which the evolutionary dynamics unfold is high. It has also been shown that evolutionary diversification can occur along nonequilibrium trajectories in phenotype space. We combine these lines of thinking by studying long-term coevolutionary dynamics of emerging lineages in multidimensional phenotype spaces. We use a statistical approach to investigate the evolutionary dynamics of many different systems. We find (1) that, for a given dimension of phenotype space, the coevolutionary dynamics tend to be fast and nonstationary for an intermediate number of coexisting lineages but tend to stabilize as the evolving communities reach a saturation level of diversity and (2) that the amount of diversity at the saturation level increases rapidly (exponentially) with the dimension of phenotype space. These results have implications for theoretical perspectives on major macroevolutionary patterns such as adaptive radiation, long-term temporal patterns of phenotypic changes, and the evolution of diversity.