Search

Diversification rates vary across species as a response to various factors, including environmental conditions and species-specific features. Phylogenetic models that allow accounting for and quantifying this heterogeneity in diversification rates have proven particularly useful for understanding clades diversification. Recently, we introduced the cladogenetic diversification rate shift model, which allows inferring multiple rate changes of small magnitude across lineages. Here, we present a new inference technique for this model that considerably reduces computation time through the use of data augmentation and provide an implementation of this method in Julia. In addition to drastically reducing computation time, this new inference approach provides a posterior distribution of the augmented data, that is the tree with extinct and unsampled lineages as well as associated diversification rates. In particular, this allows extracting the distribution through time of both the mean rate and the number of lineages. We assess the statistical performances of our approach using simulations and illustrate its application on the entire bird radiation.[Birth–death model; data augmentation; diversification; macroevolution.]

International audience; A lot of what we know about past speciation and extinction dynamics is based on statistically fitting birth–death processes to phylogenies of extant species. Despite their wide use, the reliability of these tools is regularly questioned. It was recently demonstrated that vast ‘congruent’ sets of alternative diversification histories cannot be distinguished (i.e., are not identifiable) using extant phylogenies alone, reanimating the debate about the limits of phylogenetic diversification analysis. Here, we summarize what we know about the identifiability of the birth–death process and how identifiability issues can be addressed. We conclude that extant phylogenies, when combined with appropriate prior hypotheses and regularization techniques, can still tell us a lot about past diversification dynamics.

Competition can drive macroevolutionary change, for example during adaptive radiations. However, we still lack a clear understanding of how it shapes diversification processes and patterns. To better understand the macroevolutionary consequences of competition, as well as the signal left on phylogenetic data, we developed a model linking trait evolution and species diversification in an ecological context. We find four main results: first, competition spurs trait diversity but not necessarily species richness; second, competition produces slowdowns in species diversification even in the absence of explicit ecological limits, but not in phenotypic diversification even in the presence of such limits; third, early burst patterns do not provide a reliable way of testing for adaptive radiations; and fourth, looking for phylogenetic signal in trait data and support for phenotypic models incorporating competition is a better alternative. Our results clarify the macroevolutionary consequences of competition and could help design more powerful tests of adaptive radiations in nature.

Diversification rates vary over time, yet the factors driving these variations remain unclear. Temporal declines in speciation rates have often been interpreted as the effect of ecological limits, competition, and diversity dependence, emphasising the role of biotic factors. Abiotic factors, such as climate change, are also supposed to have affected diversification rates over geological time scales, yet direct tests of these presumed effects have mainly been limited to few clades well represented in the fossil record. If warmer climatic periods have sustained faster speciation, this could explain slowdowns in speciation during the Cenozoic climate cooling. Here, we apply state-of-the art diversity-dependent and temperature-dependent phylogenetic models of diversification to 218 tetrapod families, along with constant rate and time-dependent models. We confirm the prevalence of diversification slowdowns, and find as much support for temperature-dependent than diversity-dependent models. These results call for a better integration of these two processes in studies of diversification dynamics.

Horizontal gene transfer (HGT) is an important source of novelty in eukaryotic genomes. This is particularly true for the ochrophytes, a diverse and important group of algae. Previous studies have shown that ochrophytes possess a mosaic of genes derived from bacteria and eukaryotic algae, acquired through chloroplast endosymbiosis and from HGTs, although understanding of the time points and mechanisms underpinning these transfers has been restricted by the depth of taxonomic sampling possible. We harness an expanded set of ochrophyte sequence libraries, alongside automated and manual phylogenetic annotation, in silico modeling, and experimental techniques, to assess the frequency and functions of HGT across this lineage. Through manual annotation of thousands of single-gene trees, we identify continuous bacterial HGT as the predominant source of recently arrived genes in the model diatom Phaeodactylum tricornutum. Using a large-scale automated dataset, a multigene ochrophyte reference tree, and mathematical reconciliation of gene trees, we note a probable elevation of bacterial HGTs at foundational points in diatom evolution, following their divergence from other ochrophytes. Finally, we demonstrate that throughout ochrophyte evolutionary history, bacterial HGTs have been enriched in genes encoding secreted proteins. Our study provides insights into the sources and frequency of HGTs, and functional contributions that HGT has made to algal evolution.

International audience; How ecological interaction networks emerge on evolutionary time scales remains unclear. Here we build an individual-based eco-evolutionary model for the emergence of mutualistic, antagonistic and neutral bipartite interaction networks. Exploring networks evolved under these scenarios, we find three main results. First, antagonistic interactions tend to foster species and trait diversity, while mutualistic interactions reduce diversity. Second, antagonistic interactors evolve higher specialisation, which results in networks that are often more modular than neutral ones; resource species in these networks often display phylogenetic conservatism in interaction partners. Third, mutualistic interactions lead to networks that are more nested than neutral ones, with low phylogenetic conservatism in interaction partners. These results tend to match overall empirical trends, demonstrating that structures of empirical networks that have most often been explained by ecological processes can result from an evolutionary emergence. Our model contributes to the ongoing effort of better integrating ecological interactions and macroevolution.

Much ecological and evolutionary theory predicts that interspecific interactions often drive phenotypic diversification and that species phenotypes in turn influence species interactions. Several phylogenetic comparative methods have been developed to assess the importance of such processes in nature; however, the statistical properties of these methods have gone largely untested. Focusing mainly on scenarios of competition between closely-related species, we assess the performance of available comparative approaches for analyzing the interplay between interspecific interactions and species phenotypes. We find that many currently used statistical methods often fail to detect the impact of interspecific interactions on trait evolution, that sister-taxa analyses are particularly unreliable in general, and that recently developed process-based models have more satisfactory statistical properties. Methods for detecting predictors of species interactions are generally more reliable than methods for detecting character displacement. In weighing the strengths and weaknesses of different approaches, we hope to provide a clear guide for empiricists testing hypotheses about the reciprocal effect of interspecific interactions and species phenotypes and to inspire further development of process-based models. [Character displacement; competition; interspecific interactions; phylogenetic comparative methods; trait evolution.]

