Search Results (430)

Water dynamics and nutrients are widely recognized as the main triggers of phytoplankton blooms. These factors may control the stability of marine ecosystems. Penzhina Bay and the Shelikhov Gulf are famous for their high tidal dynamics in comparison with the basins of the World Ocean and for being the feeding places of Bowhead whales. Here, we study the dynamics and thermohaline structure of water; nutrients; isotopic signatures of δ¹⁵N–$\mathrm{N}{\mathrm{O}}_3^{-}$ and δ¹⁸O–$\mathrm{N}{\mathrm{O}}_3^{-}$; as well as chlorophyll a in Penzhina Bay, the Shelikhov Gulf, and the Penzhina River to understand the features of an ecosystem with intense tidal dynamics in the subpolar region. This work is based on data obtained in three cruises of the R/V “Akademik Oparin” in the period from 2023 to 2025, with speed boat observations in the Penzhina River from May to October, including the flooding peak in June. The observations covered cases with tides from 7 to 13.4 m in height. The interaction between tides and river runoff was observed to supply dissolved inorganic nitrogen (DIN) and dissolved inorganic phosphorus (DIP) from the sea and dissolved silicate (DSi) from the river. The “white nights” in July, combined with the increased supply of nutrients, are good conditions for phytoplankton blooms, and as a result, the concentration of chlorophyll a in the study area was observed to be up to 39 µg/L. High primary production supports the food chain, and this is probably the main reason why Bowhead whales come to feed in the summer. The DIN/DIP ratio indicates DIN as a limiting factor in most of Penzhina Bay and throughout the Shelikhov Gulf. At the same time, the DSi/DIP ratio at a significant distance from the mouth of the Penzhina River is close to 0, indicating unfavorable conditions for diatoms. The DSi limit can cause the blooming of dinoflagellates, which sometimes occurs in this region. Full article

Eutrophication is a pervasive issue in Mediterranean reservoirs, where external nutrient inputs and internal sediment releases interact to impair water quality and ecological stability. This study assessed the trophic condition of the artificial lake Cuga in Sardinia (Italy), mainly used for irrigation and providing potable water, by integrating watershed nutrient load estimates, inter-lake transfers, and internal phosphorus release. Field campaigns between July 2022 and May 2023 provided bi-monthly measurements of physical, chemical, and biological parameters, complemented by GIS-based land cover analysis and export coefficient modeling to quantify spatial nutrient sources. Additional phosphorus inputs from water transfers with a nearby reservoir were calculated, while internal sediment release was estimated using a calibrated mass balance model. Results revealed high nutrient concentrations, with mean total phosphorus of 128 mg P m⁻³, chlorophyll a averaging 9.9 mg m⁻³, and Secchi depth below 1 m, classifying the reservoir as eutrophic to hypertrophic under OECD and Carlson indices. Spatial loads were dominated by agricultural areas, while inter-lake transfers and internal sediment release contributed substantially to the overall phosphorus budget. The predictive Vollenweider model closely matched the observed conditions, confirming the robustness of the combined approach. Maintaining good ecological status in Mediterranean reservoirs is essential for safeguarding human well-being, as eutrophication degrades drinking-water quality, increases treatment costs, and can promote toxin-producing algal blooms with direct implications for public health. These findings highlight the need for integrated management strategies addressing both external and internal nutrient sources to mitigate eutrophication in Mediterranean reservoirs, which affects the ecosystem functioning and the related human needs and well-being. Full article

