Search Results (1,113)

This study presents a comprehensive assessment of long-term nutrient dynamics in the northern South China Sea (NSCS), a region that hosts the world’s largest marine ranching cluster and serves as a cornerstone of China’s “Blue Granary” initiative. By integrating multi-sensor satellite remote sensing data (Landsat and Sentinel-2, 2002–2024) with in situ observations, we developed robust retrieval algorithms for total nitrogen (TN) and total phosphorus (TP), achieving high accuracy (TN: R² = 0.82, RMSE = 0.09 mg/L; TP: R² = 0.94, RMSE = 0.0071 mg/L; n = 63). Results showed that TP concentrations increased significantly faster than TN, leading to a decline in the TN:TP ratio (NP) from 19.2 to 13.2 since 2013. This shift indicates a transition from phosphorus (P) limitation to nitrogen (N) limitation, driven by warming sea surface temperatures (SST) (about 1.16 °C increase) and increased anthropogenic phosphorus inputs (about 27.84% increase). The satellite-based framework offers a scalable, cost-effective solution for monitoring aquaculture water quality. When integrated with artificial intelligence (AI) technologies, these near-real-time nutrient anomaly data can support early warning of harmful algal blooms (HABs), offering key insights for ecosystem-based management and climate adaptation. Overall, our findings highlight the utility of remote sensing in advancing sustainable marine resource governance amid environmental change. Full article

Cylindrospermopsis raciborskii is a toxin-producing cyanobacterium that is easy to overlook. It has strong environmental adaptability and is currently spreading around the world and gradually dominating to form a persistent bloom, causing ecological and environmental risks and drinking water safety issues. In this study, we systematically investigated the inhibitory effects of oleic acid on C. raciborskii and elucidated the underlying mechanisms through morphological observation, physiological assays, and bioinformatics analysis. Our results demonstrated that oleic acid strongly inhibits the growth of C. raciborskii, with a 72 h half-maximal effective concentration (EC₅₀) of 0.903 mg·L⁻¹. At 1.6 mg·L⁻¹, oleic acid achieved an inhibition rate of 99.5% within 48 h, indicating rapid suppression of cyanobacterial growth. Physiological analyses revealed that oleic acid severely impaired photosynthetic activity, as evidenced by significant reductions in key parameters (rETRmax, α, Fv/Fm, and Fv/Fo) and altered photosynthetic pigment composition, suggesting structural and functional damage to the photosynthetic apparatus. Morphological observations further showed that oleic acid disrupted filament integrity, inducing cell shrinkage, cytoplasmic vacuolation, cell wall detachment, membrane rupture, and eventual cellular disintegration. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis indicated that oleic acid interferes with multiple metabolic processes, including nutrient and cofactor synthesis, membrane transport, and signal transduction, ultimately triggering algal cell death. This study highlights oleic acid as a promising eco-friendly agent for mitigating C. raciborskii blooms, offering potential applications in ecological prevention and emergency bloom control. Full article

Harmful cyanobacterial blooms (CyanoHABs) threaten freshwater ecosystems and human health. Inhibiting cyanobacteria through plant allelopathy is an effective and environmentally friendly approach for CyanoHAB control. In this study, we evaluated the inhibitory activities of several organic solvent extracts from Artemisia argyi against the common bloom-forming cyanobacterium Microcystis aeruginosa, explored the anti-algal mechanism of the active fraction, analyzed its secondary metabolites using liquid chromatography–high-resolution mass spectrometry (LC-HRMS), and screened the potential allelochemicals. The results showed that the crude extract of A. argyi leaves (CE) exhibited significant inhibitory effects on M. aeruginosa. Among several solvent fractions of CE, the dichloromethane extract (DE) demonstrated the strongest inhibitory effect, with a 7-day IC₅₀ of 70.43 mg/L. After treatment with DE, the contents of chlorophyll a (Chl a), carotenoids, and phycobiliproteins (PBPs) in M. aeruginosa were significantly reduced. Meanwhile, an excessive accumulation of reactive oxygen species (ROS), reduction of catalase (CAT) activity, increase in malondialdehyde (MDA) content, and shrinkage of the membrane were found in M. aeruginosa cells under DE treatments. There were 81 secondary metabolites annotated in DE by LC-HRMS. Among them, hispidulin, jaceosidin, 5,7,3′-trihydroxy-6,4′,5′-trimethoxyflavone, and eupatilin possessed strong inhibitory activities, with 7-day IC₅₀ values of 26.23, 27.62, 32.02, and 34.98 mg/L, respectively. These results indicated that the A. argyi extracts possess significant allelopathic activities on M. aeruginosa, and DE was identified as the primary active fraction. It inhibits algae growth by suppressing photosynthesis and inducing peroxidation, ultimately leading to cell death. Flavonoids in DE were the main allelochemicals responsible for the inhibition on algae of A. argyi extracts. Full article

