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Cyanobacteria harmful algal blooms (cHABs) are increasingly becoming an emerging threat to aquatic life, ecotourism, and certain real estate investments. Their spontaneous yet sporadic occurrence has made mitigation measures a cumbersome task; moreover, current trends regarding anthropogenic activities, especially in agriculture and industry portend further undesirable events. Apart from the aesthetic degeneration they create in their respective habitats, they are equally capable of secreting toxins, which altogether present grave environmental and medical consequences. In this paper, we gave an update on factors that influence cHABs, cyanotoxin exposure routes, and environmental public health implications, especially impacts on fish, pets, and livestock. We discussed social economic impacts, risk assessment, and management problems for cHABs and, thereafter, assessed the extant management approaches including prevention, control, and mitigation of the proliferation of cyanobacterial blooms. In light of this, we suggest that more intensified research should be directed to the standardization of procedures for cyanotoxin analysis. Also, the provision of standardized reference material for the quantification of cyanotoxins is vital for routine monitoring as well as the development of strong in situ sensors capable of quantifying and detecting HABs cells and toxins in waterbodies to prevent the adverse impacts of cHABs. Also, more investigations into the natural and environmentally friendly approach to cyanobacteria management and the necessary and appropriate deployment of artificial intelligence are required. Finally, we wish to redirect the focus of public health authorities to protecting drinking water supply sources, agriculture products, and food sources from cyanotoxins contamination as well as to implement proper monitoring and treatment procedures to protect citizens from this potential health threat.

Marine eutrophication, primarily driven by nutrient over input from agricultural runoff, wastewater discharge, and atmospheric deposition, leads to harmful algal blooms (HABs) that pose a severe threat to marine ecosystems. This review explores the causes, monitoring methods, and control strategies for eutrophication in marine environments. Monitoring techniques include remote sensing, automated in situ sensors, modeling, forecasting, and metagenomics. Remote sensing provides large-scale temporal and spatial data, while automated sensors offer real-time, high-resolution monitoring. Modeling and forecasting use historical data and environmental variables to predict blooms, and metagenomics provides insights into microbial community dynamics. Control treatments encompass physical, chemical, and biological treatments, as well as advanced technologies like nanotechnology, electrocoagulation, and ultrasonic treatment. Physical treatments, such as aeration and mixing, are effective but costly and energy-intensive. Chemical treatments, including phosphorus precipitation, quickly reduce nutrient levels but may have ecological side effects. Biological treatments, like biomanipulation and bioaugmentation, are sustainable but require careful management of ecological interactions. Advanced technologies offer innovative solutions with varying costs and sustainability profiles. Comparing these methods highlights the trade-offs between efficacy, cost, and environmental impact, emphasizing the need for integrated approaches tailored to specific conditions. This review underscores the importance of combining monitoring and control strategies to mitigate the adverse effects of eutrophication on marine ecosystems.

Cyanobacterial harmful algal blooms (CyanoHABs) are an increasingly common feature of large, eutrophic lakes. Non-N2-fixing CyanoHABs (e.g., Microcystis) appear to be proliferating relative to N2-fixing CyanoHABs in systems receiving increasing nutrient loads. This shift reflects increasing external nitrogen (N) inputs, and a > 50-year legacy of excessive phosphorus (P) and N loading. Phosphorus is effectively retained in legacy-impacted systems, while N may be retained or lost to the atmosphere in gaseous forms (e.g., N2, NH3, N2O). Biological control on N inputs versus outputs, or the balance between N2 fixation versus denitrification, favors the latter, especially in lakes undergoing accelerating eutrophication, although denitrification removal efficiency is inhibited by increasing external N loads. Phytoplankton in eutrophic lakes have become more responsive to N inputs relative to P, despite sustained increases in N loading. From a nutrient management perspective, this suggests a need to change the freshwater nutrient limitation and input reduction paradigms; a shift from an exclusive focus on P limitation to a dual N and P co-limitation and management strategy. The recent proliferation of toxic non-N2-fixing CyanoHABs, and ever-increasing N and P legacy stores, argues for such a strategy if we are to mitigate eutrophication and CyanoHAB expansion globally.

