
Maya Groner
Senior Research Scientist
Bigelow Laboratory for Ocean Sciences Continue Reading Maya Groner
Fishery-dependent data and oceanographic model hindcasts inform potential drivers of an emerging syndrome in snow crab.
Infectious marine diseases are often highly sensitive to shifting environmental conditions. Data limitations in difficult to access species often impede marine disease investigation. However, fishery-dependent data can allow for expanded coverage in some systems. The emergence of black eye syndrome (BES) of Bering Sea snow crab (Chionoecetes opilio) coincided with massive environmental and ecological shifts in the sea, necessitating improved disease monitoring towards better understanding stock health. Here, we combine fishery-dependent data from the Alaska Department of Fish and Game Bering Sea crab observers programme and hindcasted bottom water conditions from a regional ocean model to explore potential drivers of BES in Bering Sea snow crab using spatially explicit generalized linear mixed models (N = 719 048 crab). BES was positively associated with temperature, low pH, crab size, shell condition and local snow crab density (as catch-per-unit-effort (CPUE)). The associations of temperature and localized CPUE with BES are consistent with leading hypotheses explaining the recent snow crab population collapse, suggesting similar drivers, but their mechanisms influencing BES remain unclear. Fishery-dependent data collection remains an integral part of management, providing opportunities for expanded disease monitoring efforts. This article is part of the theme issue 'Managing infectious marine diseases in wild populations'.
Philosophical transactions of the Royal Society of London. Series B, Biological sciences

Senior Research Scientist
Bigelow Laboratory for Ocean Sciences Continue Reading Maya Groner