Monitoring Of Harmful Algal Blooms Research Articles

Spatiotemporal distribution of paralytic shellfish poisoning (PSP) toxins in shellfish from Argentine Patagonian coast

Harmful algal blooms (HABs) have been recorded in the Chubut Province, Argentina, since 1980, mainly associated with the occurrence of paralytic shellfish poisoning (PSP) toxins produced by dinoflagellates of the genus Alexandrium. PSP events in this area impact on fisheries management and are also responsible for severe human intoxications by contaminated shellfish. Within the framework of a HAB monitoring program carried out at several coastal sites along the Chubut Province, we analyzed spatiotemporal patterns of PSP toxicity in shellfish during 2000–2011. The highest frequency of mouse bioassays exceeding the regulatory limit for human consumption was detected in spring and summer, with average values of up to ≈70% and 50%, respectively. By contrast, a lower percentage of positive bioassays (2–8%) or no toxicity at all was usually detected during autumn and winter. The most intense PSP events were usually observed between November and January, with values of up to 4,000 μg STX eq 100 g−1, and showed a marked interannual variability both in their magnitude and location. In addition, a severe PSP outbreak was recorded during autumn, 2009, at Camarones Bay, with toxicity values of up to 14,000 μg STX eq 100 g−1. The scallop Aequipecten tehuelchus showed significantly higher toxicity values compared to other shellfish species in SJG and SMG, suggesting a lower detoxification capacity. Our results contribute to the understanding of HABs dynamics on the Argentine Patagonian coast.

Scaling Up From Regional Case Studies to a Global Harmful Algal Bloom Observing System

Harmful algal blooms (HABs) produce local impacts in nearly all freshwater and marine systems. They are a global problem that require integrated and coordinated scientific understanding leading to regional responses and solutions. Given that these natural phenomena will never be completely eliminated, improved scientific understanding of HAB dynamics coupled with monitoring and ocean observations facilitates new prediction and prevention strategies. Regional efforts are underway worldwide to create state-of-the-art HAB monitoring and forecasting tools, vulnerability assessments, and observing networks. In the United States, these include Alaska, Pacific Northwest, California, Gulf of Mexico, Gulf of Maine, Great Lakes, and the U.S. Caribbean islands. This paper examines several regional programs in the United States, European Union, and Asia and concludes that there is no one-size-fits-all approach. At the same time, successful programs require strong coordination with stakeholders and institutional sustainability to maintain and reinforce them with new automating technologies, wherever possible, to ensure integration of modelling efforts with multiple regional to national programs. Recommendations for scaling up to a global observing system for HABs can be summarized as follows: 1) advance and improve cost-effective and sustainable HAB forecast systems that address the HAB-risk warning requirements of key end-users at global and regional levels; 2) design programs that leverage and expand regional HAB observing systems to evaluate emerging technologies for Essential Ocean Variables (EOVs) and Essential Biodiversity Variables (EBVs) in order to support interregional technology comparisons and regional networks of observing capabilities; 3) fill the essential need for sustained, preferably automated, near real-time information from nearshore and offshore sites situated in HAB transport pathways to provide improved, advanced HAB warnings; 4) merge ecological knowledge and models with existing Earth System Modelling Frameworks to enhance end-to-end capabilities in forecasting and scenario-building; 5) provide seasonal to decadal forecasts to allow governments to plan, adapt to a changing marine environment, and ensure coastal industries are supported and sustained in the years ahead; and 6) support implementation of the recent calls for action by the United Nations Decade 2010 Sustainable Development Goals (SDGs) to develop indicators that are relevant to an effective and global HAB early warning system.

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.

