Harmful Algal Blooms Research Articles

Microbial community diversity during algal inhibition using slow-release microcapsules of tea polyphenols

Harmful algal blooms (HABs) resulting from eutrophication pose a major threat to ecosystems and human health, necessitating effective control measures. Allelochemicals have shown their importance in slowing down algal proliferation due to their proven efficacy and low ecological impacts. In this study, allelopathy tea polyphenols (TPs) and β-cyclodextrin were combined to prepare slow-release algicidal microcapsules, and the diversity of microbial community in the algal inhibition process was analyzed. Results showed that TP slow-release microcapsules had strong algicidal activity. When against Microcystis aeruginosa within 20 d, their constant inhibitory rate was up to 99% compared to the control group. Microbial diversity decreased with an increase in algae density, and the species richness and diversity of algae increased under the stress of TP slow-release microcapsules. The redundancy analysis showed that the environmental factors with impacts on the abundance and diversity of bacterial communities in descending order were dissolved oxygen, pH, and temperature. This study provides a theoretical basis for the application of TP slow-release microcapsules to actual water.

From micro to mesoscale: Understanding the influence of macroalgal communities on Ostreopsis Schmidt blooms

Harmful Algal Blooms (HABs) are increasing in temperate areas, and the growth rates of benthic harmful dinoflagellates may be favoured in the context of global climate change. Benthic dinoflagellates, including species belonging to the Ostreopsis Schmidt genus, are known to develop on the surface of macroalgae and different macroalgal morphotypes and communities could host higher or lower cell abundances. The physical structure of the macroalgal substrate at the small scale (cm, microhabitat scale) and the structural complexity of the macroalgal community at the medium scale (few m, mesohabitat scale) could play a relevant role in bloom facilitation: the hypothesis that Ostreopsis species could be associated with macroalgal turfs and shrubs, structurally less complex communities than canopy-forming macroalgae, is especially under discussion and, if confirmed, could link bloom occurrence to regime shifts in temperate ecosystems. The present study, performed in two locations of the Ligurian Sea (Rochambeau, France and Vernazzola, Italy) aimed at understanding marine vegetation's role at the micro and mesohabitat scales in controlling the distribution and abundance of Ostreopsis. The abundance of the microalgal cells was quantified at different spatial scales, from cm to a few m, on different macroalgal species and communities, including artificial substrates, to tease apart the micro and mesohabitat effects. The results obtained show a high spatio-temporal variability, potentially hiding habitat-related patterns. The substrate's preferences diminish when cell abundances are very high, as in the case of Rochambeau, while in presence of moderate cell abundances as in Vernazzola or the first phases of blooms, it is possible to appreciate differences in abundances among substrates (in our study, Dictyota fasciola (Roth) Lamouroux supporting higher abundances). Our results open new research topics such as the study of blooms at a larger scale (macrohabitat) and testing different sampling methods to standardise the cells' abundances independently on the substrate.

Distribution of Ulva macroalgae before and after the outbreak of the Yellow Sea green tide in aquaculture ponds and rivers nearshore Jiangsu, China

Green tide caused by the extensive proliferation of Ulva macroalgae in the Yellow Sea has been continuously occurring for 17 years. Previous studies indicate the Neopyropia aquaculture area in Jiangsu to be the main source of green tides in the Southern Yellow Sea. However, whether there are additional supplementary sources for the green tide in the Yellow Sea remains to be studied. This study conducted sampling of Ulva macroalgae in 14 aquaculture ponds and rivers nearshore Jiangsu in February and November in 2022. The molecular biology identification of samples through ITS and 5S indicates that the Ulva macroalgae in aquaculture ponds and rivers are composed of Ulva prolifera, Ulva linza, Ulva simplex, Ulva torta, Ulva flexuosa, and Ulva meridionalis. The results of micropropagules indicate that the abundance of micropropagules in aquaculture ponds is significantly higher than in rivers. In both February and November, the points with the highest abundance of micropropagules were located in aquaculture ponds, reaching 2090 inds L−1 and891 inds L−1, respectively. This study found that before and after the outbreak of green tide, the dominant species of green tide outbreak,5S-II U. prolifera,existed in aquaculture ponds and rivers nearshore Jiangsu. 5S-II U. prolifera in aquaculture ponds and rivers may have a potential impact on the outbreak of green tide in the Yellow Sea.