The recent rise of red tide harmful algal blooms has induced ecosystem degradation, economic losses, and aquaculture damage, yet little is known on prevention and mitigation of red tides. Actual control methods involve physical, chemical, and biological processes, with varying success. Here, we review physical, chemical, and biological control methods applicable to red tide species in marine and estuarine water bodies. We discuss mechanisms of algal blooms outbreak and their applications to prevent outbreaks.

An intensification of toxic cyanobacteria blooms has occurred over the last three decades, severely affecting coastal and lake water quality in many parts of the world. Extensive research is being conducted in an attempt to gain a better understanding of the driving forces that alter the ecological balance in water bodies and of the biological role of the secondary metabolites, toxins included, produced by the cyanobacteria. In the long-term, such knowledge may help to develop the needed procedures to restore the phytoplankton community to the pre-toxic blooms era. In the short-term, the mission of the scientific community is to develop novel approaches to mitigate the blooms and thereby restore the ability of affected communities to enjoy coastal and lake waters. Here, we critically review some of the recently proposed, currently leading, and potentially emerging mitigation approaches in-lake novel methodologies and applications relevant to drinking-water treatment.

Algae serves as a food source for a wide range of aquatic species; however, a high concentration of inorganic nutrients under favorable conditions can result in the development of harmful algal blooms (HABs). Many studies have addressed HAB detection and monitoring; however, no global scale meta-analysis has specifically explored remote sensing-based HAB monitoring. Therefore, this manuscript elucidates and visualizes spatiotemporal trends in HAB detection and monitoring using remote sensing methods and discusses future insights through a meta-analysis of 420 journal articles. The results indicate an increase in the quantity of published articles which have facilitated the analysis of sensors, software, and HAB proxy estimation methods. The comparison across multiple studies highlighted the need for a standardized reporting method for HAB proxy estimation. Research gaps include: (1) atmospheric correction methods, particularly for turbid waters, (2) the use of analytical-based models, (3) the application of machine learning algorithms, (4) the generation of harmonized virtual constellation and data fusion for increased spatial and temporal resolutions, and (5) the use of cloud-computing platforms for large scale HAB detection and monitoring. The planned hyperspectral satellites will aid in filling these gaps to some extent. Overall, this review provides a snapshot of spatiotemporal trends in HAB monitoring to assist in decision making for future studies.

Aquaculture witnessed a remarkable growth as one of the fastest-expanding sector in the food production industry; however, it faces serious threat from the unavoidable impacts of climate change. Understanding this threat, the present review explores the consequences of climate change on aquaculture production and provides need based strategies for its sustainable management, with a particular emphasis on climate-resilient approaches. The study examines the multi-dimensional impacts of climate change on aquaculture which includes the shifts in water temperature, sea-level rise, ocean acidification, harmful algal blooms, extreme weather events, and alterations in ecological dynamics. The review subsequently investigates innovative scientific interventions and climate-resilient aquaculture strategies aimed at strengthening the adaptive capacity of aquaculture practices. Some widely established solutions include selective breeding, species diversification, incorporation of ecosystem-based management practices, and the implementation of sustainable and advanced aquaculture systems (aquaponics and recirculating aquaculture systems (RAS). These strategies work towards fortifying aquaculture systems against climate-induced disturbances, thereby mitigating risks and ensuring sustained production. This review provides a detailed insight to the ongoing discourse on climate-resilient aquaculture, emphasizing an immediate need for prudent measures to secure the future sustainability of fish food production sector.

