Harmful Algal Blooms Research Articles

Exploring the response and prediction of phytoplankton to environmental factors in eutrophic marine areas using interpretable machine learning methods

Coastal marine areas are frequently affected by human activities and face ecological and environmental threats, such as algal blooms and climate change. The community structure of phytoplankton—primary producers in marine ecosystems—is highly sensitive to environmental factors, such as temperature, salinity, and nutrients. However, traditional methods for exploring the relationship between phytoplankton communities and environmental factors in eutrophic marine areas are limited by various factors. Therefore, this study employed interpretable machine learning models, integrating high-dimensional data analysis and complex system modeling, to quantitatively and thoroughly analyze the dynamic relationship between phytoplankton communities and environmental variables in high-frequency samples collected over 53 weeks from eutrophic marine areas. The cell abundance of phytoplankton exhibited a distinct “two-peak pattern” variation. Interpretable machine learning model analysis revealed the dynamic contributions of different environmental factors during changes in the phytoplankton community structure. The results showed that temperature was a key environmental factor that affected phytoplankton growth during peak periods. In addition, the contribution of salinity increased during the second peak in phytoplankton abundance, highlighting its central role in the ecological dynamics of this phase. During green tide outbreaks, particularly in Area 01, the contributions of factors such as temperature and salinity increased, whereas those of phosphates and silicates decreased, indicating that green tide outbreaks substantially altered the nutritional dynamics of the ecosystem. Furthermore, different phytoplankton species, such as Skeletonema costatum, Thalassiosira spp., and Nitzschia spp., exhibit varying responses to environmental factors. Hence, the predictions made using random forest and generalized additive models for phytoplankton cell abundance in two marine areas revealed complex nonlinear relationships between environmental factors, such as temperature, salinity, and phytoplankton abundance.

The Occurrences of Harmful Algal Blooms (HABs) Species and Trophic Status Update in Kedung Ombo Reservoir

Graphical Abstract Highlight Research Water quality conditions in Kedung Ombo Reservoir. Phytoplankton species and their abundance in Kedung Ombo. Potential existence and dominance of HABs species. The updated trophic status is mapped based on the TSI, Secchi depth, chlorophyll-a, and total phosphorus. Abstract Anthropogenic inputs affect the quality of freshwater ecosystems which causes ecological and health problems to aquatic ecosystems. Harmful algal blooms (HABs) associated with cyanotoxins often occur in nutrient-rich or eutrophic freshwater ecosystems. Kedung Ombo Reservoir in Indonesia has been previously classified as eutrophic to hypertrophic. Therefore, this study aimed to identify the occurrences of potential HABs species, measure the bio-physico-chemical water quality parameters, and update the trophic status of Kedung Ombo Reservoir. Sampling was done thrice during the dry season in 2022 from 5 stations. Twenty-two species of phytoplankton were observed in Kedung Ombo Reservoir. Anabaenopsis sp., Aphanizomenon sp., Ceratium sp., Mougeotia sp., Pandorina sp., and Ulothrix sp. were identified as potentially harmful species. Among those, the potentially HABs species, Aphanizomenon sp. was the most abundant (179,344 cells/L) and Cyanophyceae (205,539 cells/L) was the dominant group of phytoplankton. Kedung Ombo Reservoir had a water temperature of 29.49±0.41°C, phosphate of 0.27±0.25 mg/L, and alkaline pH of 7.90±0.39. Kedung Ombo Reservoir also had low transparency coupled with low dissolved oxygen concentration. The occurrences of HABs species were correlated with transparency and dissolved inorganic nutrients, especially phosphate concentrations. Kedung Ombo Reservoir showed eutrophic conditions based on Secchi depth, chlorophyll-a, total phosphorus, and TSI. Based on research findings, control and mitigation efforts are needed to overcome the eutrophication problems which disrupt the balance of the aquatic ecosystem in the Kedung Ombo Reservoir.