Sea-surface chlorophyll-a concentration (Chl-a) is a core indicator reflecting phytoplankton biomass and marine ecological conditions. Its spatiotemporal variation patterns are closely related to environmental changes and human activities, especially in coastal waters around heavily populated areas, e.g., the Bohai Sea in China. Benefiting from long time-series ocean-color (i.e., Chl-a provided by Aqua-MODIS) multi-source merged sea surface temperature (SST) and wind speed (i.e., ERA5) and dissolved inorganic nitrogen concentration (DIN) data, this study investigated the long-term variation characteristics of Chl-a in the Bohai Sea and its influencing factors during the period of 2003 to 2022. After rigorous quality control and data reconstruction, this study analyzed the interannual, seasonal, and spatial variation patterns of Chl-a in the Bohai Sea across five ecological functional subregions (Bohai Bay, the Qinhuangdao coast, Liaodong Bay, Laizhou Bay, and the central Bohai Sea), and explored the influence of SST, wind speed, and DIN on variations in Chl-a. The results showed that the spatial distribution of Chl-a in the Bohai Sea exhibited a significant coastal–offshore gradient, with higher concentrations in coastal bays and the Qinhuangdao coast and lower concentrations in the central Bohai Sea. Temporally, despite a long-term trend of first increasing and then decreasing with a peak around 2011, Chl-a underwent a significant regime shift around 2015. After the shift, the average concentration decreased by 0.36 mg/m³ compared with that before the shift. On a seasonal scale, the average Chl-a concentration over the whole Bohai showed the largest decrease in summer (−0.65 mg/m³) and the smallest decrease in winter (−0.21 mg/m³), with contrasting changes among subregions: the Qinhuangdao coast had the most significant decrease (−1.54 mg/m³), while Laizhou Bay remained basically stable. Driver mechanism analysis indicated that Chl-a in the Bohai Sea was significantly negatively correlated with SST (r = −0.51, p = 0.022) and significantly negatively correlated with wind speed (r = −0.77, p < 0.01). Furthermore, both SST and wind speed have undergone significant regime shifts toward a warmer and a windier state, respectively. The timing of these climatic shifts coincided with or preceded the Chl-a regime shift, which may help suppress phytoplankton blooms and maintain lower Chl-a levels. In addition, the surface DIN concentration in Bohai Bay decreased by 23.6% after the Chl-a regime shift, indicating a reduction in nutrient input may be responsible for the decrease in Chl-a in this region. The research results reveal the long-term variation patterns and multi-factor synergistic regulatory mechanism of Chl-a in the Bohai Sea, providing a scientific reference for red-tide monitoring and early warning as well as regional ecological environment management in the Bohai Sea. Full article

Chlorophyll-a (Chl-a) is a critical indicator of freshwater ecosystem health, reflecting phytoplankton biomass and primary productivity. This study investigates the long-term dynamics of Chl-a concentrations in Chao Lake, China, over three decades (1993–2023), employing an integrated approach combining remote sensing, causality, and comprehensive land use and climate data analysis. Our findings reveal a dramatic 175% increase in Chl-a levels, from 37.26 km² (1.71%) in 1993 to 102.41 km² (4.71%) in 2023, highlighting the ongoing eutrophication crisis. Significant correlations were established between land cover changes and Chl-a dynamics, with built-up areas exhibiting a positive correlation of 0.763 with Chl-a. In contrast, vegetation cover showed an inverse correlation of −0.766. Rising land surface temperatures (LST) increased by 1.8 °C from 1993 to 2023, significantly affecting nutrient cycling and algal bloom proliferation. Precipitation trends indicate a decline of approximately 10% over the study period, further exacerbating hydrological stress and nutrient concentrations. Employing Convergent and Geographic Convergent cross-mapping, we established robust causal relationships, confirming that urbanization and climate variability are primary drivers of Chl-a fluctuations. These findings stress the urgent need for targeted management strategies to mitigate nutrient loading and improve water quality in Chao Lake. Full article

Coastal and marine systems are governed by fragile water-quality dynamics, where disturbances can trigger harmful algal blooms with significant ecological and societal consequences. These pressures have intensified interest in forecasting systems that can anticipate bloom development and support environmental management. This study presents a systematic review of simulation-based and predictive environmental modeling approaches used for marine forecasting of water quality and harmful algal bloom phenomena. Following PRISMA guidelines, 11,185 records were identified, 127 articles were screened in full text for eligibility, and 40 peer-reviewed studies published between 2015 and 2025 were included and synthesized using a structured extraction framework capturing modeling paradigms, forecast targets, data inputs, spatial and temporal scope, validation practices, operational context, and reported limitations. The reviewed literature indicates the dominance of predictive and hybrid modeling approaches, with forecasting efforts primarily focused on coastal systems and short-term applications. Harmful algal blooms and chlorophyll-a emerge as dominant forecast targets, commonly supported by satellite observations, in situ measurements, and environmental forcing variables. Despite substantial methodological advances, persistent challenges related to data availability and quality, validation rigor, system integration, and operational deployment remain evident across modeling paradigms. Overall, the findings suggest that while marine forecasting models have become increasingly sophisticated, their translation into reliable and operational systems remains uneven, highlighting the need for closer alignment. Full article

