Occurrence Of Harmful Algal Blooms Research Articles

Evaluation of metrics and thresholds for use in national-scale river harmful algal bloom assessments

The spatiotemporal distribution of harmful algal blooms (HABs) in rivers remains poorly understood, and there is an urgent need to develop a consistent set of metrics to better document HAB occurrences and forecast future events. Using data from seven sites in the Illinois River Basin, we computed metrics focused on HAB conditions related to excess algal growth and hypoxia. Daily mean chlorophyll and dissolved oxygen (DO) concentrations, gross primary productivity (GPP), and net ecosystem productivity (NEP) rates, focused on water quality status, identifying the timing of the transition from a clear-water to an algal dominated state. Early warning indicators (EWIs), the first-order autoregressive process (Ar1) and standard deviation (SD) of chlorophyll concentrations, focused on future events, forecasting blooms. Metrics were compared to either literature-derived or statistical-based thresholds and were normalized by total number of daily samples for an exceedance rate. Exceedances of a daily mean chlorophyll concentration averaged 50 % across all sites using a 10 µg L−1 threshold but increasing the threshold to 50 μg L−1 reduced the average exceedance rate to 5 %. The average exceedance rate for GPP (∼8 g O2 m2d−1 threshold) was 15 %, similar to the daily amplitude DO concentration (∼3 mg L−1 threshold), but the average for NEP (0 g O2 m2 d−1 threshold) was higher, at 28 %. The number of days with at least 1 continuous DO concentration below the threshold of 5, 3, or 2 mg L−1, had basin wide exceedance rates of 9 %, 3 %, and 2 %, respectively. Thresholds for EWIs, Ar1 and SD, were exceeded at 5 of the 7 sites with high chlorophyll concentrations and GPP rates. The correlation between proxies for algal biomass (chlorophyll concentration) and productivity (GPP) was strongest for sites in the middle region of the basin, with R2 values between 0.54 and 0.74. Although, cyanotoxin concentrations are the most commonly used metrics by states to define an inland water HAB, there is a paucity of publicly available data. The wider availability of chlorophyll and oxygen data combined with the results from this study suggest that biomass and productivity state and event-based metrics may be a promising way to assess and predict the vulnerability of rivers to some of the deleterious effects of HABs at broad spatial scales.

The rapid detection method of brown tide algae concentration based on unthresholded recurrence plots and improved broad learning system

In recent years, there have been frequent outbreaks of harmful algal blooms (HAB) in coastal areas, which have caused serious economic losses to the local community. Therefore, accurate and rapid prediction of microalgal concentrations is necessary for early warning and countermeasures before the occurrence of HAB. This paper presents a model for predicting microalgae concentration based on unthresholded recurrence plots (UTRPs) combined with an improved broad learning system (BLS). Spectral data acquisition of algae species at different concentrations using l-induced fluorescence spectroscopy. Then, the 1D spectral data are dimensionally lifted by UTRPs transformation, recurrence plots (RPs) transformation can fully extract the internal information of 1D sequence data, and at the same time, UTRPs avoids the influence of artificially selected thresholds on the feature transformation results of traditional (RPs). Finally, a lightweight flat network BLS was used for microalgae concentration regression prediction, at the same time the BLS regularization method was improved. When comparing the two most commonly used deep learning regression models and integrated learning models, UTRPs and elastic net (UTRPs-ENBLS) achieves convincing results.

Impact of typhoons on anthropogenic nitrogen sources in Lake Sihwa, South Korea

This study investigated the nitrate dual isotopic compositions (δ15NNO3 and δ18ONO3) of water samples to trace nitrate sources in Lake Sihwa, which encompasses various land-use types (e.g., urban, industry, wetland, and agriculture). The biogeochemical interactions of anthropogenic nitrogen sources (e.g., soil, road dust, and septic water) were also evaluated through multiple pathways from terrestrial boundaries to the water column. Based on increased concentrations of dissolved total nitrogen (DTN; 3.1 ± 1.6 mg/L) after typhoon, the variation of element stoichiometry (N:P:Si) in this system shifted to the relatively N-rich conditions (DIN/DIP; 14.1 ± 8.1, DIN/DSi; 1.4 ± 1.8), potentially triggering the occurrence of harmful algal blooms. Furthermore, discriminative isotopic compositions (δ15NNO3; 4.0 ± 2.1 ‰, δ18ONO3; 6.1 ± 4.3 ‰) after the typhoon suggested the increased DTN input of anthropogenic origins within Lake Sihwa would be mainly transported from urban sources (76 ± 9 %). Consequently, the isotopic-based approach may be useful for effective water quality management under increased anthropogenic activities near aquatic systems.

