Outbreaks Of Harmful Algal Blooms Research Articles

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.

A photocatalytic-microbial coupling system for simultaneous removal of harmful algae and enhanced denitrification: Construction, performance and mechanism of action

Recently, harmful algal blooms (HABs) have become occurred with increasingly frequency worldwide. High nitrate content is one of the primary causes of eutrophication. Research has shown that photocatalytic materials enhance the effectiveness of microbial denitrification while removing other contaminants, despite some shortcomings. Based on this, we loaded TiO2/C3N4 heterojunctions onto weaveable, flexible carbon fibers and established a novel photocatalytically enhanced microbial denitrification system for the simultaneous removal of harmful algae and Microcystin-LR. We found that 99.35% of Microcystis aeruginosa and 95.34% of MC-LR were simultaneously and effectively removed. Compared to existing denitrification systems, the nitrate removal capacity improved by 72.33%. The denitrifying enzyme activity and electron transport system activity of microorganisms were enhanced by 3.54–3.86 times. Furthermore, the microbial community structure was optimized by the regulation of photogenerated electrons, and the relative abundance of main denitrifying bacteria increased from 50.72% to 66.45%, including Proteobacteria and Bacteroidetes. More importantly, we found that the increased secretion of extracellular polymeric substances by microorganisms may be responsible for the persistence of the reinforcing effect caused by photogenerated electrons in darkness. The higher removal of Microcystis aeruginosa and Microcystin-LR (MC-LR) achieved by the proposed system would reduce the frequency of HAB outbreaks and prevent the associated secondary pollution.

Short-term Lake Erie algal bloom prediction by classification and regression models

The recent outbreaks of harmful algal blooms in the western Lake Erie Basin (WLEB) have drawn tremendous attention to bloom prediction for better control and management. Many weekly to annual bloom prediction models have been reported, but they only employ small datasets, have limited types of input features, build linear regression or probabilistic models, or require complex process-based computations. To address these limitations, we conducted a comprehensive literature review, complied a large dataset containing chlorophyll-a index (from 2002 to 2019) as the output and a novel combination of riverine (the Maumee & Detroit Rivers) and meteorological (WLEB) features as the input, and built machine learning-based classification and regression models for 10-d scale bloom predictions. By analyzing the feature importance, we identified 8 most important features for the HAB control, including nitrogen loads, time, water levels, soluble reactive phosphorus load, and solar irradiance. Here, both long- and short-term nitrogen loads were for the first time considered in HAB models for Lake Erie. Based on these features, the 2-, 3-, and 4-level random forest classification models achieved an accuracy of 89.6%, 77.0%, and 66.7%, respectively, and the regression model achieved an R2 value of 0.69. In addition, long-short term memory (LSTM) was implemented to predict temporal trends of four short-term features (N, solar irradiance, and two water levels) and achieved the Nash-Sutcliffe efficiency of 0.12–0.97. Feeding the LSTM model predictions for these features into the 2-level classification model reached an accuracy of 86.0% for predicting the HABs in 2017–2018, suggesting that we can provide short-term HAB forecasts even when the feature values are not available.

A singular value decomposition approach for detecting and delineating harmful algal blooms in the Red Sea

Harmful algal blooms (HABs) have adverse effects on marine ecosystems. An effective approach for detecting, monitoring, and eventually predicting the occurrences of such events is required. By combining a singular value decomposition (SVD) approach and satellite remote sensing observations, we propose a remote sensing algorithm to detect and delineate species-specific HABs. We implemented and tested the proposed SVD algorithm to detect HABs associated with the mixed assemblages of different phytoplankton functional type (PFT) groupings in the Red Sea. The results were validated with concurrent in-situ data from surface samples, demonstrating that the SVD-model performs remarkably well at detecting and distinguishing HAB species in the Red Sea basin. The proposed SVD-model offers a cost-effective tool for implementing an automated remote-sensing monitoring system for detecting HAB species in the basin. Such a monitoring system could be used for predicting HAB outbreaks based on near real-time measurements, essential to support aquaculture industries, desalination plants, tourism, and public health.