In standard models of molecular evolution, DNA sequences evolve through asynchronous substitutions according to Poisson processes with a constant rate (called the molecular clock) or a rate that can vary (relaxed clock). However, DNA sequences can also undergo episodes of fast divergence that will appear as synchronous substitutions affecting several sites simultaneously at the macroevolutionary timescale. Here, we develop a model, which we call the Relaxed Clock with Spikes model, combining basal, clock-like molecular substitutions with episodes of fast divergence called spikes arising at speciation events. Given a multiple sequence alignment and its time-calibrated species phylogeny, our model is able to detect speciation events (including hidden ones) cooccurring with spike events and to estimate the probability and amplitude of these spikes on the phylogeny. We identify the conditions under which spikes can be distinguished from the natural variance of the clock-like component of molecular substitutions and from variations of the clock. We apply the method to genes underlying snake venom proteins and identify several spikes at gene-specific locations in the phylogeny. This work should pave the way for analyses relying on whole genomes to inform on modes of species diversification.

International audience; Although mutualistic interactions are widespread and essential in ecosystem functioning, the emergence of uncooperative cheaters threatens their stability, unless there are some physiological or ecological mechanisms limiting interactions with cheaters.In this framework, we investigated the patterns of specialization and phylogenetic distribution of mycoheterotrophic cheaters vs noncheating autotrophic plants and their respective fungi, in a global arbuscular mycorrhizal network with> 25 000 interactions.We show that mycoheterotrophy evolved repeatedly among vascular plants, suggesting low phylogenetic constraints for plants. However, mycoheterotrophic plants are significantly more specialized than autotrophic plants, and they tend to be associated with specialized and closely related fungi. These results raise new hypotheses about the mechanisms (e.g. sanctions, or habitat filtering) that actually limit the interaction of mycoheterotrophic plants and their associated fungi with the rest of the autotrophic plants.Beyond mycorrhizal symbiosis, this unprecedented comparison of mycoheterotrophic vs autotrophic plants provides a network and phylogenetic framework to assess the presence of constraints upon cheating emergences in mutualisms.

International audience; Understanding how and why diversification rates vary through time, space, and across species groups is key to understanding the emergence of today's biodiversity. Phylogenetic approaches aimed at identifying variations in diversification rates during the evolutionary history of clades have focused on exceptional shifts subtending evolutionary radiations. While such shifts have undoubtedly affected the history of life (1),identifying smaller but more frequent changes is important as well. We develop ClaDS, a new Bayesian approach for estimating branch-specific diversification rates on a phylogeny, that relies on a model with changes in diversification rates at each speciation event. We show using Monte-Carlo simulations that the approach performs well at inferring both small and large changes in diversification. Applying our approach to bird phylogenies covering the entire avian radiation, we find that diversification rates are remarkably heterogeneous within evolutionary restricted species groups. Some groups such as Accipitridae (hawks and allies) cover almost the full range of speciation rates found across the entire bird radiation. As much as 76% of the variation in branch-specific rates across this radiation is due to intra-clade variation, suggesting that a large part of the variation in diversification rates is due to many small rather than few large shifts.

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 non-parametric comprehensive framework for characterising and comparing patterns of phenotypic evolution. Here we build on a recently introduced approach for using the phylogenetic spectral density profile to compare and characterize patterns of phylogenetic diversification, in order to provide a framework for non-parametric analysis of phylogenetic trait data. We show how to construct the spectral density profile of trait data on a phylogenetic tree from the normalized graph Laplacian. We demonstrate on simulated data the utility of the spectral density profile to successfully cluster phylogenetic trait data into meaningful groups and to characterise the phenotypic patterning within those groups. We furthermore demonstrate how the spectral density profile is a powerful tool for visualising 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 datasets: a comprehensive dataset of traits involved in song, plumage and resource-use in tanagers, and a high-dimensional dataset 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.

International audience; Microbiota play a central role in the functioning of multicellular life, yet understanding their inheritance during host evolutionary history remains an important challenge. Symbiotic microorganisms are either acquired from the environment during the life of the host (i.e. environmental acquisition), transmitted across generations with a faithful association with their hosts (i.e. strict vertical transmission), or transmitted with occasional host switches (i.e. vertical transmission with horizontal switches). These different modes of inheritance affect microbes’ diversification, which at the two extremes can be independent from that of their associated host or follow host diversification. The few existing quantitative tools for investigating the inheritance of symbiotic organisms rely on cophylogenetic approaches, which require knowledge of both host and symbiont phylogenies, and are therefore often not well adapted to DNA metabarcoding microbial data. Here, we develop a model‐based framework for identifying vertically transmitted microbial taxa. We consider a model for the evolution of microbial sequences on a fixed host phylogeny that includes vertical transmission and horizontal host switches. This model allows estimating the number of host switches and testing for strict vertical transmission and independent evolution. We test our approach using simulations. Finally, we illustrate our framework on gut microbiota high‐throughput sequencing data of the family Hominidae and identify several microbial taxonomic units, including fibrolytic bacteria involved in carbohydrate digestion, that tend to be vertically transmitted.

