November 4, 2024 — Machine learning helps create more accurate Alaska pollock assessments. Fisheries managers rely on accurate stock assessments to keep industries viable and protect resources. The researchers who generate those assessments rely not only on data generated by scientists and fishermen but also on their own capacity to analyze it. According to Dr. James Thorson at the Alaska Fisheries Science Center, AI and machine learning have helped improve the species distribution models (SDMs) used in generating stock assessments.
“We often use a type of machine learning called Gaussian Process Models to develop these species distribution models,” says Thorson. “The Gaussian Process Models are good at determining how many fish are in a particular area, but also why the fish are there. It can use information like temperature and bottom type.”