A combined approach detected novel species diversity and distribution of dinoflagellate cysts in the Yellow Sea, China

Resting cysts of dinoflagellates seed harmful algal blooms (HABs) and their geographic expansion, which makes it fundamentally important to obtain comprehensive inventories of dinoflagellate resting cysts in HABs-prone regions. The Yellow Sea (YS) of China has observed numerous outbreaks of dinoflagellate HABs with some novel species recorded recently indicating an underestimated HABs-causing species diversity. We report our investigation of dinoflagellate cysts of YS via an approach combining metabarcoding sequencing and single-cyst morpho-molecular identification, which identified many novel cyst species and a significant controlling effect of the Yellow Sea Cold Water Mass on cyst composition. The metabarcoding and single cyst-based sequencing detected 11 cyst species never being unambiguously reported in China, 10 never reported as cyst producers, and 3 HABs-causing species never reported from YS. Our detections of many potentially toxic or HABs-causative, particularly novel, cysts and distribution pattern provide important insights into the risks and ecology of dinoflagellate HABs.

Green algae monitoring via ground-based GNSS-R observations

Outbreaks of harmful algal blooms (HABs) exhibit high frequency, large range and damage aggravation characteristics, but existing monitoring methods, such as artificial and optical near-infrared remote sensing, cannot accommodate these characteristics. We propose a new method for monitoring green algae using Global Navigation Satellite System Reflectometry (GNSS-R) observations. The basic principle states that changes in the seawater dielectric constant and sea surface roughness due to the emergence of green algae lead to an increase in brightness temperature, which can be inverted based on the reflection time delay waveform. Shipboard reflection waveform data collected during an Enteromorpha prolifera outbreak in the Qingdao sea area were used for model development and validation of the detection and estimation performance. The results indicated that the root mean square error of GNSS-R-based inversion of the green algae density was 6.74%, indicating the potential of GNSS-R technology for rapid preliminary monitoring of green algae. Moreover, the advantages of a low cost, short return time and no climatic limitations support GNSS-R technology as a new and efficient means of green algae monitoring.

Inorganic Nitrogen Uptake Characteristics of Three Typical Bloom-Forming Algae in the East China Sea

Inorganic nitrogen (N) is an important element for eutrophication and harmful algal bloom (HAB) formation. However, the roles of inorganic N in HAB outbreaks are still unclear. Here, we compared the affinities and abilities for inorganic N uptake and assimilation among three typical bloom-forming algae in the East China Sea (ECS), Skeletonema costatum, Prorocentrum donghaiense and Alexandrium pacificum by investigating the uptake and enzymatic (nitrate reductase (NR) and glutamine synthetase (GS) kinetics for nitrate and ammonia. The Ks of nitrate and ammonium in S. costatum was lower than those in P. donghaiense and A. pacificum. The NR activity of S. costatum and P. donghaiense exhibited a positive relationship with the nitrate concentration, and NR activity of S. costatum was nearly 4-fold higher than that of P. donghaiense at high nitrate concentration. However, the NR activity of A. pacificum could not be detected. The GS activity of three species decreased with the increase of ammonium concentrations, and the highest GS activity was detected in A. pacificum. S. costatum presented the highest affinity for nitrate and ammonium, followed by P. donghaiense and A. pacificum. Moreover, P. donghaiense exhibited the highest affinity for intracellular ammonium. Our results characterized the differences in inorganic nitrogen uptake among the three typical bloom-forming algae, which may contribute to the formation of blooms in the coastal waters of the ECS.

A novel algicidal bacteria isolated from native snail lived in Taihu Lake against algal blooms: identification, degradation kinetic, and algicidal mechanism.

