Frequency Of Harmful Algal Blooms Research Articles

Influence of multi-stressor combinations of pCO2, temperature, and salinity on the toxicity of Heterosigma akashiwo (Raphidophyceae), a fish-killing flagellate.

Climate change and global warming have led to more frequent harmful algal blooms in the last decade. Among these blooms, Heterosigma akashiwo, a golden-brown phytoflagellate, is one of the 40 species with a high potential to form harmful blooms, leading to significant fish mortality. Climate change leads to rising atmospheric and ocean temperatures. These changes, along with altered rainfall patterns and meltwater input, can cause fluctuations in ocean salinity. Elevated atmospheric carbon dioxide (CO2) levels increase water acidity as oceans absorb CO2. This study investigated the effects of temperature, salinity, and CO2 levels on lipid production, hemolytic activity, and toxicity of H. akashiwo using the design of experiment approach, which can be used to investigate the effect of two or more factors on the same response simultaneously in a precise manner with fewer experiments and materials but in a larger region of the factor space. The lipid content was measured using a high-throughput Nile Red method, and the highest level of lipid content was detected at 25°C, a salinity of 30, and a CO2 concentration of 400 ppm. Hemolytic activity was assessed using rabbit blood erythrocytes in a 96-well plate, and the optimal conditions for achieving the highest hemolytic activity were determined at 15°C, a salinity of 10, and a CO2 concentration of 400 ppm. As the chemical structure of the toxin is not known, we used the toxicity against the cell line RTgill-W1 as the cell toxicity proxy. The maximum toxicity was identified at 15°C, a salinity of 10, and a CO2 level of 700 ppm.

Evaluation of best management practices for mitigating harmful algal blooms risk in an agricultural lake basin using a watershed model integrated with Bayesian Network approach

Lake eutrophication caused by nitrogen and phosphorus has led to frequent harmful algal blooms (HABs), especially under the unknown challenges of climate change, which have seriously damaged human life and property. In this study, a coupled SWAT-Bayesian Network (SWAT-BN) model framework was constructed to elucidate the mechanisms between non-point source nitrogen pollution in agricultural lake watersheds and algal activities. A typical agricultural shallow lake basin, the Taihu Basin (TB), China, was chosen in this study, aiming to investigate the effectiveness of best management practices (BMPs) in controlling HABs risks in TB. By modeling total nitrogen concentration of Taihu Lake from 2007 to 2022 with four BMPs (filter strips, grassed waterway, fertilizer application reduction and no-till agriculture), the results indicated that fertilizer application reduction proved to be the most effective BMP with 0.130 of Harmful Algal Blooms Probability Reduction (HABs-PR) when reducing 40% of fertilizer, followed by filter strips with 0.01 of HABs-PR when 4815ha of filter strips were conducted, while grassed waterway and no-till agriculture showed no significant effect on preventing HABs. Furthermore, the combined practice between 40% fertilizer application reduction and 4815ha filter strips construction showed synergistic effects with HABs-PR increasing to 0.171. Precipitation and temperature data were distorted to model scenarios of extreme events. As a result, the combined approach outperformed any single BMP in terms of robustness under extreme climates. This research provides a watershed-level perspective on HABs risks mitigation and highlights the strategies to address HABs under the influence of climate change.

Succession of phytoplankton communities from macro-scale to micro-scale in coastal waters of Qinhuangdao, China

The coastal area of Qinhuangdao, particularly the Changli Gold Coast Nature Reserve, is experiencing ecological degradation and frequent Harmful Algal Blooms (HABs). This study focuses on the changing phytoplankton communities in these coastal waters, examining them from both a macroscopic and microscopic perspective. Utilizing microscopy, molecular techniques, and pigment analysis, seasonal shifts were observed, with diatoms predominating in June and July, and dinoflagellates in August. Our morphological examination enabled the classification of 89 species into four distinct groups. The species Paralia sulcata and Pseudo-nitzschia pungens were most abundant in early summer, while Tripos furca, a dinoflagellate, dominated in August. This indicates a shift in phytoplankton communities due to environmental factors such as phosphate deficiency and high nitrogen/phosphorus ratios. Additionally, the study notes the impact of reduced river runoff and reintroduction of scallop farming contributing to nitrogen-rich eutrophication in August. Molecular analysis revealed a disparity between microscopic observations and the prevalence of Teleaulax blooms during early summer. Elevated concentrations of TN and DOC, coupled with limited water exchange, emerged as primary factors contributing to their occurrence. Sediment analysis revealed a high diversity but low abundance of dinoflagellates in August, with a significant presence of harmful species. The study highlights the shift from diatoms to harmful dinoflagellate populations, exacerbated by eutrophication and pollution, leading to HABs. These findings provide a theoretical basis for understanding toxic algal blooms and are crucial for environmental agencies in developing strategies to protect and sustainably develop offshore environments.

