Reliable biogeography requires fossils: insights from a new species-level phylogeny of extinct and living carnivores.

A central objective of historical biogeography is to understand where clades originated and how they moved across space and over time. However, given the dynamic history of ecosystem changes in response to climate change and geological events, the manifold long-distance dispersals over evolutionary timescales, and regional and global extinctions, it remains uncertain how reliable inferences based solely on extant taxa can be achieved. Using a novel species-level phylogeny of all known extant and extinct species of the mammalian order Carnivora and related extinct groups, we show that far more precise and accurate ancestral areas can be estimated by fully integrating extinct species into the analyses, rather than solely relying on extant species or identifying ancestral areas only based on the geography of the oldest fossils. Through a series of simulations, we further show that this conclusion is robust under realistic scenarios in which the unknown extinct taxa represent a biased subset of all extinct species. Our results highlight the importance of integrating fossil taxa into a phylogenetic framework to further improve our understanding of historical biogeography and reveal the dynamic dispersal and diversification history of carnivores.

Plant diversity darkspots for global collection priorities.

More than 15% of all vascular plant species may remain scientifically undescribed, and many of the > 350 000 described species have no or few geographic records documenting their distribution. Identifying and understanding taxonomic and geographic knowledge shortfalls is key to prioritising future collection and conservation efforts. Using extensive data for 343 523 vascular plant species and time-to-event analyses, we conducted multiple tests related to plant taxonomic and geographic data shortfalls, and identified 33 global diversity darkspots (those 'botanical countries' predicted to contain most undescribed and not yet recorded species). We defined priority regions for future collection according to several socio-economic and environmental scenarios. Most plant diversity darkspots are found within global biodiversity hotspots, with the exception of New Guinea. We identify Colombia, Myanmar, New Guinea, Peru, Philippines and Turkey as global collection priorities under all environmental and socio-economic conditions considered. Our study provides a flexible framework to help accelerate the documentation of global plant diversity for the implementation of conservation actions. As digitisation of the world's herbaria progresses, collection and conservation priorities may soon be identifiable at finer scales.

Trait-mediated speciation and human-driven extinctions in proboscideans revealed by unsupervised Bayesian neural networks.

Species life-history traits, paleoenvironment, and biotic interactions likely influence speciation and extinction rates, affecting species richness over time. Birth-death models inferring the impact of these factors typically assume monotonic relationships between single predictors and rates, limiting our ability to assess more complex effects and their relative importance and interaction. We introduce a Bayesian birth-death model using unsupervised neural networks to explore multifactorial and nonlinear effects on speciation and extinction rates using fossil data. It infers lineage- and time-specific rates and disentangles predictor effects and importance through explainable artificial intelligence techniques. Analysis of the proboscidean fossil record revealed speciation rates shaped by dietary flexibility and biogeographic events. The emergence of modern humans escalated extinction rates, causing recent diversity decline, while regional climate had a lesser impact. Our model paves the way for an improved understanding of the intricate dynamics shaping clade diversification.

Exploring the Macroevolutionary Signature of Asymmetric Inheritance at Speciation.

Popular comparative phylogenetic models such as Brownian Motion, Ornstein-Ulhenbeck, and their extensions, assume that, at speciation, a trait value is inherited identically by two descendant species. This assumption contrasts with models of speciation at a micro-evolutionary scale where descendants' phenotypic distributions are sub-samples of the ancestral distribution. Different speciation mechanisms can lead to a displacement of the ancestral phenotypic mean among descendants and an asymmetric inheritance of the ancestral phenotypic variance. In contrast, even macro-evolutionary models that account for intraspecific variance assume symmetrically conserved inheritance of ancestral phenotypic distribution at speciation. Here we develop an Asymmetric Brownian Motion model (ABM) that relaxes the assumption of symmetric and conserved inheritance of the ancestral distribution at the time of speciation. The ABM jointly models the evolution of both intra- and inter-specific phenotypic variation. It also infers the mode of phenotypic inheritance at speciation, which can range from a symmetric and conserved inheritance, where descendants inherit the ancestral distribution, to an asymmetric and displaced inheritance, where descendants inherit divergent phenotypic means and variances. To demonstrate this model, we analyze the evolution of beak morphology in Darwin finches, finding evidence of displacement at speciation. The ABM model helps to bridge micro- and macro-evolutionary models of trait evolution by providing a more robust framework for testing the effects of ecological speciation, character displacement, and niche partitioning on trait evolution at the macro-evolutionary scale.

