Comprehensive Insights into Harmful Algal Blooms: A Review of Chemical, Physical, Biological, and Climatological Influencers with Predictive Modeling Approaches

水华 环境科学 影响力营销 生态学 浮游植物 生物 营销 营养物 关系营销 业务 市场营销管理
作者
Zhengxiao Yan,Sara Kamanmalek,Nasrin Alamdari,Mohammad Reza Nikoo
出处
期刊:Journal of Environmental Engineering [American Society of Civil Engineers]
卷期号:150 (4) 被引量:5
标识
DOI:10.1061/joeedu.eeeng-7549
摘要

Phytoplankton plays an essential role in the biogeochemical cycle because it is at the top of the food chain and is a source of oxygen. Eutrophication causes coastal areas to deteriorate as industrialization accelerates, leading to harmful algal blooms (HABs), severely affecting human and ecological health. The frequency and extent of HAB events potentially may increase due to climate change. HAB outbreaks have led to substantial losses for major coastal economies globally, and therefore have emerged as a critical research focus in environmental sciences. However, the lack of an overview of diverse factors influencing HABs complicates the cause identification and the effective countermeasure development for HAB occurrence, thereby impeding the formulation of targeted strategies for prediction and mitigation. Therefore, this review summarizes the influential factors affecting HABs in coastal areas, including water quality factors (nutrients, salinity, stratification, and biological factors) and climatological factors (temperature, pH and pCO2, and irradiance and light). Recent work with several harmful algae species suggested that warmer temperatures combined with nutrient variation, stronger stratification, and ocean acidification may increase the growth of some toxic dinoflagellate species. Although the effects of factors vary for different species and locations, the intensification of anthropogenic activities and climate change likely will increase the frequency, outbreak scale, and severity of most coastal HABs. Because predicting HABs is crucial for understanding the factors and synergy affecting their growth and minimizing losses for decision makers and stakeholders, we reviewed models for predicting HABs, including process-based models, traditional statistical-empirical models, and data-driven machine learning models. Predicting HABs becomes more challenging as the spatial distribution of harmful algae is influenced by future climate patterns. This review paper presents a comprehensive overview of the various factors impacting HABs in coastal areas, serving as a valuable resource for decision makers and researchers to design targeted research and mitigation strategies.
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