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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. [ABSTRACT FROM AUTHOR]

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The International Union for Conservation of Nature (IUCN) Red List of Threatened Species is central in biodiversity conservation, but insufficient resources hamper its long-term growth, updating, and consistency. Models or automated calculations can alleviate those challenges by providing standardised estimates required for assessments, or prioritising species for (re-)assessments. However, while numerous scientific papers have proposed such methods, few have been integrated into assessment practice, highlighting a critical research–implementation gap. We believe this gap can be bridged by fostering communication and collaboration between academic researchers and Red List practitioners, and by developing and maintaining user-friendly platforms to automate application of the methods. We propose that developing methods better encompassing Red List criteria, systems, and drivers is the next priority to support the Red List. The IUCN Red List of Threatened Species plays a central role in monitoring biodiversity and informing conservation actions. To best inform conservation, the Red List must be frequently updated, become more taxonomically and geographically representative, and be consistent within and among taxonomic groups, but this is hampered by limited resources. A variety of models and automated calculations has been proposed in the literature to support Red List assessments, for instance using citizen science or remote-sensing data to predict extinction risk. We highlight a major research–implementation gap in the application of these methods, which could be bridged by providing assessors with easy access to the most relevant tools, hands-on training, and strengthening communication. Further efforts are needed to develop relevant methods to prioritise assessments or better predict extinction risk. [ABSTRACT FROM AUTHOR]

Amidst a global biodiversity crisis 1 , the word 'biodiversity' has become indispensable for conservation and management 2. Yet, biodiversity is often used as a buzzword in scientific literature. Resonant titles of papers claiming to have studied 'global biodiversity' may be used to promote research focused on a few taxonomic groups, habitats, or facets of biodiversity — taxonomic, (phylo)genetic, or functional. This usage may lead to extrapolating results outside the target systems of these studies with direct consequences for our understanding of life on Earth and its practical conservation. Here, we used a random sample of papers with the word 'biodiversity' in their title to take a long view of the use of this term. Despite improvements in analytical tools, monitoring technologies, and data availability 3,4 , we found that the taxonomic scope of research articles has not increased in recent years. We also show that studies with a wider taxonomic scope attract more citations and online attention. Our results have broad ramifications for understanding how extrapolating from studies with narrow taxonomic scope affects our view of global biodiversity and conservation. Mammola et al. discuss the uses and misuses of the word 'biodiversity', and how extrapolations from studies with narrow taxonomic scope affect our view of global biodiversity and conservation. [ABSTRACT FROM AUTHOR]