MULTI-TEMPORAL MODIS FOR DETECTION AND PUBLISHED LITERATURES FOR VALIDATION OF PHYTOPLANKTON BLOOMS IN SABAH AND SARAWAK, MALAYSIA

The coastal region of Sabah, Malaysia is mostly affected by harmful algal blooms (HABs) that often cause massive fish kills, and sometimes human casualties. Lack of a well-agreed, transparent and reproducible method, aperiodic nature and limited (technical) ability to monitor HAB at large regional scale, have all led to reinforced methodological improvement for bloom prediction, scientific management of coastal water resources, and regulatory attention. MODerate Resolution Imaging Spectroradiometer (MODIS), one of the well validated ocean colour sensors, enables acquiring high spectral resolution images, with short revisit time, freely accessible, and bay-wide coverage. Yet, the relative efficiency of MODIS-derived Chl-a (Chlorophyll-a), ABI (Algal Bloom Index), and nFLH (normalized Fluorescence Line Height) have not been compared in coastal regions of Malaysia. Fifteen MODIS Level 2 images acquired between 2005 and 2013 were considered as time series data that matched HAB events mentioned in previous studies. As historical real time in-situ data collection is often difficult (inaccessible), and thus unavailable; this project had to validate results obtained from literature, assuming that in-situ, would indicate HAB location at least during MODIS acquisition dates. Variations of HAB affected areas with temporal and spatial scales derived from bloom indices are shown in colour maps. Reliability of bloom information was measured by subjectively comparing HAB results provided by indices, and previously published in-situ results. ABI outperformed Chl-a and nFLH indices based on comparisons in both normal and HAB conditions occurring in the coastal waters of Sabah and Sarawak. The configuration and reliability retrieved from MODIS-ABI allowed their application in different likely tropical region as automated HAB monitoring systems and coastal water management programmes.

Determining remote sensing spatial resolution requirements for the monitoring of harmful algal blooms in the Great Lakes

Harmful algal blooms (HABs) have become a major health and environmental concern in the Great Lakes. In 2014, severe HABs prompted the State of Ohio to request NASA Glenn Research Center (GRC) to assist with monitoring algal blooms in Lake Erie. The most notable species of HAB is Microcystis aeruginosa, a hepatotoxin producing cyanobacteria that is responsible for liver complications for humans and other fauna that come in contact with these blooms. NASA GRC conducts semiweekly flights in order to gather up-to-date imagery regarding the blooms' spatial extents and concentrations. Airborne hyperspectral imagery is collected using two hyperspectral imagers, HSI-2 and HSI-3. Hyperspectral imagery is necessary in order to conduct experiments on differentiation of algal bloom types based on their spectral reflectance. In this analysis, imagery from September 19, 2016 was utilized to study the subpixel variability within the footprint of arbitrary sized pixels using several analysis techniques. This particular data set is utilized because it represents a worst case scenario where there is significant potential for public health concern due to high concentrations of microcystin toxin found in the water on this day and the concurrent observational challenges to accurately measure the algal bloom concentration variability with a remote sensing system due to the blooms high spatial variability. It has been determined that the optimal spatial resolution to monitor algal blooms in the Great Lakes is at most 50 m, and for much lower error 25 m, thus allowing for greater ease in identifying high concentration blooms near the surface. This resolution provides the best sensitivity to high concentration areas that are of significant importance in regard to human health and ecological damage.

Real time HABs mapping using NASA Glenn hyperspectral imager

The hyperspectral imaging system (HSI) developed by the NASA Glenn Research Center was used from 2015 to 2017 to collect high spatial resolution data over Lake Erie and the Ohio River. Paired with a vicarious correction approach implemented by the Michigan Tech Research Institute, radiance data collected by the HSI system can be converted to high quality reflectance data which can be used to generate near-real time (within 24 h) products for the monitoring of harmful algal blooms using existing algorithms. The vicarious correction method relies on imaging a spectrally constant target to normalize HSI data for atmospheric and instrument calibration signals. A large asphalt parking lot near the Western Basin of Lake Erie was spectrally characterized and was determined to be a suitable correction target. Due to the HSI deployment aboard an aircraft, it is able to provide unique insights into water quality conditions not offered by space-based solutions. Aircraft can operate under cloud cover and flight paths can be chosen and changed on-demand, allowing for far more flexibility than space-based platforms. The HSI is also able to collect data at a high spatial resolution (~1 m), allowing for the monitoring of small water bodies, the ability to detect small patches of surface scum, and the capability to monitor the proximity of blooms to targets of interest such as water intakes. With this new rapid turnaround time, airborne data can serve as a complementary monitoring tool to existing satellite platforms, targeting critical areas and responding to bloom events on-demand.

