Traditional anatomical analyses captured only a fraction of real phenomic information. Here, we apply deep learning to quantify total phenotypic similarity across 2468 butterfly photographs, covering 38 subspecies from the polymorphic mimicry complex of Heliconius erato and Heliconius melpomene. Euclidean phenotypic distances, calculated using a deep convolutional triplet network, demonstrate significant convergence between interspecies co-mimics. This quantitatively validates a key prediction of Müllerian mimicry theory, evolutionary biology’s oldest mathematical model. Phenotypic neighbor-joining trees are significantly correlated with wing pattern gene phylogenies, demonstrating objective, phylogenetically informative phenome capture. Comparative analyses indicate frequency-dependent mutual convergence with coevolutionary exchange of wing pattern features. Therefore, phenotypic analysis supports reciprocal coevolution, predicted by classical mimicry theory but since disputed, and reveals mutual convergence as an intrinsic generator for the unexpected diversity of Müllerian mimicry. This demonstrates that deep learning can generate phenomic spatial embeddings, which enable quantitative tests of evolutionary hypotheses previously only testable subjectively.

With the biodiversity crisis continuing unchecked, we need to establish levels and drivers of extinction risk to effectively allocate conservation resources and develop targeted actions. Given that threat appears particularly high in freshwaters, we assessed the extinction risk of 1,500 randomly selected freshwater molluscs using the IUCN Red List Categories and Criteria, as part of the Sampled Red List Index project. We show that close to one third of species in our sample are estimated to be threatened with extinction, with highest levels of threat in the Palearctic, Australasia and Nearctic and among gastropods. Threat levels were higher in lotic than lentic systems. Twenty-seven species were classified as Extinct (eight bivalves and 19 gastropods), mostly from the Nearctic realm and lotic systems. Pollution and the modification of natural systems (e.g. through damming and water abstraction) were the most frequently reported threats to freshwater molluscs, with some regional variation. Given that we found little spatial congruence between species richness patterns of freshwater molluscs and other freshwater taxa, new additional conservation priority areas emerge from our study. We discuss the implications of our findings for freshwater mollusc conservation and important next steps to estimate trends in freshwater mollusc extinction risk over time.

BackgroundThe Natural History Museum, London (NHMUK) has embarked on an ambitious programme to digitise its collections . The first phase of this programme has been to undertake a series of pilot projects that will develop the necessary workflows and infrastructure development needed to support mass digitisation of very large scientific collections. This paper presents the results of one of the pilot projects – iCollections. This project digitised all the lepidopteran specimens usually considered as butterflies, 181,545 specimens representing 89 species from the British Isles and Ireland. The data digitised includes, species name, georeferenced location, collector and collection date - the what, where, who and when of specimen data. In addition, a digital image of each specimen was taken. This paper explains the way the data were obtained and the background to the collections which made up the project.New informationSpecimen-level data associated with British and Irish butterfly specimens have not been available before and the iCollections project has released this valuable resource through the NHM data portal.

The Natural History Museum, London (NHMUK) has embarked on an ambitious programme to digitise its collections. The first phase of this programme was to undertake a series of pilot projects to develop the workflows and infrastructure needed to support mass digitisation of very large scientific collections. This paper presents the results of one of the pilot projects – iCollections. This project digitised all the lepidopteran specimens usually considered as butterflies, 181,545 specimens representing 89 species from the British Isles and Ireland. The data digitised includes, species name, georeferenced location, collector and collection date - the what, where, who and when of specimen data. In addition, a digital image of each specimen was taken. A previous paper explained the way the data were obtained and the background to the collections that made up the project. The present paper describes the technical, logistical, and economic aspects of managing the project.

As we enter the next phase of international policy commitments to halt biodiversity loss (e.g. Post-2020 Biodiversity Framework), biodiversity indicators will play an important role forming the robust basis upon which targeted, and time sensitive conservation actions are developed. Population trend indicators are perhaps the most powerful tool in biodiversity monitoring due to their responsiveness to changes over short timescales and their ability to aggregate species trends from global down to at a sub-national or even local scale. We consider how the project behind the foremost population level indicator - the Living Planet Index - has evolved over the last 25 years, its value to the field of biodiversity monitoring, and how its components have portrayed a compelling account of the changing status of global biodiversity through its application at policy, research and practice levels. We explore ways the project can develop to enhance our understanding of the state of biodiversity and share lessons learned to inform indicator development and mobilise action.