To elucidate water quality evolution and algal responses in sluice-controlled ditches, this study combined in situ monitoring (July–October 2025) in the Chong Lake Watershed of Jianghan Plain (China) with controlled experiments at Changjiang River Scientific Research Institute. This study provided the first evidence of how sluice-induced hydrodynamic changes affect water quality and Spirogyra outbreaks in Jianghan Plain irrigation ditches. In situ monitoring showed that sluice interception significantly altered hydrodynamics, reducing dissolved oxygen (DO) by 18% and increasing chlorophyll-a and total phosphorus by 32% and 12%, respectively, compared to control ditches. Simulation experiments confirmed these trends: under sluice control, suspended solids and DO decreased by 30% and 19%, while ammonia nitrogen and phosphate increased by 8% and 13%; nitrate nitrogen dropped by 20%. Spirogyra dominated both systems but shifted from attached filaments in controls to floating clumps in sluice-controlled ditches, with biomass rising 94%. Pearson correlation linked Spirogyra biomass negatively to DO and positively to ammonia and phosphate. Sluice interception promotes eutrophication and Spirogyra blooms by reducing DO and particulates, which inhibits nitrification and releases soluble phosphate. A flow velocity of 0.05 m·s⁻¹ effectively suppresses such outbreaks. Full article

Harmful algal blooms (HABs) remain a growing threat to freshwater systems, yet predictive tools often rely on generic indices centered on chlorophyll-a (Chl-a), which is not cyanobacteria-specific. This paper introduces the Threshold Index (TRINDEX) as a new tool for predicting harmful algal blooms (HABs) in freshwater lakes. Unlike classical indices, TRINDEX explicitly integrates phycocyanin (PC), the pigment unique to cyanobacteria, making it the first cyanobacteria-specific threshold-based index. Using receiver operating characteristic (ROC) curve analysis, TRINDEX demonstrated excellent predictive tool, with area under the curve (AUC) values of 0.956 for TRINDEX₂ and 0.888 for TRINDEX₁ in Lake Torment, Nova Scotia. Furthermore, cohort studies, adapted from epidemiology, introduced here for the first time in HAB research, further validated TRINDEX, showing a 14.1% predicted bloom risk compared to 17.6% observed risk in Lake Torment. Validation across three independent waterbodies in New Brunswick confirmed TRINDEX’s robustness, with AUC values ranging from 0.714 to 0.979. These innovations demonstrate that TRINDEX yields robust, quantitative bloom thresholds, providing a practical foundation for future early-warning systems linked with remote sensing and real-time sensors to support effective water-quality management. Full article

The Bering Sea and its surrounding waters are commercially and ecologically important ecosystems. Knowledge of phytoplankton phenology is crucial for understanding ecosystem dynamics. However, estimates of phenological parameters of spring phytoplankton bloom are sparse for this region. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) daily data from 2003–2024 to assess the climatology of phenological parameters. A combination of data regriding, spatial interpolation, and temporal smoothing was applied. Three methods of spatial interpolation for missing data acquisition are compared: iterative first-order neighbor, inverse distance weighted interpolation, and data interpolating empirical orthogonal functions (DINEOF). We suggest that the first outcompetes the other two methods when compared to initial data. Date of the bloom initiation, bloom peak, chlorophyll-a maximum, and duration of the bloom before its peak are evaluated. The spatial distribution of mentioned phenological parameters is presented and discussed. We show that bloom starts early in Bristol Bay, in the narrow band along the eastern shelf, along the Kamchatka Peninsula, and south of the Aleutians and Alaska Peninsula. In the deep Bering Sea, bloom starts surprisingly later considering the latitude of the region. The main reason for this may be the wind mixing during the spring. The first phase of the bloom is generally longer in the deep southern areas (up to 60 days) and shorter in the northern shelf areas (less than 2 weeks in some cases). Full article

For the first time in the bay of Annaba (Southern Mediterranean), we studied the spatiotemporal distribution of potentially toxic benthic dinoflagellates: Ostreopsis cf. ovata, Prorocentrum lima, Coolia monotis, and Amphidinium carterae, hosted by the dominant macrophytes Posidonia oceanica, Padina pavonica, Codium fragile, and Halopteris scoparia. Sampling of these macrophytes was conducted weekly during spring and summer as well as bi-weekly in autumn and winter, from October 2022 to November 2023, at contrasting sites within Annaba Bay. The measured environmental parameters included temperature, pH, dissolved oxygen, salinity, ammonium, nitrate, nitrite, dissolved organic nitrogen, dissolved inorganic nitrogen, phosphate, dissolved organic phosphorus, silicate, and chlorophyll a. A proliferation of O. cf. ovata was recorded in July 2023, coinciding with a marked increase in temperature, with a maximum abundance exceeding 40 × 10³ cells g⁻¹ of fresh weight (FW) on H. scoparia and C. fragile. The maximum abundance of P. lima reached 8700 cells g⁻¹ FW on H. scoparia during July and August 2023. Coolia monotis exhibited a peak of 2800 cells g⁻¹ FW on H. scoparia. The abundance of A. carterae increased with temperature, reaching a maximum of 980 cells g⁻¹ FW on P. pavonica. The distribution of epiphytic dinoflagellates varied according to the macrophyte substrate. Overall, statistical analyses indicate that benthic dinoflagellate community structure is shaped by the combined effects of temperature, nutrient availability, and ecological niche differentiation, with temperature emerging as the dominant driver. This suggests that climate-driven increases in Mediterranean Sea surface temperatures are likely to extend the seasonal window of harmful benthic algal blooms, thereby enhancing ecological disturbances and potential risks to human health. This study provides the first assessment of BHAB dynamics along the Eastern Algerian coast, highlighting the role of ongoing regional warming in shaping future bloom patterns. Full article