Building the Tree of Life (ToL) is a major challenge of modern biology, requiring advances in cyberinfrastructure, data collection, theory, and more. Here, we argue that phylogenomics stands to benefit by embracing the many heterogeneous genomic signals emerging from the first decade of large-scale phylogenetic analysis spawned by high-throughput sequencing (HTS). Such signals include those most commonly encountered in phylogenomic datasets, such as incomplete lineage sorting, but also those reticulate processes emerging with greater frequency, such as recombination and introgression. Here we focus specifically on how phylogenetic methods can accommodate the heterogeneity incurred by such population genetic processes; we do not discuss phylogenetic methods that ignore such processes, such as concatenation or supermatrix approaches or supertrees. We suggest that methods of data acquisition and the types of markers used in phylogenomics will remain restricted until a posteriori methods of marker choice are made possible with routine whole-genome sequencing of taxa of interest. We discuss limitations and potential extensions of a model supporting innovation in phylogenomics today, the multispecies coalescent model (MSC). Macroevolutionary models that use phylogenies, such as character mapping, often ignore the heterogeneity on which building phylogenies increasingly rely and suggest that assimilating such heterogeneity is an important goal moving forward. Finally, we argue that an integrative cyberinfrastructure linking all steps of the process of building the ToL, from specimen acquisition in the field to publication and tracking of phylogenomic data, as well as a culture that values contributors at each step, are essential for progress. Funding Agencies|Chalmers University of Technology; University of Gothenburg; Swedish Research Council; U.S. National Science Foundation; European Research Council under the European Unions Seventh Framework Programme (FP/2007-2013, ERC) [331024]; Swedish Foundation for Strategic Research; Wallenberg Academy Fellowship; Conselho Nacional de Desenvolvimento Cientifico e Tecnologico-CNPq; U.S. National Academy of Sciences; U.S. Agency of International Development-PEER NAS/USAID; LOreal-Unesco For Women in Science Program

Understanding the relative influence of various abiotic and biotic variables on diversification dynamics is a major goal of macroevolutionary studies. Recently, phylogenetic approaches have been developed that make it possible to estimate the role of various environmental variables on diversification using time-calibrated species trees, paleoenvironmental data, and maximum-likelihood techniques. These approaches have been effectively employed to estimate how speciation and extinction rates vary with key abiotic variables, such as temperature and sea level, and we can anticipate that they will be increasingly used in the future. Here we compile a series of biotic and abiotic paleodatasets that can be used as explanatory variables in these models and use simulations to assess the statistical properties of the approach when applied to these paleodatasets. We demonstrate that environment-dependent models perform well in recovering environment-dependent speciation and extinction parameters, as well as in correctly identifying the simulated environmental model when speciation isenvironment-dependent. We explore how the strength of the environment-dependency, tree size, missing taxa, and characteristics of the paleoenvironmental curves influence the performance of the models. Finally, using these models, we infer environment-dependent diversification in three empirical phylogenies: temperature-dependence in Cetacea,δ13C-dependence in Ruminantia, andCO2-dependence in Portulacaceae. We illustrate how to evaluate the relative importance of abiotic and biotic variables in these three clades and interpret these results in light of macroevolutionary hypotheses for mammals and plants. Given the important role paleoenvironments are presumed to have played in species evolution, our statistical assessment of how environment-dependent models behave is crucial for their utility in macroevolutionary analysis.

Diatoms are one of the most abundant and diverse groups of phytoplankton and play a major role in marine ecosystems and the Earth's biogeochemical cycles. Here we combine DNA metabarcoding data from the Tara Oceans expedition with palaeoenvironmental data and phylogenetic models of diversification to analyse the diversity dynamics of marine diatoms. We reveal a primary effect of variation in carbon dioxide partial pressure (pCO

Striking evolutionary convergence can lead to similar sets of species in different locations, such as in cichlid fishes and Anolis lizards, and suggests that evolution can be repeatable and predictable across clades. Yet, most examples of convergence involve relatively small temporal and/or spatial scales. Some authors have speculated that at larger scales (e.g., across continents), differing evolutionary histories will prevent convergence. However, few studies have compared the contrasting roles of convergence and history, and none have done so at large scales. Here we develop a two-part approach to test the scale over which convergence can occur, comparing the relative importance of convergence and history in macroevolution using phylogenetic models of adaptive evolution. We apply this approach to data from morphology, ecology, and phylogeny from 167 species of anuran amphibians (frogs) from 10 local sites across the world, spanning ~160 myr of evolution. Mapping ecology on the phylogeny revealed that similar microhabitat specialists (e.g., aquatic, arboreal) have evolved repeatedly across clades and regions, producing many evolutionary replicates for testing for morphological convergence. By comparing morphological optima for clades and microhabitat types (our first test), we find that convergence associated with microhabitat use dominates frog morphological evolution, producing recurrent ecomorphs that together encompass all sampled species in each community in each region. However, our second test, which examines whether and how much species differ from their inferred optima, shows that convergence is incomplete: that is, phenotypes of most species are still somewhat distant from the estimated optimum for each microhabitat, seemingly because of insufficient time for more complete adaptation (an effect of history). Yet, these effects of history are related to past ecologies, and not clade membership. Overall, our study elucidates the dominant drivers of morphological evolution across a major vertebrate clade and shows that evolution can be repeatable at much greater temporal and spatial scales than commonly thought. It also provides an analytical framework for testing other potential examples of large-scale convergence.

