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Whale populations recovering from historical whaling are particularly vulnerable to incidental mortality and disturbance caused by growing ocean industrialization. Several distinct populations of rorqual whales (including humpback, blue, and fin whales) migrate and feed off the coast of Oregon, USA where spatial overlap with human activities are on the rise. Effective mitigation of conflicts requires better foundational understanding of spatial and temporal habitat use patterns to inform conservation management. Based on a year-round, multi-platform distance sampling dataset (2016-2021, 177 survey days, 754 groups observed), this study generated density models to describe and predict seasonal distribution of rorqual whales in Oregon. Phenology analysis of sightings revealed a peak of humpback whale and blue whale density over the Oregon continental shelf in August and September respectively, and higher fin whale density in the winter (December). Additionally, we compared rorqual sighting rates across three decades of survey effort (since 1989) and demonstrate that rorqual whales are strikingly more prevalent in the current dataset, including distinct increases of blue and fin whales. Finally, density surface models relating whale densities to static and dynamic environmental variables acquired from data-assimilative ocean models revealed that summer and spring rorqual distribution were influenced by dynamic oceanographic features indicative of active upwelling and frontal zones (respectively 27 % and 40 % deviance explained). On the continental shelf, blue whales were predicted to occur closer to shore than humpback whales and in the more southern waters off Oregon. Summer and spring rorqual models, and humpback whale models, showed predictive performance suitable for management purposes, assessed through internal cross-validation and comparison to an external dataset (388 groups observed). Indeed, monthly hotspots of high predicted rorqual whale density across multiple years were validated by independent sightings (77 % overlap in the summer model). These predictive models lay a robust basis for fine-scale dynamic spatial management to reduce impacts of human activities on endangered populations of rorqual whales in Oregon.

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