NSF Award
2333604
The coral reef crisis is characterized by global declines in the abundance of corals and fishes, and a rise in the abundance of macroalgae. This project assesses the abundance and extinction risk of two rare coral species using artificial intelligence (AI)-powered underwater robots in autonomous deployments. This novel technology allows quantification of corals that occur at such low population densities that human divers cannot spend long enough underwater to find them, and is applicable to other fields of research, transforming the study of rare animals. The project also builds an academic bridge between a Hispanic Serving 4-year university and a marine research institution, provides cross-training for two graduate students and an early-career research engineer in coral ecology and underwater robotics, and supports robotics-themed training for local high school students. <br/><br/>Coral reefs have become depleted of corals, and many species are entering a period of rarity that might be a prelude to extinction. Traditional ecological tools are inadequate to enumerate these corals, which is the first step in quantifying the risk of extinction and the prospects for recovery. This project trains an autonomous underwater vehicle (AUV) with artificial intelligence (AI) to search for rare corals and challenges it in a test bed created by 37 y of data from coral reefs where iconic pillar and brain corals are being pushed to extinction. The project team is testing two hypotheses: (1) recent events have catalyzed a new decline in abundance of corals, and (2) demographic trajectories of rare corals will end in extinction. This novel technology is applicable to other ecosystems, transforming the study of rare organisms. <br/><br/>This project is co-funded by the Directorate for Geosciences to support AI/ML advancement in the geosciences.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
