Red Tide Occurrence Research Articles

Red tide dataset in the waters around the Korean Peninsula

Red tide blooms are increasing worldwide. Since 1995, Margalefidium polykrikoides blooms have occurred frequently in the waters around the Korean Peninsula. These blooms generally appear first on the South Sea of Korea in summer. When they occur on a large scale, they extend to the East Sea of Korea and the West Sea of Korea, causing great damage to fisheries and marine ecosystems. Harmless red tide can also adversely affect the environment of the waters by causing oxygen depletion in waters when occurring at high density. Currently, the National Institute of Fisheries Science (NIFS) is providing the daily red tide report based on M. polykrikoides red tide species. This report contains red tide species, location, and cell abundance information, but is limited to use as cell abundance data based on exact location. In addition, the waters around the Korean peninsula have different characteristics, so that the optical characteristics and seawater environment are different for each water. In the East Sea in Aug. 2013, the West Sea in Aug. 2016, the South Sea in Aug. 2018, and the South Sea in Aug. and Sep. 2019, during red tide season, dataset were obtained for red tide cell abundance, spectrum, chlorophyll concentration, and suspended particulate matter concentration. Noctiluca scintillans species were observed in the field survey conducted in 2016, and M. polykrikoides was mainly found in the other field surveys. Location-based red tide cell abundance data and seawater environment information obtained during red tide occurrence will be useful data for the construction of red tide warning system to reduce damage due to red tide blooms.

The dynamics of dissolved inorganic nitrogen species mediated by fresh submarine groundwater discharge and their impact on phytoplankton community structure

Submarine groundwater discharge (SGD)-driven nutrient inputs have long been speculated to sustain the high frequency of red tide occurrence in Tolo Harbour, Hong Kong, for its larger flux and higher nutrient loadings than river discharge. Based on analysis of high resolution time series biogeochemical and climatological data from 2000 to 2015, fresh SGD-derived dissolved inorganic nitrogen (DIN) is found to be a significant regulator of the annual cycle of phytoplankton community structure in the harbour. In the wet season, fresh SGD supplies nutrients with NH4+:NO3– ratio < 1 to the seawater, meanwhile creates an intensive vertical stratification environment. As a result, diatom which is a NO3– specialist, is prone to be the major group in the harbour. Fresh SGD delivers a same orders of magnitude of DIN as river and precipitation, but it is more important to phytoplankton community structure dynamics because fresh groundwater has smaller NH4+:NO3– ratio that significantly changes the ratio in the harbour. In the dry season, with the decline of fresh SGD and the ease of stratification, vertical mixing uplifts the nutrient (NH4+:NO3– ratio > 1) released from the bottom sediment leading to a NH4+ dominant environment in water column. Dinoflagellate and other groups then become dominant species of phytoplankton in the harbour. Fresh SGD has a major influence on the NH4+:NO3– ratio in the seawater compared to tide-driven SGD, even though the latter contributes a larger proportion SGD. Tide-driven SGD also produces NH4+ and NO3–, but NH4+:NO3– ratio are mainly subject to the beach environment (bare/mangrove beach), which does not change much seasonally, thus dominant DIN species do not change significantly throughout a year. In a conclusion, fresh SGD plays the most important role among all the endmembers in regulating the DIN composition in Tolo Harbour and its fluctuation mediates the phytoplankton community structure.

