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The conservation of evolutionary history has been linked to increased benefits for humanity and can be captured by phylogenetic diversity (PD). The Evolutionarily Distinct and Globally Endangered (EDGE) metric has, since 2007, been used to prioritise threatened species for practical conservation that embody large amounts of evolutionary history. While there have been important research advances since 2007, they have not been adopted in practice because of a lack of consensus in the conservation community. Here, building from an interdisciplinary workshop to update the existing EDGE approach, we present an “EDGE2” protocol that draws on a decade of research and innovation to develop an improved, consistent methodology for prioritising species conservation efforts. Key advances include methods for dealing with uncertainty and accounting for the extinction risk of closely related species. We describe EDGE2 in terms of distinct components to facilitate future revisions to its constituent parts without needing to reconsider the whole. We illustrate EDGE2 by applying it to the world’s mammals. As we approach a crossroads for global biodiversity policy, this Consensus View shows how collaboration between academic and applied conservation biologists can guide effective and practical priority-setting to conserve biodiversity.

The rapid diversification and high species richness of flowering plants is regarded as ‘Darwin’s second abominable mystery’. Today the global spatiotemporal pattern of plant diversification remains elusive. Using a newly generated genus-level phylogeny and global distribution data for 14,244 flowering plant genera, we describe the diversification dynamics of angiosperms through space and time. Our analyses show that diversification rates increased throughout the early Cretaceous and then slightly decreased or remained mostly stable until the end of the Cretaceous–Paleogene mass extinction event 66 million years ago. After that, diversification rates increased again towards the present. Younger genera with high diversification rates dominate temperate and dryland regions, whereas old genera with low diversification dominate the tropics. This leads to a negative correlation between spatial patterns of diversification and genus diversity. Our findings suggest that global changes since the Cenozoic shaped the patterns of flowering plant diversity and support an emerging consensus that diversification rates are higher outside the tropics.

A prominent question in animal research is how the evolution of morphology and ecology interacts in the generation of phenotypic diversity. Spiders are some of the most abundant arthropod predators in terrestrial ecosystems and exhibit a diversity of foraging styles. It remains unclear how spider body size and proportions relate to foraging style, and if the use of webs as prey capture devices correlates with changes in body characteristics. Here, we present the most extensive data set to date of morphometric and ecological traits in spiders. We used this data set to estimate the change in spider body sizes and shapes over deep time and to test if and how spider phenotypes are correlated with their behavioral ecology. We found that phylogenetic variation of most traits best fitted an Ornstein–Uhlenbeck model, which is a model of stabilizing selection. A prominent exception was body length, whose evolutionary dynamics were best explained with a Brownian Motion (free trait diffusion) model. This was most expressed in the araneoid clade (ecribellate orb-weaving spiders and allies) that showed bimodal trends toward either miniaturization or gigantism. Only few traits differed significantly between ecological guilds, most prominently leg length and thickness, and although a multivariate framework found general differences in traits among ecological guilds, it was not possible to unequivocally associate a set of morphometric traits with the relative ecological mode. Long, thin legs have often evolved with aerial webs and a hanging (suspended) locomotion style, but this trend is not general. Eye size and fang length did not differ between ecological guilds, rejecting the hypothesis that webs reduce the need for visual cue recognition and prey immobilization. For the inference of the ecology of species with unknown behaviors, we propose not to use morphometric traits, but rather consult (micro-)morphological characters, such as the presence of certain podal structures. Thes

Populations of Atlantic salmon are crashing across most of its natural range: understanding the underlying causes and predicting these collapses in time to intervene effectively are urgent ecological and socioeconomic priorities. Current management techniques rely on phenomenological analyses of demographic population time-series and thus lack a mechanistic understanding of how and why populations may be declining. New multidisciplinary approaches are thus needed to capitalize on the long-term, large-scale population data that are currently scattered across various repositories in multiple countries, as well as marshaling additional data to understand the constraints on the life cycle and how salmon operate within the wider food web. Here, we explore how we might combine data and theory to develop the mechanistic models that we need to predict and manage responses to future change. Although we focus on Atlantic salmon-given the huge data resources that already exist for this species-the general principles developed here could be applied and extended to many other species and ecosystems.

Biodiversity accumulates hierarchically by means of ecological and evolutionary processes and feedbacks. Within ecological communities drift, dispersal, speciation, and selection operate simultaneously to shape patterns of biodiversity. Reconciling the relative importance of these is hindered by current models and inference methods, which tend to focus on a subset of processes and their resulting predictions. Here we introduce Massive Eco-evolutionary Synthesis Simulations (MESS), a unified mechanistic model of community assembly, rooted in classic island biogeography theory, which makes temporally explicit joint predictions across three biodiversity data axes: i) species richness and abundances; ii) population genetic diversities; and iii) trait variation in a phylogenetic context. Using simulations we demonstrate that each data axis captures information at different timescales, and that integrating these axes enables discriminating among previously unidentifiable community assembly models. MESS is unique in generating predictions of community-scale genetic diversity, and in characterizing joint patterns of genetic diversity, abundance, and trait values. MESS unlocks the full potential for investigation of biodiversity processes using multi-dimensional community data including a genetic component, such as might be produced by contemporary eDNA or metabarcoding studies. We combine with supervised machine learning to fit the parameters of the model to real data and infer processes underlying how biodiversity accumulates, using communities of tropical trees, arthropods, and gastropods as case studies that span a range of data availability scenarios, and spatial and taxonomic scales.