| Summary: | 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. Documentation, data, and code accompanying Hamilton et al., 2021 Pycnopodia Rangewide Assessment paper. Data MasterPycno_ToShare: Dec_lat = latitude in decimal degrees. Numeric. Dec_lon = longitude in decimal degrees. Numeric. Depth = depth in meters. Numeric. Pres_abs = presence or absence of Pycnopodia on that survey. Binary. Presence = 1, absence = 0 Density_m2 = density in meters squared if available for that set of surveys. Numeric. NA = no density data available for that survey. Source = shorthand name of the group that shared the data with us and the type of data (e.g. trawl, dive). To get further info on who that dataset, group, and group contact, see Table S1. Character. Note: When datasets contained more than ...
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