Mapping the main harmful algal species in the East China Sea (Yangtze River estuary) and their possible response to the main ecological status and global climate change via a global vision

The Yangtze River Estuary (YRE) is one of the areas in China most severely affected by harmful algal blooms (HABs). This study explored the distributive patterns of HABs in the YRE and how they are influenced by the El Niño-Southern Oscillation (ENSO) and other environmental factors. Quantitative real-time PCR (qPCR) was employed to detect and quantify the four predominant HAB species in the YRE, Karenia mikimotoi, Margalefidinium polykrikoides, Prorocentrum donghaiense, and Heterosigma akashiwo. Additionally, the study analyzed how turbidity, pH, salinity, and temperature influence these algae. Distribution of the four HAB species in the YRE area shows clear geographical variations: K. mikimotoi is predominantly found in the northwest and central sea areas, M. polykrikoides (East Asian Ribotype, EAR) is mainly distributed in the southeastern part, P. donghaiense is abundant in the northern regions, and H. akashiwo is especially prevalent at stations S26 and S27 in the northeastern part of the study area. HABs dominated by H. akashiwo and P. donghaiense were observed in the northeastern sea area of the YRE on July 22, 2020. Our study reveals that K. mikimotoi, M. polykrikoides (EAR), and P. donghaiense are mainly affected by turbidity, pH, and salinity, while temperature predominantly influences the blooms of H. akashiwo. Moreover, runoff in the YRE has a certain correlation with ENSO events, which may also impact the nutrient content of the region. The findings of this study illustrate the distributive patterns of the four HAB species under various ecological conditions in the YRE and emphasize the importance of establishing practical cases for future warning systems. To better understand how climate change affects HABs, exploring the link between ENSO and HABs is essential.

An unusual winter bloom of dinoflagellates with notable damage to kelp cultivation around Shandong peninsula, China

In the coastal waters around Shandong peninsula, an unprecedented winter bloom of dinoflagellates Gonyaulax polygramma and Akashiwo sanguinea occurred in 2021 from late November to early December. The bloom affected a wide area of coastal waters extending from west to east along the northern Shandong peninsula and had a devastating blow to the kelp cultivation industry. Based on the remote-sensing data, the initiation of the bloom was traced back to the region adjacent to the mouth of the Yellow River in Laizhou Bay, where enhanced freshwater discharge from the Yellow River was recorded from September to November. It's proposed that the increased precipitation in the Yellow River basin associated with northward extension of the precipitation band in China could be an important reason for this winter bloom. This unusual winter bloom around Shandong peninsula highlights the potential risks of harmful algal blooms and their impacts on coastal ecosystems under the background of climate change.

A short-term exposure to saxitoxin triggers a multitude of deleterious effects in Daphnia magna at levels deemed safe for human health

Harmful algal blooms and the toxins produced during these events are a human and environmental health concern worldwide. Saxitoxin and its derivatives are potent natural aquatic neurotoxins produced by certain freshwater cyanobacteria and marine algae species during these bloom events. Saxitoxins effects on human health are well studied, however its effects on aquatic biota are still largely unexplored. This work aims at evaluating the effects of a pulse acute exposure (24 h) of the model cladoceran Daphnia magna to 30 μg saxitoxin L−1, which corresponds to the safety guideline established by the World Health Organization (WHO) for these toxins in recreational freshwaters. Saxitoxin effects were assessed through a comprehensive array of biochemical (antioxidant enzymes activity and lipid peroxidation), genotoxicity (alkaline comet assay), neurotoxicity (total cholinesterases activity), behavioral (swimming patterns), physiological (feeding rate and heart rate), and epigenetic (total 5-mC DNA methylation) biomarkers. Exposure resulted in decreased feeding rate, heart rate, total cholinesterases activity and catalase activity. Contrarily, other antioxidant enzymes, namely glutathione-S-transferases and selenium-dependent Glutathione peroxidase had their activity increased, together with lipid peroxidation levels. The enhancement of the antioxidant enzymes was not sufficient to prevent oxidative damage, as underpinned by lipid peroxidation enhancement. Accordingly, average DNA damage level was significantly increased in STX-exposed daphnids. Total DNA 5-mC level was significantly decreased in exposed organisms. Results showed that even a short-term exposure to saxitoxin causes significant effects on critical molecular and cellular pathways and modulates swimming patterns in D. magna individuals. This study highlights sub-lethal effects caused by saxitoxin in D. magna, suggesting that these toxins may represent a marked challenge to their thriving even at a concentration deemed safe for humans by the WHO.