Impact of harmful algal bloom severity on bacterial communities in a full-scale biological filtration system for drinking water treatment

The occurrence of harmful algal blooms (HABs) in freshwater environments has been expanded worldwide with growing frequency and severity. HABs can pose a threat to public water supplies, raising concerns about safety of treated water. Many studies have provided valuable information about the impacts of HABs and management strategies on the early-stage treatment processes (e.g., pre-oxidation and coagulation/flocculation) in conventional drinking water treatment plants (DWTPs). However, the potential effect of HAB-impacted water in the granular media filtration has not been well studied. Biologically-active filters (BAFs), which are used in drinking water treatment and rely largely on bacterial community interactions, have not been examined during HABs in full-scale DWTPs. In this study, we assessed the bacterial community structure of BAFs, functional profiles, assembly processes, and bio-interactions in the community during both severe and mild HABs. Our findings indicate that bacterial diversity in BAFs significantly decreases during severe HABs due to the predominance of bloom-associated bacteria (e.g., Spingopyxis, Porphyrobacter, and Sphingomonas). The excitation-emission matrix combined with parallel factor analysis (EEM-PARAFAC) confirmed that filter influent affected by the severe HAB contained a higher portion of protein-like substances than filter influent samples during a mild bloom. In addition, BAF community functions showed increases in metabolisms associated with intracellular algal organic matter (AOM), such as lipids and amino acids, during severe HABs. Further ecological process and network analyses revealed that severe HAB, accompanied by the abundance of bloom-associated taxa and increased nutrient availability, led to not only strong stochastic processes in the assembly process, but also a bacterial community with lower complexity in BAFs. Overall, this study provides deeper insights into BAF bacterial community structure, function, and assembly in response to HABs.

Potentially toxigenic phytoplankton patterns in the northwestern Iberian Peninsula

The Galician estuaries are Europe’s foremost supplier of mussels, generating millions of euros annually and offering substantial employment opportunities for its population. One of the most critical threats to shellfish production is the occurrence of harmful algal blooms (HABs), contaminating bivalves with phytotoxins. To successfully tackle this problem, there needs to be a collaborative effort between the scientific community and decision-makers to establish a dynamic and effective monitoring system. This could enable early warnings and preventive actions to avert the loss of millions of tons of shellfish. Remote sensing, despite its limitations, requires commitment and effort by experts to devise effective methods for detecting target optical constituents mixed with other undesired target but that exhibit strong signals. Therefore, the essential necessity arises to identify approaches for mitigating the shortcomings of the undertaken efforts. The objective of this study is to assess the main environmental drivers of potential harmful genera (Pseudo-nitzschia, Dinophysis, Alexandrium, and Gymnodinium) in the Rías Baixas from 2015 to 2022, developing regression-based models and customizing Generalized Additive Models (GAMs) to investigate their spatial-temporal dynamics. Risk-susceptible bloom zones were identified in the river mouth of the Ría Pontevedra and from the center to offshore of the Ría Vigo. Early upwelling events triggered peaks in chlorophyll-a (Chl-a), driving Dinophysis grazing on phytoplankton communities mainly dominated by diatoms, flagellates, and ciliates. Subsequently, the upwelling intensity favoring Pseudo-nitzschia or Alexandrium minutum growth as larger diatoms declined. A. minutum exhibited elevated incidence over the past five years. Gymnodinium catenatum presented a rare occurrence across the three studied estuaries, which limited the assessment of its spatial dynamics in the region. This study emphasizes the need to integrate remote sensing evaluation of high-risk bloom areas (July to September), in-situ cell count collection, and enhanced efforts for forecasting future critical occurrences of HABs.