ANALYSIS OF THE RED TIDE OCCURRENCE PATTERN WHEN HIGH WATER TEMPERATURE

Abstract. In 1982, the red tide caused by Cochlodimium polykrikodies occurred at first in Jinhae Bay in Korea. Since then, it causes serious fisheries damage every year. In 2018, red tide occurred when high water temperature. We analyzed red tide occurrence pattern when high water temperature. Red tide occurrence date, occurrence area caused by the Cochlodinium polykrikoides were used provided by National Institute of Fisheries Science. SST data were used the GHRSST Level 4 OSTIA data provided by NOAA. The red tide occurred July 14 to September 2 in 2013, July 29 to October 4 in 2014, August 5 to September 23 in 2015, and July 23 to August 8 in 2018 in Korea. The nearest SST data from the red tide occurrence area were extracted. When red tide occurred, SST was 22~28 °C in 2013, 23~25 °C in 2014, 21~27 °C in 2015, 26~28 °C in 2018. SST in 2013 was increasing trend and 2015 was downward trend. SST in 2018 occurred at high water temperatures above 25 °C. The spatial pattern by using the self-organizing map (3x3 map), node 4 was the highest frequency (16.9%). It is considered that it appears at the beginning and end of red tide occurrence. Node 1 was 16.3% frequency, it showed at the end of 2014 and 2015. SST of node 1 and 4 maintained 22~23 °C on the southern sea of Korea. Node 9 was 13.9%, which is the late 2013 and 2018. Node 9 showed high temperature pattern of more than 26 °C in the southern sea of Korea.

PREDICTION AND MAPPING OF COCHLODINIUM POLYKRIKOIDES RED TIDE USING MACHINE LEARNING UNDER IMBALANCED DATA

Abstract. Cochlodinium polykrikoides (C. polykrikoides) is a phytoplankton that causes red tides every year in the middle of the South Sea of Korea. C. polykrikoides is a harmful Algae that has migratory ability and causes the fisheries damage over a long period of wide sea area if it causes red tide once. To minimize red tide damage, it is important to anticipate and prepare the red tide occurrence timing and location in advance. In this study, we predicted the occurrence of red tide of C. polykrikoides using machine learning techniques and compared the results of each algorithm. Logistic regression model, decision tree model, and multilayer neural network model were used for prediction of red tide occurrence. To produce the data set for model learning, we used the red tide occurrence map provided by the National Institute of Fisheries Science, the Local Data Assimilation and Prediction System (LDAPS) provided by the Korea Meteorological Agency, and the G1SST provided by the National Oceanic and Atmospheric Administration (NOAA). The feature vectors used for modeling consisted of 59 elements, which were made by using temperature, water temperature, precipitation, solar radiation, wind direction and wind speed. Only a very small number of red tide cases can be collected compared to the case of no red tide cases. Thus, an imbalance data problem arises in the data set. To overcome this imbalanced data problem, we used adding noise after oversampling to data of red tide occurrence to solve the difference of data between two classes.The data set is divided into 8 : 2 to prevent over-fitting and 80% is used as the learning data. The remaining 20% was used to evaluate the performance of each model. As a result of evaluating the prediction performance of each model, the multilayer neural network model showed the highest prediction accuracy.

Relationship between the Occurrence of Red Tides and the Dynamic Response Mechanisms in the Northern Beibu Gulf

Chen, B.; Dong, D.; Qin, X.; Xu, M.; Chen, X., and Shi, M., 2019. Relationship between the occurrence of red tides and the dynamic response mechanisms in the northern Beibu Gulf. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 185–193. Coconut Creek (Florida), ISSN 0749-0208.Unlike the common outbreak mechanism of red tides, the northern Beibu Gulf in the Guangxi Zhuang Autonomous Region of China experiences frequent red tides with distinct characteristics, such as large distances from the mainland and the presence of industrial pollution. By tracing the sources and transport of the high concentrations of nitrogen and phosphorus, the relationship between pollutant transport and the dynamic response mechanisms was explored. The results showed that the concentrations of nitrogen and phosphorus nutrients in the areas of red tide outbreaks near Weizhou Island and in the Qinzhou Gulf in the northern Beibu Gulf were higher than those in the surrounding areas. However, the high concentrations of nitrogen and phosphorus nutrients in the northern Beibu Gulf did not originate from terrestrial pollution from Guangxi Province; rather, these pollutants originated on the east coast of China and were transported through the Qiongzhou Strait. The primary sources were the Pearl River Estuary and the coastal waters of eastern Guangdong. In addition, the differences in the concentration distributions of nitrogen and phosphorus nutrients between the east and west coasts of the Qinzhou Gulf in the northern Beibu Gulf were clearly related to dynamic response mechanisms.