Working with high-dimensional phylogenetic comparative data sets is challenging because likelihood-based multivariate methods suffer from low statistical performances as the number of traits $p $ approaches the number of species $n $ and because some computational complications occur when $p $ exceeds $n$. Alternative phylogenetic comparative methods have recently been proposed to deal with the large $p $ small $n $ scenario but their use and performances are limited. Herein, we develop a penalized likelihood (PL) framework to deal with high-dimensional comparative data sets. We propose various penalizations and methods for selecting the intensity of the penalties. We apply this general framework to the estimation of parameters (the evolutionary trait covariance matrix and parameters of the evolutionary model) and model comparison for the high-dimensional multivariate Brownian motion (BM), Early-burst (EB), Ornstein-Uhlenbeck (OU), and Pagel’s lambda models. We show using simulations that our PL approach dramatically improves the estimation of evolutionary trait covariance matrices and model parameters when $p$ approaches $n$, and allows for their accurate estimation when $p$ equals or exceeds $n$. In addition, we show that PL models can be efficiently compared using generalized information criterion (GIC). We implement these methods, as well as the related estimation of ancestral states and the computation of phylogenetic principal component analysis in the R package RPANDA and mvMORPH. Finally, we illustrate the utility of the new proposed framework by evaluating evolutionary models fit, analyzing integration patterns, and reconstructing evolutionary trajectories for a high-dimensional 3D data set of brain shape in the New World monkeys. We find a clear support for an EB model suggesting an early diversification of brain morphology during the ecological radiation of the clade. PL offers an efficient way to deal with high-dimensional multivariate comparative data.

Studies of phylogenetic diversification often show evidence for slowdowns in diversification rates over the history of clades. Recent studies seeking biological explanations for this pattern have emphasized the role of niche differentiation, as in hypotheses of adaptive radiation and ecological limits to diversity. Yet many other biological explanations might underlie diversification slowdowns. In this paper, we focus on the geographic context of diversification, environment-driven bursts of speciation, failure of clades to keep pace with a changing environment, and protracted speciation. We argue that, despite being currently underemphasized, these alternatives represent biologically plausible explanations that should be considered along with niche differentiation. Testing the importance of these alternative hypotheses might yield fundamentally different explanations for what influences species richness within clades through time.

Estimating rates of speciation and extinction, and understanding how and why they vary over evolutionary time, geographical space and species groups, is a key to understanding how ecological and evolutionary processes generate biological diversity. Such inferences will increasingly benefit from phylogenetic approaches given the ever-accelerating rates of genetic sequencing. In the last few years, models designed to understand diversification from phylogenetic data have advanced significantly. Here, I review these approaches and what they have revealed about diversification in the natural world. I focus on key distinctions between different models, and I clarify the conclusions that can be drawn from each model. I identify promising areas for future research. A major challenge ahead is to develop models that more explicitly take into account ecology, in particular the interaction of species with each other and with their environment. This will not only improve our understanding of diversification; it will also present a new perspective to the use of phylogenies in community ecology, the science of interaction networks and conservation biology, and might shift the current focus in ecology on equilibrium biodiversity theories to non-equilibrium theories recognising the crucial role of history.

Predicting how biodiversity will be affected and will respond to human-induced environmental changes is one of the most critical challenges facing ecologists today. Here, we put current environmental changes and their effects on biodiversity in a macroevolutionary perspective. We build on research in palaeontology and recent developments in phylogenetic approaches to ask how macroevolution can help us understand how environmental changes have affected biodiversity in the past, and how they will affect biodiversity in the future. More and more paleontological and phylogenetic data are accumulated, and we argue that much of the potential these data have for understanding environmental changes remains to be explored.

International audience; Understanding why species richness peaks along the Andes is a fundamental question in the study of Neotropical biodiversity. Several biogeographic and diversification scenarios have been proposed in the literature, but there is confusion about the processes underlying each scenario, and assessing their relative contribution is not straightforward. Here, we propose to refine these scenarios into a framework which evaluates four evolutionary mechanisms: higher speciation rate in the Andes, lower extinction rates in the Andes, older colonization times and higher colonization rates of the Andes from adjacent areas. We apply this framework to a species-rich subtribe of Neotropical butterflies whose diversity peaks in the Andes, the Godyridina (Nymphalidae: Ithomi-ini). We generated a time-calibrated phylogeny of the Godyridina and fitted time-dependent diversification models. Using trait-dependent diversification models and ancestral state reconstruction methods we then compared different biogeographic scenarios. We found strong evidence that the rates of colonization into the Andes were higher than the other way round. Those colonizations and the subsequent local diversification at equal rates in the Andes and in non-Andean regions mechanically increased the species richness of Andean regions compared to that of non-Andean regions ('species-attractor' hypothesis). We also found support for increasing speciation rates associated with Andean lineages. Our work highlights the importance of the Andean slopes in repeatedly attracting non-Andean lineages, most likely as a result of the diversity of habitats and/or host plants. Applying this analytical framework to other clades will bring important insights into the evolutionary mechanisms underlying the most species-rich biodiversity hotspot on the planet.

Models of phenotypic evolution fit to phylogenetic comparative data are widely used to make inferences regarding the tempo and mode of trait evolution. A wide range of models is already available for this type of analysis, and the field is still under active development. One of the most needed development concerns models that better account for the effect of within- and between-clade interspecific interactions on trait evolution, which can result from processes as diverse as competition, predation, parasitism, or mutualism. Here, we begin by developing a very general comparative phylogenetic framework for (multi)-trait evolution that can be applied to both ultrametric and nonultrametric trees. This framework not only encapsulates many previous models of continuous univariate and multivariate phenotypic evolution, but also paves the way for the consideration of a much broader series of models in which lineages coevolve, meaning that trait changes in one lineage are influenced by the value of traits in other, interacting lineages. Next, we provide a standard way for deriving the probabilistic distribution of traits at tip branches under our framework. We show that a multivariate normal distribution remains the expected distribution for a broad class of models accounting for interspecific interactions. Our derivations allow us to fit various models efficiently, and in particular greatly reduce the computation time needed to fit the recently proposed phenotype matching model. Finally, we illustrate the utility of our framework by developing a toy model for mutualistic coevolution. Our framework should foster a new era in the study of coevolution from comparative data.