Smartphone as an alternative to measure chlorophyll-a concentration in small waterbodies

Monitoring chlorophyll-a concentrations (Chl-a, μg·L−1) in aquatic ecosystems has attracted much attention due to its direct link to harmful algal blooms. However, there has been a lack of a cost-effective method for measuring Chl-a in small waterbodies. Inspired by the increase of smartphone photography, a Smartphone-based convolutional neural networks (CNN) framework (SCCA) was developed to estimate Chl-a in Aquatic ecosystem. To evaluate the performance of SCCA, 238 paired records (a smartphone image with a 12-color background and a measured Chl-a value) were collected from diverse aquatic ecosystems (e.g., rivers, lakes and ponds) across China in 2023. Our performance-evaluation results revealed a NS and R2 value of 0.90 and 0.94 in Chl-a estimation, demonstrating a satisfactory (NS = 0.84, R2 = 0.86) model fit in lower Chl-a (<30 μg L−1) conditions. SCCA had involved a realtime-update method with hyperparameter optimization technology. In comparison with the existing methods of measuring Chl-a, SCCA provides a useful screening tool for cost-effective measurement of Chl-a and has the potential for being an algal bloom screening means in small waterbodies, using Huajin River as a case study, especially under limited resources for water measurement. Overall, we highlight that the SCCA can be potentially integrated into a smartphone application in the future to diverse waterbodies in environmental management.

Low-frequency ultrasound assisted contact-electro-catalysis for efficient inactivation of Microcystis aeruginosa

Frequent cyanobacterial blooms pose a serious threat to the aquatic ecosystem and human health, so developing an efficient algae removal method is a long-term goal for bloom management. Current technologies for algal bloom control need urgent improvement in terms of algicide recovery, eco-friendliness and cost. Here we propose a contact-electro-catalytic method, using polytetrafluoroethylene (PTFE) film as a reusable catalyst. This contact-electro-catalytic approach involves the generation of reactive oxygen species (e.g., O2•–, HO•, 1O2 and H2O2) through water-PTFE contact electrification under the low-frequency ultrasonic waves, facilitating the inactivation of algae. The removal rate of the cyanobacterium Microcystis aeruginosa (M. aeruginosa) exposured to the water-PTFE contact-electro-catalytic system is almost five times greater than that of ultrasound alone after 5 h. A mechanistic investigation revealed that the contact-electro-catalytic system damaged the photosynthetic activity, antioxidant system and membrane integrity of the cells. Additionally, LC-MS metabolomic analysis indicated that this system caused substantial significant disruptions in the TCA cycle, amino acid metabolism, purine metabolism and phospholipid metabolism. Three-dimensional fluorescence spectroscopy suggested contact-electro-catalysis could further availably degrade the organic matter. We anticipate that this method can provide an eco-friendly, highly efficient and economic approach for effective control of harmful algal blooms.

A newly identified algicidal bacterium of Pseudomonas fragi YB2: Algicidal compounds and effects

Harmful algal bloom (HAB) is an unresolved existing problem worldwide. Here, we reported a novel algicidal bacterium, Pseudomonas fragi YB2, capable of lysing multiple algal species. To Chlorella vulgaris, YB2 exhibited a maximum algicidal rate of 95.02 % at 120 h. The uniqueness of YB2 lies in its ability to self-produce three algicidal compounds: 2-methyl-1, 3-cyclohexanedione (2-MECHD), N-phenyl-2-naphthylamine, and cyclo (Pro-Leu). The algicidal properties of 2-MECHD have not been previously reported. YB2 significantly affected the chloroplast and mitochondrion, thus decreasing in chlorophyll a by 4.74 times for 120 h and succinate dehydrogenase activity by 103 times for 36 h. These physiological damages disrupted reactive oxygen species and Ca2+ homeostasis at the cellular level, increasing cytosolic superoxide dismutase (23 %), catalase (35 %), and Ca2+ influx. Additionally, the disruption of Ca2+ homeostasis rarely reported in algicidal bacteria–algae interaction was observed using the non-invasive micro-test technology. We proposed a putative algicidal mechanism based on the algicidal outcomes and physiological algicidal effects and explored the potential of YB2 through an algicidal simulation test. Overall, this study is the first to report the algicidal bacterium P. fragi and identify a novel algicidal compound, 2-MECHD, providing new insights and a potent microbial resource for the biocontrol of HAB.