An investigation of cyanobacteria, cyanotoxins and environmental variables in selected drinking water treatment plants in New Jersey

Harmful Algal Blooms (HAB) have the potential to impact human health primarily through their possible cyanotoxins production. While conventional water treatments can result in the removal of unlysed cyanobacterial cells and low levels of cyanotoxins, during severe HAB events, cyanotoxins can break through and can be present in the treated water due to a lack of adequate toxin treatment. The objectives of this study were to assess the HAB conditions in drinking water sources in New Jersey and investigate relationships between environmental variables and cyanobacterial communities in these drinking water sources. Source water samples were collected monthly from May to October 2019 and analyzed for phytoplankton and cyanobacterial cell densities, microcystins, cylindrospermopsin, Microcystis 16S rRNA gene, microcystin-producing mcyB gene, Raphidiopsis raciborskii-specific rpoC1 gene, and cylindrospermopsin-producing pks gene. Water quality parameters included water temperature, pH, dissolved oxygen, specific conductance, fluorescence of phycocyanin and chlorophyll, chlorophyll-a, total suspended solids, total dissolved solids, dissolved organic carbon, total nitrogen, ammonia, and total phosphorus. In addition to source waters, microcystins and cylindrospermopsin were analyzed for treated waters. The results showed all five selected New Jersey source waters had high total phosphorus concentrations that exceeded the established New Jersey Surface Water Quality Standards for lakes and rivers. Commonly found cyanobacteria were identified, such as Microcystis and Dolichospermum. Site E was the site most susceptible to HABs with significantly greater HAB variables, such as extracted phycocyanin, fluorescence of phycocyanin, cyanobacterial cell density, microcystins, and Microcystis 16S rRNA gene. All treated waters were undetected with microcystins, indicating treatment processes were effective at removing toxins from source waters. Results also showed that phycocyanin values had a significantly positive relationship with microcystin concentration, copies of Microcystis 16S rRNA and microcystin-producing mcyB genes, suggesting these values can be used as a proxy for HAB monitoring. This study suggests that drinking water sources in New Jersey are vulnerable to forthcoming HAB. Monitoring and management of source waters is crucial to help safeguard public health.

Changes in the limiting nutrients and dominant phytoplankton communities of three major European rivers: Response to catchment lithologies and human activities

Catchment lithologies and human activities can cause variations in riverine carbon (C), nitrogen (N), and phosphorus (P) loads, and the ratio of these nutrients may affect the primary productivity of rivers and their phytoplankton communities. We conducted a comparative study of biogeochemical variations in three major European rivers—the Rhine, Danube, and Seine—which reveals the impacts of different carbonate outcrops and human impacts (agricultural activities and sewage input) on the changes in the limiting nutrients and phytoplankton community compositions of flowing water systems. N limitation was observed in the Rhine and Danube owing to their low average NO3– loads (4.04–6.45 mg/L). Although the extensive outcrops of carbonate rocks in the Seine catchment result in high average HCO3– concentrations of ∼ 4.68 mmol/L, the elevated inorganic C input did not match the high average NO3– loads (∼19.38 mg/L), driven by intensive agricultural activity and urban sewage input, demonstrating a potential C limitation on productivity. Our results show that the productivity of the Seine River, determined by the chlorophyll-a concentration, was significantly related to the dissolved inorganic carbon (DIC) concentration (coefficient of determination: R2 = 0.68, P < 0.05). Our results demonstrate that changes in DIC content can significantly alter the dominant phytoplankton species in the water column. The high inputs of DIC and aqueous CO2(aq) to the Seine lead to Bacillariophyta proportions that are 3.96–8.81 % and 19.87–22.56 % higher than those of the Rhine and Danube in the wet and dry seasons, respectively. This can be explained by the difference in the efficiency of carbon concentrating mechanisms (CCMs) among phytoplankton species. Therefore, to mitigate river eutrophication and improve the quality of the aquatic environment, we suggest that future water–carbon management in the flowing water systems with abundant nutrients should consider C-limitation alleviation and its potential effect for reducing the abundance of harmful algae.