Identifying modes of species diversification is fundamental to our understanding of how biodiversity changes over evolutionary time. Diversification modes are captured in species phylogenies, but characterizing the landscape of diversification has been limited by the analytical tools available for directly comparing phylogenetic trees of groups of organisms. Here, we use a novel, non-parametric approach and 214 family-level phylogenies of vertebrates representing over 500 million years of evolution to identify major diversification modes, to characterize phylogenetic space, and to evaluate the bounds and central tendencies of species diversification. We identify five principal patterns of diversification to which all vertebrate families hold. These patterns, mapped onto multidimensional space, constitute a phylogenetic space with distinct properties. Firstly, phylogenetic space occupies only a portion of all possible tree space, showing family-level phylogenies to be constrained to a limited range of diversification patterns. Secondly, the geometry of phylogenetic space is delimited by quantifiable trade-offs in tree size and the heterogeneity and stem-to-tip distribution of branching events. These trade-offs are indicative of the instability of certain diversification patterns and effectively bound speciation rates (for successful clades) within upper and lower limits. Finally, both the constrained range and geometry of phylogenetic space are established by the differential effects of macroevolutionary processes on patterns of diversification. Given these properties, we show that the average path through phylogenetic space over evolutionary time traverses several diversification stages, each of which is defined by a different principal pattern of diversification and directed by a different macroevolutionary process. The identification of universal patterns and natural constraints to diversification provides a foundation for understanding the deep-time evolution of biodiversity., A meta-analysis of 214 family-level vertebrate trees containing more than 12,000 species and spanning 500 million years of evolution reveals general patterns of species diversification and the constraints acting on them., Author Summary Are there universal laws in the evolution of biodiversity? Why do some clades go extinct and others flourish? These questions are fundamental to our understanding of present-day biodiversity. In a meta-analysis of nearly 12,000 species spanning ~500 million years of evolution, we find that there are five principal patterns of diversification to which all vertebrate families hold, and that these patterns can be mapped into a multidimensional phylogenetic space. Importantly, because certain diversification patterns invariably lead to extinction, clades do not explore all possible phylogenetic space, and thus the evolution of biodiversity is constrained by a set of loose but inviolable rules. We characterize the biotic and abiotic factors precipitating those rules with important implications for our knowledge of the emergence and maintenance of the diversity of life around us.

The study of elevational diversity gradients dates back to the foundation of biogeography. Although elevational patterns of plant and animal diversity have been studied for centuries, such patterns have not been reported for microorganisms and remain poorly understood. Here, in an effort to assess the generality of elevational diversity patterns, we examined soil bacterial and plant diversity along an elevation gradient. To gain insight into the forces that structure these patterns, we adopted a multifaceted approach to incorporate information about the structure, diversity, and spatial turnover of montane communities in a phylogenetic context. We found that observed patterns of plant and bacterial diversity were fundamentally different. While bacterial taxon richness and phylogenetic diversity decreased monotonically from the lowest to highest elevations, plants followed a unimodal pattern, with a peak in richness and phylogenetic diversity at mid-elevations. At all elevations bacterial communities had a tendency to be phylogenetically clustered, containing closely related taxa. In contrast, plant communities did not exhibit a uniform phylogenetic structure across the gradient: they became more overdispersed with increasing elevation, containing distantly related taxa. Finally, a metric of phylogenetic beta-diversity showed that bacterial lineages were not randomly distributed, but rather exhibited significant spatial structure across the gradient, whereas plant lineages did not exhibit a significant phylogenetic signal. Quantifying the influence of sample scale in intertaxonomic comparisons remains a challenge. Nevertheless, our findings suggest that the forces structuring microorganism and macroorganism communities along elevational gradients differ.

The relationship between clade age and species richness has been increasingly used in macroevolutionary studies as evidence for ecologically versus time-dependent diversification processes. However, theory suggests that phylogenetic structure, age type (crown or stem age), and taxonomic delimitation can affect estimates of the age-richness correlation (ARC) considerably. We currently lack an integrative understanding of how these different factors affect ARCs, which in turn, obscures further interpretations. To assess its informative breadth, we characterize ARC behavior with simulated and empirical phylogenies, considering phylogenetic structure and both crown and stem ages. First, we develop a two-state birth-death model to simulate phylogenies including the origin of higher taxa and a hierarchical taxonomy to determine ARC expectations under ecologically and time-dependent diversification processes. Then, we estimate ARCs across various taxonomic ranks of extant amphibians, squamate reptiles, mammals, birds, and flowering plants. We find that our model reproduces the general ARC trends of a wide range of biological systems despite the particularities of taxonomic practice within each, suggesting that the model is adequate to establish a framework of ARC null expectations for different diversification processes when taxa are defined with a hierarchical taxonomy. ARCs estimated with crown ages were positive in all the scenarios we studied, including ecologically dependent processes. Negative ARCs were only found at less inclusive taxonomic ranks, when considering stem age, and when rates varied among clades. This was the case both in ecologically and time-dependent processes. Together, our results warn against direct interpretations of single ARC estimates and advocate for a more integrative use of ARCs across age types and taxonomic ranks in diversification studies. [Birth-Death models; crown age; diversity dependence; extinction; phylogenetic structure; speciation; stem age; taxonomy; time dependence; tree simulations.].

Phylogenetic trees are central to many areas of biology, ranging from population genetics and epidemiology to microbiology, ecology, and macroevolution. The ability to summarize properties of trees, compare different trees, and identify distinct modes of division within trees is essential to all these research areas. But despite wide-ranging applications, there currently exists no common, comprehensive framework for such analyses. Here we present a graph-theoretical approach that provides such a framework. We show how to construct the spectral density profiles of phylogenetic trees from their Laplacian graphs. Using ultrametric simulated trees as well as non-ultrametric empirical trees, we demonstrate that the spectral density successfully identifies various properties of the trees and clusters them into meaningful groups. Finally, we illustrate how the eigengap can identify modes of division within a given tree. As phylogenetic data continue to accumulate and to be integrated into various areas of the life sciences, we expect that this spectral graph-theoretical framework to phylogenetics will have powerful and long-lasting applications.

