First meeting: tba
Pollinators, including bumble bees (genus Bombus), provide pollination services for much of the food we eat and are important components of natural ecosystems across the world. Yet, many populations and species are increasingly threatened by habitat loss, climate change, insecticide use, diseases, and invasive species. Among the greatest impediments to global pollinator research are the scattered nature of datasets and the labor-intensive methods of monitoring efforts, which relies on experts for specimen identification. This identification bottleneck, however, may be alleviated by new applications of AI technology. Such technology is highly scalable and transferable, and will be transformative for biodiversity research. Given the global threats to Bombus, we need to (1) bring together heterogeneous datasets from around the world in order to (2) synthesize current knowledge of global Bombus trends and expand existing AI-based identification methods to all Bombus species, (3) synthesize existing monitoring protocols and develop a global monitoring plan that leverages AI technology, and (4) develop community resources, best practices, and standards for applying AI to the task of insect identification.