Rate-induced tipping can trigger plankton blooms

Plankton blooms are complex nonlinear phenomena whose occurrence can be described by the two-timescale (fast-slow) phytoplankton-zooplankton model introduced by Truscott and Brindley (Bulletin of Mathematical Biology 56(5):981–998, 1994). In their work, they observed that a sufficiently fast rise of the water temperature causes a critical transition from a low phytoplankton concentration to a single outburst: a so-called plankton bloom. However, the dynamical mechanism responsible for the observed transition has not been identified to the present day. Using techniques from geometric singular perturbation theory, we uncover the formerly overlooked rate-sensitive quasithreshold which is given by special trajectories called canards. The transition from low to high concentrations occurs when this rate-sensitive quasithreshold moves past the current state of the plankton system at some narrow critical range of warming rates. In this way, we identify rate-induced tipping as the underlying dynamical mechanism of largely unpredictable plankton blooms such as red tides, or more general, harmful algal blooms. Our findings explain the previously reported transitions to a single plankton bloom, and allow us to predict a new type of transition to a sequence of blooms for higher rates of warming. This could provide a possible mechanism of the observed increased frequency of harmful algal blooms.

Wide ecological niches ensure frequent harmful dinoflagellate blooms

Harmful algal blooms (HABs) and their consequences cause multiple devastating effects in various freshwater, brackish and marine ecosystems. However, HAB species at moderate population densities have positive ecological roles as primary producers of organic matter and food for zooplankton and fish. They also enhance benthic-pelagic coupling and participate in the biogeochemical cycles. The consequences of HABs are transported across the conventional environmental boundaries by numerous cascade effects in the food webs and beyond. Meanwhile, forecasts of bloom events are still limited, largely because of scarcity of reliable information on ecological niches of the bloom-forming algae. To fill up this knowledge gap, this study focused on dinoflagellates, a diverse group of mostly photosynthesizing protists (unicellular eukaryotes) capable of mixotrophy, since they play a key role in primary production and formation of blooms in marine and brackish waters worldwide. In this study, ecological niches of 17 abundant bloom-forming dinoflagellate species from coastal regions of the southern Baltic Sea were identified for the first time. It was hypothesized that wider ecological niches ensure more frequent dinoflagellate blooms compared to the species with narrower niches. This hypothesis was verified using the long-term (44 years) database on phytoplankton abundance and physical-chemical characteristics of the environment. It were analyzed 4534 datasets collected from 1972 to 2016. Fourteen abiotic parameters (water temperature, salinity, Secchi depth, pH, Chl a, and concentration of basic nutrients) were considered as ecological niche dimensions. The Principal Component Analysis presented the dissolved inorganic nitrogen, total nitrogen, Chl a, and temperature as principal niche dimensions of dinoflagellates. The algal bloom criteria were refined. It was for the first time proved statistically that HAB frequency of dinoflagellate species robustly correlated with the width of their ecological niches.

A comprehensive approach to assessing eutrophication for the Guangdong coastal waters in China

