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.

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.

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 substitutions, 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.

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.

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.

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.

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.

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.

Dollo meets Bergmann: morphological evolution in secondary aquatic mammals.

Secondary transitions to aquatic environments are common among vertebrates, and aquatic lineages display several adaptations to this realm, some of which might make these transitions irreversible. At the same time, discussions about secondary transitions often focus only on the marine realm, comparing fully terrestrial with fully aquatic species. This, however, captures only a fraction of land-to-water transitions, and freshwater and semi-aquatic groups are often neglected in macroevolutionary studies.

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.

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.

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.

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.

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.

Madagascar's extraordinary biodiversity: Threats and opportunities.

Madagascar's unique biota is heavily affected by human activity and is under intense threat. Here, we review the current state of knowledge on the conservation status of Madagascar's terrestrial and freshwater biodiversity by presenting data and analyses on documented and predicted species-level conservation statuses, the most prevalent and relevant threats, ex situ collections and programs, and the coverage and comprehensiveness of protected areas. The existing terrestrial protected area network in Madagascar covers 10.

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.

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.

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.

The origin and evolution of open habitats in North America inferred by Bayesian deep learning models.

Some of the most extensive terrestrial biomes today consist of open vegetation, including temperate grasslands and tropical savannas. These biomes originated relatively recently in Earth's history, likely replacing forested habitats in the second half of the Cenozoic. However, the timing of their origination and expansion remains disputed.

Improving biodiversity protection through artificial intelligence.

Over a million species face extinction, urging the need for conservation policies that maximize the protection of biodiversity to sustain its manifold contributions to people. Here we present a novel framework for spatial conservation prioritization based on reinforcement learning that consistently outperforms available state-of-the-art software using simulated and empirical data. Our methodology, CAPTAIN (Conservation Area Prioritization Through Artificial INtelligence), quantifies the trade-off between the costs and benefits of area and biodiversity protection, allowing the exploration of multiple biodiversity metrics.