Cyanobacterial blooms pose a serious threat to freshwater ecosystems, necessitating accurate remote sensing monitoring. Although red-edge bands show potential in terrestrial monitoring, their multi-dimensional features (i.e., spectral, textural, and index-based characteristics) remain underutilized for aquatic blooms. This study leverages the dual red-edge bands (710 nm and 750 nm) of GF-6/WFV to enhance cyanobacterial bloom identification in Lake Taihu. Multi-temporal images from 2019–2023 were used to construct red-edge features in three dimensions: spectral (evaluated via adaptive band selection method) and Jeffries–Matusita–Bhattacharyya distance), texture (based on Gray Level Co-occurrence Matrix and principal component analysis), and indices (nine vegetation indices ranked by Random Forest importance). Twelve feature-combination schemes were designed and implemented with a Random Forest classifier. Results show that red-edge features consistently improve identification accuracy. Quantitatively, compared to the basic four-band (RGBN) combination, the 710 nm band improved spectral separability by an average of 9.63%, whereas the 750 nm band yielded a lower average improvement of 5.69%. Red-edge indices, especially the modified chlorophyll absorption reflectance index 1 (MCARI1) and normalized difference red-edge index (NDRE), exhibited higher importance than non-red-edge indices. All schemes incorporating red-edge features achieved mean overall accuracies of 92.8–94.9% and Kappa coefficients of 0.86–0.94, surpassing the basic four-band scheme. Among these features, red-edge indices contributed most significantly to accuracy gains, increasing the overall accuracy by an average of 0.36–6.06% and the Kappa coefficient by up to 0.06. The enhancement effect of the red-edge 710 nm band features was superior to that of the 750 nm band. This study demonstrates that multi-dimensional red-edge features effectively enhance the identification accuracy of cyanobacterial blooms and provides a methodological reference for operational GF-6 applications in water quality monitoring. Full article

Climate change influences the agronomic behaviour of fruit trees. It is necessary to determine which cultivars adapt best to conditions in which water supplies are becoming increasingly scarce. This study analyses different phenological, morphological, physiological, agronomic and productive parameters to evaluate water stress tolerance in six late-blooming almond cultivars widely grown in Spain (‘Ferragnès’, ’Francolí’, ‘Masbovera’, ‘Glorieta’, ’Guara’ and ‘Lauranne’). Two different plots were analysed: one under regulated deficit irrigation, at Les Borges Blanques, Lleida, with a water deficit (146.2 mm/year) and the other under rainfed conditions, at Mas Bové, Constantí, Tarragona, with a water deficit (284.5 mm/year). Parameters, including an increase in canopy volume, leaf-to-air thermal gradient, and slope between leaf water potential and level of leaf saturation, have proven to be good indicators of resistance to water stress. Yield variation and leaf temperature variation between rainfed and irrigated conditions also perform quite well. An assessment of leaf chlorophyll content, measured using SPAD-502, suggested the presence of a collateral effect resulting from the opacity of the biomass, as well as to chlorophyll-related cuticular colouring. Finally, under the experimental conditions, ‘Guara’ and ‘Masbovera’ proved the most resistant cultivars; ‘Glorieta’ and ‘Francolí’ exhibited an intermediate level, and ‘Lauranne’ and ‘Ferragnès’ were the least resistant cultivars. Full article