Eutrophication, a growing environmental concern, exacerbates algal blooms and alters the physical and chemical properties of water, thereby diminishing biodiversity, water quality, and ecosystem services. While various control strategies have been developed, most are designed for temperate regions and may not be applicable to tropical systems, which differ ecologically and climatically. This study reviewed 84 articles published between 2000 and 2024, focusing on eutrophication management in tropical and subtropical lakes. The studies were categorized into physical (8), chemical (17), and biological (59) approaches. Over time, research activity has increased, with Asia leading in publication output. Among biological strategies, biomanipulation—especially the use of macrophytes—emerged as the most common and effective strategy. Macrophytes are preferred due to their strong antagonistic interaction with algae, ease of implementation, cost-effectiveness, and minimal ecological risks. While the review also addresses the limitations of each method, it concludes that macrophyte-based biomanipulation remains a promising tool for mitigating eutrophication in tropical and subtropical freshwater ecosystems. In this context, effective lake restoration requires balancing ecological goals with human needs, supported by stakeholder engagement, community education, and multi-sectoral governance. Full article

Understanding mixing behavior at river confluences is essential for effective watershed management in response to increasing environmental issues such as algal blooms and chemical pollution. This study focused on the confluence of the Nakdong and Geumho Rivers, employing high-resolution field measurements using an ADCP (M9) and YSI EXO sensors. Water temperature (°C) and electrical conductivity (μS/cm) data were collected under three representative conditions, including flow ratios of 0.91, 0.45, and 0.29, as well as 0.05, with a maximum temperature difference of up to 6 °C. Mixing behavior was three-dimensionally analyzed by integrating cross-sectional and longitudinal data, and the accuracy of visualization was evaluated using IDW and Kriging spatial interpolation techniques. The analysis revealed that under low flow ratio conditions, vertical mixing was delayed; the thermal stratification persisted up to approximately 3 km downstream from the confluence (Line 3), and complete mixing was not achieved until about 7 km downstream (Line 5) due to density currents. Quantitative comparison indicated that IDW (R² = 0.901, RMSE = 31.522) outperformed Kriging (R² = 0.79, RMSE = 35.458). This study provides a quantitative criterion for identifying the mixing completion zone, thereby addressing the limitations of previous studies that relied on numerical models or limited field data, and offering practical evidence for water quality monitoring and sustainable river management. Full article

Algal blooms are ecological phenomena with long-lasting effects on the ecosystem and on the climate. Often, they reduce the oxygen level underwater, creating adverse circumstances for aquatic species’ survival, development, and reproduction. In this article, the mapping of algal bloom incidents and their daily monitoring is automated using Python script and the Earthdata website. The automation is carried out in eight separate modules and then integrated. Test site dictionary, configuration, query data, download MODIS data, open image data, clip data, implementing a novel Normalized Difference MODIS Algae Index (NDMAI), and threshold are the eight modules used for automating the extraction and daily monitoring. This automation requires two inputs: firstly, the bounding box, i.e., lower left coordinate (LLC) and upper right coordinate (URC) of the test site, and secondly, the date range. In this article, eight test sites are used to extract algal bloom incidents, and a ninth test site is used for the extraction and daily monitoring, which are reported by the NASA Earth Observatory (NEO). The proposed framework automates the process of enhancing algal bloom features in MODIS imagery, and daily monitoring is successfully accomplished, and the results perfectly match the algal bloom region in the test sites reported by the NEO. Full article

