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Bayesian phylogenetic inference requires a tree prior, which models the underlying diversification process which gives rise to the phylogeny. Existing birth-death diversification models include a wide range of features, for instance lineage-specific variations in speciation and extinction rates. While across-lineage variation in speciation and extinction rates is widespread in empirical datasets, few heterogeneous rate models have been implemented as tree priors for Bayesian phylogenetic inference. As a consequence, rate heterogeneity is typically ignored when reconstructing phylogenies, and rate heterogeneity is usually investigated on fixed trees. In this paper, we present a new BEAST2 package implementing the cladogenetic diversification rate shift (ClaDS) model as a tree prior. ClaDS is a birth-death diversification model designed to capture small progressive variations in birth and death rates along a phylogeny. Unlike previous implementations of ClaDS, which were designed to be used with fixed, user-chosen phylogenies, our package is implemented in the BEAST2 framework and thus allows full phylogenetic inference, where the phylogeny and model parameters are co-estimated from a molecular alignment. Our package provides all necessary components of the inference, including a new tree object and operators to propose moves to the MCMC. It also includes a graphical interface through BEAUti. We validate our implementation of the package by comparing the produced distributions to simulated data, and show an empirical example of the full inference, using a dataset of cetaceans.

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.]

Current understanding of ecological and evolutionary processes underlying island biodiversity is heavily shaped by empirical data from plants and birds, although arthropods comprise the overwhelming majority of known animal species, and as such can provide key insights into processes governing biodiversity. Novel high throughput sequencing (HTS) approaches are now emerging as powerful tools to overcome limitations in the availability of arthropod biodiversity data, and hence provide insights into these processes. Here, we explored how these tools might be most effectively exploited for comprehensive and comparable inventory and monitoring of insular arthropod biodiversity. We first reviewed the strengths, limitations and potential synergies among existing approaches of high throughput barcode sequencing. We considered how this could be complemented with deep learning approaches applied to image analysis to study arthropod biodiversity. We then explored how these approaches could be implemented within the framework of an island Genomic Observatories Network (iGON) for the advancement of fundamental and applied understanding of island biodiversity. To this end, we identified seven island biology themes at the interface of ecology, evolution and conservation biology, within which collective and harmonized efforts in HTS arthropod inventory could yield significant advances in island biodiversity research., The iGON Working Group was organized by the iBioGen project, which has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 810729.

Long-term vertical transmissions of gut bacteria are thought to be frequent and functionally important in mammals. Several phylogenetic-based approaches have been proposed to detect, among species-rich microbiota, the bacteria that have been vertically transmitted during a host clade radiation. Applied to mammal microbiota, these methods have sometimes led to conflicting results; in addition, how they cope with the slow evolution of markers typically used to characterize bacterial microbiota remains unclear. Here, we use simulations to test the statistical performances of two widely-used global-fit approaches (ParaFit and PACo) and two event-based approaches (ALE and HOME). We find that these approaches have different strengths and weaknesses depending on the amount of variation in the bacterial DNA sequences and are therefore complementary. In particular, we show that ALE performs better when there is a lot of variation in the bacterial DNA sequences, whereas HOME performs better when there is not. Global-fit approaches (ParaFit and PACo) have higher type-I error rates (false positives) but have the advantage to be very fast to run. We apply these methods to the gut microbiota of primates and our results suggest that only a small fraction of their gut bacteria is vertically transmitted.

Analysing diversification dynamics is key to understanding the past evolutionary history of clades that led to present-day biodiversity patterns. While such analyses are widespread in well-characterized groups of species, they are much more challenging in groups for which diversity is mostly known through molecular techniques. Here, we use the largest global database on the small subunit (SSU) rRNA gene of Glomeromycotina, a subphylum of microscopic arbuscular mycorrhizal fungi that provide mineral nutrients to most land plants by forming one of the oldest terrestrial symbioses, to analyse the diversification dynamics of this clade in the past 500 million years. We perform a range of sensitivity analyses and simulations to control for potential biases linked to the nature of the data. We find that Glomeromycotina tend to have low speciation rates compared to other eukaryotes. After a peak of speciations between 200 and 100 million years ago, they experienced an important decline in speciation rates toward the present. Such a decline could be at least partially related to a shrinking of their mycorrhizal niches and to their limited ability to colonize new niches. Our analyses identify patterns of diversification in a group of obligate symbionts of major ecological and evolutionary importance and illustrate that short molecular markers combined with intensive sensitivity analyses can be useful for studying diversification dynamics in microbial groups.