U-Net Convolutional Neural Network Model for Deep Red Tide Learning Using GOCI

Kim, S.M.; Shin, J.; Baek, S., and Ryu, J.-H., 2019. U-Net convolutional neural network model for deep red tide learning using GOCI. In: Jung, H.-S.; Lee, S.; Ryu, J.-H., and Cui, T. (eds.), Advances in Remote Sensing and Geoscience Information Systems of Coastal Environments. Journal of Coastal Research, Special Issue No. 90, pp. 302-309. Coconut Creek (Florida), ISSN 0749-0208.GOCI launched in 2010 is a geostationary satellite image sensor that monitors ocean color. It captures 8-band spectral satellite images of northeast Asian regions hourly, eight times a day. The spatial resolution of GOCI is about 500 m. GOCI is capable of monitoring a large ocean area for sensing various events such as red tide occurrences, tidal movement changes and ocean disasters. In this study, we propose a deep convolutional neural network model, U-Net, for automatic pixel-based detection of red tide occurrence from the spectral images captured by GOCI. We construct two training datasets with GOCI images and the corresponding red-tide index maps (RI maps) accumulated through 2011 to 2018. The RI maps indicate where red tides occurred and what kind of red tide species were there. U-Net consists of five U-shaped encoder and decoder layers to extract spectral features relating to red-tide species from GOCI images. We compared the performances of U-Nets trained from two datasets (i) consisting of only four spectral bands and (ii) consisting of all six spectral bands. The RI maps predicted by the trained U-Nets showed considerably matching spatial occurrence tendencies of three red tide species to the ground truths for validation images. The mean target accuracy with the four-band dataset was 13 % lower than that with the six-band dataset. The trained U-Net for pixel-wise red tide detection would be able to effectively inspect red tide occurrences in the huge area of water surrounding the Korean peninsula.

The Response of Pollution Load from Coastal River Waterfront on Red Tides in South Sea

Iqbal, M.M.; Shoaib, M. and Agwanda, P., 2019. The response of pollution loadings of the coastal river waterfront on red tides in South Sea. In: Lee, J.L.; Yoon, J.-S.; Cho, W.C.; Muin, M., and Lee, J. (eds.), The 3rd International Water Safety Symposium. Journal of Coastal Research, Special Issue No. 91, pp. 231-235. Coconut Creek (Florida), ISSN 0749-0208.The red tide is an abnormal water environment phenomenon, which harshly effects economic growth, aquatic life, and human health. It characterizes a major ecological problem in the marine ecosystem universally. The process of red tide prevalence has been investigated for several years, and a lot of systems and approaches have been established. Though previous researches have efficiently explored the knowledge of the process involved in red tide development, the combined effect of the coastal riverfront water quality of different coastal areas on red tide development has not attained sufficient consideration. The study has examined the connection between red tides and pollution load from the coastal waterfront. The research assesses the water quality of the coastal river waterfront (Tamjin River) using Water Quality Analysis Simulation Program (WASP 8.1) and nutrient load discharged into the West Sea using LOADEST. Through long-term investigation of the study region, it was found that red tides only occur in the late summer season. By investigating all the nutrient's load, TN (Total Nitrogen) and Chl-a (Chlorophyll-a) shows significant impact on red tides to some extent. The result of this study reveals that the pollution load from the coastal waterfront is also one of the possible factors of red tide occurrence in coastal region of the South Sea near the Tamjin River delta.

Effects of rainfall-runoff pollution on eutrophication in coastal zone: a case study in Shenzhen Bay, southern China

Abstract The concentration of human activities in coastal cities results in the increase of nutrient salts released into the coastal environment and is identified as a major environmental problem for coastal zone management. Large amounts of nitrogen and phosphorus are transported by rainwater-runoff from urban catchments to coastal zones during episodic rainfall events inducing eutrophication problems and increasing the risk of red tide occurrence. This study used a coupled model based on the Storm Water Management Model (SWMM) and Environment Fluid Dynamic Code (EFDC) to simulate the rainfall-runoff pollution load and its effects on eutrophication in Shenzhen Bay, southern China. A storm event of 2014 was used to build the modeling scenarios and thus analyzed the spatial-temporal variation of the rainfall-runoff pollution. The results indicated that: (i) rainfall-runoff pollution loads accounted for 60–80% of the total pollution loads, and rainfall-runoff pollution can result in a short-term impact pollution load on the receiving seawater body; (ii) the transportation of nutrient salts in the coastal zone and the nutrient salts absorbing process by algae are at different times, which suggests urban rainfall-runoff pollution has evidently an effect on variation of the concentration of chlorophyll-A in the bay, and with increasing distance to the city, the seawater body is gradually less affected by rainfall-runoff pollution.

