Artificial intelligence tools are helping Oregon wildlife researchers study hard-to-reach threatened species like the marbled murrelet. Researchers with Oregon State University and the U.S. Forest Service collected millions of hours of audio from federal forests in Washington and Oregon between 2018 and 2022. “We cannot physically review all the audio data that we collect,” said OSU College of Forestry doctoral student Matthew Weldy. “So we are reliant on computational tools to filter this data set and find sounds of interest.” To comb through that colossal amount of data, Weldy and other researchers developed a machine learning algorithm to identify the call patterns of marbled murrelets. Their findings — published this month in the Ecological Indicators journal — could help biologists understand which areas are most important to these enigmatic seabirds, thereby improving habitat conservation efforts.