Many classical ecological and evolutionary theoretical frameworks posit that competition between species is an important selective force. For example, in adaptive radiations, resource competition between evolving lineages plays a role in driving phenotypic diversification and exploration of novel ecological space. Nevertheless, current models of trait evolution fit to phylogenies and comparative datasets are not designed to incorporate the effect of competition. The most advanced models in this direction are diversity-dependent models where evolutionary rates depend on lineage diversity. However, these models still treat changes in traits in one branch as independent of the value of traits on other branches, thus ignoring the effect of species similarity on trait evolution. Here, we consider a model where the evolutionary dynamics of traits involved in interspecific interactions are influenced by species similarity in trait values and where we can specify which lineages are in sympatry. We develop a maximum-likelihood based approach to fit this model to combined phylogenetic and phenotypic data. Using simulations, we demonstrate that the approach accurately estimates the simulated parameter values across a broad range of parameter space. Additionally, we develop tools for specifying the biogeographic context in which trait evolution occurs. In order to compare models, we also apply these biogeographic methods to specify which lineages interact sympatrically for two diversity- dependent models. Finally, we fit these various models to morphological data from a classical adaptive radiation (Greater Antillean Anolis lizards). We show that models that account for competition and geography perform better than other models. The matching competition model is an important new tool for studying the influence of interspecific interactions, in particular competition, on phenotypic evolution. More generally, it constitutes a step toward a better integration of interspecific interactions in many ecological and evolutionary processes.

Background Bayesian relaxed-clock dating has significantly influenced our understanding of the timeline of biotic evolution. This approach requires the use of priors on the branching process, yet little is known about their impact on divergence time estimates. We investigated the effect of branching priors using the iconic cycads. We conducted phylogenetic estimations for 237 cycad species using three genes and two calibration strategies incorporating up to six fossil constraints to (i) test the impact of two different branching process priors on age estimates, (ii) assess which branching prior better fits the data, (iii) investigate branching prior impacts on diversification analyses, and (iv) provide insights into the diversification history of cycads. Results Using Bayes factors, we compared divergence time estimates and the inferred dynamics of diversification when using Yule versus birth-death priors. Bayes factors were calculated with marginal likelihood estimated with stepping-stone sampling. We found striking differences in age estimates and diversification dynamics depending on prior choice. Dating with the Yule prior suggested that extant cycad genera diversified in the Paleogene and with two diversification rate shifts. In contrast, dating with the birth-death prior yielded Neogene diversifications, and four rate shifts, one for each of the four richest genera. Nonetheless, dating with the two priors provided similar age estimates for the divergence of cycads from Ginkgo (Carboniferous) and their crown age (Permian). Of these, Bayes factors clearly supported the birth-death prior. Conclusions These results suggest the choice of the branching process prior can have a drastic influence on our understanding of evolutionary radiations. Therefore, all dating analyses must involve a model selection process using Bayes factors to select between a Yule or birth-death prior, in particular on ancient clades with a potential pattern of high extinction. We also provide new insights into the history of cycad diversification because we found (i) periods of extinction along the long branches of the genera consistent with fossil data, and (ii) high diversification rates within the Miocene genus radiations. Electronic supplementary material The online version of this article (doi:10.1186/s12862-015-0347-8) contains supplementary material, which is available to authorized users.

Understanding patterns in the distribution and abundance of functional traits across a landscape is of fundamental importance to ecology. Mapping these distributions is particularly challenging for species-rich groups with sparse trait measurement coverage, such as flowering plants, insects, and microorganisms. Here, we use likelihood-based character reconstruction to infer and analyze the spatial distribution of unmeasured traits. We apply this framework to a microbial dataset comprised of 11,732 ketosynthase alpha gene sequences extracted from 144 soil samples from three continents to document the spatial distribution of putative microbial polyketide antibiotic production. Antibiotic production is a key competitive strategy for soil microbial survival and performance. Additionally, novel antibiotic discovery is highly relevant to human health, making natural antibiotic production by soil microorganisms a major target for bioprospecting. Our comparison of trait-based biogeographical patterns to patterns based on taxonomy and phylogeny is relevant to our basic understanding of microbial biogeography as well as the pressing need for new antibiotics.

Summary The Proteaceae is a large angiosperm family displaying the common pattern of uneven distribution of species among genera. Previous studies have shown that this disparity is a result of variation in diversification rates across lineages, but the reasons for this variation are still unclear. Here, we tested the impact of floral symmetry and occurrence in Mediterranean climate regions on speciation and extinction rates in the Proteaceae. A rate shift analysis was conducted on dated genus-level phylogenetic trees of the Proteaceae. Character-dependent analyses were used to test for differences in diversification rates between actinomorphic and zygomorphic lineages and between lineages located within or outside Mediterranean climate regions. The rate shift analysis identified 5–10 major diversification rate shifts in the Proteaceae tree. The character-dependent analyses showed that speciation rates, extinction rates and net diversification rates of the Proteaceae were significantly higher for lineages occurring in Mediterranean hotspots. Higher speciation and extinction rates were also detected for zygomorphic species, but net diversification rates appeared to be similar in actinomorphic and zygomorphic Proteaceae. Presence in Mediterranean hotspots favors Proteaceae diversification. In contrast with observations at the scale of angiosperms, floral symmetry is not a trait that strongly influences their evolutionary success.