International audience; The degree of similarity between the microbiotas of host species often mirrors the phylogenetic proximity of the hosts. This pattern, referred to as phylosymbiosis, is widespread in animals and plants. While phylosymbiosis was initially interpreted as the signal of symbiotic transmission and coevolution between microbes and their hosts, it is now recognized that similar patterns can emerge even if the microbes are environmentally acquired. Distinguishing between these two scenarios, however, remains challenging. We recently developed HOME (host-microbiota evolution), a cophylogenetic model designed to detect vertically transmitted microbes and host switches from amplicon sequencing data. Here, we applied HOME to the microbiotas of Hawaiian spiders of the genus Ariamnes, which experienced a recent radiation on the archipelago. We demonstrate that although Hawaiian Ariamnes spiders display a significant phylosymbiosis, there is little evidence of microbial vertical transmission. Next, we performed simulations to validate the absence of transmitted microbes in Ariamnes spiders. We show that this is not due to a lack of detection power because of the low number of segregating sites or an effect of phylogenetically driven or geographically driven host switches. Ariamnes spiders and their associated microbes therefore provide an example of a pattern of phylosymbiosis likely emerging from processes other than vertical transmission. IMPORTANCE How host-associated microbiotas assemble and evolve is one of the outstanding questions of microbial ecology. Studies aiming at answering this question have repeatedly found a pattern of "phylosymbiosis," that is, a phylogenetic signal in the composition of host-associated microbiotas. While phylosymbiosis was often interpreted as evidence for vertical transmission and host-microbiota coevolution, simulations have now shown that it can emerge from other processes, including host filtering of environmentally acquired microbes. However, distinguishing the processes driving phylosymbiosis in nature remains challenging. We recently developed a cophylogenetic method that can detect vertical transmission. Here, we applied this method to the microbiotas of recently diverged spiders from the Hawaiian archipelago, which display a clear phylosymbiosis pattern. We found that none of the bacterial operational taxonomic units is vertically transmitted. We show with simulations that this result is not due to methodological artifacts. Thus, we provide a striking empirical example of phylosymbiosis emerging from processes other than vertical transmission. KEYWORDS microbiota, phylosymbiosis, vertical transmission, host filtering, Hawaiian arthropods, endosymbionts M ost multicellular organisms host complex microbial communities, referred to as microbiotas, which provide important functions to their hosts (1, 2). Although these microbial communities can fluctuate over short timescales and according to external variables such as animal diet or soil composition (3-5), microbiotas of host individuals from the

Disentangling the relative role of environmental filtering and spatial processes in driving metacommunity structure across mountainous regions remains challenging, as the way we quantify spatial connectivity in topographically and environmentally heterogeneous landscapes can influence our perception of which process predominates. More empirical data sets are required to account for taxon- and context-dependency, but relevant research in understudied areas is often compromised by the taxonomic impediment. Here we used haplotype-level community DNA metabarcoding, enabled by stringent filtering of amplicon sequence variants (ASVs), to characterize metacommunity structure of soil microarthropod assemblages across a mosaic of five forest habitats on the Troodos mountain range in Cyprus. We found similar β diversity patterns at ASV and species (OTU, operational taxonomic unit) levels, which pointed to a primary role of habitat filtering resulting in the existence of largely distinct metacommunities linked to different forest types. Within-habitat turnover was correlated to topoclimatic heterogeneity, again emphasizing the role of environmental filtering. However, when integrating landscape matrix information for the highly fragmented Quercus alnifolia habitat, we also detected a major role of spatial isolation determined by patch connectivity, indicating that stochastic and niche-based processes synergistically govern community assembly. Alpha diversity patterns varied between ASV and OTU levels, with OTU richness decreasing with elevation and ASV richness following a longitudinal gradient, potentially reflecting a decline of genetic diversity eastwards due to historical pressures. Our study demonstrates the utility of haplotype-level community metabarcoding for characterizing metacommunity structure of complex assemblages and improving our understanding of biodiversity dynamics across mountainous landscapes worldwide.

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.