Eutrophication is a global issue associated with increasing anthropogenic activities. Previous studies have mainly focused on nutrients and phytoplankton biomass in some typical estuaries and bays along the Guangdong coast, while integrated evaluations of eutrophication status based on ecological symptoms is still rare in this area. To better understand the health of the Guangdong coastal waters, two comprehensive methods including the Assessment of Estuarine Trophic Status (ASSETS) and the Northwest Pacific Action Plan Common Procedure (NOWPAP CP) were employed with slight modifications. The study area was divided into eight coastal zones (Z1~Z8) based on multiple criteria including salinity, catchment range, and administrative division. The results of the modified NOWPAP CP method demonstrated a generally increasing trend in the degree and effects of nutrient enrichment along the Guangdong coast in the past 30 years mainly due to the increasing nutrients and chlorophyll a (Chl-a). The results of the modified ASSETS method revealed that the water quality was between moderate and high for most coastal zones during 2015-2018, with the highest score (0.83) in the northern part of the Pearl River Estuary (PRE). However, the ecological symptoms showed inconsistent spatial patterns with the water quality, being high or moderate high in Z2 (including Zhanjiang Harbor and Leizhou Bay), Z4~Z5 (representing the northern and southern parts of the PRE, respectively), and Z6 (containing Mirs Bay and Daya Bay) for severe ecological symptoms, such as high levels of Chl-a, frequent harmful algal blooms (HABs). Moreover, eutrophication in Z4~Z6 may further deteriorate due to the increasing nutrient loads driven by growing economy and population. Synthetically, Z2, Z4~Z6 were graded between poor and bad for the overall eutrophication conditions (OEC), while Z1 (including the western and southern parts of the Leizhou Peninsula) and Z7 (consisting of Honghai Bay and Jieshi Bay) had a good OEC. The application of the modified ASSETS method effectively identified areas of severe eutrophication problems and the prospect of nutrient load along the Guangdong coast. The assessment results revealed the spatiotemporal variations and potential trends in the eutrophication status, providing scientific basis for the coastal management related to nutrient problems.

Comprehensive analysis of harmful algal blooms in indonesia: from occurrence to impact

The occurrence and frequency of harmful algal blooms have become a significant problem in Indonesia's coastal waters since 1991. This article aims to thoroughly analyze the diversity of algal species involved in these harmful algal blooms (HABs). It highlights that some algae, such as toxic species, can produce dangerous toxins, while others, such as non-toxic algae, remain harmless. This article reviews research studies that describe the occurrence, frequency, and causative types of bloom events in several contaminated coastal regions of Indonesia. The blooms had many consequences for fisheries, the aquatic environment, the economy, and public health. Among the identified species, Pyrodinium bahamense var. compressum is known for its high toxicity. The most common taxa contributing to bloom tragedy are Chaetoceros, Noctiluca, and Skeletonema. The study recognizes that human-induced nutrient enrichment is a major and significant factor in triggering the bloom phenomena. The paper recommends various management strategies and further research initiatives to prevent and reduce the impacts of HABs in Indonesia.

Small and patchy is enough: An example about how toxic HAB events can spread through low resting cyst loads

The frequency of harmful algal blooms (HABs) has increased over the last two decades, a phenomenon enhanced by global climate change. However, the effects of climate change will not be distributed equally, and Chile has emerged as one important, vulnerable area. The Chilean Patagonian region (41‒56°S) hosts two marine ecoregions that support robust blue economies via wild fisheries, aquaculture, and tourism. However, the harmful algal bloom-forming dinoflagellate Alexandrium catenella, a causative agent of paralytic shellfish poisoning outbreaks, threatens the viability of blue industries in this region and others worldwide. Despite the proliferation of A. catenella blooms over the last few decades, the role of sedimentary resting cysts in the recurrence of harmful algal blooms and the species’ northward expansion across Chilean Patagonia is not well understood. As a resting cyst-producing species, the sediment-cyst dynamics of A. catenella likely contribute to the geographical expansion and bloom recurrence of this species. For this purpose, we analyzed a decade of A. catenella surface sediment cyst records across the two ecoregions of the Chilean Patagonian System that were further stratified into five subregions based on water temperature, salinity, dissolved oxygen, and nutrient characteristics. We also analyzed spatio-temporal cyst dynamics in a pre-, during-, and post-bloom scenario of the Chiloense ecoregion (more northern) of the Magellanic province. Our results indicated highly variable A. catenella resting cyst abundances, with a maximum of 221 cysts cm−3 recorded in 2002 after an intense bloom. Generalized linear mixed models and linear mixed models found that sampling season, subregion, and Total Organic Matter (%) explained resting cyst presence and density. The results also demonstrated the presence of A. catenella cysts in northern subregions, evidencing the northward geographical expansion observed during the last few decades. The risks of A. catenella bloom recurrence from small, patchy resting cyst distributions across broad geographical areas and under changing environmental conditions are discussed.