Harmful algal blooms (HABs) impacted negatively the water ecosystem, and produced toxic microcystins that poses toxic effect on liver, nervous, and genital system. The introduction of useful and adaptive algae-degrading microbes or bio-augmentation can be regarded as an efficient way to inhibit the outbreak of HABs. The purpose of this study is to evaluate the application potential of algicidal bacteria named XMC, which is isolated from native snails. Response surface methodology (RSM) experiments showed that self-characteristic and various external conditions affected the actual algae inhibition ability of XMC. In particular, actual algicidal efficiency was strongly depend on the temperature and growth stage of XMC, and the maximum algicidal rate could reach 93.95% within 7days. The degradation curve of Microcystis aeruginosa was compliant with the first-order kinetic model, which could be used to predict the degradation effect of Microcystis aeruginosa in engineering applications. The analysis results of algae dissolution products showed that algicidal bacteria XMC had both direct and indirect algicidal capacity. In addition, XMC had strong algicidal ability and greater environmental adaptability, and its algae dissolution products were environmentally friendly. All results indicated that XMC had the potential to be used in the bio-degradation of cyanobacteria bloom.

Comparative Study of Algal Responses and Adaptation Capability to Ultraviolet Radiation with Different Nutrient Regimes.

Frequent outbreaks of harmful algal blooms (HABs) represent one of the most serious outcomes of eutrophication, and light radiation plays a critical role in the succession of species. Therefore, a better understanding of the impact of light radiation is essential for mitigating HABs. In this study, Chlorella pyrenoidosa and non-toxic and toxic Microcystis aeruginosa were mono-cultured and co-cultured to explore algal responses under different nutrient regimes. Comparisons were made according to photosynthetically active radiation (PAR), UV-B radiation exerted oxidative stresses, and negative effects on the photosynthesis and growth of three species under normal growth conditions, and algal adaptive responses included extracellular polymeric substance (EPS) production, the regulation of superoxide dismutase (SOD) activity, photosynthetic pigments synthesis, etc. Three species had strain-specific responses to UV-B radiation and toxic M. aeruginosa was more tolerant and showed a higher adaptation capability to UV-B in the mono-cultures, including the lower sensitivity and better self-repair efficiency. In addition to stable μmax in PAR ad UV-B treatments, higher EPS production and enhanced production of photosynthetic pigments under UV-B radiation, toxic M. aeruginosa showed a better recovery of its photosynthetic efficiency. Nutrient enrichment alleviated the negative effects of UV-B radiation on three species, and the growth of toxic M. aeruginosa was comparable between PAR and UV-B treatment. In the co-cultures with nutrient enrichment, M. aeruginosa gradually outcompeted C. pyrenoidosa in the PAR treatment and UV-B treatment enhanced the growth advantages of M. aeruginosa, when toxic M. aeruginosa showed a greater competitiveness. Overall, our study indicated the adaptation of typical algal species to ambient UV-B radiation and the stronger competitive ability of toxic M. aeruginosa in the UV-radiated waters with severer eutrophication.

Advances in multiplex molecular detection technologies for harmful algae.

As the eutrophication of natural water bodies becomes more and more serious, the frequency of outbreaks of harmful algal blooms (HABs) mainly formed by harmful algae also increases. HABs have become a global ecological problem that poses a serious threat to human health and food safety. Therefore, it is extremely important to establish methods that can rapidly detect harmful algal species for early warning of HABs. The traditional morphology-based identification method is inefficient and inaccurate. In recent years, the rapid development of molecular biology techniques has provided new ideas for the detection of harmful algae and has become a research hotspot. The current molecular detection methods for harmful algal species mainly include fluorescence in situ hybridization, sandwich hybridization, and quantitative PCR (qPCR), but all of these methods can only detect single harmful algal species at a time. The establishment of methods for the simultaneous detection of multiple harmful algal species has become a new trend in the development of molecular detection technology because various harmful algal species may coexist in the natural water environment. The established molecular techniques for multiple detections of harmful algae mainly include gene chip, multiplex PCR, multiplex qPCR, massively parallel sequencing, antibody chip, and multiple isothermal amplification. This review mainly focuses on the principles, advantages and disadvantages, application progress, and application prospects of these multiple detection technologies, aiming at providing effective references not only for the fisheries but also for economic activities, environment, and human health.

