bioRxiv · 10.64898/2025.12.16.694770
Marine biotoxin depuration rates: management applications, research priorities, and predictions for unstudied species
Abstract
Monitoring and managing the public health risk posed by marine biotoxins is a daunting challenge. With expansive coastlines, 1000s of seafood species, and dozens of biotoxins, monitoring cannot occur everywhere at once. Improving the cost-effectiveness of biotoxin monitoring is thus critical to expanding coverage to include more species, toxins, and locations. Notably, understanding the rate at which seafood species depurate biotoxins can be used to optimize the cadence of monitoring. We conducted a systematic review to collate marine biotoxin depuration rates and synthesize the factors that influence them; identify knowledge gaps, best practices, and research priorities; and generate predictions of depuration rates for unstudied species. We found that only 85 marine species have been studied for their biotoxin depuration rates. Depuration rates for non-bivalves and for toxins besides paralytic shellfish toxins (PSTs) are especially understudied. Depuration half-lives varied from 0.03 to 1269 days based on species, toxin, tissue, and environmental conditions. In general, depuration accelerates with increased temperature and food availability, with implications for aquaculture siting, depuration enhancement, and biotoxin monitoring. We identified unstudied bivalve and finfish species that are highly produced and vulnerable to HABs that are high priorities for future research. Finally, we used a Bayesian regression model to predict PST depuration rates for 102 unstudied bivalve species, the only clade-syndrome with sufficient training data. These predictions can guide efficient monitoring and management until lab- or field-based depuration rates become available. We recommend that future studies directly estimate depuration rates to ensure their comparability across studies and utility to managers.
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Free, C. M., Fang, Y.. 2025-12-19. Marine biotoxin depuration rates: management applications, research priorities, and predictions for unstudied species. https://doi.org/10.64898/2025.12.16.694770
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