Microcystis abundance is predictable through ambient bacterial communities: A data-oriented approach

The number of cyanobacterial harmful algal blooms (cyanoHABs) has increased, leading to the widespread development of prediction models for cyanoHABs. Although bacteria interact closely with cyanobacteria and directly affect cyanoHABs occurrence, related modeling studies have rarely utilized microbial community data compared to environmental data such as water quality. In this study, we built a machine learning model, the multilayer perceptron (MLP), for the prediction of Microcystis dynamics using both bacterial community and weekly water quality data from the Daechung Reservoir and Nakdong River, South Korea. The modeling performance, indicated by the R2 value, improved to 0.97 in the model combining bacterial community data with environmental factors, compared to 0.78 in the model using only environmental factors. This underscores the importance of microbial communities in cyanoHABs prediction. Through the post-hoc analysis of the MLP models, we revealed that nitrogen sources played a more critical role than phosphorus sources in Microcystis blooms, whereas the bacterial amplicon sequence variants did not have significant differences in their contribution to each other. Similar to the MLP model results, bacterial data also had higher predictability in multiple linear regression (MLR) than environmental data. In both the MLP and MLR models, Microscillaceae showed the strongest association with Microcystis. This modeling approach provides a better understanding of the interactions between bacteria and cyanoHABs, facilitating the development of more accurate and reliable models for cyanoHABs prediction using ambient bacterial data.

Exploring the Green Tide Transport Mechanisms and Evaluating Leeway Coefficient Estimation via Moderate-Resolution Geostationary Images

The recurring occurrence of green tides as an ecological disaster has been reported annually in the Yellow Sea. While remote sensing technology effectively tracks the scale, extent, and duration of green tide outbreaks, there is limited research on the underlying driving mechanisms of green tide drift transport and the determination of the leeway coefficient. This study investigates the green tide transport mechanism and evaluates the feasibility of estimating the leeway coefficient by analyzing green tide drift velocities obtained from Geostationary Ocean Color Imager-II (GOCI-II) images using the maximum cross-correlation (MCC) technique and leeway method across various time intervals alongside ocean current and wind speed data. The results reveal the following: (1) Significant spatial variations in green tide movement, with a distinct boundary at 34°40′N. (2) Short-term green tide transport is primarily influenced by tidal forces, while wind and ocean currents, especially the combined Ekman and geostrophic current component, predominantly govern net transport. (3) Compared to 1, 3, and 7 h intervals, estimating the leeway coefficient with a 25 h interval is feasible for moderate-resolution geostationary images, yielding values consistent with previous studies. This study offers new insights into exploring the transport mechanisms of green tides through remote sensing-driven velocity.

Multi-scale feature extraction and TrasMLP encoder module for ocean HABs segmentation

Due to tiny edge and texture details of harmful algae blooms(HABs), existing segmentation networks are not effective for HABs segmentation. In order to solve the above problems, this paper proposes a Multi-scale Feature extraction and TrasMLP Encoder Fusion-based network (MFTS). To tackle the complex morphological characteristics and the complex backgrounds of HABs, a TrasMlp module which can effectively identify long-range patterns and adapt network parameters is introduced, enabling accurately parsing of complex algae images. Secondly, the deep convolution module is constructed by combining deep separable convolution with a two-channel attention mechanism to separate the target region from the background. In addition, this paper proposes a Weighted Feature Fusion of Deep Convolution and INRS Encoder Module classification network(FDIR) is proposed to quantify the performance of the image segmentation network. The segmentation results on HABs dataset from AICO Lab show that our proposed MFTS model achieves a miou of 90.02%, outperforming the performance of classical segmentation networks such as U-Net and Mask R-CNN. Compared to original HABs dataset, the segmented result shows a 5.1% improvement in the classification accuracy of the FDIR model.