Characteristics of Harmful Algal Species in the Coastal Waters of China from 1990 to 2017.

Harmful algal blooms (HABs) have occurred frequently in coastal waters of China, imposing negative effects on the marine ecological environment. A dataset of HABs and terrestrial runoff was collected and analyzed in this study, and factors responsible for HABs were further explored. Frequency and expansion of HABs peaked between 2001 and 2007, and although they have declined slightly since then, they have remained quite high. Frequency and accumulative area of HABs peaked in 2004–2005, and most occurred from April to August during these years. HABs occurred frequently in the Changjiang (Yangtze River) estuary, and Prorocentrum donghaiense, Noctiluca scientillans, Karenia mikimotoi, and Skeletonema costatum were the main algal species. The increases of eutrophication, the abnormal sea surface temperature caused by climate and ocean currents, and the species invasion caused by the discharge of ballast water may be important factors for the long-term outbreak of HABs in the Chinese coastal waters. These findings provide a better understanding of HABs in China, which will be helpful to further prevention and control.

Antibacterial activity of γFe2 O3 /TiO2 nanoparticles on toxic cyanobacteria from a lake in Southern Illinois.

Frequent outbreaks of harmful algal blooms (HABs) have brought adverse impacts on human health, economic viability, and recreational activities in many communities in the United States. Cyanobacteria (or blue-green algae) blooms are the most common type of HABs in surface water. Current bactericides for controlling the blooms are disadvantageous due to the recycling difficulty. In this study, an innovative magnetic nanomaterial-γFe2 O3 /TiO2 nanoparticle-was used to inactivate toxic cyanobacteria species found in a lake in Southern Illinois that frequently experienced HABs. Cyanotoxin genes of mcy, nda, cyr, and sxt were used for targeting microcystin-, nodularin-, cylindrospermopsin-, and saxitoxin-producing cyanobacteria, respectively, by quantitative polymerase chain reaction (PCR) method. It was found that the concentration of chlorophyll a presents a strong correlation (R2 = 0.6024) with the gene copy obtained from 16S rRNA targeted for all cyanobacteria, but not with that from individual toxigenic cyanobacteria. The inactivation efficiencies of the nanomaterials under visible light were as high as 5-log and 1-log for cyanobacteria species containing mcyE/ndaF and sxtA genes, respectively, an improvement over the treatment under darkness. These nanomaterials can be recycled by their magnetic properties for reuse. Communities susceptible to HAB outbreaks are expected to benefit from the developed method for mitigating the blooms. PRACTITIONER POINTS: Lab-made γFe2 O3 /TiO2 nanoparticles can be used to inactivate microcystin/nodularin- and saxitoxin-producing cyanobacteria species. qPCR method can be used for targeting toxic cyanobacteria; Chl a cannot be used as a standalone indicator for HABs. Better inactivation efficiency under visible light indicated possible application of the technology under sunlight for HAB mitigation from surface water.

Transcriptional Responses of Flavin-Containing Monooxygenase Genes in Scallops Exposed to PST-Producing Dinoflagellates Implying Their Involvements in Detoxification