Amphidinols (AM) are a diverse group of bioactive polyketides produced by dinoflagellates of the genus Amphidinium, known for their hemolytic, antifungal, and cytotoxic activities. This work presents the assessment of AM profiles in a comprehensive number of strains, whose species boundaries were previously established through detailed taxonomic analysis. Using UHPLC-MS/MS, we characterized the spectrum of AM analogs in 54 Amphidinium strains isolated from diverse geographical locations. In addition, toxicity was assessed using brine shrimp assays, which revealed significant inter- and intraspecific variability. Despite the broad diversity in AM content, no clear correlation was observed between total AM levels and toxicity across all strains. Multivariate analysis grouped the strains into clusters distinguished by distinct AM profiles and toxicity levels, suggesting that AM production alone does not predict toxicity. Our findings highlight the complexity of Amphidinium bioactivity, emphasizing the influence of strain-specific factors and other bioactive compounds. This work highlights the importance of integrating chemical, genetic, and biological assessments to understand better the factors that govern toxicity in this genus, with implications for ecological studies and the monitoring of harmful dinoflagellates. Full article

The coastal waters of Qinhuangdao are a major hotspot for harmful algal blooms (HABs) in the Bohai Sea, with Noctiluca scintillans being one of the primary algal species responsible for these events. A comprehensive understanding of the microbial community structure and functional responses to N. scintillans bloom events is crucial for elucidating their underlying mechanisms and ecological impacts. This study investigated the microbial community dynamics, metabolic shifts, and the environmental drivers associated with a N. scintillans bloom in the coastal waters of Qinhuangdao, China, using high-throughput sequencing of 16S and 18S rRNA genes, co-occurrence network analysis, and metabolic pathway prediction. The results revealed that the proliferation of autotrophic phytoplankton, such as Minutocellus spp., likely provided a nutritional foundation and favorable conditions for the N. scintillans bloom. The bloom significantly altered the community structures of prokaryotes and microeukaryotes, resulting in significantly lower α-diversity indices in the blooming region (BR) compared to the non-blooming region (NR). Co-occurrence network analyses demonstrated reduced network complexity and stability in the BR, with keystone taxa primarily belonging to Flavobacteriaceae and Rhodobacteraceae. Furthermore, the community structures of both prokaryotes and microeukaryotes correlated with multiple environmental factors, particularly elevated levels of NH₄⁺-N and PO₄³⁻-P. Metabolic predictions indicated enhanced anaerobic respiration, fatty acid degradation, and nitrogen assimilation pathways, suggesting microbial adaptation to bloom-induced localized hypoxia and high organic matter. Notably, ammonia assimilation was upregulated, likely as a detoxification strategy. Additionally, carbon flux was redirected through the methylmalonyl-CoA pathway and pyruvate-malate shuttle to compensate for partial TCA cycle downregulation, maintaining energy balance under oxygen-limited conditions. This study elucidates the interplay between N. scintillans blooms, microbial interactions, and functional adaptations, providing insights for HAB prediction and management in coastal ecosystems. Full article

Intensified human activities in recent years, such as wastewater discharge and agricultural non-point source pollution have led to a decline in lake water quality, especially in the middle and lower reaches of the Yangtze River Basin, which threaten the stability of lake water ecosystems. Therefore, it is necessary to conduct a scientific assessment of the water eco-environmental quality of shallow lakes and implement targeted management measures. Considering the characteristics of shallow lakes, major ecological and environmental issues, and current standards and guidelines, an indicator system method was employed to establish a water eco-environmental quality evaluation system tailored for typical shallow lakes in the middle and lower reaches of the Yangtze River Basin. This evaluation system comprises three criteria layers (aquatic organism, habitat quality, and water quality) and 10 indicator layers. Using survey data from 2022 to 2024 for evaluation, the results showed that the water eco-environmental quality of Lake Gehu was rated as poor, with the lowest score for macrophyte coverage and the highest score for riparian vegetation coverage. This indicates that the shoreline restoration project in Lake Gehu was effective, while the lake water quality still needs improvement. Remedial measures include increasing aquatic vegetation coverage, reducing nitrogen and phosphorus pollution loads, and controlling the occurrence of algal blooms. This evaluation system combines field surveys with remote sensing monitoring data, fully considering historical and current conditions, and can guide local authorities in evaluating lake water environmental quality. The constructed evaluation system is applicable for the assessment of shallow lakes in the middle and lower reaches of Yangtze River Basin. It provides a scientific basis for the continuous improvement of eco-environmental quality and the construction of Beautiful Lakes Initiative, contributing to the management and protection of lake ecosystems. Full article

