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Machine Learning to Aid Pollinator Monitoring of Endangered Plants
Abstract
Rare plants are often dependent on pollinators to maintain their populations. In some cases, the pollinators themselves are of high conservation value, resulting in a system that has inherently high value for conservation. The North Campus Open Space (NCOS) at UCSB is home to such a system, where the Federally Endangered Salt Marsh Bird’s Beak (Chloropyron maritimum) is pollinated by recently listed Crotch’s Bumblebee (Bombus crotchii) along with other bumblebee, and insect species.
Monitoring pollination events is time-consuming, and researchers are looking to automated cameras to capture images of pollination events and machine learning to help extract pollinator identifications from the captured images.
Presented at the URCA Poster Colloquium 5/14/2025