Flavin-containing monooxygenase (FMO) is one of the most prominent xenobiotic metabolic enzymes. It can catalyze the conversion of heteroatom-containing chemicals to polar, readily excretable metabolites and is considered an efficient detoxification system for xenobiotics. Bivalves can accumulate paralytic shellfish toxins (PSTs) produced by dinoflagellates, especially during outbreaks of harmful algal blooms. Exploring FMO genes in bivalves may contribute to a better understanding of the adaptation of these species and the mechanisms of PSTs bioavailability. Therefore, through genome screening, we examined the expansion of FMO genes in two scallops (Patinopecten yessoensis and Chlamys farreri) and found a new subfamily (FMO_like). Our expression analyses revealed that, in both scallops, members of the FMO_N-oxide and FMO_like subfamilies were mainly expressed from the D-stage larvae to juveniles, whereas the FMO_GS-OX subfamily genes were mainly expressed at and prior to the trochophore stage. In adult organs, higher expressions of FMOs were observed in the kidney and hepatopancreas than in other organs. After exposure to PST-producing algae, expression changes in FMOs occurred in hepatopancreas and kidney of both scallops, with more members being up-regulated in hepatopancreas than in kidney for Alexandrium catenella exposure, while more up-regulated FMOs were found in kidney than in hepatopancreas of C. farreri exposed to A. minutum. Our findings suggest the adaptive functional diversity of scallop FMO genes in coping with the toxicity of PST-producing algae.

Effect of Modified Clay on the Growth Dynamics and Physio—Biochemical Response of Newly Hatched Larvae of the Marine Medaka (Oryzias melastigma)

An outbreak of harmful algal blooms (HABs) often leads to the death of fish and other marine organisms and causes serious losses to human economic activities. Modified clay (MC) technology is an effective way to control HABs. Although the material and preparation process are based on the premise of green and safety, the potential eco-environmental impacts of MC on non-target organisms should still have to receive attention before field applications can occur. Therefore, the effects of one commonly used modified clay, polyaluminum chloride-modified clay (PAC-MC), on the survival, growth, and oxidative stress of the marine medaka (Oryzias melastigma) were studied. The toxicity test results showed that the 96-h median lethal concentration (96-h LC50) of PAC-MC for newly hatched medaka larvae was 5.204 g/L, which was much higher than the concentration used on site (4–10 t/km2). Within the concentration range of PAC-MC used in this experiment (≤2 g/L), the morphology, heart rate, growth, and aluminum content of larvae did not change with the increase in the modified clay concentration. Low concentrations of PAC-MC (≤0.5 g/L) did not significantly affect catalase (CAT) activity, superoxide dismutase (SOD) activity, peroxidase (POD) activity, and the content of malondialdehyde (MDA), but higher concentrations of PAC-MC (such as 2 g/L) caused oxidative damage to the larvae and increased the antioxidant enzyme activity of the larvae. The present study revealed that under an effective dosage for treating harmful algal blooms on site, PAC-MC had no adverse effects on the survival, growth, oxidative stress, and aluminum content of the newly hatched marine medaka, which provides a scientific basis for the field application of modified clay.

Predicting coastal algal blooms with environmental factors by machine learning methods

Harmful algal blooms are a major type of marine disaster that endangers the marine ecological environment and human health. Since the algal bloom is a complex nonlinear process with time characteristics, traditional statistical methods often cannot provide good predictions. In this paper, we propose a method based on machine learning with the aim to predict the occurrence of algal blooms by environmental parameters. The features related to algal bloom growth have been experimented for achieving a good prediction of algal concentrations by a combination strategy. We validate the prediction performance on two real datasets from two locations in US and China, i.e., Scripps Pier, California and Sishili Bay, Shandong, respectively. The models and feature subsets have been selected to complete the missing data and predict the phytoplankton concentration. The results demonstrate the efficiency of our method in the short-term prediction of concentrations by selecting appropriate features. The comparison studies prove the advantage of our developed machine learning method. The importance of every features for the prediction performance reveals crucial factors for the outbreak of harmful algal blooms.

