| Summary: | Abstract The prevalence of disease-driven mass mortality events is increasing, but our understanding of spatial variation in their magnitude, timing, and triggers are often poorly resolved. Here, we use a novel range-wide dataset comprised of 48,810 surveys to quantify how Sea Star Wasting Disease affected Pycnopodia helianthoides , the sunflower sea star, across its range from Baja California, Mexico to the Aleutian Islands, USA. We found that the outbreak occurred more rapidly, killed a greater percentage of the population, and left fewer survivors in the southern half of the species’ range. Pycnopodia now appears to be functionally extinct (> 99.2% declines) from Baja California, Mexico to Cape Flattery, Washington, USA and exhibited severe declines (> 87.8%) from the Salish Sea to the Gulf of Alaska. The importance of temperature in predicting Pycnopodia distribution rose 450% after the outbreak, suggesting these latitudinal gradients may stem from an interaction between disease severity and warmer waters. We found no evidence of population recovery in the years since the outbreak. Natural recovery in the southern half of the range is unlikely over the short-term and assisted recovery will likely be required for recovery in the southern half of the range on ecologically-relevant time scales. Methods Thirty research groups from Canada, the United States, Mexico, including First Nations, shared 34 datasets containing field surveys of Pycnopodia (Table S1). The data included 48,810 surveys from 1967 to 2020 derived from trawls, remotely operated vehicles, SCUBA dives, and intertidal surveys. We compiled survey data into a standardized format that included at minimum the coordinates, date, depth, area surveyed, and occurrence of Pycnopodia for each survey. When datasets contained more than one survey at a site in the same day (e.g. multiple transects), we divided the total Pycnopodia count in all surveys by the total survey area and averaged the latitude, longitude, and depth as necessary. Using breaks ...
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