Colorimetric DNA-based assay for the specific detection and quantification of Ostreopsis cf. ovata and Ostreopsis cf. siamensis in the marine environment

Ostreopsis is a toxic benthic dinoflagellate largely distributed worldwide in tropical and temperate areas. In the Mediterranean Sea, periodic summer blooms have been reported and have become a serious concern due to their direct impact on human health and the environment. Current microalgae identification is performed via light microscopy, which is time-consuming and is not able to differentiate among Ostreopsis species. Therefore, there is mature need for rapid, specific and easy-to-use detection tools. In this work, a colorimetric assay exploiting a combination of recombinase polymerase amplification (RPA) and a sandwich hybridisation assay was developed for O. cf. ovata and O. cf. siamensis detection and quantification. The specificity of the system was demonstrated by cross-reactivity experiments and calibration curves were successfully constructed using genomic DNA, achieving limits of detection of 10 and 14 pg/μL for O. cf. ovata and O. cf. siamensis, respectively. The assay was applied to the analysis of planktonic and benthic environmental samples from different sites of the Catalan coast. Species-specific DNA quantifications were in agreement with qPCR analysis, demonstrating the reliability of the colorimetric approach. Significant correlations were also obtained between DNA quantifications and light microscopy counts. The approach may be a valuable tool to provide timely warnings, facilitate monitoring activities or study population dynamics, and paves the way towards the development of in situ tools for the monitoring of harmful algal blooms.

Development of a TaqMan qPCR assay for detection of Alexandrium spp and application to harmful algal bloom monitoring.

The Genus Alexandrium is a widespread dinoflagellate marine phytoplankton that is the primary causative organism causing Paralytic Shellfish Poisoning (PSP) intoxications in European waters. EU food safety directives specify that EU Member States must implement a routine monitoring programme to mitigate risks associated with bio-accumulation of biotoxins by bivalve shellfish, such as those produced by Alexandrium. This strategic drive comprises of both direct testing of bivalve flesh for the presence of regulated toxins and an early warning phytoplankton monitoring programme. In the UK the flesh testing moved away from animal bio-assays to analytical chemistry techniques, whereas phytoplankton monitoring methods have seen little technological advancement since implementation. Methods currently utilize light microscopy and manual enumeration of different algal species. These methods although proven are time consuming, reliant on highly trained staff, have high limits of detection (LOD) with low specificity, unable to reliably identify Alexandrium to species level. The implications of these limitations of the techniques mean that in the case of Alexandrium the LOD is also the action limit and as such it is easy to miss positive samples affecting the efficacy of any early warning strategy. This study outlines the development, preliminary method characterisation, validation and trial implementation of an alternative early warning technique, utilizing quantitative PCR to identify water samples containing Alexandrium cells. The approach outlined in this document, showed an improved correlation with flesh toxicity, improved sensitivity, improved throughput compared to traditional light microscopy methods and there was also good correlation with higher cell abundance samples when compared to the light microscopy results. The application of this approach to routine water samples was explored and was found to demonstrate potential as a corroborative method for use during flesh intoxication episodes. This study offers potential for future improvements in the accuracy and sensitivity of phytoplankton monitoring whilst ensuring continuity of public safety, providing cost savings and offering new research opportunities.

Satellite monitoring of harmful algal blooms in the Western Basin of Lake Erie: A 20-year time-series