Common fate of sister lakes in Hulunbuir Grassland: Long-term harmful algal bloom crisis from multi-source remote sensing insights

With the increasing impact of drought and anthropogenic c activities, middle and high latitude lakes are increasingly facing exacerbated eutrophication. The sister lakes Hulun Lake and Buir Lake, the former located in the Hulunbuir Grassland in northeast China and the latter shared by China and Mongolia, have been exposed to outbreaks of harmful algal blooms (HABs) of varying degrees. In this study, multi-source remote sensing technologies were utilized to explore the essential factors causing HAB occurrences in the Hulun Basin. First, a simplified adjusted floating algae index (AFAI) algorithm was applied to invert the HAB sequence from 1984 to 2019. The results show that large-scale HABs were detected in both lakes on or close to the same days in 1984, 1999, and 2013. From a long-term perspective, the HAB events of Hulun Lake are more serious and intractable than those of Buir Lake in terms of outbreak frequency, duration, and scale. Furthermore, the effects of meteorological and hydrological conditions were evaluated quantitatively. In situ sampling of the two lakes highlights the limiting effect of nutrients on the algae flooding in Buir Lake with perennial outflow. In contrast, Hulun Lake turned into an internal flow lake without outlets from 2000 to 2012 and the decreasing water volume stimulated the accumulation of total nitrogen (TN) and phosphorus (TP), with averages of 2.36 and 0.21 mg/L, respectively. Analysis of the comprehensive driving factors demonstrates that the level of exogenous nutrients caused a difference in the severity of the HAB event between the sister lakes, which are largely determined by drought and eco-unfriendly anthropogenic activities. Our work emphasizes the pivotal role of substantial increases of nutrient loads and stricter regulations are necessary to curb further deterioration of this situation.

Isolation and Identification of Two Algae-Lysing Bacteria against Microcystis aeruginosa

Algae blooms present an environmental problem worldwide. In response to the outbreak of harmful algal blooms in cyanobacteria, the role of biological control has drawn wide attention, particularly for algicidal bacteria. The mechanism underlying algicidal activity was determined in our study. Algae-lysing bacteria used were separated from water and sediment collected from the Fenhe scenic spot of Taiyuan. Genetic and molecular identification was conducted by polymerase chain reaction amplification based on 16S rDNA gene. These bacterial strains were identified as Raoultella planticola and Aeromonas sp. The algae-lysing characteristics were evaluated on Microcystis aeruginosa. For the two algicidal bacteria, the high inoculation ratio (>8%) of bacteria strains contributed to the lytic effect. M. aeruginosa could be completely removed by these strains at different cell ages. However, the time used decreased with an increase in cell age. The removal rate was increased while M. aeruginosa was in the lag and logarithmic phases. The earlier bacteria strains could be inoculated, the sooner all algae could be removed. Both algicidal substances were protein, which could destroy the photosynthetic systems and break the cell of M. aeruginosa. The algicidal bacteria strain has important theoretical and practical significance for economic and feasible algae removal and provides good germplasm resources and technical support for the control of cyanobacterial bloom.

Harmful algal blooms significantly reduce the resource use efficiency in a coastal plankton community

Harmful algal blooms (HABs) have been investigated for their catastrophic effects on public health and aquaculture intensively, but the research about HABs effects on the diversity patterns and intrinsic functions of the plankton community based on a species identification with high resolution and accuracy has been scarce. We therefore investigated the shifts of plankton diversity via pyrosequencing during and around a natural dinoflagellate (Prorocentrum donghaiense) bloom and analyzed the effect of P. donghaiense abundance on the operationally-defined resource use efficiency (RUE) of plankton community to test our hypothesis that outbreaks of HABs will reduce RUE of the plankton community via shifting the plankton community structure, species composition in particular. We found that the species diversity of eukaryotic plankton community was significantly decreased during the bloom, as reflected in OTU (operational taxonomic unit) richness, and Pielou’s evenness index. Principal coordinates analysis indicated significant difference in plankton community structure between blooming and non-blooming periods. As hypothesized, the species richness was positively correlated to RUE (defined as the ratio of phytoplankton biomass to total phosphorus), and more importantly, the cell density of P. donghaiense exhibited significant negative correlation with RUE. Our results explicitly demonstrated HABs reduce RUE via reducing species richness (corresponding to a less occupancy of the trophic niches), which supports the previously documented notion that niche partitioning enhances RUE (a key ecosystem function). Also, our work provides striking evidence for the relationship between plankton species richness (or diversity) and community function (resource use efficiency) via studying on HABs, a natural but exceptional phenomenon, in addition to revealing a profound consequence of HABs.