Metabarcoding of DNA extracted from community samples of whole organisms (whole organism community DNA, wocDNA) is increasingly being applied to terrestrial, marine and freshwater metazoan communities to provide rapid, accurate and high resolution data for novel molecular ecology research. The growth of this field has been accompanied by considerable development that builds on microbial metabarcoding methods to develop appropriate and efficient sampling and laboratory protocols for whole organism metazoan communities. However, considerably less attention has focused on ensuring bioinformatic methods are adapted and applied comprehensively in wocDNA metabarcoding. In this study we examined over 600 papers and identified 111 studies that performed COI metabarcoding of wocDNA. We then systematically reviewed the bioinformatic methods employed by these papers to identify the state-of-the-art. Our results show that the increasing use of wocDNA COI metabarcoding for metazoan diversity is characterised by a clear absence of bioinformatic harmonisation, and the temporal trends show little change in this situation. The reviewed literature showed (i) high heterogeneity across pipelines, tasks and tools used, (ii) limited or no adaptation of bioinformatic procedures to the nature of the COI fragment, and (iii) a worrying underreporting of tasks, software and parameters. Based upon these findings we propose a set of recommendations that we think the wocDNA metabarcoding community should consider to ensure that bioinformatic methods are appropriate, comprehensive and comparable. We believe that adhering to these recommendations will improve the long-term integrative potential of wocDNA COI metabarcoding for biodiversity science.

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; 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.

AimLong‐distance dispersal has contributed to the disjunct biogeographical distribution of rain forest plants—something that has fascinated biogeographers since Humboldt's time. However, the dispersal agent for these tropical plant lineages remains puzzling. Here, we investigate which frugivory‐related traits may have facilitated past intercontinental long‐distance dispersal in the custard apple family (Annonaceae), a major vertebrate‐dispersed tropical plant family. We hypothesize that long‐distance dispersal was associated with the evolution of traits related to dispersal by large‐bodied mammals (e.g., large, dull‐coloured, “megafaunal” fruits) and strong‐flying, ocean‐crossing birds and bats (e.g., dehiscent, moniliform or cauliflorous fruits).LocationGlobal.TaxonAnnonaceae.MethodsWe used a fossil‐calibrated phylogenetic framework to infer the biogeographic history of 234 Annonaceae species (10%, covering nearly all genera) in relation to the evolution of 15 frugivory‐related traits, using maximum likelihood and Bayesian inferences. Furthermore, we used linear and generalized linear models and phylogenetic simulations to test whether ancestral fruit traits during intercontinental dispersal were different from those of other lineages not involved in long‐distance dispersal.ResultsWe inferred the ancestral Annonaceae fruits to be small with a single or few small seeds and a small number of fruitlets. These fruits were most probably apocarpous, indehiscent and/or moniliform (i.e., long beads of fruitlets). Furthermore, most of the long‐distance dispersal events in Annonaceae occurred via the expanded tropical forests in the Early Cenozoic (“geodispersal”), and were significantly associated with large (c. 3 cm long), dull‐coloured fruits and short stipes. Additionally, long‐distance dispersal was also facilitated by dehiscent, moniliform and non‐cauliflorous fruits.Main conclusionsWe suggest that the evolution of frugivory‐related traits associated with dispersal by frugivores that frequently move across large distances and/or barriers, such as large‐bodied mammals and strong‐flying birds, has contributed to the disjunct tropical biogeographical distribution of Annonaceae, and probably of tropical rain forest plants more generally.

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.

International audience; A number of approaches for studying macroevolution using phylogenetic trees have been developed in the last few years. Here, we present RPANDA, an R package that implements model‐free and model‐based phylogenetic comparative methods for macroevolutionary analyses. The model‐free approaches implemented in RPANDA are recently developed approaches stemming from graph theory that allow summarizing the information contained in phylogenetic trees, computing distances between trees, and clustering them accordingly. They also allow identifying distinct branching patterns within single trees. RPANDA also implements likelihood‐based models for fitting various diversification models to phylogenetic trees. It includes birth–death models with i) constant, ii) time‐dependent and iii) environmental‐dependent speciation and extinction rates. It also includes models with equilibrium diversity derived from the coalescent process, as well as a likelihood‐based inference framework to fit the individual‐based model of Speciation by Genetic Differentiation, which is an extension of Hubbell's neutral theory of biodiversity. RPANDA can be used to (i) characterize trees by plotting their spectral density profiles (ii) compare trees and cluster them according to their similarities, (iii) identify and plot distinct branching patterns within trees, (iv) compare the fit of alternative diversification models to phylogenetic trees, (v) estimate rates of speciation and extinction, (vi) estimate and plot how these rates have varied with time and environmental variables and (vii) deduce and plot estimates of species richness through geological time. RPANDA provides investigators with a set of tools for exploring patterns in phylogenetic trees and fitting various models to these trees, thereby contributing to the ongoing development of phylogenetics in the life sciences.

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 (pCO2) on early diatom diversification, followed by a major burst of diversification in the late Eocene epoch, after which diversification is chiefly affected by sea level, an influx of silica availability and competition with other planktonic groups. Our results demonstrate a remarkable heterogeneity of diversification dynamics across diatoms and suggest that a changing climate will favour some clades at the expense of others. DNA metabarcoding data from the Tara Oceans expedition are combined with palaeoenvironmental data and phylogenetic models of diversification to analyse the diversity dynamics of marine diatoms since the Jurassic period.