Blooms of harmful cyanobacteria (cyanoHABs) have occurred on an annual basis in western Lake Erie for more than a decade. Previously, we developed and validated an algorithm to map the extent of the submerged and surface scum components of cyanoHABs using MODIS ocean-color satellite data. The algorithm maps submerged cyanoHABs by identifying high chlorophyll concentrations (>18 mg/m3) combined with water temperature >20 °C, while cyanoHABs surface scums are mapped using near-infrared reflectance values. Here, we adapted this algorithm for the SeaWiFS sensor to map the annual areal extents of cyanoHABs in the Western Basin of Lake Erie for the 20-year period from 1998 to 2017. The resulting classified maps were validated by comparison with historical in situ measurements, exhibiting good agreement (81% accuracy). Trends in the annual mean and maximum total submerged and surface scum extents demonstrated significant positive increases from 1998 to 2017. There was also an apparent 76% increase in year-to-year variability of mean annual extent between the 1998–2010 and 2011–2017 periods. The 1998–2017 time-series was also compared with several different river discharge nutrient loading metrics to assess the ability to predict annual cyanoHAB extents. The prediction models displayed significant relationships between spring discharge and cyanoHAB area; however, substantial variance remained unexplained due in part to the presence of very large blooms occurring in 2013 and 2015. This new multi-sensor time-series and associated statistics extend the current understanding of the extent, location, duration, and temporal patterns of cyanoHABs in western Lake Erie.

Monitoring Coastal Chlorophyll-a Concentrations in Coastal Areas Using Machine Learning Models

Harmful algal blooms have negatively affected the aquaculture industry and aquatic ecosystems globally. Remote sensing using satellite sensor systems has been applied on large spatial scales with high temporal resolutions for effective monitoring of harmful algal blooms in coastal waters. However, oceanic color satellites have limitations, such as low spatial resolution of sensor systems and the optical complexity of coastal waters. In this study, bands 1 to 4, obtained from Landsat-8 Operational Land Imager satellite images, were used to evaluate the performance of empirical ocean chlorophyll algorithms using machine learning techniques. Artificial neural network and support vector machine techniques were used to develop an optimal chlorophyll-a model. Four-band, four-band-ratio, and mixed reflectance datasets were tested to select the appropriate input dataset for estimating chlorophyll-a concentration using the two machine learning models. While the ocean chlorophyll algorithm application on Landsat-8 Operational Land Imager showed relatively low performance, the machine learning methods showed improved performance during both the training and validation steps. The artificial neural network and support vector machine demonstrated a similar level of prediction accuracy. Overall, the support vector machine showed slightly superior performance to that of the artificial neural network during the validation step. This study provides practical information about effective monitoring systems for coastal algal blooms.

Compact and Low-Cost Fluorescence Based Flow-Through Analyzer for Early-Stage Classification of Potentially Toxic Algae and in Situ Semiquantification.

The occurrence and intensity of (harmful) algal blooms (HABs) have increased through the years due to rapidly changing environmental conditions. At the same time, the demand for low-cost instrumentation has increased substantially, enabling the real-time monitoring and early-stage detection of HABs. To meet this challenge, we have developed a compact multi-wavelength fluorometer for less than 400 USD. This is possible by using readily available and low-cost optical and electronic components. Its modular design results in a highly versatile and flexible monitoring tool. The algae detection module enables a continuous identification and control of relevant algal groups based on their spectral characteristics with a detection limit of 10 cells per liter. Besides its usage as a benchtop module in the laboratory, the algae module has been integrated into submersible housings and applied in coastal environments. During its first in situ application in the Port of Genoa, seawater samples of mixed algal composition were used to demonstrate the successful discrimination of cyanobacteria and dinophytes as well-known toxin producing classes. Fabrication, operation, and performance as well as its first in situ application are addressed.

Evaluating the portability of satellite derived chlorophyll-a algorithms for temperate inland lakes using airborne hyperspectral imagery and dense surface observations