Phytoplankton optical fingerprint libraries for development of phytoplankton ocean color satellite products

Phytoplankton respond to physical and hydrographic forcing on time and space scales up to and including those relevant to climate change. Quantifying changes in phytoplankton communities over these scales is essential for predicting ocean food resources, occurrences of harmful algal blooms, and carbon and other elemental cycles, among other predictions. However, one of the best tools for quantifying phytoplankton communities across relevant time and space scales, ocean color sensors, is constrained by its own spectral capabilities and availability of adequately vetted and relevant optical models. To address this later shortcoming, greater than fifty strains of phytoplankton, from a range of taxonomic lineages, geographic locations, and time in culture, alone and in mixtures, were grown to exponential and/or stationary phase for determination of hyperspectral UV-VIS absorption coefficients, multi-angle and multi-spectral backscatter coefficients, volume scattering functions, particle size distributions, pigment content, and fluorescence. The aim of this publication is to share these measurements to expedite their utilization in the development of new optical models for the next generation of ocean color satellites.

Combined effects of spinetoram and Microcystis aeruginosa on Daphnia pulex offspring: Maternal effects and multigenerational implications

The increasing occurrence of harmful algal blooms (HABs) in freshwater ecosystems detrimentally affect global water environments. Zooplankton's role in controlling HABs is hindered by contaminant exposure, necessitating research into combined stressors' ecological impacts. The response of Daphnia, a freshwater keystone species, to environmental stressors can be influenced by its maternal effects. Here, we investigated the combined effects of the world-widely used insecticide spinetoram and non-toxic HABs species Microcystis aeruginosa on the life-history traits of D. pulex offspring produced from different maternal food conditions. Four maternal groups were established, with each group receiving a specific blend of C. vulgaris (Ch) and M. aeruginosa (Ma) in varying proportions: A (100% Ch), B (90% Ch + 10% Ma), C (80% Ch + 20% Ma), and D (70% Ch + 30% Ma). The offspring from the third brood were gathered, and a 21-day experiment was carried out, involving various feeding groups (AA, AD, BA, BB, CA, CC, DA, and DD). Results demonstrated that grazing on M. aeruginosa by D. pulex induced maternal effects on their offspring, with the continuous exposure group showing an enhanced tolerance to M. aeruginosa. This study also unveiled that spinetoram could interfere with the molting of D. pulex, leading to developmental retardation. The Recovery Group exhibited an intriguing phenomenon: under the influence of both concentrations of the pesticide spinetoram (0.18, 0.35 μg L−1), D. pulex produced more offspring. This might be due to a combined strategy of allocating more energy towards reproduction in response to low-quality food and a potential hormetic effect from low concentrations of spinetoram. Assessing the interplay of combined stressors across multiple generations, encompassing harmful algal blooms (HABs) and environmental pollutants, is essential for predicting population responses to evolving environmental conditions. This understanding is vital for the protection and management of aquatic environments and ecosystems.

Contamination Status and Acute Dietary Exposure Assessment of Paralytic Shellfish Toxins in Shellfish in the Dalian Area of the Yellow-Bohai Sea, China

The Yellow-Bohai Sea is an important semi-enclosed continental shelf marginal seas with an intensive aquaculture industry in China. The current study analyzed the contamination status and the time variations of paralytic shellfish toxins (PSTs) in shellfish between 2019 and 2020 from the Yellow-Bohai Sea in the Dalian area and estimated the acute health risks to consumers in China. A total of 199 shellfish samples (including 34 Pacific oysters, 25 Mediterranean blue mussels, 34 Manila clams, 36 bay scallops, 34 veined rapa whelks and 36 bloody clams) were analyzed from four representative aquaculture zones around the Yellow-Bohai Sea in Dalian. Among the samples, scallops and blood clams were the shellfish species with the highest detection rate of PSTs (94.4%), and the highest level of PSTs was detected in scallops with 3953.5 μg STX.2HCl eq./kg (μg STX.2HCL equivalents per kg shellfish tissue), followed by blood clams with 993.4 μg STX.2HCl eq./kg. The contents of PSTs in shellfish showed a time variation trend, and autumn was the season of concern for PST contamination in Dalian. For general Chinese consumers, the probability of acute health risks to shellfish consumers from dietary exposure to PSTs was around 13%. For typical consumers in coastal areas of China, especially those with higher shellfish intake, there was an acute health risk associated with exposure to PSTs through shellfish consumption during the occurrence of harmful algal blooms. It is suggested that the government continue to strengthen the monitoring of the source of PSTs and the monitoring of harmful algal blooms and give reasonable advice on shellfish consumption for consumers in coastal areas, such as not eating scallop viscera.