Comprehensive study of algal blooms variation in Jiaozhou Bay based on google earth engine and deep learning

The Jiaozhou Bay ecosystem, a crucial marine ecosystem in China, has been plagued by frequent harmful algal blooms as due to deteriorating water quality and eutrophication. This study analyzed the temporal and spatial changes of harmful algal blooms in Jiaozhou Bay from 2000 to 2022 using the Floating Algae Index (FAI) calculated from MODIS (2000–2022) and Sentinel-2 (2015–2022) satellite image datasets. The calculation results of the image datasets were compared. The frequency of planktonic algal outbreaks was low and constant until 2017, but has increased annually since then. Algae blooms are most common in the summer and primarily concentrated along the bay’s coast, middle, and mouth, with obvious seasonal and spatial distribution characteristics. Several factors influencing algal outbreaks were identified, including sea surface temperature, wind speed, air pressure, dissolved oxygen, nitrogen and phosphorus ratios, chemical oxygen demand, and petroleum pollutants. Algal bloom outbreaks in Jiaozhou Bay are expected to remain high in 2023. The findings provide crucial information for water quality management and future algal outbreak prediction and prevention in Jiaozhou Bay.

Parametric versus nonparametric machine learning modelling for conditional density estimation of natural events: Application to harmful algal blooms

Besides the complex effect of global warming on extreme events, spatiotemporal variability of natural phenomena often carries the legacy of anthropogenic activities. Moreover, any feedback induced by these activities on climate brings additional complexity when modelling natural events. For extreme values, climate or physiographic patterns often induce non stationarity, or long-term changes. In this context, parametric models may become inadequate given the complexity of the studied phenomena and their systematic changes through space and time. In this paper, we assess the use and ensuing efficiency of nonparametric machine learning (npML) methods to estimate and predict extreme values associated with natural events. These npML methods are compared to a commonly used parametric machine learning (pML) approach, the nonstationary frequency analysis model. We use a historical database compiling the frequency of harmful algal blooms (HAB) in Québec, Canada. Results show that a 19-covariate RFCDE model leads to the best mean estimate among the considered models. However, for low and large quantiles, the 4-covariate RCDE model provides better agreement between observed and simulated bloom frequencies. The models may be used to assess the effects of climate change and anthropogenic developments on the frequency of HAB. They may also be leveraged to measure the efficiency of mitigation scenarios and to identify priority areas for restoration plan strategies. Recommendations are finally made regarding the estimation of the conditional density to predict extreme values associated with natural events.

Pseudo-nitzschia species, toxicity, and dynamics in the southern Indian River Lagoon, FL

The Indian River Lagoon (IRL) spans approximately one-third of the east coast of Florida and, in recent years, has faced frequent harmful algal blooms (HABs). Blooms of the potentially toxic diatom, Pseudo-nitzschia, occur throughout the lagoon and were reported primarily from the northern IRL. The goal of this study was to identify species of Pseudo-nitzschia and characterize their bloom dynamics in the southern IRL system where monitoring has been less frequent. Surface water samples collected from five locations between October 2018 and May 2020 had Pseudo-nitzschia spp. present in 87% of samples at cell concentrations up to 1.9×103 cells mL−1. Concurrent environmental data showed Pseudo-nitzschia spp. were associated with relatively high salinity waters and cool temperatures. Six species of Pseudo-nitzschia were isolated, cultured, and characterized through 18S Sanger sequencing and scanning electron microscopy. All isolates demonstrated toxicity and domoic acid (DA) was present in 47% of surface water samples. We report the first known occurrence of P. micropora and P. fraudulenta in the IRL, and the first known DA production from P. micropora.

A cross-regional examination of patterns and environmental drivers of Pseudo-nitzschia harmful algal blooms along the California coast

Pseudo-nitzschia species with the ability to produce the neurotoxin domoic acid (DA) are the main cause of harmful algal blooms (HABs) along the U.S. West Coast, with major impacts on ecosystems, fisheries, and human health. While most Pseudo-nitzschia (PN) HAB studies to date have focused on their characteristics at specific sites, few cross-regional comparisons exist, and mechanistic understanding of large-scale HAB drivers remains incomplete. To close these gaps, we compiled a nearly 20-year time series of in situ particulate DA and environmental observations to characterize similarities and differences in PN HAB drivers along the California coast. We focus on three DA hotspots with the greatest data density: Monterey Bay, the Santa Barbara Channel, and the San Pedro Channel. Coastwise, DA outbreaks are strongly correlated with upwelling, chlorophyll-a, and silicic acid limitation relative to other nutrients. Clear differences also exist across the three regions, with contrasting responses to climate regimes across a north to south gradient. In Monterey Bay, PN HAB frequency and intensity increase under relatively nutrient-poor conditions during anomalously low upwelling intensities. In contrast, in the Santa Barbara and San Pedro Channels, PN HABs are favored under cold, nitrogen-rich conditions during more intense upwelling. These emerging patterns provide insights on ecological drivers of PN HABs that are consistent across regions and support the development of predictive capabilities for DA outbreaks along the California coast and beyond.