This study evaluated the performances of twenty-nine algorithms that use satellite-based spectral imager data to derive estimates of chlorophyll-a concentrations that, in turn, can be used as an indicator of the general status of algal cell densities and the potential for a harmful algal bloom (HAB). The performance assessment was based on making relative comparisons between two temperate inland lakes: Harsha Lake (7.99 km2) in Southwest Ohio and Taylorsville Lake (11.88 km2) in central Kentucky. Of interest was identifying algorithm-imager combinations that had high correlation with coincident chlorophyll-a surface observations for both lakes, as this suggests portability for regional HAB monitoring. The spectral data utilized to estimate surface water chlorophyll-a concentrations were derived from the airborne Compact Airborne Spectral Imager (CASI) 1500 hyperspectral imager, that was then used to derive synthetic versions of currently operational satellite-based imagers using spatial resampling and spectral binning. The synthetic data mimics the configurations of spectral imagers on current satellites in earth’s orbit including, WorldView-2/3, Sentinel-2, Landsat-8, Moderate-resolution Imaging Spectroradiometer (MODIS), and Medium Resolution Imaging Spectrometer (MERIS). High correlations were found between the direct measurement and the imagery-estimated chlorophyll-a concentrations at both lakes. The results determined that eleven out of the twenty-nine algorithms were considered portable, with r2 values greater than 0.5 for both lakes. Even though the two lakes are different in terms of background water quality, size and shape, with Taylorsville being generally less impaired, larger, but much narrower throughout, the results support the portability of utilizing a suite of certain algorithms across multiple sensors to detect potential algal blooms through the use of chlorophyll-a as a proxy. Furthermore, the strong performance of the Sentinel-2 algorithms is exceptionally promising, due to the recent launch of the second satellite in the constellation, which will provide higher temporal resolution for temperate inland water bodies. Additionally, scripts were written for the open-source statistical software R that automate much of the spectral data processing steps. This allows for the simultaneous consideration of numerous algorithms across multiple imagers over an expedited time frame for the near real-time monitoring required for detecting algal blooms and mitigating their adverse impacts.

A novel portable filtration system for sampling and concentration of microorganisms: Demonstration on marine microalgae with subsequent quantification using IC-NASBA

This paper presents a novel portable sample filtration/concentration system, designed for use on samples of microorganisms with very low cell concentrations and large volumes, such as water-borne parasites, pathogens associated with faecal matter, or toxic phytoplankton. The example application used for demonstration was the in-field collection and concentration of microalgae from seawater samples. This type of organism is responsible for Harmful Algal Blooms (HABs), an example of which is commonly referred to as “red tides”, which are typically the result of rapid proliferation and high biomass accumulation of harmful microalgal species in the water column or at the sea surface. For instance, Karenia brevis red tides are the cause of aquatic organism mortality and persistent blooms may cause widespread die-offs of populations of other organisms including vertebrates. In order to respond to, and adequately manage HABs, monitoring of toxic microalgae is required and large-volume sample concentrators would be a useful tool for in situ monitoring of HABs. The filtering system presented in this work enables consistent sample collection and concentration from 1 L to 1 mL in five minutes, allowing for subsequent benchtop sample extraction and analysis using molecular methods such as NASBA and IC-NASBA. The microalga Tetraselmis suecica was successfully detected at concentrations ranging from 2 × 105 cells/L to 20 cells/L. Karenia brevis was also detected and quantified at concentrations between 10 cells/L and 106 cells/L. Further analysis showed that the filter system, which concentrates cells from very large volumes with consequently more reliable sampling, produced samples that were more consistent than the independent non-filtered samples (benchtop controls), with a logarithmic dependency on increasing cell numbers. This filtering system provides simple, rapid, and consistent sample collection and concentration for further analysis, and could be applied to a wide range of different samples and target organisms in situations lacking laboratories.

Advection of Karenia brevis blooms from the Florida Panhandle towards Mississippi coastal waters