Hazard Zoning of Harmful Algal Bloom Disasters in Zhejiang Coastal Waters Using GIS: 1933-2021

The coastal waters of Zhejiang Province in China experience a high incidence of harmful algal blooms (HABs). It is therefore important to carry out hazard zoning to prevent and mitigate these HAB disasters. According to the historical record data of HAB disasters from 1933 to 2021, the frequency, duration, area and algal toxicity of HAB occurrences can be used as evaluation indicators. A method for hazard zoning of HAB disasters and a method for verifying the rationality of the zoning results are proposed. The hazard zoning results of HAB disasters in the coastal waters of Zhejiang from 1933 to 2021 (H1933-2021) show that very-high hazard degree areas of coastal waters of Zhejiang Province were found in Shengshan waters, the eastern waters of Zhujiajian and Nanji Islands' waters. Due to the influence of marine environmental factors, the spatial distribution of hazard degree of HAB disasters is dynamic, so it is recommended that the hazard zoning of HAB disasters be carried out once every five years. The rationality of the zoning results from 2017 to 2021 is verified, showing that the hazard zoning method of HAB disasters proposed in this study has a good rationality and credibility. This study utilized a qualitative approach to visually identify the spatial distribution of hazard degree zoning of HAB disasters in the Zhejiang Province coastal waters over the last 88 years. This has provided useful information to help prevent and mitigate HAB disasters and guide mariculture and coastal tourism planning.

Organic nutrient availability and extracellular enzyme activities influence harmful algal bloom proliferation in a coastal aquaculture area

Small-scale but highly destructive harmful algal blooms (HABs) are increasingly observed in coastal aquaculture areas. However, the impact of elevated organic nutrients generated during mariculture production and their bioavailability for HABs are not yet fully understood. This study investigated the population dynamics of HAB-causing species and the hydrolytic dynamics of different extracellular enzyme activities (EEAs) along with variations in environmental inorganic and organic nutrients during a dinoflagellate bloom of Prorocentrum shikokuense adjacent to the coastal aquaculture area in Sansha Town, located in the East China Sea. The results indicated that both inorganic and organic nutrients were enriched in the study area, with organic nutrients comprising more than half of the total nutrient content. The presence of enriched organic nutrients and a high N:P ratio significantly contributed to bloom occurrence. Organic nutrient concentrations played a predominant role in controlling both the density and duration of the P. shikokuense bloom. The significant increase in EEAs during the bloom stages, primarily contributed by P. shikokuense, emphasized the crucial hydrolytic role of extracellular enzymes in nutrient recycling and supply for the bloom. The enzymatic kinetic parameters indicated enhanced efficiency in the recycling of organic nutrients as the bloom progressed. This study highlights the significant role of organic nutrients facilitated by EEAs in determining the occurrence, duration, and magnitude of HABs in coastal aquaculture areas.

The double heterostructure photocatalyst MoS2@ZIF-67/TiO2: Triumphant modification of TiO2 and efficient removal of Karenia mikimotoi

Water eutrophication led to the occurrence of harmful algal blooms (HABs) with the increase of urban sewage and industrial wastewater. As a periodic ecological disaster, it caused serious harm to the ecological environment (including the destruction of the food chain and the death of animals, etc.) and human health. Karenia mikimotoi (K. mikimotoi) was a kind of common algae that caused red tides, and it could produce harmful toxins. Therefore, a composite photocatalyst MoS2@ZIF-67/TiO2 (MZ/T) for the inactivation of K. mikimotoi was synthesized by a simple and easy-to-operate hydrothermal synthesis method. The MoS2@ZIF-67 nanoflowers were attached by the grainy TiO2. The composite photocatalyst MZ/T showed excellent photocatalytic performance, and the inactivation efficiency of MZ/T was up to 97.2 % in 4 h and 99.45 % in 12 h. The composite photocatalyst MZ/T could inactivate algal cells by destroying cell membrane structure, reducing chlorophyll content, soluble protein content. This study would provide a novel photocatalyst for water treatment of HABs.

Machine Learning-Based Early Warning Level Prediction for Cyanobacterial Blooms Using Environmental Variable Selection and Data Resampling.