Algal blooms pose a serious threat not only to the lake ecosystem of Lake Bosten but also by negatively impacting its rapidly developing fisheries and tourism industries. This study focuses on Lake Bosten as the research area and utilizes multi-source remote sensing imagery from Landsat TM/ETM+/OLI and Sentinel-2 MSI. The Adjusted Floating Algae Index (AFAI) was employed to extract algal blooms in Lake Bosten from 2004 to 2023, analyze their spatiotemporal evolution characteristics and driving factors, and construct a Long Short Term Memory (LSTM) network model to predict the spatial distribution of algal-bloom frequency. The stability of the model was assessed through temporal segmentation of historical data combined with temporal cross-validation. The results indicate that (1) during the study period, algal blooms in Lake Bosten were predominantly of low-risk level, with low-risk bloom coverage accounting for over 8% in both 2004 and 2005. The intensity of algal blooms in summer and autumn was significantly higher than in spring. The coverage of medium- and high-risk blooms reached 2.74% in the summer of 2004 and 3.03% in the autumn of 2005, while remaining below 1% in spring. (2) High-frequency algal bloom areas were mainly located in the western and northwestern parts of the lake, and the central region experienced significantly more frequent blooms during 2004–2013 compared to 2014–2023, particularly in spring and summer. (3) The LSTM model achieved an R² of 0.86, indicating relatively stable performance. The prediction results suggest a continued low frequency of algal blooms in the future, reflecting certain achievements in sustainable water-resource management. (4) The interactions among meteorological factors exhibited significant influence on bloom formation, with the q values of temperature and precipitation interactions both exceeding 0.5, making them the most prominent meteorological driving factors. Monitoring of sewage discharge and analysis of agricultural and industrial expansion revealed that human activities have a more direct impact on the water quality of Lake Bosten. In addition, changes in lake area and water environment were mainly influenced by anthropogenic factors, ultimately making human activities the primary driving force behind the spatiotemporal variations of algal blooms. This study improved the timeliness of algal-bloom monitoring through the integration of multi-source remote sensing and successfully predicted the future spatial distribution of bloom frequency, providing a scientific basis and decision-making support for the sustainable management of water resources in Lake Bosten. Full article

Monitoring optically-active water quality (OAWQ) parameters faces key challenges, primarily due to limited in situ measurements and the restricted availability of high-resolution multispectral remote sensing imagery. While deep learning has shown promise for OAWQ estimation, existing approaches such as GeoTile2Vec, which relies on geographic proximity, and SimCLR, a domain-agnostic contrastive learning method, fail to capture land cover-driven water quality patterns, limiting their generalizability. To address this, we present deep meta-connectivity representation (DMCR), which integrates multispectral remote sensing imagery with limited in situ measurements to estimate OAWQ parameters. Our approach constructs meta-feature vectors from land cover images to represent the water quality characteristics of each multispectral remote sensing image tile. We introduce the meta-connectivity concept to quantify the OAWQ similarity between different tiles. Building on this concept, we design a contrastive self-supervised learning framework that uses sets of quadruple tiles extracted from Sentinel-2 imagery based on their meta-connectivity to learn DMCR vectors. After the core neural network is trained, we apply a random forest model to estimate parameters such as chlorophyll-a (Chl-a) and turbidity using matched in situ measurements and DMCR vectors across time and space. We evaluate DMCR on Lake Erie and Lake Ontario, generating a series of Chl-a and turbidity distribution maps. Performance is assessed using the $R^2$ and $RMSE$ metrics. Results show that meta-connectivity more effectively captures water quality similarities between tiles than widely utilized geographic proximity approaches such as those used in GeoTile2Vec. Furthermore, DMCR outperforms baseline models such as SimCLR with randomly cropped tiles. The resulting distribution maps align well with known factors influencing Chl-a and turbidity levels, confirming the method’s reliability. Overall, DMCR demonstrates strong potential for large-scale OAWQ estimation and contributes to improved monitoring of inland water bodies with limited in situ measurements through meta-connectivity-informed deep learning. The temporal-spatial water quality maps can support large-scale inland water monitoring, early warning of harmful algal blooms. Full article