From genes to toxins: Profiling Prymnesium parvum during a riverine harmful algal bloom

Blooms of Prymnesium parvum, a unicellular alga globally distributed in marine and brackish environments, frequently result in massive fish kills due to the production of toxins called prymnesins by this haptophyte. In August 2022, a harmful algal bloom (HAB) of this species occurred in the lower Oder River (Poland and Germany), which caused mass mortalities of fish and other organisms. This HAB was linked to low discharge of the Oder and mining activities that caused a significant increase in salinity. In this context, we report on the molecular detection and screening of this haptophyte and its toxins in environmental samples and clonal cultures derived thereof. Both conventional PCR and droplet digital PCR assays reliably detected P. parvum in environmental samples. eDNA metabarcoding using the V4 region of the 18S rRNA gene revealed a single Prymnesium sequence variant, but failed to identify it to species level. Four clonal cultures established from environmental samples were unambiguously identified as P. parvum by molecular phylogenetics (near full-length 18S rRNA gene) and light microscopy. Phylogenetic analysis (ITS1–5.8S-ITS2 marker region) placed the cultured phylotype within a clade containing other P. parvum strains known to produce B-type prymnesins. Toxin-screening of the cultures using liquid chromatography-electrospray ionization - time of flight mass spectrometry identified B-type prymnesins, which were also detected in extracts of filter residues from water samples of the Oder collected during the HAB. Overall, our investigation provides a detailed characterization of P. parvum, including their prymnesins, during this HAB in the Oder River, contributing valuable insights into this ecological disaster. In addition, the droplet digital PCR assay established here will be useful for future monitoring of low levels of P. parvum on the Oder River or any other salt-impacted and brackish water bodies.

Diversity and biogeography of dinoflagellates in the Kuroshio region revealed by 18S rRNA metabarcoding

Dinoflagellate is one of the most diverse and pervasive protists and a fundamental player in the marine food web dynamics and biogeochemical cycles. While possessing different nutritional strategies from purely autotrophy or heterotrophy to mixotrophy, some of them are also known as toxic harmful algal bloom (HAB) formers over the world. Despite their ordinariness, their diversity and biogeography are understudied in the open ocean compared with coastal region. As the first metabarcoding survey covering the Kuroshio current region from the offshore of Okinawa to the south of Honshu, we investigated the distribution of free-living dinoflagellates using the hypervariable V4 and V9 regions on 18S rRNA and their relation to ambient environments influenced by this oligotrophic but highly productive current in the northwest Pacific Ocean. We observed community structures differentiated by depth and nutrient concentrations. Most species annotated are autotrophic or mixotrophic and had a distribution correlated to warmer surface water, whereas heterotrophic species correlated to high nutrient levels or deeper layer. Our results also confirmed the overall high genetic diversity of dinoflagellates that decreased with depth and onshore. Most species present at stations offshore, and the relative abundance of HAB assemblages was lower at nutrient-rich stations on the continental shelf than stations influenced by the Kuroshio current, exhibiting the role of the Kuroshio transporting dinoflagellates including HAB species. To fully understand the dynamics of dinoflagellate communities in marine ecosystems, further seasonal monitoring is foremost for correlating dinoflagellates and environmental factors while completing the reference genomic database.

Multi-source remote sensing big data mining reveals cross-regional correlation between aquaculture and Enteromorpha disaster outbreaks

ABSTRACT Marine aquaculture is one of the most important marine resource utilization types, widely distributed in seashore areas. Because mass marine aquaculture development will lead to the eutrophication disaster of macroalgae blooms (green tide), it is imperative to discover the latent relationship. Inspired by the big data analysis theory, the spatiotemporal correlation change in 2017 and 2019 of the marine aquaculture and macroalgae blooms in Jiangsu Shoal in the West of the Yellow Sea and its adjacent seas were monitored and extracted respectively based on multi-source remote sensing images. Through optical and Synthetic Aperture Radar (SAR) images, the imaging characteristics of marine aquaculture in different growth cycles and sea conditions are analyzed. The relationship between the green tide and marine aquaculture harvest was explored from the early green algae distribution and spatiotemporal distribution changes. The earliest harvest area of marine aquaculture is the exact location of the outbreak of green tide. Along with the rapid reduction of aquaculture area, the distribution range of green tide gradually increased. The two showed opposite trends through many multi-source remote sensing data statistical analyses. Therefore, they have a strong correlation, which can be utilized to offer a significant value for the balance of marine environmental protection and resource development.