Many countries have attempted to mitigate and manage issues related to harmful algal blooms (HABs) by monitoring and predicting their occurrence. The infrequency and duration of HABs occurrence pose the challenge of data imbalance when constructing machine learning models for their prediction. Furthermore, the appropriate selection of input variables is a significant issue because of the complexities between the input and output variables. Therefore, the objective of this study was to improve the predictive performance of HABs using feature selection and data resampling. Data resampling was used to address the imbalance in the minority class data. Two machine learning models were constructed to predict algal alert levels using 10 years of meteorological, hydrodynamic, and water quality data. The improvement in model accuracy due to changes in resampling methods was more noticeable than the improvement in model accuracy due to changes in feature selection methods. Models constructed using combinations of original and synthetic data across all resampling methods demonstrated higher prediction performance for the caution level (L-1) and warning level (L-2) than models constructed using the original data. In particular, the optimal artificial neural network and random forest models constructed using combinations of original and synthetic data showed significantly improved prediction accuracy for L-1 and L-2, representing the transition from normal to bloom formation states in the training and testing steps. The test results of the optimal RF model using the original data indicated prediction accuracies of 98.8% for L0, 50.0% for L1, and 50.0% for L2. In contrast, the optimal random forest model using the Synthetic Minority Oversampling Technique-Edited Nearest Neighbor (ENN) sampling method achieved accuracies of 85.0% for L0, 85.7% for L1, and 100% for L2. Therefore, applying synthetic data can address the imbalance in the observed data and improve the detection performance of machine learning models. Reliable predictions using improved models can support the design of management practices to mitigate HABs in reservoirs and ultimately ensure safe and clean water resources.

Development and Application of an Integrated System for the Detection and Prediction of Harmful Algal Blooms in Korea

Harmful algal blooms (HABs) are types of phytoplankton overgrowth that adversely affect marine ecosystems and aquaculture resources. One such HAB species, Cochlodinium polykrikoides, occurs irregularly and causes significant damage to the aquaculture industry along the coastal regions of Korea. In this study, we developed and implemented an integrated system to detect and predict HAB occurrences in real time. This system comprises four main components: (1) a real-time detection system utilizing acoustic sensing, ocean weather, water temperature, salinity, and chlorophyll, satellite images, genetic analysis, and optics; (2) a prediction model system based on current and tidal, HAB occurrence, and HAB movement and diffusion models; (3) an additional data based on HAB information of sampling data and HAB information of GPS data, and (4) an integrated information system utilizing data storage servers and a visualization platform. We applied and assessed the efficiency of this integrated system in the South Sea of Korea from 2017 to 2019. Particularly, HABs occurred significantly in 2019, and the system demonstrated the feasibility of detection and prediction under field conditions. Implementing a more advanced integrated detection and prediction system in the field is anticipated to minimize the damage caused by irregular HAB occurrences every year.

Phytoplankton metabolism in a stratified nearshore ecosystem with recurrent harmful algal blooms (HABs)

Abstract The coastal ocean is experiencing changes in its physical and chemical properties that strongly affect planktonic metabolism assemblages and, in some cases, favor the occurrence of harmful algal blooms (HABs). Here we analyze the variations in phytoplankton biomass, gross and net primary production (NCP) as well as community respiration (CR) at two nearshore sampling sites (P1 and P2) located at a Mediterranean beach where high biomass HABs are recurrent. At P1, the most exposed site, phytoplankton chlorophyll was generally low, whereas dinoflagellates outbreaks of the genus Gymnodinium and Alexandrium were recurrent during summer at P2 spanning for 10–20 days. During bloom episodes, NCP increased up to 10-fold (>80 mmol O2 m−3 day−1). Contrastingly, variation in CR only reached an average of 1.8-fold the rates of non-bloom conditions. Remarkably, although the enhanced NCP:CR ratio suggests net autotrophic population growth, production per unit biomass at P1 and P2 was not significantly different. Our results indicate that although summer conditions favor the necessary primary production enhancement leading to HAB occurrences, the short-term dynamics driving high biomass episodes are not driven by metabolic variations but instead are governed by subtle accumulative processes of some flagellate species in the nutrient-rich nearshore environment.