Lake Taihu, a large, shallow freshwater lake in China, has experienced severe eutrophication for decades under intense human activities occurring around cities. Through long-term water quality management since 1995, the eutrophication of Lake Taihu has been controlled. This review examines the eutrophication characteristics, source identification methods, and control measures in Lake Taihu. Phosphorus is a primary driver of eutrophication, correlating strongly with chlorophyll a. The lake exhibits significant temporal and spatial variability in nutrient dynamics, influenced by human activities and the climate. Historical data show fluctuating nutrient levels and persistent algal blooms despite government efforts. A critical assessment of various source apportionment methods, including statistical analysis, physical modeling, and empirical models, is presented to elucidate the relative contributions of different nutrient sources. These methods identify agricultural non-point and urban point sources as major external contributors, with sediment nutrient release as a significant internal source. Implemented controls, including wastewater treatment plants and non-point-source management, have had limited success. Increased sewage and sediment nutrients necessitate integrated watershed management. Future research should prioritize advanced source tracking, sediment dynamics, climate impacts, and integrated ecological models. Sustainable eutrophication management in Lake Taihu requires integrated science, policy, and public engagement to ensure ecosystem health. Full article

SPX domain-containing proteins (SPXc) are crucial for regulating phosphorus (P) homeostasis in plants. Recently, the SPX gene was identified in the diatom model Phaeodactylum tricornutum and shown to serve as a negative regulator of P acquisition. Whether SPXc occurs in dinoflagellates is unclear. Here, we report the presence and potential functions of genes encoding SPXc in dinoflagellates (dino-SPXc). Four classes of SPXc were identified in dinoflagellates, including the three known classes—the stand-alone SPX, SPX-EXS, and SPX-VTC—and SPX-other, with SPX and SPX-EXS being dominant. Using the TARA Oceans database, we investigated the taxonomic and geographic distributions of dino-SPXc and found variations in dino-SPXc expression among size classes of dinoflagellates. The harmful algal bloom-causative species Prorocentrum shikokuense possesses all four classes of SPXc proteins, showing a fluctuating expression pattern under different nutrient conditions and during different phases of the cell cycle and algal bloom. In addition, the SPXc genes in Symbiodiniaceae respond not only to P stress but also to thermal variations. These results are consistent with a role of dino-SPXc in maintaining P homeostasis in dinoflagellates and suggest the importance of SPX-related genes in enabling dinoflagellates to sustain population growth in nutrient-variable oceans, warranting further research. Full article

Alexandrium spp. blooms and paralytic shellfish poisoning pose serious economic threats to coastal communities and aquaculture. This study evaluated the removal efficiency of two Alexandrium minutum strains using natural kaolinite clay (KNAC) and kaolinite with polyaluminum chloride (KPAC) at three concentrations (0.1, 0.25, and 0.3 g L⁻¹), two pH levels (7 and 8), and two cell densities (1.0 and 2.0 × 10⁷ cells L⁻¹) in seawater. PAC significantly enhanced removal, achieving up to 100% efficiency within two hours. Zeta potential analysis showed that PAC imparted positive surface charges to the clay, promoting electrostatic interactions with negatively charged algal cells and enhancing flocculation through Van der Waals attractions. In addition, the study conducted a cost estimate analysis and found that treating one hectare at 0.1 g L⁻¹ would cost approximately USD 31.75. The low KPAC application rate also suggests minimal environmental impact on benthic habitats. Full article

Eutrophication has become the primary water quality issue for most of the freshwater and coastal marine ecosystems in the world. Caused by excessive nitrogen (N) and phosphorus (P) inputs, it has a significant impact on aquatic ecosystems, resulting in algal blooms, oxygen depletion, and biodiversity loss. Zeolites have been identified as effective adsorbents for removal of these pollutants, improving water quality and ecosystem health. Kinetic and isotherm adsorption experiments were conducted to examine the adsorption efficiency of four zeolites of various origins (Greek, Slovakian, Turkish, and Bulgarian) and a specific modification (ZeoPhos) to determine the most effective material for N and P removal. The aim of the study is to discover the best zeolite for chemical adsorption in eutrophic waters by comparing their adsorption capacities and pollutant removal efficiencies along with SEM, TEM, and X-RD spectrographs. Slovakian ZeoPhos has been identified as the best-performing material for long-term and efficient water treatment systems for eutrophication management. Full article