There is a long tradition in ecology of studying models of biodiversity at equilibrium. These models, including the influential Neutral Theory of Biodiversity, have been successful at predicting major macroecological patterns, such as species abundance distributions. But they have failed to predict macroevolutionary patterns, such as those captured in phylogenetic trees. Here, we develop a model of biodiversity in which all individuals have identical demographic rates, metacommunity size is allowed to vary stochastically according to population dynamics, and speciation arises naturally from the accumulation of point mutations. We show that this model generates phylogenies matching those observed in nature if the metacommunity is out of equilibrium. We develop a likelihood inference framework that allows fitting our model to empirical phylogenies, and apply this framework to various mammalian families. Our results corroborate the hypothesis that biodiversity dynamics are out of equilibrium.

What explains why some groups of organisms, like birds, are so species rich? And what explains their extraordinary ecological diversity, ranging from large, flightless birds to small migratory species that fly thousand of kilometers every year? These and similar questions have spurred great interest in adaptive radiation, the diversification of ecological traits in a rapidly speciating group of organisms. Although the initial formulation of modern concepts of adaptive radiation arose from consideration of the fossil record, rigorous attempts to identify adaptive radiation in the fossil record are still uncommon. Moreover, most studies of adaptive radiation concern groups that are less than 50 million years old. Thus, it is unclear how important adaptive radiation is over temporal scales that span much larger portions of the history of life. In this issue, Benson et al. test the idea of a "deep-time" adaptive radiation in dinosaurs, compiling and using one of the most comprehensive phylogenetic and body-size datasets for fossils. Using recent phylogenetic statistical methods, they find that in most clades of dinosaurs there is a strong signal of an "early burst" in body-size evolution, a predicted pattern of adaptive radiation in which rapid trait evolution happens early in a group's history and then slows down. They also find that body-size evolution did not slow down in the lineage leading to birds, hinting at why birds survived to the present day and diversified. This paper represents one of the most convincing attempts at understanding deep-time adaptive radiations.

International audience; Speciation is not instantaneous but takes time. The protracted birth-death diversification model incorporates this fact and predicts the often observed slowdown of lineage accumulation toward the present. The mathematical complexity of the protracted speciation model has barred estimation of its parameters until recently a method to compute the likelihood of phylogenetic branching times under this model was outlined (Lambert et al. ). Here, we implement this method and study using simulated phylogenies of extant species how well we can estimate the model parameters (rate of initiation of speciation, rate of extinction of incipient and good species, and rate of completion of speciation) as well as the duration of speciation, which is a combination of the aforementioned parameters. We illustrate our approach by applying it to a primate phylogeny. The simulations show that phylogenies often do not contain enough information to provide unbiased estimates of the speciation-initiation rate and the extinction rate, but the duration of speciation can be estimated without much bias. The estimate of the duration of speciation for the primate clade is consistent with literature estimates. We conclude that phylogenies combined with the protracted speciation model provide a promising way to estimate the duration of speciation.

A popular line of research in evolutionary biology is the use of time-calibrated phylogenies for the inference of diversification processes. This requires computing the likelihood of a given ultrametric tree as the reconstructed tree produced by a given model of diversification. Etienne & Rosindell (2012) proposed a lineage-based model of diversification, called protracted speciation, where species remain incipient during a random duration before turning good species, and showed that this can explain the slowdown in lineage accumulation observed in real phylogenies. However, they were unable to provide a general likelihood formula. Here, we present a likelihood formula for protracted speciation models, where rates at which species turn good or become extinct can depend both on their age and on time. Our only restrictive assumption is that speciation rate does not depend on species status. Our likelihood formula utilizes a new technique, based on the contour of the phylogenetic tree and first developed in Lambert (2010). We consider the reconstructed trees spanned by all extant species, by all good extant species, or by all representative species, which are either good extant species or incipient species representative of some good extinct species. Specifically, we prove that each of these trees is a coalescent point process, that is, a planar, ultrametric tree where the coalescence times between two consecutive tips are independent, identically distributed random variables. We characterize the common distribution of these coalescence times in some, biologically meaningful, special cases for which the likelihood reduces to an elegant analytical formula or becomes numerically tractable., 27 pages, 5 figures

The current diversity of life on earth is the product of macroevolutionary processes that have shaped the dynamics of diversification. Although the tempo of diversification has been studied extensively in macroorganisms, much less is known about the rates of diversification in the exceedingly diverse and species-rich microbiota. Decreases in diversification rates over time, a signature of explosive radiations, are commonly observed in plant and animal lineages. However, the few existing analyses of microbial lineages suggest that the tempo of diversification in prokaryotes may be fundamentally different. Here, we use multilocus and genomic sequence data to test hypotheses about the rate of diversification in a well-studied pathogenic bacterial lineage, Borrelia burgdorferi sensu lato (sl). Our analyses support the hypothesis that an explosive radiation of lineages occurred near the origin of the clade, followed by a sharp decay in diversification rates. These results suggest that explosive radiations may be a general feature of evolutionary history across the tree of life.

International audience; Historical patterns of species diversity inferred from phylogenies typically contradict the direct evidence found in the fossil record. According to the fossil record, species frequently go extinct, and many clades experience periods of dramatic diversity loss. However, most analyses of molecular phylogenies fail to identify any periods of declining diversity, and they typically infer low levels of extinction. This striking inconsistency between phylogenies and fossils limits our understanding of macroevolution, and it undermines our confidence in phylogenetic inference. Here, we show that realistic extinction rates and diversity trajectories can be inferred from molecular phylogenies. To make this inference, we derive an analytic expression for the likelihood of a phylogeny that accommodates scenarios of declining diversity, time-variable rates, and incomplete sampling; we show that this likelihood expression reliably detects periods of diversity loss using simulation. We then study the cetaceans (whales, dolphins, and porpoises), a group for which standard phylogenetic inferences are strikingly inconsistent with fossil data. When the cetacean phylogeny is considered as a whole, recently radiating clades, such as the Balaneopteridae, Delphinidae, Phocoenidae, and Ziphiidae, mask the signal of extinctions. However, when isolating these groups, we infer diversity dynamics that are consistent with the fossil record. These results reconcile molecular phylogenies with fossil data, and they suggest that most extant cetaceans arose from four recent radiations, with a few additional species arising from clades that have been in decline over the last ~10 Myr.