The Use of Electrochemical Cells to Generate Nanobubbles As Innovative Agents for Alleviating Eutrophication in Aquatic Environments

Eutrophication, characterized by the excessive accumulation of nutrients, notably nitrogen and phosphorus, in aquatic environments, represents a growing concern in contemporary environmental science. Specifically, eutrophication is intricately associated with the proliferation of algae, giving rise to the development of dense populations known as algal blooms. Harmful Algal Blooms (HABs), primarily composed of cyanobacteria and green algae, pose a threat to aquatic ecosystems by diminishing water clarity, depleting oxygen levels, and, in certain instances, generating detrimental toxins. The global incidence of HABs is increasing, and their frequency is anticipated to further rise due to the impacts of climate change.Conventional methods of water management often encounter significant challenges in effectively addressing and mitigating occurrences of algae blooms. HAB present a multifaceted challenge, influenced by nutrient pollution, climate factors, and diverse algal species. The intricate interactions among these elements contribute to the complexity of the issue. Additionally, the varying responses of algae to environmental conditions and the potential toxicity of certain species further complicate mitigation efforts. To address this challenge effectively, a nuanced understanding of these interconnected factors is essential. Implementing targeted strategies for sustainable water management is crucial for mitigating the impact of algae blooms on aquatic ecosystems and human health.Nanobubble technology represents a revolutionary approach to gas exchange, generating ultrafine bubbles with distinctive properties. These bubbles, with diameters smaller than 1000 nm, are non-buoyant, negatively charged, and exhibit remarkable longevity. These attributes allow them to spontaneously form at the interface between solid surfaces and aqueous solutions. Moreover, their small size enhances mass transport at the electrode-electrolyte interface, impacting reaction rates and catalytic activity. These electrochemical properties position nanobubbles as promising candidates for applications in electrosynthesis, energy storage, and water treatment, with ongoing research aiming to further understand their intricate interplay in diverse electrochemical processes. Nanobubbles play a pivotal role in improving water quality by reducing surface tension, preventing the escape of gas molecules into the atmosphere. This action effectively enhances the concentration of dissolved oxygen in bodies of water. By mitigating the adverse effects of HABs, nanobubbles emerge as a transformative technology with the potential to revolutionize water management strategies.Our research entails a thorough investigation into the formation mechanisms and diverse applications of nanobubbles. The work presented here specialized focuses on nanobubble generation using electrochemical cells. We aim to present how nanobubbles are generated using customized and portable electrochemical cells and the unique properties of these generated nanobubbles. Preliminary results will also be presented to compare the nanobubbles generated using electrochemical cells to the nanobubbles generated using conventional approaches currently employed in the industry. By delving into the details of nanobubble formation, we seek to understand their effectiveness at addressing the challenges associated with eutrophication and HABs in aquatic environments. This comparative analysis will shed light on the advantages and limitations of generating nanobubbles using electrochemical cells in the context of restoration of bodies of water, offering valuable insights for future applications and guiding decisions in environmental management practices.

Seasonal and interannual variations of nutrients in the Subei Shoal and their implication for the world's largest green tide

The world's largest “green tide” (Ulva prolifera) has occurred every year since 2007 in the Yellow Sea. The Subei Shoal area is thought to be the origin of the green tide. Based on field data from 2016 to 2023, seasonal and interannual variations of dissolved nutrients and their ecological effects in the Subei Shoal were analyzed. Spatial distribution of dissolved inorganic nitrogen (DIN), dissolved inorganic phosphorus (DIP) and dissolved silicate (DSi) showed clear terrestrial sources, while ammonia (NH4-N) and dissolved organic nitrogen (DON) were not solely controlled by terrestrial sources. The seasonal variations of NH4-N, DIN, DON, DIP and DSi concentrations were significant, and the interannual variations of DIN, DON, DIP and DSi concentrations showed general decreasing trends from 2016 to 2023. The key factors affecting the seasonal and interannual variations of DIN and DIP concentrations were terrestrial input, aquaculture wastewater discharge, atmospheric deposition, submarine groundwater discharge and macroalgae absorption, while the dominant factor determining the variations of DSi concentrations was terrestrial input. NH4-N and DON concentrations were mainly influenced by aquaculture wastewater discharge and the absorption and release of macroalgae. The high nutrient concentrations in the Subei Shoal throughout the year provided sufficient material basis for the growth of Ulva prolifera in the source area of green tide outbreak.