Five Karenia species along the Chinese coast: With the description of a new species, Karenia hui sp. nov. (Kareniaceae, Dinophyta)

Dinoflagellates within the genus Karenia are well known for their potential to cause harmful algal blooms and induce detrimental ecological consequences. In this study, five Karenia species, Karenia longicanalis, Karenia papilionacea, Karenia mikimotoi, Karenia selliformis, and a new species, Karenia hui sp. nov., were isolated from Chinese coastal waters. The new species exhibits the typical characteristics of the genus Karenia, including a linear apical groove and butanoyl-oxyfucoxanthin as the major accessory pigment. It is distinguished from the other Karenia species by a wide-open sulcal intrusion onto the epicone, a conical epicone with an apical crest formed by the rim of the apical groove, and a hunchbacked hypocone. It is most closely related to Karenia cristata, with a genetic divergence of 3.16 % (22 bp out of 883 bp of LSU rDNA). Acute toxicity tests indicated that the five Karenia species from China are all toxic to marine medaka Oryzias melastigma. Karenia selliformis and K. hui were very toxic to O. melastigma, resulting in 100 % mortality within 4 h and 24 h, respectively. Further analysis by high-performance liquid chromatography revealed that four species, K. selliformis, K. longicanalis, K. papilionacea and K. mikimotoi were capable of producing Gymnodimine-A (GYM-A). The highest GYM-A content was in K. selliformis (strain HK-43), in which the value was 889 fg/cell. No GYM-A was detected in the new species K. hui, however and its toxin remains unknown. Below we provide a comprehensive report of the morphology, phylogeny, pigment composition, and toxicity profiles of Karenia species along the Chinese coast. These findings contribute new insights for monitoring of Karenia species, with important toxicological and ecological implications.

Insights into how characteristics of dissolved algal organic matter affect the efficiency of modified clay in controlling harmful algal blooms

Dissolved algal organic matter (dAOM) originating from harmful algal blooms (HABs) can deteriorate the quality of municipal water supplies, threaten the health of aquatic environments, and interfere with modified clay (MC)-based HABs control measures. In this study, we explored the composition of dAOM from Prorocentrum donghaiense, a typical HAB organism, and assessed the influence of dAOM on MC flocculation. Our results suggested that dAOM composition was complex and had a wide molecular weight (MW) distribution. MW and electrical properties were important dAOM characteristics affecting flocculation and algal removal efficiency of MC. Negatively charged high-MW components (>50 kDa) critically affected algal removal efficiency, reducing the zeta potential of MC particles and leading to small and weak flocs. However, the effect of dAOM depended on its concentration. When the cell density of P. donghaiense reached HAB levels, the high-MW dAOM strongly decreased the algal removal efficiency of MC.

Underwater Backscatter: What is its Practical Communication Distance?

Recent years have seen mounting interest in low-power, distributed subsea internet-of-things (IoT) networks because of their potential in environmental, industrial, and defense applications [1,2]. Energy-efficient ocean IoT networks can enable long-term sensing of ocean variables (temperature, pH, pressure, salinity, etc.) to create more accurate climate and weather prediction models and monitor the impact of climate change on the ocean [3]. Similarly, low-cost and efficient ocean IoT networks can help boost the growth of the world's blue economy by enabling active monitoring of marine infrastructures ranging from oil/gas pipelines to underwater tunnels [4]. Real-time distributed underwater sensor networks can help boost aquaculture (seafood farm) production by monitoring the farm vitals (water temperature, dissolved nutrients, pH, etc.) and detecting environmental hazards (such as harmful algae blooms) early [5].

Modeling- and Simulation-Driven Methodology for the Deployment of an Inland Water Monitoring System

In response to the challenges introduced by global warming and increased eutrophication, this paper presents an innovative modeling and simulation (M&amp;S)-driven model for developing an automated inland water monitoring system. This system is grounded in a layered Internet of Things (IoT) architecture and seamlessly integrates cloud, fog, and edge computing to enable sophisticated, real-time environmental surveillance and prediction of harmful algal and cyanobacterial blooms (HACBs). Utilizing autonomous boats as mobile data collection units within the edge layer, the system efficiently tracks algae and cyanobacteria proliferation and relays critical data upward through the architecture. These data feed into advanced inference models within the cloud layer, which inform predictive algorithms in the fog layer, orchestrating subsequent data-gathering missions. This paper also details a complete development environment that facilitates the system lifecycle from concept to deployment. The modular design is powered by Discrete Event System Specification (DEVS) and offers unparalleled adaptability, allowing developers to simulate, validate, and deploy modules incrementally and cutting across traditional developmental phases.