Toward a semi-supervised learning approach to phylogenetic estimation.

Models have always been central to inferring molecular evolution and to reconstructing phylogenetic trees. Their use typically involves the development of a mechanistic framework reflecting our understanding of the underlying biological processes, such as nucleotide substitu- tions, and the estimation of model parameters by maximum likelihood or Bayesian inference. However, deriving and optimizing the likelihood of the data is not always possible under complex evolutionary scenarios or even tractable for large datasets, often leading to unrealistic simplifying assumptions in the fitted models. To overcome this issue, we coupled stochastic simulations of genome evolution with a new supervised deep learning model to infer key parameters of molecular evolution. Our model is designed to directly analyze multiple sequence alignments and estimate per-site evolutionary rates and divergence, without requiring a known phylogenetic tree. The accuracy of our predictions matched that of likelihood-based phylogenetic inference, when rate heterogeneity followed a simple gamma distribution, but it strongly exceeded it under more complex patterns of rate variation, such as codon models. Our approach is highly scalable and can be efficiently applied to genomic data, as we showed on a dataset of 26 million nucleotides from the clownfish clade. Our simulations also showed that the integration of per-site rates obtained by deep learning within a Bayesian framework led to significantly more accu- rate phylogenetic inference, particularly with respect to the estimated branch lengths. We thus propose that future advancements in phylogenetic analysis will benefit from a semi-supervised learning approach that combines deep-learning estimation of substitution rates, which allows for more flexible models of rate variation, and probabilistic inference of the phylogenetic tree, which guarantees interpretability and a rigorous assessment of statistical support.

Heterogeneous selectivity and morphological evolution of marine clades during the Permian-Triassic mass extinction.

Morphological disparity and taxonomic diversity are distinct measures of biodiversity, typically expected to evolve synergistically. However, evidence from mass extinctions indicates that they can be decoupled, and while mass extinctions lead to a drastic loss of diversity, their impact on disparity remains unclear. Here we evaluate the dynamics of morphological disparity and extinction selectivity across the Permian-Triassic mass extinction. We developed an automated approach, termed DeepMorph, for the extraction of morphological features from fossil images using a deep learning model and applied it to a high-resolution temporal dataset encompassing 599 genera across six marine clades. Ammonoids, brachiopods and ostracods experienced a selective loss of complex and ornamented forms, while bivalves, gastropods and conodonts did not experience morphologically selective extinctions. The presence and intensity of morphological selectivity probably reflect the variations in environmental tolerance thresholds among different clades. In clades affected by selective extinctions, the intensity of diversity loss promoted the loss of morphological disparity. Conversely, under non-selective extinctions, the magnitude of diversity loss had a negligible impact on disparity. Our results highlight that the Permian-Triassic mass extinction had heterogeneous morphological selective impacts across clades, offering new insights into how mass extinctions can reshape biodiversity and ecosystem structure.

Two Major Extinction Events in the Evolutionary History of Turtles: One Caused by an Asteroid, the Other by Hominins.

AbstractWe live in a time of accelerated biological extinctions that has the potential to mirror past mass extinction events. However, the rarity of mass extinctions and the restructuring of diversity they cause complicate direct comparisons between the current extinction crisis and earlier events. Among animals, turtles (Testudinata) are one of few groups that have both a rich fossil record and sufficiently stable ecological and functional roles to enable meaningful comparisons between the end-Cretaceous mass extinction (∼66 Ma) and the ongoing wave of extinctions. Here we analyze the fossil record of the entire turtle clade and identify two peaks in extinction rates over their evolutionary history. The first coincides with the Cretaceous-Paleogene transition, reflecting patterns previously reported for other taxa. The second major extinction event started in the Pliocene and continues until now. This peak is detectable only for terrestrial turtles and started much earlier in Africa and Eurasia than elsewhere. On the basis of the timing, geography, and functional group of this extinction event, we postulate a link to co-occurring hominins rather than climate change as the cause. These results lend further support to the view that negative biodiversity impacts were already incurred by our ancestors and related lineages and demonstrate the severity of this continued impact through human activities.