Research into the effects of environmental stressors associated with global climate change (GCC) on cyanobacteria and microalgae is scarce, with bloom-forming planktonic cyanobacteria being the exception. This study aimed to address the issue by assessing morphological and biochemical changes in cyanobacterial and microalgal cells exposed to an increased temperature (T), ultraviolet radiation (UVR) and carbon dioxide (CO₂) concentration. The strains selected were Calothrix sp. SLM0211 and Coelastrella sp. SLM0503, which were isolated from a coastal environment in the central Mediterranean island of Malta. Elevated UVR had a pronounced effect on Calothrix sp. filaments, which produced screening compounds and resorted to trichome coiling to enhance self-shading. Enhanced growth was observed in cultures of Calothrix sp. grown at an increased CO₂ concentration, which produced significantly high amounts of biomass, chlorophylls and carotenoids. An increased T resulted in stunted growth and low biomass accumulation in both strains. Each strain exhibited a unique response to T and UVR stressors, which stimulated the production of exopolymeric substances (EPS) and mycosporine-like amino acids (MAAs) in cultures of Calothrix sp. and lipid production in Coelastrella sp. cells. Our findings indicate that the effects of stressors related to GCC on cyanobacterial and microalgal cells are strain-specific, making changes at community and ecosystem levels difficult to predict. Full article

Nutrient runoff from agricultural activities in the watershed of Western Lake Erie (WLE) is a dominant driver of harmful algal blooms (HABs). While phosphorus (P) is a key factor causing these blooms and has been the focus for researchers and policymakers, the influence of nitrogen (N) on bloom dynamics has been overlooked. Total Kjeldahl N (TKN; organic N and ammonium N) has not been the focus of eutrophication research but was recently linked to bloom development in WLE. Here, monotonic and oscillatory statistical trend analyses were performed to interpret long-term (1982 to 2022) patterns of TKN in the Maumee River and were compared to algal biomass data as chlorophyll a. A predictive regression model used principal component analysis to estimate a chlorophyll-based index of HABs in WLE, and a systematic iterative process identified that TKN influences bloom dynamics along with soluble reactive phosphorus (SRP), total suspended solids (TSS) and flow. Although TKN loads exhibited a long-term decline, this decrease did not correspond to reduced HAB severity, reflecting the strong influence of flow-driven hydrologic variability on nutrient delivery and bloom response. The modeling results demonstrate that TKN, together with SRP, TSS, and flow, significantly contributes to predicting bloom magnitude. These findings highlight the need for dual-nutrient (N and P) management strategies and additional analyses of nutrient–hydrology interactions to improve HAB mitigation in WLE. Full article

Phytoplankton blooms represent a typical ecological process in marine systems. Climate change drives shifts in its phenology, both directly via impacts on physiology and indirectly by modifying stratification intensity, nutrients, light availability, and grazing pressure. Using satellite remote sensing and reanalysis data from 2000 to 2022, this study partitions the Yellow Sea based on interannual variability in the Yellow Sea Cold Water Mass (YSCWM). Clear spatial differences in autumn bloom phenology are observed within the YSCWM. Earlier initiation dominates the Southern YSCWM (SYSCWM), while delayed later initiation concentrates in the Northern YSCWM (NYSCWM) and along the SYSCWM’s eastern margins. This pattern can be explained by the differences in regional hydrodynamics, i.e., the Yellow Sea Warm Current (YSWC) enhances upwelling and convergence in some YSCWM areas, boosting nutrient supply and earlier blooms, whereas weaker circulation-driven nutrient supply causes the bloom delay. Interannual variation analysis further reveals that the bloom timing is regulated by seasonal YSCWM dissipation since intensified autumn northerly winds accelerate dissipation and nutrient supply, thereby advancing blooms, while weaker northerly winds and stable circulation delay bloom progress by maintaining strong thermocline stability. These findings provide further insights into the underlying mechanisms driving autumn bloom dynamics and support ecosystem monitoring efforts in shelf seas. Full article

We analyzed six years (2019–2025) of Sentinel-2 and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery to quantify how turbidity and water temperature relate to algal blooms in Utah Lake. We generated satellite-derived estimates of chlorophyll-a (chl-a), turbidity, and surface temperature at 600 randomly distributed sample points. Using generalized least squares models, we found that temperature and turbidity explain only a small fraction of the variance in chl-a (temperature coefficients 0.02–0.03; turbidity coefficients −0.18–0.42), and the strength and sign of correlations vary by location. Despite weak linear correlations, we identified a strong nonlinear pattern: 94% of intense bloom events (chl-a > 87 µg/L) occurred when turbidity was below 120 Nephelometric Turbidity Units (NTU), indicating that blooms more often form under low-turbidity conditions. We also found that the first mild blooms of the season (chl-a > 34 µg/L) typically occurred five days after the largest short-term temperature increase (3–12 °C/day) at a given location, but only when blooms first appeared in April. These results suggest that Utah Lake blooms may be light-limited, with turbidity constraining algal growth that would otherwise occur in response to high nutrient levels, while temperature spikes influence early-season bloom initiation. Our findings have direct implications for monitoring and management strategies that target algal blooms on Utah Lake. Full article