Harmful cyanobacterial blooms (CBs) have a growing global prevalence, emerging as a significant environmental concern due to their potential toxicity. Understanding how the different mechanisms affect CBs is crucial to develop actionable management strategies. For this, we derive a stoichiometric dynamical system that describes the qualitative population dynamics of cyanobacteria and their toxicity in north-temperate freshwater ecosystems. Our model quantifies the hypoxic effects of CBs on fish mortality and the effect of microcystin-LR (MC-LR), a potent toxin produced by cyanobacteria, on aquatic macro-invertebrates, phytoplankton, and fish species. By fitting the model to lakes with varying physical characteristics, eutrophic conditions, and water temperature, we can delineate and understand the driving components of CBs. We show that decreases in water exchange rate, depth of epilimnion, or light attenuation increases bloom intensity and duration. Furthermore, our models concur that eutrophication and increasing water temperatures exacerbate the intensity of CBs. We observe a severe bioaccumulative effect of MC-LR in aquatic species, stressing the potential impact on humans and other terrestrial animals. We validate our model with field measurements demonstrating its applicability to several realistic lake conditions. These insights are essential for informing targeted interventions to reduce CBs and their ecological impacts.

翻译：有害蓝藻水华在全球范围内日益频发，因其潜在毒性已成为重大环境问题。厘清不同机制如何影响蓝藻水华对于制定可操作的管理策略至关重要。为此，我们推导了一个描述北温带淡水生态系统中蓝藻种群动态及其毒性的化学计量动力学模型。该模型量化了蓝藻水华导致的缺氧对鱼类死亡率的影响，以及蓝藻产生的强效毒素微囊藻毒素-LR对水生大型无脊椎动物、浮游植物和鱼类的影响。通过将模型适配至具有不同物理特征、富营养化条件和水温的湖泊，我们能够解析并理解驱动蓝藻水华的关键要素。研究表明，水体交换率降低、变温层深度减小或光衰减增强均会加剧水华强度与持续时间。此外，模型证实富营养化与水温上升会恶化蓝藻水华强度。我们观察到微囊藻毒素-LR在水生物种中产生严重的生物累积效应，这警示了其对人类及其他陆生动物的潜在影响。通过实地测量数据验证，本模型在多种实际湖泊条件下均展现出适用性。这些发现对于制定针对性干预措施以减少蓝藻水华及其生态影响具有重要意义。