(Invited) Probing the Reaction Microenvironment during Electrochemical Nitrate Reduction to Ammonia

Nitrate pollution of wastewater from agricultural runoff and industrial waste streams is common around the globe. Nitrate negatively impacts the environment through harmful algal blooms and can be dangerous for human consumption. Strict limits have been set on nitrate discharge and the concentration in drinking water (< 50 ppm). Nitrate is currently removed from water by conversion to nitrogen through a biological process that requires chemical inputs (e.g., methanol) and post-treatment to remove biomass and organics.Electrochemical reduction of nitrate (NO3RR) to ammonia can remove nitrate from water and is an alternative to Haber-Bosch (HB) ammonia production, a significant source of global CO2 emissions. Ammonia is an important chemical precursor with potential applications in sustainable energy as a fuel or H2 carrier, or can be used as a fertilizer in the form of ammonium sulfate. This research addresses the water–energy nexus by converting nitrate to a valuable product, off-setting the cost of water treatment, and reducing demand for HB.NO3RR can be done from small to large scales, use renewable electricity, and eliminate the need for expensive and hazardous chemicals. However, NO3RR processes must exhibit selectivity toward ammonia to avoid the formation of other undesired products and occur at a low overpotential to minimize operating costs from electricity. To address these challenges, we must understand the reaction environment at the electrode–electrolyte interface, where heterogeneous electrochemical reactions occur. We use in situ attenuated total reflectance–surface-enhanced infrared adsorption spectroscopy (ATR–SEIRAS) to investigate the adsorbed reactants, intermediates, and interfacial pH. We studied the repeatability of the technique for in situ interfacial pH measurement and recommend controls to the community when using this method. The ATR–SEIRAS results are correlated with electrochemical experiments measuring NO3RR selectivity, activity, and efficiency. NO3RR products are measured by ion chromatography and gas chromatography. Our results relate bulk electrolyte properties with interfacial properties, and interfacial properties with reaction activity and selectivity. This understanding could lead to the development of electrolyte engineering strategies to optimize ammonia production in electrochemical NO3RR.

Giant polyketide synthase enzymes in the biosynthesis of giant marine polyether toxins.

Prymnesium parvum are harmful haptophyte algae that cause massive environmental fish kills. Their polyketide polyether toxins, the prymnesins, are among the largest nonpolymeric compounds in nature and have biosynthetic origins that have remained enigmatic for more than 40 years. In this work, we report the "PKZILLAs," massive P. parvum polyketide synthase (PKS) genes that have evaded previous detection. PKZILLA-1 and -2 encode giant protein products of 4.7 and 3.2 megadaltons that have 140 and 99 enzyme domains. Their predicted polyene product matches the proposed pre-prymnesin precursor of the 90-carbon-backbone A-type prymnesins. We further characterize the variant PKZILLA-B1, which is responsible for the shorter B-type analog prymnesin-B1, from P. parvum RCC3426 and thus establish a general model of haptophyte polyether biosynthetic logic. This work expands expectations of genetic and enzymatic size limits in biology.