DeepDive: estimating global biodiversity patterns through time using deep learning.

Understanding how biodiversity has changed through time is a central goal of evolutionary biology. However, estimates of past biodiversity are challenged by the inherent incompleteness of the fossil record, even when state-of-the-art statistical methods are applied to adjust estimates while correcting for sampling biases. Here we develop an approach based on stochastic simulations of biodiversity and a deep learning model to infer richness at global or regional scales through time while incorporating spatial, temporal and taxonomic sampling variation. Our method outperforms alternative approaches across simulated datasets, especially at large spatial scales, providing robust palaeodiversity estimates under a wide range of preservation scenarios. We apply our method on two empirical datasets of different taxonomic and temporal scope: the Permian-Triassic record of marine animals and the Cenozoic evolution of proboscideans. Our estimates provide a revised quantitative assessment of two mass extinctions in the marine record and reveal rapid diversification of proboscideans following their expansion out of Africa and a >70% diversity drop in the Pleistocene.

The Clade Replacement Theory: a framework to study age-dependent extinction.

There is no scientific consensus about whether and how species' evolutionary age, or the elapsed time since their origination, might affect their probability of going extinct. Different age-dependent extinction (ADE) patterns have been proposed in theoretical and empirical studies, while the existence of a consistent and universal pattern across the tree of life remains debated. If evolutionary age predicts species extinction probability, then the study of ADE should comprise the elapsed time and the ecological process acting on species from their origin to their extinction or to the present for extant species. Additionally, given that closely related species share traits associated with fitness, evolutionary proximity could generate similar ADE patterns. Considering the historical context and extinction selectivity based on evolutionary relatedness, we build on previous theoretical work to formalize the Clade Replacement Theory (CRT) as a framework that considers the ecological and evolutionary aspects of species age and extinction probability to produce testable predictions on ADE patterns. CRT's domain is the diversification dynamics of two or more clades competing for environmental space throughout time, and its propositions or derived hypotheses are as follows: (i) incumbency effects by an early arriving clade that limit the colonization and the diversification of a younger clade leading to a negative ADE scenario (younger species more prone to extinction than older ones) and (ii) an ecological shift triggered by an environmental change that imposes a new selective regime over the environmental space and leads to a positive ADE scenario (extinction probability increasing with age). From these propositions, we developed the prediction that the ADE scenario would be defined by whether an ecological shift happens or not. We discuss how the CRT could be tested with empirical data and provide examples where it could be applied. We hope this article will provide a common ground to unify results from different fields and foster new empirical tests of the mechanisms derived here while providing insights into CRT theoretical structuration.

Functional diversity of sharks and rays is highly vulnerable and supported by unique species and locations worldwide.

Elasmobranchs (sharks, rays and skates) are among the most threatened marine vertebrates, yet their global functional diversity remains largely unknown. Here, we use a trait dataset of >1000 species to assess elasmobranch functional diversity and compare it against other previously studied biodiversity facets (taxonomic and phylogenetic), to identify species- and spatial- conservation priorities. We show that threatened species encompass the full extent of functional space and disproportionately include functionally distinct species. Applying the conservation metric FUSE (Functionally Unique, Specialised, and Endangered) reveals that most top-ranking species differ from the top Evolutionarily Distinct and Globally Endangered (EDGE) list. Spatial analyses further show that elasmobranch functional richness is concentrated along continental shelves and around oceanic islands, with 18 distinguishable hotspots. These hotspots only marginally overlap with those of other biodiversity facets, reflecting a distinct spatial fingerprint of functional diversity. Elasmobranch biodiversity facets converge with fishing pressure along the coast of China, which emerges as a critical frontier in conservation. Meanwhile, several components of elasmobranch functional diversity fall in high seas and/or outside the global network of marine protected areas. Overall, our results highlight acute vulnerability of the world's elasmobranchs' functional diversity and reveal global priorities for elasmobranch functional biodiversity previously overlooked.