Analysis of the Spatiotemporal Distribution of Algal Blooms and Its Driving Factors in Chaohu Lake Based on Multi-source Datasets

Eutrophication and harmful algae blooms are one of the common ecological and environmental problems faced by freshwater lakes all over the world. As a typical inland freshwater lake, Chaohu Lake exhibits a high level of eutrophication and algae blooms year-round and shows a spatiotemporal difference in different regions of the lake. In order to understand the basic regularity of the development and outbreak of algal blooms in Chaohu Lake, the data from the comprehensive water observation platform and remote sensing were integrated to obtain the spatiotemporal distribution of algal blooms from 2015 to 2020. Then, an evaluation model based on Boosted Regression Trees (BRT) was constructed to quantitatively assess the importance and interactions of various environmental factors on algal blooms at different stages. The results indicated that:① The occurrence of algal blooms in Chaohu Lake exhibited significant seasonal variations, with the cyanobacteria beginning to recover in spring and bring about a light degree of algal blooms in the western and coastal areas of Chaohu Lake. The density of cyanobacteria reached its maximum in summer and autumn, accompanied by moderate and severe degrees of algal bloom outbreaks. ② During the non-outbreak period, the variation in the cyanobacteria density was greatly affected by physical and chemical factors, which explained 80.3% of the variance in the change in cyanobacteria density. The high concentrations of dissolved oxygen content in the water column and the weak alkalinity (7.2-7.6) and appropriate water temperature (about 3℃) provided a favorable environmental condition for the breeding and growth of cyanobacteria. In addition, the onset of algal blooms was closely related to the air temperature steadily passing through the threshold. According to the statistics, the date of first outbreak of algal blooms in Chaohu Lake was 11 days or so after the air temperature steadily remained above 7℃. ③ During the outbreak period, the occurrence of algal blooms was influenced by the combination of cyanobacterial biomass and meteorological conditions such as temperature, wind speed, and sunshine duration. The cumulative contribution ratio of the four factors was as high as 95%, and each factor had an optimal interval conductive to the outbreak of algal blooms. Furthermore, the results of multi-factor interaction analysis indicated a larger probability of the outbreak of algal blooms in Chaohu Lake under the combined effect of high cyanobacteria density, suitable temperature, and the breeze. This study analyzed and revealed the spatiotemporal characteristics and the dominant influencing factors of algal blooms in Chaohu Lake at different stages, which could provide the scientific basis for the prediction, early warning, and disposal of algal blooms under the context of climate change.

Insights and machine learning predictions of harmful algal bloom in the East China Sea and Yellow Sea

The increase in harmful algal blooms (HABs) globally has been linked to climate change and anthropogenic activities such as agricultural runoff and urbanization. This study focused on analyzing the impact of these factors on HAB occurrences in the East China Sea and the Yellow Sea, identifying influential factors, and predicting future HAB events. For this study, random forest and numerical modeling were employed, with datasets encompassing physical and chemical properties of river water, seawater, and precipitation to assess the impact of discharge on HABs. Additionally, climate change scenarios derived from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) were employed to predict future HAB occurrences, supported by a sensitivity analysis to identify influential factors affecting HAB occurrence. This study demonstrated that the growth rate and occurrence of HABs in the East China Sea (ECS) and Korean coastal waters (KCW) distinctively increased in July and November after the operation of the Three Gorges Dam (TGD). It is likely affected by the decreasing discharge from the Yangtze River (YR) owing to the operation of the TGD. Using the Random Forest model, future HAB events were predicted in good agreement with observations. The sensitivity results revealed that environmental properties, such as precipitation, water temperature, and salinity are major features affecting the HAB trends in both the KCW and YR basins. Moreover, based on the random forest model and climate change scenarios, HAB events were predicted to increase in frequency in July, September, and October. Therefore, the findings can contribute to preventing biological pollution of the ocean system in the ECS and KCW by supporting efficient environmental management.

