Harmful algae bloom (HAB) forecasting has developed rapidly over recent decades, but predicting harmful levels of marine biotoxins in shellfish is still a challenge. New discoveries suggest that predator-prey interactions may be an important driver in the formation of HABs. Key species of harmful algae respond to copepod infochemicals with increased toxin production. In addition, copepods feed selectively on less defended prey, which may further promote harmful taxa. Here we explore if eavesdropping on predator-prey dynamics by monitoring zooplankton can improve HAB forecasting. We first examine an 8-yr time series including copepod biomass, harmful algae cells (Dinophysis spp.), and diarrhetic shellfish toxins in blue mussels (Mytilus edulis) using generalized additive models. Models including copepod biomass more accurately predicted okadaic acid in mussels than phytoplankton alone. We then apply this connection more narrowly by analyzing the specific copepod exudates known to induce toxin production, copepodamides, from the mussels sampled in biotoxin monitoring. Adding copepodamide data from shellfish extracts increased model performance compared to copepod biomass. Results suggest that including grazing effects through copepodamide measurements may provide a cost-efficient way to improve accuracy and lead time for predicting the accumulation of microalgal toxins in shellfish.

中文翻译：

---

窃听浮游生物——浮游动物监测能否改善对有害藻类大量繁殖的生物毒素的预测？

近几十年来，有害藻华 (HAB) 预测发展迅速，但预测贝类中海洋生物毒素的有害水平仍然是一个挑战。新发现表明，捕食者-猎物相互作用可能是 HAB 形成的重要驱动因素。有害藻类的关键物种对桡足类信息化学物质的反应会增加毒素的产生。此外，桡足类动物有选择地捕食防御力较低的猎物，这可能会进一步促进有害的分类群。在这里，我们探讨通过监测浮游动物来窃听捕食者-猎物动态是否可以改善 HAB 预测。我们首先检查了一个 8 年的时间序列，包括桡足类生物量、有害藻类细胞 ( Dinophysis spp.) 和蓝贻贝 ( Mytilus edulis ) 中的腹泻性贝类毒素) 使用广义加性模型。包括桡足类生物量的模型比单独的浮游植物更准确地预测贻贝中的冈田酸。然后，我们通过分析从生物毒素监测中取样的贻贝中已知可诱导毒素产生的特定桡足类分泌物（桡足类动物），更狭隘地应用这种联系。与桡足类生物量相比，从贝类提取物中添加桡足类数据可提高模型性能。结果表明，通过桡足类测量包括放牧效应可以提供一种具有成本效益的方法，以提高预测贝类中微藻毒素积累的准确性和提前期。