Ontogeny and phylogeny of mating behaviour: social heteroch rony in primates.

Based on the Recognition Concept of species, the specific-mate contact model posits that mating systems develop as combinations of two fundamental courtship strategies that we interpret here in terms of behavioural heterochrony: territorial mate-attraction evolved as an effect of peramorphosis whereas group-living mate-seeking evolved as an effect of paedomorphosis. We tested this hypothesis on primates in a phylogenetic and paleo-climatic context. Our results suggest that primate promiscuity (both males and females are mate-seekers) evolved with group-living from ancestral pair-living monogamy (both males and females are mate-attractors) in the Palaeogene, as the result of a slowdown in growth (neoteny) caused by increased environmental predictability. A secondary return to territorial monogamy probably evolved as the result of accelerated growth driven by seasonality (acceleration). Polygamy evolved in the Neogene during periods of forest fragmentation and environmental unpredictability. Small monogamous ancestors evolved seasonal polyandry (female attraction) as an effect of truncated development (progenesis). Large promiscuous, neotenic ancestors evolved non-seasonal polygyny (male attraction) as an effect of prolonged development (hypermorphosis) in males. We conclude that social heterochrony offers alternative explanations for the coevolution of life history and mating be-haviour; and we discuss the implications of our model for human social evolution.

Conceptual and empirical bridges between micro- and macroevolution.

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

Machine learning enhances prediction of plants as potential sources of antimalarials.

Plants are a rich source of bioactive compounds and a number of plant-derived antiplasmodial compounds have been developed into pharmaceutical drugs for the prevention and treatment of malaria, a major public health challenge. However, identifying plants with antiplasmodial potential can be time-consuming and costly. One approach for selecting plants to investigate is based on ethnobotanical knowledge which, though having provided some major successes, is restricted to a relatively small group of plant species. Machine learning, incorporating ethnobotanical and plant trait data, provides a promising approach to improve the identification of antiplasmodial plants and accelerate the search for new plant-derived antiplasmodial compounds. In this paper we present a novel dataset on antiplasmodial activity for three flowering plant families - Apocynaceae, Loganiaceae and Rubiaceae (together comprising c. 21,100 species) - and demonstrate the ability of machine learning algorithms to predict the antiplasmodial potential of plant species. We evaluate the predictive capability of a variety of algorithms - Support Vector Machines, Logistic Regression, Gradient Boosted Trees and Bayesian Neural Networks - and compare these to two ethnobotanical selection approaches - based on usage as an antimalarial and general usage as a medicine. We evaluate the approaches using the given data and when the given samples are reweighted to correct for sampling biases. In both evaluation settings each of the machine learning models have a higher precision than the ethnobotanical approaches. In the bias-corrected scenario, the Support Vector classifier performs best - attaining a mean precision of 0.67 compared to the best performing ethnobotanical approach with a mean precision of 0.46. We also use the bias correction method and the Support Vector classifier to estimate the potential of plants to provide novel antiplasmodial compounds. We estimate that 7677 species in Apocynaceae, Loganiaceae and Rubiaceae warrant further investigation and that at least 1300 active antiplasmodial species are highly unlikely to be investigated by conventional approaches. While traditional and Indigenous knowledge remains vital to our understanding of people-plant relationships and an invaluable source of information, these results indicate a vast and relatively untapped source in the search for new plant-derived antiplasmodial compounds.

A timescale for placental mammal diversification based on Bayesian modeling of the fossil record.