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.

How individual species and entire ecosystems will respond to future climate change are among the most pressing questions facing ecologists. Past biodiversity dynamics recorded in the paleoecological archives show a broad array of responses, yet significant knowledge gaps remain. In particular, the relative roles of evolutionary adaptation, phenotypic plasticity, and dispersal in promoting survival during times of climate change have yet to be clarified. Investigating the paleo-archives offers great opportunities to understand biodiversity responses to future climate change. In this review we discuss the mechanisms by which biodiversity responds to environmental change, and identify gaps of knowledge on the role of range shifts and tolerance. We also outline approaches at the intersection of paleoecology, genomics, experiments, and predictive models that will elucidate the processes by which species have survived past climatic changes and enhance predictions of future changes in biological diversity., F.R-S. was supported by a postdoctoral fellowship from the Spanish Ministerio de Economía y Competitividad (FPD-2013-16756) and a Severo Ochoa Excellence Award (SEV-2012-0262) to Estación Biológica de Doñana. H.M. acknowledges support from the European Research Council Grant ERC 616419- PANDA. L.O. thanks the Natural Environment Research Council UK (NERC) grant NE/N016777/1. DAF acknowledges support from the Australian Research Council Grant FT140101192.

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.

Aim Understanding the relative contribution of diversification rates (speciation and extinction) and dispersal in the formation of the latitudinal diversity gradient – the decrease in species richness with increasing latitude – is a main goal of biogeography. The mammalian order Carnivora, which comprises 286 species, displays the traditional latitudinal diversity gradient seen in almost all mammalian orders. Yet the processes driving high species richness in the tropics may be fundamentally different in this group from that in other mammalian groups. Indeed, a recent study suggested that in Carnivora, unlike in all other major mammalian orders, net diversification rates are not higher in the tropics than in temperate regions. Our goal was thus to understand the reasons why there are more species of Carnivora in the tropics. Location World-wide. Methods We reconstructed the biogeographical history of Carnivora using a time-calibrated phylogeny of the clade comprising all terrestrial species and dispersal–extinction–cladogenesis models. We also analysed a fossil dataset of carnivoran genera to examine how the latitudinal distribution of Carnivora varied through time. Results Our biogeographical analyses suggest that Carnivora originated in the East Palaearctic (i.e. Central Asia, China) in the early Palaeogene. Multiple independent lineages dispersed to low latitudes following three main paths: toward Africa, toward India/Southeast Asia and toward South America via the Bering Strait. These dispersal events were probably associated with local extinctions at high latitudes. Fossil data corroborate a high-latitude origin of the group, followed by late dispersal events toward lower latitudes in the Neogene. Main conclusions Unlike most other mammalian orders, which originated and diversified at low latitudes and dispersed ‘out of the tropics’, Carnivora originated at high latitudes, and subsequently dispersed southward. Our study provides an example of combining phylogenetic and fossil data to understand the generation and maintenance of global-scale geographical variations in species richness.

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.

Understanding how ecological processes determine patterns among species coexisting within ecosystems is central to ecology. Here, we explore relationships between species' local coexistence and their trophic niches in terms of their feeding relationships both as consumers and as resources. We build on recent concepts and methods from community phylogenetics to develop a framework for analysing mechanisms responsible for community composition using trophic similarity among species and null models of community assembly. We apply this framework to 50 food webs found in 50 Adirondack lakes and find that species composition in these communities appears to be driven by both bottom-up effects by which the presence of prey species selects for predators of those prey, and top-down effects by which prey more tolerant of predation out-compete less tolerant prey of the same predators. This approach to community food webs is broadly applicable and shows how species interaction networks can inform an increasingly large array of theory central to community ecology.

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.

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.

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.

Diatoms are one of the most abundant and diverse groups of phytoplankton and play a major role in marine ecosystems and 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 pCO2 variation on early diatom diversification, followed by a major burst of diversification in the late Eocene, after which diversification is chiefly affected by sea level, an influx of silica availability, and competition with other planktonic groups. Our results demonstrate a remarkable heterogeneity of diversification dynamics across diatoms and suggest that a changing climate will favor some clades at the expense of others.