Numerical study on the summertime patches of red tide in the adjacent sea of the Changjiang (Yangtze) River Estuary, China

High incident rates of red tide have occurred off the coast of the Changjiang (Yangtze) River Estuary in summer, resulting from a magnified population growth discharging substantial nutrient loads into this vicinity. The presence of elevated Chlorophyll-a concentrations (≥36.3 μg/l), low suspended sediment concentrations in surface and mid-layers (<10 mg/l), a strong saline front and surface water temperature gradient, veering surface winds, and a bimodal shape to the Changjiang Diluted Water (CDW) revealed two red tide patches appearing between August 6–13, 2010. Two distinguishable hydrodynamic driving mechanisms, connected to these incidents, are diagnosed. Field observations and numerical simulations determined a red tide patch in the northeastern offshore area is caused by a northeast transport of the CDW truncated by a northwest intrusion of the Taiwan Warm Current (TWC) as winds deviated. Red tide occurrence in the southern nearshore area originated from a plume front where CDW interfaces with the TWC.

Hot spot analysis on the red tide occurrence in the South Sea of Korea using GIS

Red tide occurs usually every years in the south sea of Korea and causes damage to a fishing farm, and it researched to analyze the spatial characteristics and the movement characteristics of red tide are continuing. In this study, the occurrence of blooming of Cochlodinium polykrikoides in the south sea of Korea, 2013 was analyzed with the temporal-spatial terms during the period of red tide occurrence. In addition, the changes from red tide occurrence and disappear period are analyzed. As a result of analyzing using Standard Deviation Ellipse and Hotspot analysis, moving were found to extend from the western area of the South Sea to the eastern area of the South Sea at the time of occurrence of red tide. In the red tide Extinction period, we could see that the centroid moved to the west again.

The First Occurrence of Red Tide Caused by Karenia sp. in the Atlantic Moroccan Coast (Oualidia Lagoon)

The First Occurrence of Red Tide Caused by Karenia sp. in the Atlantic Moroccan Coast (Oualidia Lagoon)

A Bio-physical Assessment of Harmful Algal Bloom (HAB) Outbreak using Multi-dimensional Array Data during 1998–2017

Jeong, J.-Y.; Kang, Y.H.; Park, K.; Um, J.-H., and Son, Y.B., 2018. A bio-physical assessment of Harmful Algal Bloom (HAB) outbreak using multi-dimensional array data during 1998–2017. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 836–840. Coconut Creek (Florida), ISSN 0749-0208.Harmful algal blooms (HABs), Cochlodinium polykrikoides, which related a devastating algal bloom, recently have caused the serious problems of fishery and aquaculture activities in the south coast of Korea (SCK). To understand the evolution of red tide and determine physical factors as a function of the bloom occurrence and disappearance, we used the multi-dimensional data (satellite and in-situ) during 1998–2017. Red tides generally have started with finishing the raining season and then increased with increasing the sea surface temperature and tidal range. To understand the general trend of red tide occurrence, we classify three different scales with cell density, area, and duration of red tides such as small, medium, and large scale red tides. Small and medium scale red tides started in the middle of August. The periods of the maximum cell density and extinction were shown in the early and end of September. SST in small and medium scale red tides was higher than in large scale red tides. Even though the tidal range was relatively small at the beginning of the outbreak, it was increased in the maximum cell density and decreased in the extinction period. Large scale red tides began in the early of August and the maximum cell density appeared at the end of August. SST was the lowest and the tidal range was the largest difference in the beginning outbreak and the lowest difference in the maximum cell density. In particular, the phenomenon of large-scale variation in the overall time series was that the SST and PAR in large scale red tides were relatively low compared to the small and medium scale red tides. Even though the tidal range was less difference before the beginning outbreak, it is analyzed that there was a growing difference in time.