Studying Conditions of Intense Harmful Algal Blooms Based on Long-Term Satellite Data

Harmful algal blooms (HABs) adversely impact aquatic organisms, human health, and the marine economy. The need to understand the origins and mechanisms of HAB occurrence and development determines the relevance of the study of these phenomena, including using remote sensing methods and assets. Here we present the results of a comprehensive study of conditions and precursors of some intense HABs detected in the water areas near the island of Chiloe (Chile, 2016), near the Kamchatka Peninsula (Russia, 2020), near the island of Hokkaido (Japan, 2021), among others. The study involves statistical analysis of long-term satellite and model data arrays on significant parameters of the marine environment and near-surface atmosphere, as well as empirical modeling of HAB risks. Information products on the following environmental parameters were used: sea surface temperature (SST, NOAA OISST, since 1981), the level of photosynthetically active radiation (PAR) and chlorophyll-a concentration (MODIS Ocean Color SMI, since 2000), sea surface salinity and height (HYCOM, since 1993), and near-surface wind speed and direction (NCEP CFSv2, since 1979). Quantitative assessments of the dynamics of informative criteria were applied. The key criterion is the ratio (Δσ) of the absolute deviation of the studied parameter from the expected norm to the RMS deviation of its values. Intense HABs were often preceded by excessive SST (up to Δσ ~1.99) and PAR (up to Δσ ~2.25) values, as well as low near-surface wind speed (up to Δσ ~−1.83). These environmental parameters considerably contribute to HAB generation and intensification. An approach and empirical function were proposed that allow us to assess the risk of HAB phenomena and reveal their precursors. Using the proposed approach and empirical function, the precursors of ten HABs were identified, nine of which were confirmed by in situ data. The results can be used as a tool for forecasting and studying the conditions for the occurrence of HABs, representing one of the promising directions for monitoring these dangerous phenomena.

Metabolomics and lipidomics reveal the effects of the toxic dinoflagellate Alexandrium catenella on immune cells of the blue mussel, Mytilus edulis

The increasing occurrence of harmful algal blooms, mostly of the dinoflagellate Alexandrium catenella in Canada, profoundly disrupts mussel aquaculture. These filter-feeding shellfish feed on A. catenella and accumulate paralytic shellfish toxins, such as saxitoxin, in tissues, making them unsafe for human consumption. Algal toxins also have detrimental effects upon several physiological functions in mussels, but particularly on the activity of hemocytes – the mussel immune cells. The objective of this work was to determine the effects of experimental exposure to A. catenella upon hemocyte metabolism and activity in the blue mussel, Mytilus edulis. To do so, mussels were exposed to cultures of the toxic dinoflagellate A. catenella for 120 h. The resulting mussel saxitoxin load had measurable effects upon survival of hemocytes and induced a stress response measured as increased ROS production. The neutral lipid fraction of mussel hemocytes decreased two-fold, suggesting a differential use of lipids. Metabolomic 1H nuclear magnetic resonance (NMR) analysis showed that A. catenella modified the energy metabolism of hemocytes as well as hemocyte osmolyte composition. The modified energy metabolism was reenforced by contrasting plasma metabolomes between control and exposed mussels, suggesting that the blue mussel may reduce feed assimilation when exposed to A. catenella.

Weak local upwelling may elevate the risks of harmful algal blooms and hypoxia in shallow waters during the warm season

Harmful algal blooms (HABs) and hypoxia, as common ecological disasters, are typically site-specific and recurrent, causing enduring environmental problems for coastal communities. Although these issues are often attributed to coastal eutrophication, in certain low-nutrient areas, such ecological disasters still frequently occur while the underlying cause is poorly understood. A prime example is the Qinhuangdao coastal waters in North China. This study intends to investigate the controlling factors of such incongruous ecological issues recurring in those low-nutrient areas with a case study of Qinhuangdao, utilizing numerical models and satellite observations. The result indicates that the weak tide-induced upwelling during summer creates favorable conditions (warm water with high transparency) for the occurrence of HABs and hypoxia in this region. It is due to that Qinhuangdao is precisely situated at the current amphidromic point of semi-diurnal tides, characterized by weak tide mixing. Likewise, the same story happens on the northern shelf of the Shandong Peninsula, where ecological problems are also prominent in China. The present study implies that shallow waters with weak local upwelling are susceptible to ecological issues during the warm season. This finding challenges the traditional view that strong-upwelling zones are more vulnerable to ecological disasters due to ample nutrient supply within the euphotic layer. It implies that tidal dynamics can greatly affect the vulnerability of coastal waters to ecological issues, which can be of significance to coastal management. Furthermore, the finding may have broader global applicability, given the ubiquity of tide-induced upwelling in various other coastal regions.

Occurrence of Harmful Algal Blooms in Freshwater Sources of Mindu and Nyumba ya Mungu Dams, Tanzania.