The timing of the placental mammal radiation has been the focus of debate over the efficacy of competing methods for establishing evolutionary timescales. Molecular clock analyses estimate that placental mammals originated before the Cretaceous-Paleogene (K-Pg) mass extinction, anywhere from the Late Cretaceous to the Jurassic. However, the absence of definitive fossils of placentals before the K-Pg boundary is compatible with a post-Cretaceous origin. Nevertheless, lineage divergence must occur before it can be manifest phenotypically in descendent lineages. This, combined with the non-uniformity of the rock and fossil records, requires the fossil record to be interpreted rather than read literally. To achieve this, we introduce an extended Bayesian Brownian bridge model that estimates the age of origination and, where applicable, extinction through a probabilistic interpretation of the fossil record. The model estimates the origination of placentals in the Late Cretaceous, with ordinal crown groups originating at or after the K-Pg boundary. The results reduce the plausible interval for placental mammal origination to the younger range of molecular clock estimates. Our findings support both the Long Fuse and Soft Explosive models of placental mammal diversification, indicating that the placentals originated shortly prior to the K-Pg mass extinction. The origination of many modern mammal lineages overlapped with and followed the K-Pg mass extinction.

Patterns and drivers of heat production in the plant genus Amorphophallus.

Thermogenesis - the ability to generate metabolic heat - is much more common in animals than in plants, but it has been documented in several plant families, most prominently the Araceae. Metabolic heat is produced in floral organs during the flowering time (anthesis), with the hypothesised primary functions being to increase scent volatilisation for pollinator attraction, and/or to provide a heat reward for invertebrate pollinators. Despite in-depth studies on the thermogenesis of single species, no attempts have yet been made to examine plant thermogenesis across an entire clade. Here, we apply time-series clustering algorithms to 119 measurements of the full thermogenic patterns in inflorescences of 80 Amorphophallus species. We infer a new time-calibrated phylogeny of this genus and use phylogenetic comparative methods to investigate the evolutionary determinants of thermogenesis. We find striking phenotypic variation across the phylogeny, with heat production in multiple clades reaching up to 15°C, and in one case 21.7°C above ambient temperature. Our results show that the thermogenic capacity is phylogenetically conserved and is also associated with inflorescence thickness. Our study paves the way for further investigations of the eco-evolutionary benefits of thermogenesis in plants.

Dwarfism and gigantism drive human-mediated extinctions on islands.

Islands have long been recognized as distinctive evolutionary arenas leading to morphologically divergent species, such as dwarfs and giants. We assessed how body size evolution in island mammals may have exacerbated their vulnerability, as well as how human arrival has contributed to their past and ongoing extinctions, by integrating data on 1231 extant and 350 extinct species from islands and paleo islands worldwide spanning the past 23 million years. We found that the likelihood of extinction and of endangerment are highest in the most extreme island dwarfs and giants. Extinction risk of insular mammals was compounded by the arrival of modern humans, which accelerated extinction rates more than 10-fold, resulting in an almost complete demise of these iconic marvels of island evolution.

Light, rather than circadian rhythm, regulates gas exchange in ferns and lycophytes.

Circadian regulation plays a vital role in optimizing plant responses to the environment. However, while circadian regulation has been extensively studied in angiosperms, very little is known for lycophytes and ferns, leaving a gap in our understanding of the evolution of circadian rhythms across the plant kingdom. Here, we investigated circadian regulation in gas exchange through stomatal conductance and photosynthetic efficiency in a phylogenetically broad panel of 21 species of lycophytes and ferns over a 46 h period under constant light and a selected few under more natural conditions with day-night cycles. No rhythm was detected under constant light for either lycophytes or ferns, except for two semi-aquatic species of the family Marsileaceae (Marsilea azorica and Regnellidium diphyllum), which showed rhythms in stomatal conductance. Furthermore, these results indicated the presence of a light-driven stomatal control for ferns and lycophytes, with a possible passive fine-tuning through leaf water status adjustments. These findings support previous evidence for the fundamentally different regulation of gas exchange in lycophytes and ferns compared to angiosperms, and they suggest the presence of alternative stomatal regulations in Marsileaceae, an aquatic family already well known for numerous other distinctive physiological traits. Overall, our study provides evidence for heterogeneous circadian regulation across plant lineages, highlighting the importance of broad taxonomic scope in comparative plant physiology studies.

Slow and steady wins the race: Diversification rate is independent from body size and lifestyle in Malagasy skinks (Squamata: Scincidae: Scincinae).

