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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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Given the current biodiversity crisis, pragmatic approaches to detect global conservation trends across a broad range of taxa are critical. A sampled approach to the Red List Index (RLI) was proposed, as many groups are highly speciose. However, a decade after its conception, the recommended 900 species sample has only been implemented in six groups and trend data are available for none, potentially because this sample is unfeasibly high. Using a broader set of all available data we show that when re‐assessments are conducted every 10 years, 200 species (400 in some cases) should be sufficient to detect a RLI trend. Correctly detecting changes in slope still requires samples of 900 species (11,000 in some cases). Sampled assessments can accelerate biodiversity monitoring and complement current metrics, but the time‐period between assessments and the approaches' purpose should be carefully considered, as there is a trade‐off between sample size and the resulting indices. [ABSTRACT FROM AUTHOR]

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]