Nutrient pollution and greenhouse gas emissions related to crop agriculture and confined animal feeding operations (CAFOs) in the US have changed substantially in recent years, in amounts and forms. This review is intended to provide a broad view of how nutrient inputs—from fertilizer and CAFOs—as well as atmospheric NH 3 and greenhouse gas emissions, are changing regionally within the US and how these changes compare with nutrient inputs from human wastewater. Use of commercial nitrogen (N) fertilizer in the US, which now exceeds 12,000,000 metric tonnes (MT) continues to increase, at a rate of 60,000 MT per year, while that of phosphorus (P) has remained nearly constant over the past decade at around 1,800,000 MT. The number of CAFOs in the US has increased nearly 10% since 2012, driven largely by a near 13% increase in hog production. The annualized inventory of cattle, dairy cows, hogs, broiler chickens and turkeys is approximately 8.7 billion, but CAFOs are highly regionally concentrated by animal sector. Countrywide, N applied by fertilizer is about threefold greater than manure N inputs, but for P these inputs are more comparable. Total manure inputs now exceed 4,000,000 MT as N and 1,400,000 MT as P. For both N and P, inputs and proportions vary widely by US region. The waste from hog and dairy operations is mainly held in open lagoons that contribute to NH₃ and greenhouse gas (as CH₄ and N₂O) emissions. Emissions of NH 3 from animal waste in 2019 were estimated at [4,500,000 MT. Emissions of CH 4 from manure management increased 66 % from 1990 to 2017 (that from dairy increased 134 %, cattle 9.6 %, hogs 29 % and poultry 3 %), while those of N 2 O increased 34 % over the same time period (dairy 15 %, cattle 46 %, hogs 58 %, and poultry 14 %). Waste from CAFOs contribute substantially to nutrient pollution when spread on fields, often at higher N and P application rates than those of commercial fertilizer. Managing the runoff associated with fertilizer use has improved with best management practices, but reducing the growing waste from CAFO operations is essential if eutrophication and its effects on fresh and marine waters–namely hypoxia and harmful algal blooms (HABs)—are to be reduced.

Background “Red tides” are harmful algal blooms caused by dinoflagellate microalgae that accumulate toxins lethal to other organisms, including humans via consumption of contaminated seafood. These algal blooms are driven by a combination of environmental factors including nutrient enrichment, particularly in warm waters, and are increasingly frequent. The molecular, regulatory, and evolutionary mechanisms that underlie the heat stress response in these harmful bloom-forming algal species remain little understood, due in part to the limited genomic resources from dinoflagellates, complicated by the large sizes of genomes, exhibiting features atypical of eukaryotes. Results We present the de novo assembled genome (~ 4.75 Gbp with 85,849 protein-coding genes), transcriptome, proteome, and metabolome from Prorocentrum cordatum , a globally abundant, bloom-forming dinoflagellate. Using axenic algal cultures, we study the molecular mechanisms that underpin the algal response to heat stress, which is relevant to current ocean warming trends. We present the first evidence of a complementary interplay between RNA editing and exon usage that regulates the expression and functional diversity of biomolecules, reflected by reduction in photosynthesis, central metabolism, and protein synthesis. These results reveal genomic signatures and post-transcriptional regulation for the first time in a pelagic dinoflagellate. Conclusions Our multi-omics analyses uncover the molecular response to heat stress in an important bloom-forming algal species, which is driven by complex gene structures in a large, high-G+C genome, combined with multi-level transcriptional regulation. The dynamics and interplay of molecular regulatory mechanisms may explain in part how dinoflagellates diversified to become some of the most ecologically successful organisms on Earth.

In the last few decades, harmful algal blooms (HABs, also known as “red tides”) have become one of the most detrimental natural phenomena in Florida’s coastal areas. Karenia brevis produces toxins that have harmful effects on humans, fisheries, and ecosystems. In this study, we developed and compared the efficiency of state-of-the-art machine learning models (e.g., XGBoost, Random Forest, and Support Vector Machine) in predicting the occurrence of HABs. In the proposed models the K. brevis abundance is used as the target, and 10 level-02 ocean color products extracted from daily archival MODIS satellite data are used as controlling factors. The adopted approach addresses two main shortcomings of earlier models: (1) the paucity of satellite data due to cloudy scenes and (2) the lag time between the period at which a variable reaches its highest correlation with the target and the time the bloom occurs. Eleven spatio-temporal models were generated, each from 3 consecutive day satellite datasets, with a forecasting span from 1 to 11 days. The 3-day models addressed the potential variations in lag time for some of the temporal variables. One or more of the generated 11 models could be used to predict HAB occurrences depending on availability of the cloud-free consecutive days. Findings indicate that XGBoost outperformed the other methods, and the forecasting models of 5–9 days achieved the best results. The most reliable model can forecast eight days ahead of time with balanced overall accuracy, Kappa coefficient, F-Score, and AUC of 96%, 0.93, 0.97, and 0.98 respectively. The euphotic depth, sea surface temperature, and chlorophyll-a are always among the most significant controlling factors. The proposed models could potentially be used to develop an “early warning system” for HABs in southwest Florida.