Succession and controlling factors of phytoplankton assemblages during a period with recurrent outbreaks of Phaeocystis globosa blooms in Qinzhou Bay, China

Qinzhou Bay is a tropical semiclosed bay with the highest phytoplankton diversity and a high frequency of harmful algal blooms (HABs) in the Guangxi coastal area, located north of the Beibu Gulf. Phaeocystis globosa is a typical HAB species in the Guangxi coastal area, and blooms mainly occur in autumn and winter. The causes of these blooms and the succession of phytoplankton assemblages related to the blooms are complicated and not fully understood. Therefore, a continuous survey was conducted monthly from October 2018 to March 2019 to study the succession of the phytoplankton community in Qinzhou Bay and its relationship with environmental variables in this area. The results revealed that the dynamics of the phytoplankton assemblages varied significantly with time, and P. globosa was the most frequent dominant species in five of these voyages, with the highest cell density of 3.79 ± 1.34 × 106 cells/L in January. Chaetoceros species had a high density and were a dominant species associated with P. globosa in the early stage, while they were replaced by Guinardia striata when the density of P. globosa increased rapidly in January, and the abundance of dinoflagellates increased after the decline in P. globosa. The diversity index indicated that the community structure was more stable from October to December, while the sharp increase in P. globosa in January caused a decline in phytoplankton diversity. The redundancy analysis (RDA) results revealed that the phytoplankton community structure and its variation were mainly affected by hydrological and chemical factors, including DIN/DIP, temperature, DSi, DIP and DSi/DIP. Furthermore, we inferred that phosphorus (P) was the key factor limiting the colony formation of P. globosa, and P limitation prevented the outbreak of blooms. This research may provide more insight into the mechanisms driving and prevention of P. globosa blooms.

Diversity and Distribution of Harmful Algal Bloom Species from Seamount to Coastal Waters in the South China Sea.

Mount Xianbei is one of the largest shallow seamounts located in the middle of the South China Sea (SCS), which might play a role in shaping the biodiversity of surrounding continental coastal waters, particularly the diversity of phytoplankton species causing frequent harmful algal blooms (HABs) in northern SCS. However, the diversity, composition, and distribution of phytoplankton species in the seamount regions of Xianbei remain largely unexplored. In this study, samples around and outside the seamount regions were collected during a late summer cruise of 2021 to test whether seamounts play a role in HAB species propagation. In total, we identified 19 HAB species across all samples using the ASV-based DNA metabarcoding approach, 6 of which had not been reported previously in the SCS, suggesting a diverse HAB species in the SCS. Specifically, 16 HAB species were found in the seamount region of Xianbei, and 5 of them were also found in the coastal waters, indicating a close connection between seamount and coastal waters. This study was the first attempt to explore HAB species' spatial diversity and vertical distribution in the seamount region of Xianbei at single-nucleotide resolution, which provides a novel explanation for the coastal HAB occurrence in the northern SCS. IMPORTANCE There are a number of seamounts under the water of the South China Sea (SCS). The seamounts might play a role in shaping the biodiversity of surrounding continental coastal waters. However, there is no direct evidence revealing the relationship of the biodiversity of phytoplankton between seamounts and coastal waters in the SCS, especially those species having the potential to form harmful algal blooms (HABs). Some HAB species might proliferate in certain geographic locations, while others may be broadly distributed across oceanic provinces. In this study, we provided a detailed analysis of phytoplankton composition and molecular detection of HAB species from seamount to coastal waters in the SCS, which suggested a strong interaction in the HAB species between the two areas. This finding provides new insights into the diversity and distribution of HABs in seamounts and their role in shaping the composition and the occurrence of HABs in coastal water.