Dynamic disparities in inorganic nitrogen and phosphorus fluxes into estuarine systems under different flow regimes and streamflow droughts

Elongated periods of low flow conditions, which can be termed as streamflow droughts, influence the nutrient (e.g., nitrogen and phosphorus) balance in estuarine systems. Analyzing temporal trends of nutrient fluxes into such systems under different streamflow regimes can complement the understanding about the dynamic evolution of streamflow droughts and their impacts on nutrient levels. The objective of this paper was to evaluate how dynamic evolution of streamflow droughts (from low flow conditions) affects the inorganic nutrient flux in a tropical estuarine system. We analyzed a 20-year time series of streamflow data together with the concentrations of two nutrient parameters—dissolved inorganic phosphorus (DIP) and dissolved inorganic nitrogen (DIN)—in the Lower Apalachicola River that drains into Apalachicola Bay in northeastern Gulf of Mexico, Florida. Our findings revealed that droughts affect the seasonal patterns and fluxes of both DIP and DIN. We also observed post-drought flushing patterns in DIP and contrasting changes in DIP and DIN fluxes in the long-term (20 years here) under different streamflow conditions. Dynamically changing correlations between the streamflow and the fluxes were found throughout different phases of droughts. In the long-term (from 2003 to 2021), the DIP flux in high flows increased by 35.3%, while the flux decreased by 15.7% in low flows. Conversely, DIN flux in high flows showed a decrease of <1.2%, but an increase of <23.7% in low flows after droughts end. The insights from this study highlighted the need for effective regulation plans such as proper nutrient management against streamflow droughts to mitigate negative ecological consequences in estuarine systems such as harmful algal blooms.

Climate Change and Nitrogen Dynamics: Challenges and Strategies for a Sustainable Future

Global warming driven by climate change has profound impacts on nitrogen dynamics in terrestrial and aquatic ecosystems. The increased emissions of greenhouse gases alter the distribution and availability of nitrogen, which is a critical nutrient for all living organisms. This review examines the connections between climate change and nitrogen cycling, highlighting the adverse effects on ecosystem health and productivity. The proliferation of nitrogen pollution due to agricultural runoff, industrial effluents, and urban wastewater aggravates eutrophication, leading to significant environmental and economic consequences. The imbalance in nitrogen availability not only affects plant growth and soil fertility but also disrupts aquatic ecosystems, resulting in harmful algal blooms and hypoxic conditions. Effective mitigation and adaptation strategies are essential to addressing these challenges. Sustainable agricultural practices, such as precision farming and the use of slow-release fertilizers, along with robust policies and innovative technologies, like biochar application and nitrification inhibitors, are essential in managing nitrogen levels. This review underscores the importance of interdisciplinary approaches that involve integrating insights from ecology, agronomy, and the social sciences to develop comprehensive solutions. Future research should focus on long-term studies to assess the cumulative impacts of climatic changes on nitrogen availability and ecosystem health to guide policies and management practices for sustainable development.

Unlocking Biological Activity and Metabolomics Insights: Primary Screening of Cyanobacterial Biomass from a Tropical Reservoir.

Cyanobacterial harmful algal blooms can pose risks to ecosystems and human health worldwide due to their capacity to produce natural toxins. The potential dangers associated with numerous metabolites produced by cyanobacteria remain unknown. Only select classes of cyanopeptides have been extensively studied with the aim of yielding substantial evidence regarding their toxicity, resulting in their inclusion in risk management and water quality regulations. Information about exposure concentrations, co-occurrence, and toxic impacts of several cyanopeptides remains largely unexplored. We used liquid chromatography-mass spectrometry (LC-MS)-based metabolomic methods associated with chemometric tools (NP Analyst and Data Fusion-based Discovery), as well as an acute toxicity essay, in an innovative approach to evaluate the association of spectral signatures and biological activity from natural cyanobacterial biomass collected in a eutrophic reservoir in southeastern Brazil. Four classes of cyanopeptides were revealed through metabolomics: microcystins, microginins, aeruginosins, and cyanopeptolins. The bioinformatics tools showed high bioactivity correlation scores for compounds of the cyanopeptolin class (0.54), in addition to microcystins (0.54-0.58). These results emphasize the pressing need for a comprehensive evaluation of the (eco)toxicological risks associated with different cyanopeptides, considering their potential for exposure. Our study also demonstrated that the combined use of LC-MS/MS-based metabolomics and chemometric techniques for ecotoxicological research can offer a time-efficient strategy for mapping compounds with potential toxicological risk. Environ Toxicol Chem 2024;43:2222-2231. © 2024 SETAC.

