AbstractAtlantic sturgeon (Acipenser oxyrinchus oxyrinchus) is an endangered species that migrate through, and occupy the coastal waters of the mid-Atlantic Bight where they interact with anthropogenic activities. Measures to understand and avoid Atlantic sturgeon that take into consideration the dynamic nature of their habitat may reduce harmful interactions. In this study, we matched fisheries independent biotelemetry observations of Atlantic sturgeon with daily satellite observations to construct a time resolved spatial distribution model of Atlantic sturgeon. We determined that depth, day-of-year, sea surface temperature, and light absorption by seawater were the most important predictors of Atlantic sturgeon occurrence. Demographic factors, such as sex and river-of-origin were of secondary importance. We found strong spatial differences in spring and fall migration patterns, when anthropogenic interactions peak. Our cross-validated models correctly identified > 88% of biotelemetry observations in our study region. Our models also correctly identified ∼64% of bycatch observations throughout the year. However, during their migrations, when harmful interactions were highest, our models correctly identified ∼90% of fisheries dependent observations. We suggest that this model can be used for guidance to managers and stakeholders to reduce interactions with this highly imperiled species, thereby enhancing conservation and recovery efforts.
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