Most of the unique and diverse vertebrate fauna that inhabits Madagascar derives from in situ diversification from colonisers that reached this continental island through overseas dispersal. The endemic Malagasy Scincinae lizards are amongst the most species-rich squamate groups on the island. They colonised all bioclimatic zones and display many ecomorphological adaptations to a fossorial (burrowing) lifestyle. Here we propose a new phylogenetic hypothesis for their diversification based on the largest taxon sampling so far compiled for this group. We estimated divergence times and investigated several aspects of their diversification (diversification rate, body size and fossorial lifestyle evolution, and biogeography). We found that diversification rate was constant throughout most of the evolutionary history of the group, but decreased over the last 6-4 million years and independently from body size and fossorial lifestyle evolution. Fossoriality has evolved from fully quadrupedal ancestors at least five times independently, which demonstrates that even complex morphological syndromes - in this case involving traits such as limb regression, body elongation, modification of cephalic scalation, depigmentation, and eyes and ear-opening regression - can evolve repeatedly and independently given enough time and eco-evolutionary advantages. Initial diversification of the group likely occurred in forests, and the divergence of sand-swimmer genera around 20 Ma appears linked to a period of aridification. Our results show that the large phenotypic variability of Malagasy Scincinae has not influenced diversification rate and that their rich species diversity results from a constant accumulation of lineages through time. By compiling large geographic and trait-related datasets together with the computation of a new time tree for the group, our study contributes important insights on the diversification of Malagasy vertebrates.

The origin of modern patterns of continental diversity in Mauritiinae palms: the Neotropical museum and the Afrotropical graveyard.

While the latitudinal diversity gradient has received much attention, biodiversity and species richness also vary between continents across similar latitudes. Fossil information can be used to understand the evolutionary mechanisms that generated such variation between continents of similar latitudes. We integrated fossil data into a phylogenetic analysis of the Mauritiinae palms, whose extant diversity is restricted to the Neotropics, but extended across Africa and India during most of the Cenozoic. Mauritiinae diverged from its sister lineage Raphiinae ca 106 Ma. Using ancestral state estimation and a lineage through time analysis, we found that diversity arose globally during the late Cretaceous and Palaeocene across South America, Africa and India. The Palaeocene-Eocene transition (ca 56 Ma) marked the end of global Mauritiinae expansion, and the beginning of their decline in both Africa and India. Mauritiinae disappeared from the Indian subcontinent and Africa at the end of the Eocene and the Miocene, respectively. By contrast, Neotropical diversity steadily increased over the last 80 Myr. Taken together, our results suggest that the Neotropics functioned as a continental-scale refuge for Mauritiinae palms, where lineages survived and diversified while global climatic changes that drastically reduced rainforests led to their demise on other continents.

Short-term paleogeographic reorganizations and climate events shaped diversification of North American freshwater gastropods over deep time.

What controls species diversity and diversification is one of the major questions in evolutionary biology and paleontology. Previous studies have addressed this issue based on various plant and animal groups, geographic regions, and time intervals. However, as most previous research focused on terrestrial or marine ecosystems, our understanding of the controls on diversification of biota (and particularly invertebrates) in freshwater environments in deep time is still limited. Here, we infer diversification rates of North American freshwater gastropods from the Late Triassic to the Pleistocene and explore potential links between shifts in speciation and extinction and major changes in paleogeography, climate, and biotic interactions. We found that variation in the speciation rate is best explained by changes in continental fragmentation, with rate shifts coinciding with major paleogeographic reorganizations in the Mesozoic, in particular the retreat of the Sundance Sea and subsequent development of the Bighorn wetland and the advance of the Western Interior Seaway. Climatic events in the Cenozoic (Middle Eocene Climate Optimum, Miocene Climate Optimum) variably coincide with shifts in speciation and extinction as well, but no significant long-term association could be detected. Similarly, no influence of diversity dependence was found across the entire time frame of ~ 214 Myr. Our results indicate that short-term climatic events and paleogeographic changes are relevant to the diversification of continental freshwater biota, while long-term trends have limited effect.