Ecologists and conservation biologists have historically used species–area and distance–decay relationships as tools to predict the spatial distribution of biodiversity and the impact of habitat loss on biodiversity. These tools treat each species as evolutionarily equivalent, yet the importance of species' evolutionary history in their ecology and conservation is becoming increasingly evident. Here, we provide theoretical predictions for phylogenetic analogues of the species–area and distance–decay relationships. We use a random model of community assembly and a spatially explicit flora dataset collected in four Mediterranean-type regions to provide theoretical predictions for the increase in phylogenetic diversity – the total phylogenetic branch-length separating a set of species – with increasing area and the decay in phylogenetic similarity with geographic separation. These developments may ultimately provide insights into the evolution and assembly of biological communities, and guide the selection of protected areas.

Summary: Picante is a software package that provides a comprehensive set of tools for analyzing the phylogenetic and trait diversity of ecological communities. The package calculates phylogenetic diversity metrics, performs trait comparative analyses, manipulates phenotypic and phylogenetic data, and performs tests for phylogenetic signal in trait distributions, community structure and species interactions. Availability: Picante is a package for the R statistical language and environment written in R and C, released under a GPL v2 open-source license, and freely available on the web (http://picante.r-forge.r-project.org) and from CRAN (http://cran.r-project.org). Contact: skembel@uoregon.edu

A novel approach to infer diversification dynamics shows that biodiversity is still expanding but at a slower rate than in the past., Recent analyses of the fossil record and molecular phylogenies suggest that there are fundamental limits to biodiversity, possibly arising from constraints in the availability of space, resources, or ecological niches. Under this hypothesis, speciation rates decay over time and biodiversity eventually saturates, with new species emerging only when others are driven to extinction. This view of macro-evolution contradicts an alternative hypothesis that biodiversity is unbounded, with species ever accumulating as they find new niches to occupy. These contrasting theories of biodiversity dynamics yield fundamentally different explanations for the disparity in species richness across taxa and regions. Here, we test whether speciation rates have decayed or remained constant over time, and whether biodiversity is saturated or still expanding. We first derive a general likelihood expression for internode distances in a phylogeny, based on the well-known coalescent process from population genetics. This expression accounts for either time-constant or time-variable rates, time-constant or time-variable diversity, and completely or incompletely sampled phylogenies. We then compare the performance of different diversification scenarios in explaining a set of 289 phylogenies representing amphibians, arthropods, birds, mammals, mollusks, and flowering plants. Our results indicate that speciation rates typically decay over time, but that diversity is still expanding at present. The evidence for expanding-diversity models suggests that an upper limit to biodiversity has not yet been reached, or that no such limit exists., Author Summary Is species diversity in equilibrium, or is it still expanding? Are there ecological limits on diversity, or will evolution always find new niches for further specialization? These are all long-standing questions about the dynamics of macro-evolution, which have been examined using the fossil record and, more recently, molecular phylogenies. Understanding these long-term dynamics is central to our knowledge of how species diversify and ultimately what controls present-day biodiversity across groups and regions. We have developed a novel approach to infer diversification dynamics from the phylogenies of present-day species. Applying our approach to a diverse set of empirical phylogenies, we demonstrate that speciation rates have decayed over time, suggesting ecological constraints to diversification. Nonetheless, we find that diversity is still expanding at present, suggesting either that these ecological constraints do not impose an upper limit to diversity or that this upper limit has not yet been reached.

Understanding what shapes species phenotypes over macroevolutionary timescales from comparative data often requires studying the relationship between phenotypes and putative explanatory factors or testing for differences in phenotypes across species groups. In phyllostomid bats for example, is mandible morphology associated to diet preferences? Performing such analyses depends upon reliable phylogenetic regression techniques and associated tests (e.g., phylogenetic Generalized Least Squares, pGLS, and phylogenetic analyses of variance and covariance, pANOVA, pANCOVA). While these tools are well established for univariate data, their multivariate counterparts are lagging behind. This is particularly true for high-dimensional phenotypic data, such as morphometric data. Here, we implement much-needed likelihood-based multivariate pGLS, pMANOVA, and pMANCOVA, and use a recently developed penalized-likelihood framework to extend their application to the difficult case when the number of traits $p$ approaches or exceeds the number of species $n$. We then focus on the pMANOVA and use intensive simulations to assess the performance of the approach as $p$ increases, under various levels of phylogenetic signal and correlations between the traits, phylogenetic structure in the predictors, and under various types of phenotypic differences across species groups. We show that our approach outperforms available alternatives under all circumstances, with greater power to detect phenotypic differences across species group when they exist, and a lower risk of improperly detecting nonexistent differences. Finally, we provide an empirical illustration of our pMANOVA on a geometric-morphometric data set describing mandible morphology in phyllostomid bats along with data on their diet preferences. Overall our results show significant differences between ecological groups. Our approach, implemented in the R package mvMORPH and illustrated in a tutorial for end-users, provides efficient multivariate phylogenetic regression tools for understanding what shapes phenotypic differences across species. [Generalized least squares; high-dimensional data sets; multivariate phylogenetic comparative methods; penalized likelihood; phenomics; phyllostomid bats; phylogenetic MANOVA; phylogenetic regression.]