Potential effects of climate change on the growth response of the toxic dinoflagellate Karenia selliformis from Patagonian waters of Chile

Northern Patagonia (41–44°S) is affected by climatic, hydrological and oceanographic anomalies, which in synergy with processes such as global warming and acidification of the coastal oceans may affect the frequency and intensity of harmful algal blooms (HABs). Greater frequency of HABs has been reported in the southeastern Pacific Ocean, including blooms of the toxic dinoflagellate Karenia selliformis, causing massive mortality of marine fauna in the oceanic and coastal areas of Patagonia. The objective of this study was to determine the effects of temperature and pH interaction on the growth of K. selliformis (strain CREAN_KS02), since these factors have wide seasonal fluctuations in the Patagonian fjord ecosystem. The CREAN_KS02 strain isolated from the Aysén Region (43°S) was used in a factorial experiment with five pH levels (7.0, 7.4, 7.7, 8.1 and 9.0) and two temperatures (12 and 17 °C) during a period of 18–21 days. Results indicated a significant effect of temperature and pH interaction on growth rate (range 0.22 ± 0.00 to 0.08 ± 0.01 d−1) and maximum density (range 13,710 ± 2,616 to 2,385 ± 809 cells mL−1) of K. selliformis. The highest density and growth of K. selliformis was found at 12 °C with a reduced pH (7.0–7.7). The results suggest that the current environmental conditions of coastal Patagonia, waters of low temperature and relatively low pH, may be favorable for the development of blooms of this species during autumn. We suggest that there is natural plasticity of K. selliformis in a wide pH range (7.0–8.1) but in a narrow low temperature range (10.6–12.9 °C), values that are typically recorded in the oceanic region of northern Patagonia. In contrast, in an extreme climate change scenario (ocean warming and coastal acidification) in northern Patagonia, a negative effect on the growth of K. selliformis may be expected due to amplification of the acidification effects caused by the thermal stress of high temperature water.

Projected harmful algal bloom frequency in the Yangtze River Estuary and adjacent waters

Harmful algal blooms (HABs) are a frequent occurrence in China's offshore waters due to climate change and human activity, particularly in the Yangtze River Estuary and adjacent waters. Here, we studied HABs and their relationship with climatic and environmental factors in these waters from 1979 to 2016 using historical observations and reanalysis data. We then projected HABs frequency under various climate scenarios using the “environmental impact factor-frequency of HABs” mathematical model built using the BP neural network method and CIMP5 model data (RCP 2.6, RCP 4.5, and RCP 8.5). The results suggest a significant positive correlation between HABs frequency and seawater nutrient concentration, winter sea surface temperature, and low-wind days, and HABs frequency is anticipated to increase significantly by the 2040s compared with that of the historical era. Furthermore, future phytoplankton conditions are predicted to favor HAB species.

Sources and long-term variation characteristics of dissolved nutrients in Maowei Sea, Beibu Gulf, China

Maowei Sea is a typical semi-enclosed subtropical bay where eutrophication has been rising due to human activities in recent years. At present, the source and long-term variability properties of nutrients are not well understood. This study investigated the dissolved inorganic nutrients in the riverine sections to the sea and the coastal areas from 2011 to 2017 in Qinzhou Bay (QZB), Beibu Gulf. Results showed that harmful blooms were frequent in the dry season due to rapid urbanization in recent years. During dry season, the concentrations of dissolved inorganic nitrogen (DIN) and dissolved inorganic phosphorus (DIP) increased by 67% and 150%, respectively. Most of the nutrients input to the bay were supplied by the adjoining rivers, followed by groundwater discharge according to the classical box model devised by the Land-Ocean Interactions in the Coastal Zone. High DIN concentrations in rivers were mainly caused by intensified agriculture, including urban and rural effluents, due to inadequate sanitary sewer systems. Maowei Sea (the inner bay of QZB) is a sink system for DIN but a strong source system for DIP, which surpassed riverine input, probably due to the discharge of DIP-containing effluent from the industries around the Maoling River mouth. The discrepancy in DIN and DIP sources resulted in different DIN/DIP ratios between the wet and dry seasons. P-limitation generally occurs in the wet season and is relieved in the dry season. The relief of P-limitation in the dry season may be crucial for the frequent harmful algal blooms, which may be further aggravated in the future with the rapid increase in DIP concentrations in the bay. Therefore, the results of this study provide a basis for the effective improvement of the ecological environment in the Maowei Sea.

Economic impacts of harmful algal blooms on fishery-dependent communities

The recreational razor clam fishery is the largest recreational bivalve fishery in the Pacific Northwest and a major source of tourism-related income to small communities in the region. Delays and closures of recreational shellfisheries due to the increasing frequency of harmful algal blooms (HABs) threaten to have significant negative impacts on fishery dependent communities. Coupling previous recreational shellfishing expenditure estimates from the literature with a novel dataset of daily visits to local businesses, we estimate a range of economic impacts resulting from the cancellation of razor clam digs at Long Beach, WA, the most popular beach in the State for recreational clam diggers. Our results indicate that a full season closure can lead to lost sales revenues of $16,875 for gas stations, $117,600 for food stores, $217,800 for accommodations and $491,400 for food service places for a total lower bound economic impact of $843,675. We discuss the opportunity for early warning systems, like the Pacific Northwest HAB Bulletin, to guide policy and facilitate business decisions that hedge the risk of revenue losses associated with dig cancellations.