Multi-year three-dimensional simulation of seasonal variation in phytoplankton species composition in a large shallow lake

Lake Erie has been negatively impacted by multiple stressors, including nutrient enrichment and climate change, that have exacerbated eutrophication and harmful algal blooms. Management of these long-term water quality problems requires numerical models that can be run over years to decades. The three-dimensional hydrodynamics and biogeochemistry models applied to date, however, have not been tested for continuous runs longer than one year and have not been shown to accurately reproduce seasonal variation in phytoplankton species composition (e.g., the development of harmful algal blooms) over decadal timescales. We simulated the three-dimensional nutrient and phytoplankton concentrations in western Lake Erie continuously from 2002 to 2014. Using a single parameter set, we were able to reproduce both seasonal and inter-annual variation in phytoplankton species composition. The model qualitatively reproduced the observed seasonal succession (i.e., variation in phytoplankton species composition), including the spring diatom bloom and late summer cyanobacterial growth. This study demonstrates that three-dimensional models can be applied for multi-year simulations of nutrients and phytoplankton to inform large lake research and management.

Exploring the human dimensions of harmful algal blooms through a well-being framework to increase resilience in a changing world

Climate change is expected to alter harmful algal bloom (HAB) dynamics in marine and freshwater systems around the world, with some regions already experiencing significant increases in HAB events. There has been considerable investment of effort to identify, characterize, track, and predict the direction and magnitude of HAB response to climate variability and change. In comparison, far less effort has been devoted to understanding how human communities respond to HABs in a changing world. Harmful algal blooms alter social-ecological interactions and can have negative consequences for human well-being. This is especially true for fishing communities because their resource-based economies operate at the interface of the natural environment and society. Identifying the components of human well-being that are most affected by HABs can advance ecosystem assessment and inform choices about climate-ready management strategies in and across complex systems. This study uses a framework for considering human well-being in management contexts to explore the effects of HABs of Pseudo-nitzschia spp. on US West Coast fishing communities. We find that HABs, and the management strategies to address them, affect almost every domain of human well-being; however, less than half of these effects meet the criteria to be considered by federal disaster response and recovery programs that provide relief to impacted communities. Moreover, much of the data used to measure the effects of HABs that are eligible for consideration by these programs are not consistently collected, which could lead to inequitable access to disaster relief. Our analysis provides a starting point for communities to develop a suite of high-quality indicators of human well-being to evaluate HAB impacts, assess the effectiveness of management actions and the equity of management outcomes, and track adaptation to system dynamics and external pressures.

Phosphorus depletion is exacerbated by increasing nitrogen loading in the Bohai sea

Phosphorus (P) is an essential nutrient for algal growth in nearshore ecosystems. In recent years, there has been a shift in nutrient dynamics in nearshore areas, leading to an exacerbation of P limitation, although the underlying mechanisms remain unclear. This study analyzed the P species and budget in the Bohai Sea (BS) from 2011 to 2020, aiming to explore the intrinsic mechanisms of P limitation in the BS. The results show that the main external source of P in the BS was river transport (89%), and the primary fate of P was burial (96%) into the sediment. Due to excessive nitrogen (N) input and biological processes in the BS, the P budget in the BS is unbalanced, resulting in an increase in the N/P ratio, particularly in nearshore areas. Nearshore areas typically have lower concentrations of dissolved inorganic P (DIP) in the water and higher concentrations of reactive P (Reac-P) in the sediments. This pattern is particularly evident in Bohai Bay and the northwest nearshore region, where harmful algal blooms occur frequently. To cope with enhanced P limitation, the biologically driven P regeneration and cycling processes within the BS are accelerated. From 2011 to 2020, the concentration of DIP in the BS during autumn increased, while the content of Reac-P in sediments slightly decreased. Historical data indicate that P depletion in the BS is intensifying and expanding, primarily due to N enrichment and algal production. N enrichment alters the structure and composition of primary production, potentially exacerbating P depletion in the BS. Excessive N may have significant impacts on the P pool, potentially influencing the stability of future coastal ecosystems.

