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This study compares alternative implementations of species distribution models (SDMs) for quantifying static and dynamic patterns in marine habitat use, with a case study focusing on juvenile salmon in the eastern Bering Sea. We compare the performance of two prevalent SDM frameworks—generalized additive models (GAMs) and vector autoregressive spatio-temporal (VAST) models—in predicting juvenile salmon distributions and assessing interannual variation in habitat utilization. The two SDM frameworks produced similar spatial predictions but performed differently in tests of within-sample and out-of-sample predictive power. Our findings indicate that VAST models may provide more precise estimates of distribution compared to GAMs. Maps of predicted juvenile salmon distributions showed highest salmon densities in habitats within the 50 m isobath of the continental shelf, underscoring the importance of these coastal areas, although among-species differences were evident. Model performance results suggested evidence for spatial variation in juvenile salmon species’ distributions through time. Our findings suggest that an SDM approach can be effective for estimating static and dynamic juvenile salmon distributions, and for providing insights that are useful in spatial fisheries management contexts.