Harmful algal blooms (HABs) pose a significant threat to aquatic ecosystems and human health due to the production of toxins. The identification and quantification of these toxins are crucial for water quality management decisions. This study used DNA analysis (PCR techniques) to identify toxin-producing strains and liquid-chromatography-tandem mass spectrometry (LC-MS/MS) to quantify microcystins in samples from Mindu and Nyumba ya Mungu Dams in Tanzania. The results showed that HABs were detected in both dams. The BLAST results revealed that the 16S gene sequences of uncultured samples were very similar to an Antarctic cyanobacterium, Leptolyngbya sp, Anabaena sp, and Microcystis aeruginosa. Sequences of the cultured samples were most similar to Nodularia spumigena, Amazoninema brasiliense, Anabaena sp, and Microcystis aeruginosa. Further analyses showed that the nucleotide sequence similarity of uncultured isolates from this study and those from the GenBank ranged from 85 to 100%. For cultured isolates from this study and others from the GenBank, nucleotide identity ranged from 81 to 100%. The molecular identification of Microcystis aeruginosa confirmed the presence of HABs in both Mindu and Nyumba ya Mungu Dams in Tanzania. At Mindu Dam, the mean concentrations (± standard deviation) of microcystin-LR, -RR, and -YR were 1.08 ± 0.749 ppm, 0.120 ± 0.0211 ppm, and 1.37 ± 0.862 ppm, respectively. Similarly, at Nyumba ya Mungu Dam, the concentrations of microcystin-LR, -RR, and -YR were 1.07 ± 0.499 ppm, 0.124 ± 0.0224 ppm, and 0.961 ± 0.408 ppm, respectively. This paper represents the first application of PCR and LC-MS/MS to study microcystins in small freshwater reservoirs in Tanzania. This study confirms the presence of toxin-producing strains of Microcystis aeruginosa in both dams and also provides evidence of the occurrence of microcystins from these strains. These findings contribute in improving the monitoring of HABs contamination and their potential impact on water quality in Tanzanian reservoirs.

Phosphorus and Lake Eutrophication: Recent Findings and Emerging Challenges

This presentation reviews some recent and ongoing research on phosphorus (P) cycling in a variety of lake systems. Phosphorus is an essential nutrient element, and its anthropogenic enrichment is generally considered to be the main driver of cultural eutrophication of freshwater lakes, which, in the worst case, leads to the occurrence of harmful algal blooms, the intensification of hypoxia and the die-off of aquatic life. The research presented shows that excess external P loading causes the accumulation of reactive chemical P forms in the bottom sediments of lakes (Update #1). The slow release of this reactive legacy P back to the water column can significantly delay a lake’s recovery following the reduction of external P loading (Update #2). Land use changes accompanying agricultural intensification and urbanization generally increase P emissions, but the implementation of agricultural and stormwater best management practices can effectively mitigate external P loads to receiving lakes (Update #3). However, additional stressors, including climate change and salinization, magnify in-lake P mobilization pathways and, hence, increase the risks of lake (re-)eutrophication (Update #4).

Potential geographical distribution of harmful algal blooms caused by the toxic dinoflagellate Karenia mikimotoi in the China Sea

The fish-killing dinoflagellate Karenia mikimotoi frequently blooms in China and poses a threat to food safety and human health. To better understand harmful algal blooms (HABs) caused by K. mikimotoi and predict the risk of HABs under climate change, the combined effect of nitrate and norfloxacin (NOR) on the growth of K. mikimotoi was tested. A growth model was used to test the effects of nutrients and pollutants on the carrying capacity of the unicellular algae. The carrying capacity increased with increasing concentrations of nitrate and NOR, reaching a maximum at 62.2 μmol L−1 of nitrate and 9.03 mg L−1 of NOR. The calculated carrying capacity of K. mikimotoi in the China Sea showed a declining trend from nearshore to offshore, with a value >30 × 106 cells L−1 in the estuary of the Changjiang River and Hangzhou Bay. The HAB index proposed in this study as a measurement of HAB risk was constructed using the carrying capacity and relative abundance from the MaxEnt (maximum entropy) model. The index showed that HABs caused by K. mikimotoi consecutively occurred in Zhejiang and Fujian coastal waters and predicted that they will continue until 2100, regardless of the greenhouse gas emission scenario. The center of the integrated area moved northward, with a range of 120–900 km. The HAB index integrates the characteristics of the carrying capacity and suitability of habitats, and expresses the information contained in the intensive and extensive variables that affect HAB occurrence. This index is a promising predictor of HAB risk in coastal waters.