First insights into the distribution and diversity of toxic dinoflagellate cysts in the surface sediments of Dakhla Bay (African Atlantic coast): relationships with environmental factors and mollusk intoxication events.

Dakhla Bay, situated on the African Atlantic coast, has witnessed sporadic harmful algal blooms (HABs) caused by toxic dinoflagellate species over the past two decades. In this study, we investigated the distribution, abundance, and diversity of dinoflagellate cysts, with a focus on potentially toxic species that develop in this ecosystem where such data are lacking. Sediment samples were collected in April 2018 through coring at 49 stations distributed across the bay. The highest abundance of dinoflagellate cysts was recorded at 304 cysts/g dry sediment, observed at the inner part of the bay, indicating that this area is the preferential zone for cyst accumulation. Pearson's tests revealed significant positive correlations (P < 0.05) between cyst abundance and the water content, organic matter, and fine fraction (< 63μm) of the sediment. Cyst morphotypes of potentially toxic dinoflagellate species known to produce saxitoxins, such as Alexandrium minutum, Alexandrium tamarense species complex, Gymnodinium catenatum, and yessotoxins, such as Lingulodinium polyedrum and Gonyaulax cf. spinifera, were identified in the sediment of Dakhla Bay. These findings were further supported by our long-term monitoring period (2005-2018), underscoring the presence of these HAB species in Dakhla Bay. During our survey, sporadic mollusk intoxication events were recorded at station PK25 for the grooved razor shell Solen marginatus and at station Boutelha for the oyster Crassostrea gigas. Paralytic shellfish toxin concentrations exceeded the sanitary threshold (80μg STX di-HCl eq/100g of shellfish meat) only twice, in December 2006 and January 2007 at station PK25. Contamination by amnesic shellfish toxins occurred sporadically but never reached the sanitary threshold of 20µg/g of shellfish meat. Lipophilic shellfish intoxication occurred multiple times in the two investigated areas. These observations suggest that the cysts of the identified HAB species germinated and inoculated the water column, resulting in the observed intoxication events. Relatively low levels of intoxication could be attributed to the moderate abundances of cysts, which may reduce the seeding capacity. This could be explained by the significant interaction of Dakhla Bay with the Atlantic Ocean, characterized by hydrological dynamics that impede the deposition and accumulation of cysts in the bay's sediments. This study reaffirms the importance of investigating dinoflagellate cysts in assessing the diversity of HAB species and evaluating associated sanitary risks.

Toxic effects of the emerging Alexandrium pseudogonyaulax (Dinophyceae) on multiple trophic levels of the pelagic food web

The dinoflagellate Alexandrium pseudogonyaulax, a harmful algal bloom species, is currently appearing in increasing frequency and abundance across Northern European waters, displacing other Alexandrium species. This mixotrophic alga produces goniodomins (GDs) and bioactive extracellular substances (BECs) that may pose a threat to coastal ecosystems and other marine resources. This study demonstrated the adverse effects of A. pseudogonyaulax on four marine trophic levels, including microalgae (Rhodomonas salina), microzooplankton (Polykrikos kofoidii) and mesozooplankton (Acartia tonsa), as well as fish gill cells (RTgill-W1, Oncorhynchus mykiss), ultimately leading to enhanced mortality and cell lysis. Furthermore, cell-free supernatants collected from A. pseudogonyaulax cultures caused complete loss of metabolic activity in the RTgill-W1 cell line, indicating ichthyotoxic properties, while all tested GDs were much less toxic. In addition, cell-free supernatants of A. pseudogonyaulax led to cell lysis of R. salina, while all tested GDs were non-lytic. Finally, reduced egg hatching rates of A. tonsa eggs exposed to cell-free supernatants of A. pseudogonyaulax and impaired mobility of P. kofoidii and A. tonsa exposed to A. pseudogonyaulax were also observed. Altogether, bioassay results suggest that the toxicity of A. pseudogonyaulax is mainly driven by BECs and not by GDs, although further research into factors modulating the lytic activity of Alexandrium spp. are needed.