Harmful Algal Blooms (HABs) of Karenia brevis have been documented along coastal waters of every state bordering the Gulf of Mexico (GoM). Some Gulf Coast locations, such as Florida and Texas, suffer from recurrent intense and spatially large blooms, while others such as Mississippi seem to rarely observe them. The main objective of this work is to understand the dynamics that led to the K. brevis bloom in Mississippi coastal waters in fall 2015. Blooms of K. brevis from the Florida Panhandle region are often advected westward towards the Mississippi-Alabama coast; however there is interannual variability in their presence and intensity in Mississippi coastal waters. The 2015 K. brevis bloom was compared to the 2007 Florida Panhandle K. brevis bloom, which showed a westward advection pattern, but did not intensify along the Mississippi coast. Cell counts and flow cytometry were obtained from the Mississippi Department of Marine Resources, Alabama Department of Public Health, Florida Fish and Wildlife Conservation Commission and The University of Southern Mississippi. Ocean color satellite imagery from the Moderate Resolution Imaging Spectroradiometer onboard the Aqua satellite was used to detect and delineate the blooms in 2007 and 2015. Two different regional applications of NCOM-Navy Coastal Ocean Model (1-km resolution NCOM-GoM/Gulf of Mexico and 6-km resolution NCOM-IASNFS/Intra Americas Sea Nowcast Forecast System) were used to understand the circulation and transport pathways. A Lagrangian particle tracking software was used to track the passive movement of particles released at different locations for both bloom events. Ancillary data (e.g., nutrients, wind, salinity, river discharge) from local buoys, monitoring stations and coincident oceanographic cruises were also included in the analysis. The blooms of K. brevis reached the Mississippi coast both years; however, the bloom in 2007 lasted only a few days and there is no evidence that it entered the Mississippi Sound. Two major differences were observed between both years. First, circulation patterns in 2015 resulting from an intense westward-northwestward that persisted until December allowed for continuous advection, whereas this pattern was not evident in 2007. Second, local river discharge was elevated throughout late fall 2015 while 2007 was below the average. Thus, elevated discharge may have provided sufficient nutrients for bloom intensification. These results illustrate the complex, but important interactions in coastal zones. Further, they emphasize the importance in establishing comprehensive HAB monitoring programs, which facilitate our understanding of nutrient and phytoplankton dynamics, and stress the importance for multi-agency cooperation across state boundaries.

Microcystin biosynthesis in Microcystis aeruginosa: Indirect regulation by iron variation

Harmful cyanobacterial blooms have been observed in various water bodies all over the world and their secondary metabolite, microcystins (MCs), have threatened aquatic organisms and human health. Meanwhile, iron is one of the key nutrients for algal growth due to its important role in many physiological functions. In our study, different iron regimes were set to investigate their effects on physiological indices and gene expressions of MC biosynthesis in toxic Microcystis aeruginosa. The results showed that iron addition promoted algal growth and chlorophyll-a (Chl-a) production. Photosynthetic capacity was inhibited under iron limitation, which blocked the electron transport chain, intensified the production of reactive oxygen species (ROS) and further damaged algal antioxidant defensive system in cells. Moreover, unsynchronized changes of microcystin-leucine-arginine (MC-LR) level and mcy gene expressions were observed in all iron regimes. Interestingly, despite that the intracellular quantity of MC-LR under iron limitation was less than that under iron-replete condition, the potential toxicity was greater in the former. Iron variation had little influence on the excretion of the toxin, which can be further confirmed by scanning electron microscopic observations. In consequence, we propose an indirect influence of iron on MC biosynthesis that starts with the decreased photosynthetic capacity and energy production by iron limitation, followed by the damaged electron transport in cells, and eventually causes the variation of mcy gene expressions due to energy shortage. Therefore, our study has provided the evidences for the close relationship between iron variation and MC biosynthesis in M. aeruginosa, suggesting that iron should be taken into account during the monitoring of harmful algal blooms in the future.

Quantitative real‐time PCR detection of a harmful unarmoured dinoflagellate, Karlodinium australe (Dinophyceae)

SUMMARYWe investigated a harmful algal bloom (HAB) associated with the massive fish kills in Johor Strait, Malaysia, which recurred a year after the first incident in 2014. This incident has urged for the need to have a rapid and precise method in HAB monitoring. In this study, we develop a SYBR green‐based real‐time PCR (qPCR) to detect the culpable dinoflagellate species, Karlodinium australe. Species‐specific qPCR primers were designed in the gene region of the second internal transcribed spacer of the ribosomal RNA gene (rDNA). The species specificity of the primers designed was evaluated by screening on the non‐target species (Karlodinium veneficum, Takayama spp., and Karenia spp.) and no cross‐detection was observed. The extractable gene copies per cell of K. australe determined in this study were 19 998 ± 505 (P < 0.0001). Estimation of cell densities by qPCR in the experimental spiked samples showed high correlation with data determined microscopically (R2 = 0.93). Using the qPCR assay developed in this study, we successfully detected the 2015 bloom species as K. australe. Single‐cell PCR and rDNA sequencing from the field samples further confirmed the finding. With the sensitivity as low as five cells, the qPCR assay developed in this study could effectively and rapidly detect cells of K. australe in the environmental samples for monitoring purpose.

