Harmful Algal Blooms in Eutrophic Marine Environments: Causes, Monitoring, and Treatment

Water, Journal Year: 2024, Volume and Issue: 16(17), P. 2525 - 2525

Published: Sept. 5, 2024

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

Language: Английский

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Machine learning to identify environmental drivers of phytoplankton blooms in the Southern Baltic Sea

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 24, 2025

Abstract Phytoplankton blooms exhibit varying patterns in timing and number of peaks within ecosystems. These differences blooming are partly explained by phytoplankton:nutrient interactions external factors such as temperature, salinity light availability. Understanding these drivers is essential for effective bloom management modelling driving potentially differ or shared across ecosystems on regional scales. Here, we used a 22-year data set (19 years training 3 validation data) containing chlorophyll, nutrients (dissolved total), (temperature, salinity, light) the southern Baltic Sea coast, European brackish shelf sea, which constituted six different phytoplankton patterns. We employed generalized additive mixed models to characterize similar trained an artificial neural network Universal Differential Equation framework learn differential equation representation pattern. Applying Sparse Identification Nonlinear Dynamics uncovered algebraic relationships phytoplankton:nutrient:external driver interactions. Nutrients availability was factor enclosed coastal waters; temperature more open regions. found evidence hydrodynamical export phytoplankton, natural mortality grazing not explicitly measured data. This data-driven workflow allows new insight into driver-differences region specific dynamics.

Language: Английский

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Impact of water quality parameters on harmful algal bloom mitigation and phosphorus removal by lab-synthesized γFe2O3/TiO2 magnetic photocatalysts

Algal Research, Journal Year: 2025, Volume and Issue: 86, P. 103932 - 103932

Published: Jan. 27, 2025

Language: Английский

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Mind the gap - The need to integrate novel plankton methods alongside ongoing long-term monitoring

Ocean & Coastal Management, Journal Year: 2025, Volume and Issue: unknown, P. 107542 - 107542

Published: Jan. 1, 2025

Language: Английский

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Mapping Harmful Algae Blooms: The Potential of Hyperspectral Imaging Technologies

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(4), P. 608 - 608

Published: Feb. 11, 2025

Harmful algae blooms (HABs) pose critical threats to aquatic ecosystems and human economies, driven by their rapid proliferation, oxygen depletion capacity, toxin release, biodiversity impacts. These blooms, increasingly exacerbated climate change, compromise water quality in both marine freshwater ecosystems, significantly affecting life coastal economies based on fishing tourism while also posing serious risks inland bodies. This article examines the role of hyperspectral imaging (HSI) monitoring HABs. HSI, with its superior spectral resolution, enables precise classification mapping diverse species, emerging as a pivotal tool environmental surveillance. An array HSI techniques, algorithms, deployment platforms are evaluated, analyzing efficacy across varied geographical contexts. Notably, sensor-based studies achieved up 90% accuracy, regression-based chlorophyll-a (Chl-a) estimations frequently reaching coefficients determination (R2) above 0.80. quantitative findings underscore potential for robust HAB diagnostics early warning systems. Furthermore, we explore current limitations future management, highlighting strategic importance addressing growing economic challenges posed paper seeks provide comprehensive insight into HSI’s capabilities, fostering integration global strategies against proliferation.

Language: Английский

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The need for advancing algal bloom forecasting using remote sensing and modeling: Progress and future directions

Ecological Indicators, Journal Year: 2025, Volume and Issue: 172, P. 113244 - 113244

Published: Feb. 21, 2025

Language: Английский

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Vegetative-cell morphology changes depending on nutritional conditions in Japanese strains of the noxious red-tide microalgae Chattonella

Fisheries Science, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 23, 2025

Language: Английский

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Disruptive Synergism: The Co-occurrence of Scyphozoan Pelagia noctiluca (Forsskål, 1775) Swarms with Green Tide-Causing Dinoflagellate Noctiluca scintillans (Macartney) Kofoid & Swezy, 1921

Continental Shelf Research, Journal Year: 2025, Volume and Issue: 288, P. 105447 - 105447

Published: Feb. 25, 2025

Language: Английский

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Biology, Ecology and Management of Aquatic Macrophytes and Algae (Volume I)

Biology, Journal Year: 2025, Volume and Issue: 14(3), P. 246 - 246

Published: Feb. 28, 2025

Aquatic macrophytes and algae constitute essential components of aquatic ecosystems, fulfilling diverse critical roles in sustaining ecological integrity equilibrium [...]

Language: Английский

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Satellite Retrieval and Spatiotemporal Variability in Chlorophyll-a for Marine Ranching: An Example from Daya Bay, Guangdong Province, China

Water, Journal Year: 2025, Volume and Issue: 17(6), P. 780 - 780

Published: March 7, 2025

With the planning and construction of marine ranching in China, water quality has become one critical limiting factors for development ranching. Due to geographical differences, ranches exhibit varying conditions under influence continental shelf. To best our knowledge, there is limited research on satellite-based monitoring spatiotemporal variations different locations. Chlorophyll-a (Chl-a) a key indicator ecological health disaster prevention capacity ranching, as it reflects eutrophication crucial high-quality, sustainable operation Using physically based model, this study focuses retrieval Chl-a concentration Daya Bay. The coefficient determination (R2) between model values situ data 0.69, with root mean square error (RMSE) 1.52 μg/L absolute percentage (MAPE) 44.25%. Seasonal are observed Bay higher spring–summer lower autumn–winter. In YangMeikeng waters, shows declining trend A comparison (nearshore) XiaoXingshan (offshore) suggests that offshore may be less impacted by terrestrial pollutants. primary sources input Dan’ao River aquaculture areas northeastern part bay. This can provide valuable information protection management

Language: Английский

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