Temperature and nutrients drive distinct successions between diatoms and dinoflagellates over the past 40 years: Implications for climate warming and eutrophication

Diatoms and dinoflagellates are two typical functional groups of phytoplankton, playing important roles in ecosystem processes and biogeochemical cycles. Changes in diatoms and dinoflagellates are thought to be one of the possible mechanisms for the increase in harmful algal blooms (HABs), due to changing hydrological conditions associated with climate change and human activities. However, little is known about their ability to adapt to changing ocean environments, thus making it difficult to know whether and how they are adapting. By analyzing a 44-year monitoring dataset in the central Bohai Sea during 1978–2021, we found that the abundance ratio of diatoms to dinoflagellates showed a decreasing trend seasonally and ecologically, indicating that the phytoplankton community underwent distinct successional processes from diatom dominance to diatom-dinoflagellate co-dominance. These processes exhibited varying responses to temperature, nutrient concentrations and ratios, and their interactions, of which temperature primarily drove the seasonal succession whereas nutrients were responsible for the ecological succession. Specifically, diatoms showed a preference for lower temperatures and higher DIP concentrations, and were able to tolerate lower DIN at lower temperatures. In contrast, dinoflagellates tended to prevail at conditions of warming and high N/P ratios. These different traits of diatoms and dinoflagellates reflected the fact that warming as a result of rising temperature and eutrophication as a consequence of nutrient input would favor dinoflagellates over diatoms. Moreover, the increasing dominance of dinoflagellates indicated that dinoflagellate blooms were likely to become more frequent and intense in the central Bohai Sea.

Assessment of in-situ monitoring and tracking the vertical migration of cyanobacterial blooms using LISST-HAB

Cyanobacterial harmful algal blooms (cyanoHABs) are becoming increasingly common in aquatic ecosystems worldwide. However, their heterogeneous distributions make it difficult to accurately estimate the total algae biomass and forecast the occurrence of surface cyanoHABs by using traditional monitoring methods. Although various optical instruments and remote sensing methods have been employed to monitor the dynamics of cyanoHABs at the water surface (i.e., bloom area, chlorophyll a), there is no effective in-situ methodology to monitor the dynamic change of cell density and integrated biovolume of algae throughout the water column. In this study, we propose a quantitative protocol for simultaneously measurements of multiple indicators (i.e., biovolume concentration, size distribution, cell density, and column-integrated biovolume) of cyanoHABs in water bodies by using the laser in-situ scattering and transmissometry (LISST) instrument. The accuracy of measurements of the biovolume and colony size of algae was evaluated and exceeded 95% when the water bloom was dominated by cyanobacteria. Furthermore, the cell density of cyanobacteria was well estimated based on total biovolume and mean cell volume measured by the instrument. Therefore, this methodology has the potential to be used for broader applications, not only to monitor the spatial and temporal distribution of algal biovolume concentration but also monitor the vertical distribution of cell density, biomass and their relationship with size distribution patterns. This provides new technical means for the monitoring and analysis of algae migration and early warning of the formation of cyanoHABs in lakes and reservoirs.

Margalefidinium polykrikoides dinoflagellate blooms increase mortality of Acartia tonsa copepods

Previous research on phytoplankton blooms has often focused on the initiation of blooms, while studies on the mechanisms underlying bloom decline and termination have been more limited. This study aimed to explore the extent of which Acartia tonsa (copepod) grazing does or does not contribute to Margalefidinium polykrikoides (dinoflagellate) bloom decline. M. polykrikoides is a prominent harmful algal bloom (HAB) species that forms dense blooms in coastal and estuarine systems around the world with known ichthyotoxic effects. Sampling occurred in the lower York River Estuary, Virginia, USA in 2021 and 2022 during two M. polykrikoides blooms. Prey removal experiments were conducted using organisms collected from the field to estimate A. tonsa ingestion rates on M. polykrikoides. While A. tonsa was capable of ingesting M. polykrikoides at low abundance, when M. polykrikoides abundance exceeded 2000 cells mL−1, A. tonsa experienced nearly 100% mortality in the 24-hour prey removal experiments. This suggests that A. tonsa likely cannot exert any top-down control on M. polykrikoides blooms, rather, at high concentrations, M. polykrikoides may act as its own grazing deterrent. Extensive M. polykrikoides blooms could therefore continue to persist due to a reduction in grazing pressure, rather than an increase. This would suggest that the decline of M. polykrikoides blooms is likely caused by another factor. As the frequency, duration, and magnitude of HABs are expected to increase in the future, these findings provide key insights to the trophic interactions that may be influencing the duration of M. polykrikoides blooms.