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Artificial intelligence has been found to be a promising new tool for monitoring the marbled murrelet and other hard-to-study species, according to research by Oregon State University and the U.S. Forest Service. The study used data from acoustic recorders to develop a machine learning algorithm that can mine the recordings for murrelet calls. The findings were tested against known murrelet population data and determined to be correct at a rate exceeding 90%. The research team is now testing whether murrelet sounds can predict reproduction and occupancy in the species. The marbled murrelet is an iconic Pacific Northwest seabird that is closely related to puffins and murres, and it is listed as threatened under the U.S. Endangered Species Act in Washington, Oregon, and California. The study offers considerable promise for species distribution modeling and long-term population monitoring for rare species.