The species abundance distribution (SAD) is one of the few universal patterns in ecology. Research on this fundamental distribution has primarily focused on the study of numerical counts, irrespective of the traits of individuals. Here we show that considering a set of Generalized Species Abundance Distributions (GSADs) encompassing several abundance measures, such as numerical abundance, biomass and resource use, can provide novel insights into the structure of ecological communities and the forces that organize them. We use a taxonomically diverse combination of macroecological data sets to investigate the similarities and differences between GSADs. We then use probability theory to explore, under parsimonious assumptions, theoretical linkages among them. Our study suggests that examining different GSADs simultaneously in natural systems may help with assessing determinants of community structure. Broadening SADs to encompass multiple abundance measures opens novel perspectives in biodiversity research and warrants future empirical and theoretical developments.

Species spatial turnover, or β-diversity, induces a decay of community similarity with geographic distance known as the distance–decay relationship. Although this relationship is central to biodiversity and biogeography, its theoretical underpinnings remain poorly understood. Here, we develop a general framework to describe how the distance–decay relationship is influenced by population aggregation and the landscape-scale species-abundance distribution. We utilize this general framework and data from three tropical forests to show that rare species have a weak influence on distance–decay curves, and that overall similarity and rates of decay are primarily influenced by species abundances and population aggregation respectively. We illustrate the utility of the framework by deriving an exact analytical expression of the distance–decay relationship when population aggregation is characterized by the Poisson Cluster Process. Our study provides a foundation for understanding the distance–decay relationship, and for predicting and testing patterns of beta-diversity under competing theories in ecology. Ecology Letters (2008) 11: 904–917

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.

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.

© 2014 John Wiley & Sons Ltd/CNRS. The study of islands as model systems has played an important role in the development of evolutionary and ecological theory. The 50th anniversary of MacArthur and Wilson's (December 1963) article, 'An equilibrium theory of insular zoogeography', was a recent milestone for this theme. Since 1963, island systems have provided new insights into the formation of ecological communities. Here, building on such developments, we highlight prospects for research on islands to improve our understanding of the ecology and evolution of communities in general. Throughout, we emphasise how attributes of islands combine to provide unusual research opportunities, the implications of which stretch far beyond islands. Molecular tools and increasing data acquisition now permit re-assessment of some fundamental issues that interested MacArthur and Wilson. These include the formation of ecological networks, species abundance distributions, and the contribution of evolution to community assembly. We also extend our prospects to other fields of ecology and evolution - understanding ecosystem functioning, speciation and diversification - frequently employing assets of oceanic islands in inferring the geographic area within which evolution has occurred, and potential barriers to gene flow. Although island-based theory is continually being enriched, incorporating non-equilibrium dynamics is identified as a major challenge for the future., This work was supported by the FRB (Fondation pour la Recherche sur la Biodiversite), through its Centre for Synthesis and Analysis of Biodiversity (CESAB), and the ‘Laboratoire d’Excellence’ TULIP (ANR-10-LABX- 41; ANR-11-IDEX-0002-02). BHW acknowledges funding from the EU Seventh Framework Programme under grant 263958 (RUN-Emerge) and 267243 (Plant Fellows).

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.

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.]

Departamento de Medio Ambiente y Agronomía (INIA)., High‐throughput sequencing (HTS) is increasingly being used for the characterization and monitoring of biodiversity. If applied in a structured way, across broad geographical scales, it offers the potential for a much deeper understanding of global biodiversity through the integration of massive quantities of molecular inventory data generated independently at local, regional and global scales. The universality, reliability and efficiency of HTS data can potentially facilitate the seamless linking of data among species assemblages from different sites, at different hierarchical levels of diversity, for any taxonomic group and regardless of prior taxonomic knowledge. However, collective international efforts are required to optimally exploit the potential of site‐based HTS data for global integration and synthesis, efforts that at present are limited to the microbial domain. To contribute to the development of an analogous strategy for the nonmicrobial terrestrial domain, an international symposium entitled “Next Generation Biodiversity Monitoring” was held in November 2019 in Nicosia (Cyprus). The symposium brought together evolutionary geneticists, ecologists and biodiversity scientists involved in diverse regional and global initiatives using HTS as a core tool for biodiversity assessment. In this review, we summarize the consensus that emerged from the 3‐day symposium. We converged on the opinion that an effective terrestrial Genomic Observatories network for global biodiversity integration and synthesis should be spatially led and strategically united under the umbrella of the metabarcoding approach. Subsequently, we outline an HTS‐based strategy to collectively build an integrative framework for site‐based biodiversity data generation., The international symposium “Next Generation Biodiversity Monitoring” held in November 2019 in Nicosia (Cyprus) was organized by the iBioGen project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 810729. G.F.F. is funded by the European Research Council under the European Union’s Horizon 2020 programme, grant agreement No. 772284 (IceCommunities).