HARMFUL ALGAL BLOOM 2012 EVENT VERIFICATION IN LAMPUNG BAY USING RED TIDE DETECTION ON SPOT 4 IMAGE

In mid-December 2012, harmful algal bloom phenomenon occurred in Lampung Bay. Harmful Algal Bloom (HAB) is blooming of algae in aquatic ecosystems. It has negative impact on living organism, due to its toxic. This study was applied Red Tide (RT) detection algorithm on SPOT 4 images and verified the distribution of HAB 2012 event in Lampung Bay. The HAB event in 2012 in Lampung Bay can be detected by using RT algorithm on SPOT 4 images quantitatively and qualitatively. According to field measurement, the phytoplankton blooming which happen at Lampung Bay in 2012 were Cochlodinium sp. Image analysis showed that Cochlodinium sp has specific pattern of RT with values, digitally, were 13 to 41 and threshold value of red band SPOT 4 image was 57. The total area of RT distribution, which are found in Lampung Bay, was 11,545.3 Ha. Based on the RT classification of RT images and field data measurement, the RT which is caused many fishes died on the western coastal of Lampung Bay spread out from Bandar Lampung City to Batumenyan village. By using confusion matrix, the accuracy of this this method was 74.05 %. This method was expected to be used as early warning system for HAB monitoring in Lampung Bay and perhaps in another coastal region of Indonesia.

Occurrence of four species of algae in the marine water of Hong Kong

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 4.3×103cellsL−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 3.3×103cellsL−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.

Use of biosensors for the detection of marine toxins.

Increasing occurrences of harmful algal blooms (HABs) in the ocean are a major concern for countries around the globe, and with strong links between HABs and climate change and eutrophication, the occurrences are only set to increase. Of particular concern with regard to HABs is the presence of toxin-producing algae. Six major marine biotoxin groups are associated with HABs. Ingestion of such toxins via contaminated shellfish, fish, or other potential vectors, can lead to intoxication syndromes with moderate to severe symptoms, including death in extreme cases. There are also major economic implications associated with the diverse effects of marine biotoxins and HABs. Thus, effective monitoring programmes are required to manage and mitigate their detrimental global effect. However, currently legislated detection methods are labour-intensive, expensive and relatively slow. The growing field of biosensor diagnostic devices is an exciting area that has the potential to produce robust, easy-to-use, cost-effective, rapid and accurate detection methods for marine biotoxins and HABs. This review discusses recently developed biosensor assays that target marine biotoxins and their microbial producers, both in harvested fish/shellfish samples and in the open ocean. The effective deployment of such biosensor platforms could address the pressing need for improved monitoring of HABs and marine biotoxins, and could help to reduce their global economic impact.

Temporal and spatial characteristics of harmful algal blooms in Qingdao Waters, China

Qingdao waters, including both the semi-enclosed Jiaozhou Bay (JB) and the adjacent water out of JB (OJB), have been the areas that are most frequently affected by harmful algal blooms (HABs) in the western Yellow Sea (west of 124°E). In this research, HAB occurrences in Qingdao waters from 1990 to 2009 were investigated using spatial tools in geographic information system (GIS) and are discussed in terms of their connection to temporal variation. Additionally, the effects of each HAB occurrence were further evaluated using a simple model. The calculated results were then visualized using a GIS software to indicate the effects of HABs in Qingdao waters during the entire period. As a result, the OJB was proven to be responsible for the frequent HAB occurrences in Qingdao waters after 2000, although JB was traditionally believed to be the principle source of HAB occurrences in Qingdao waters. In addition, increasing nitrogen and N/P structure imbalance were essential for increasing HAB occurrences in Qingdao waters throughout the entire period, especially for the recent HAB occurrences in the OJB. The results of this research would improve the current understanding on HAB occurrences in Qingdao waters, which would benefit HAB monitoring and the implementation of a control strategy in China as well.