Meta‐analysis reveals enhanced growth of marine harmful algae from temperate regions with warming and elevated CO2 levels

Elevated pCO2 and warming may promote algal growth and toxin production, and thereby possibly support the proliferation and toxicity of harmful algal blooms (HABs). Here, we tested whether empirical data support this hypothesis using a meta‐analytic approach and investigated the responses of growth rate and toxin content or toxicity of numerous marine and estuarine HAB species to elevated pCO2 and warming. Most of the available data on HAB responses towards the two tested climate change variables concern dinoflagellates, as many members of this phytoplankton group are known to cause HAB outbreaks. Toxin content and toxicity did not reveal a consistent response towards both tested climate change variables, while growth rate increased consistently with elevated pCO2. Warming also led to higher growth rates, but only for species isolated at higher latitudes. The observed gradient in temperature growth responses shows the potential for enhanced development of HABs at higher latitudes. Increases in growth rates with more CO2 may present an additional competitive advantage for HAB species, particularly as CO2 was not shown to enhance growth rate of other non‐HAB phytoplankton species. However, this may also be related to the difference in representation of dinoflagellate and diatom species in the respective HAB and non‐HAB phytoplankton groups. Since the proliferation of HAB species may strongly depend on their growth rates, our results warn for a greater potential of dinoflagellate HAB development in future coastal waters, particularly in temperate regions.

Nephrotonic and nephroprotective herbs from Persian medicine and evidences in new researches

Harmful algal blooms (HABs) have broken out frequently throughout the world in recent decades; they are caused by the rapid multiplication of algal cells in near-coastal waters polluted with nitrogen and phosphorus and greatly affect the quality of marine water and human health. Over the past several decades, climate change and increasing environmental degradation have provided favourable growth conditions for certain phytoplankton species. Therefore, it is essential to rapidly identify and enumerate harmful marine algae to control these species. In this study, quantitative PCR (qPCR) was used to detect four representative species of HABs that are widespread in the marine water of Hong Kong, namely, Alexandrium catenella, Pseudo-nitzschia spp., Karenia mikimotoi and Heterosigma akashiwo. We applied qPCR with the dye SYBR Green to detect Alexandrium spp. and Pseudo-nitzschia spp. and used TaqMan probe for the enumeration of Karenia mikimotoi and Heterosigma akashiwo. The total genomic DNA of these algae from Hong Kong marine water was extracted successfully using the CTAB method, and for each kind of alga, we constructed a ten-fold series of recombinant plasmid solutions containing certain gene fragments of 18S rDNA and ITS1-5.8S-ITS2 as standard samples. Ten-fold dilutions of the DNA of known numbers of the extracted algal cells were also used to create an additional standard curve. In this way, the relationship between the cell number and the related plasmid copy number was established. The qPCR assay displayed high sensitivity in monitoring marine water samples in which the low concentrations of harmful algae were not detected accurately by traditional methods. The results showed that the cell numbers of the four species were all in low abundance. For Alexandrium catenella, the cell abundances at 12 sites ranged from 3.8 × 102 to 4.3 × 103 cells L− 1, while H. akashiwo, K. mikimotoi and Pseudo-nitzschia ranged from 1.1 × 102 to 1.3 × 103, from 23 to 6.5 × 102 and from 45 to 3.3 × 103 cells L− 1, respectively. The concentrations of these algae were much lower than those observed during outbreaks of HABs in Hong Kong. These results may be useful for local aquaculture development and may provide effective suggestions and a theoretical basis for HAB monitoring and management.