Temporal prediction of algal parameters in Three Gorges Reservoir based on highly time-resolved monitoring and long short-term memory network

Many dammed rivers throughout the world have experienced frequent harmful algal blooms (HABs) in the context of climate change and anthropogenic activities. Accurate forecasting of algal parameters (i.e., algal cell density and microcystin concentration) has great practical significance for taking precautions against HABs risks. Long short-term memory (LSTM) networks have recently shown potential in predicting water quality parameters. However, there is still little known about the robustness of the LSTM in forecasting highly time-resolved measurement of algal parameters. This study developed a hybrid deep-learning architecture (XG-LSTM) composed of one XGBoost module and two parallel LSTM models to predict algal cell density and microcystin concentration in the Three Gorges Reservoir (TGR). The proposed model was validated by in situ multi-sensor-system monitoring data at four bloom-impacted tributaries in the TGR. Each modelling process utilized the antecedent information of the algal parameters and the corresponding environmental variables as inputs for forecasting the algal parameters for the coming hours and days. As expected, the presented model achieved better performance than those without special feature extraction procedures, providing that the use of selected environmental parameters can improve LSTM performance. In addition, the hybrid XG-LSTM model successfully captured the time-series patterns of both algal cell density and microcystin concentration compared with other data-driven models, further suggesting the reliable utilization of this model in early warnings of bloom toxicity. Thus, the results presented demonstrate the potential of deep learning technology for real-time prediction of algal parameters in the TGR, and possibly for rapid detection of developing HABs in other aquatic ecosystems.

Isolated and combined effects of a submerged macrophyte and a cladoceran on the interactions between Microcystis aeruginosa (Cyanobacteria) and Raphidocelis subcapitata (Chlorophyta)

Introduction: Cyanobacterial blooms in tropical water bodies are increasingly common, because of eutrophication and rising temperatures. Consequently, many freshwater systems are affected, by reducing water quality, biodiversity, and ecosystem services. With the increased frequency of harmful algal blooms, the development of biological tools to improve water quality is an urgent issue. Objective: To evaluate the effects of a submerged macrophyte and a cladoceran on the microcystin-producing cyanobacteria Microcystis aeruginosa (NPLJ-4) and the chlorophyte Raphidocelis subcapitata (BMIUFRPE-02) in mixed cultures. Methods: Two parallel experiments were carried out for ten days to evaluate the effects of the submerged macrophyte Ceratophyllum demersum and the cladoceran Moina micrura on microalgal interactions. Microalgal strains were cultivated in the ASM1 culture medium, under controlled laboratory conditions. The first experiment presented four treatments: M (C. demersum), Z (M. micrura), MZ (C. demersum and M. micrura), and C (control). Meanwhile, the second experiment consisted of five treatments, in which the microalgae were cultivated together at different Microcystis:Raphidocelis ratios: 1:0, 3:1, 1:1, 1:3, and 0:1. Biomass and growth rates of the strains were evaluated every two days, which were statistically treated with three-way or two-way repeated-measures ANOVA. Results: In the first experiment, M. aeruginosa was significantly inhibited in M and MZ treatments from the second day, and Z from the fourth, while R. subcapitata showed no reduction in its biomass in any treatment. On the other hand, R. subcapitata was stimulated from the eighth and tenth days in M treatment and only on the eighth day in Z treatment. In the second experiment, M. aeruginosa was significantly inhibited when cultivated with R. subcapitata in low ratios (Microcystis:Raphidocelis ratio of 1:3) throughout the experiment, while the chlorophyte was stimulated in that treatment. Conclusions: The coexistence of a cyanobacterium with a green alga did not alter the main negative response of M. aeruginosa to the submerged macrophyte and zooplankton but stimulated the green alga. Accordingly, the introduction of submerged macrophytes and cladocerans already adapted to eutrophic conditions, both isolated and combined, proved to be a good method to control cyanobacterial blooms without negatively affecting other coexisting phytoplankton species.