Spatiotemporal variations of aquatic ecosystem health status in Tolo Harbor, Hong Kong from 1986 to 2014

Tolo Harbor is a nearly land-locked body of water located northeast of Hong Kong with only one narrow exit opening to the sea at Mirs Bay. Rapid urbanization accompanied by various anthropogenic stresses caused the frequent occurrences of red tides and associated fish kills, as well as coral deaths, in Tolo Harbor in the late 1980s. To stop “Hong Kong’s First Marine Disaster”, the Tolo Harbor Action Plan (THAP) has been employed by the Hong Kong Government since 1988. The present study evaluated the spatiotemporal variations of aquatic ecosystem health (AEH) in Tolo Harbor, using monthly monitoring data from 1986 to 2014. The Physical-Chemical-Biological index Triangle Area Method (PCBTAM) was developed to integrate physical, chemical and biological indicators and to identify the dominating factors. The results showed that the AEH of Tolo Harbor would be divided into six periods with two deteriorations and two convalescences. The first deterioration was caused by violent anthropogenic impacts, mainly from urban areas. With the implementation of THAP, the AEH was significantly improved. Later, the harbor underwent a physical index-dominated deterioration. With the rapid decrease of the physical index in 2009, Tolo Harbor came into a stable healthy stage. A spatial gradient of AEH in Tolo Harbor, from bad to good, was: Harbor Subzone > Buffer Subzone > Channel Subzone. In addition, seasonal component extraction illustrated that the AEH had a bad tendency in most months and the biological index dominated the AEH tendency pattern.

Estimating submarine groundwater discharge and associated nutrient inputs into Daya Bay during spring using radium isotopes

Daya Bay, a semi-enclosed bay in the South China Sea, is well known for its aquaculture, agriculture, and tourism. In recent years, many environmental problems have emerged, such as the frequent (almost yearly) occurrence of harmful algal blooms and red tides. Therefore, investigations of submarine groundwater discharge (SGD) and associated nutrient inputs to this bay have important theoretical and practical significance to the protection of the ecological system. Such a study was conducted using short-lived radium isotopes 223Ra and 224Ra. The estimated SGD fluxes were 2.89 × 107 m3/d and 3.05 × 107 m3/d based on 223Ra and 224Ra, respectively. The average SGD flux was about 35 times greater than that of all the local rivers. The SGD-associated dissolved inorganic nitrogen (DIN) and dissolved inorganic phosphorus (DIP) fluxes ranged from 1.95 × 106 to 2.06 × 106 mol/d and from 5.72 × 104 to 6.04 × 104 mol/d, respectively. The average ratio of DIN to DIP fluxes in SGD was 34, much higher than that in local rivers (about 6.46), and about twice as large as the Redfield ratio (16). Our results indicate that SGD is a significant source of nutrients to the bay and may cause frequent occurrence of harmful algal blooms. This study provides baseline data for evaluating potential environmental effects due to urbanization and economic growth in this region.

Nutrient input through submarine groundwater discharge in two major Chinese estuaries: the Pearl River Estuary and the Changjiang River Estuary

In this study, we used a 224Ra mass balance model to evaluate the importance of submarine groundwater discharge (SGD) for the budgets of biogenic elements in two major Chinese estuaries: the Pearl River Estuary (PRE) and the Changjiang River Estuary (CRE). The apparent water age in the PRE was estimated to be 4.8 ± 1.1 days in the dry season and 1.8 ± 0.6 days in the wet season using a physical model based on the tidal prism. In the dry season, the water age in the CRE was estimated to be 11.7 ± 3.0 days using the 224Ra/223Ra activities ratios apparent age model. By applying the 224Ra mass balance model, we obtained calculations of the SGD flow in the PRE of (4.5–10) × 108 m3 d−1 (0.23–0.50 m3 m−2 d−1) and (1.2–2.7) × 108 m3 d−1 (0.06–0.14 m3 m−2 d−1) in the dry season and wet season, respectively, and the estimated SGD flux was (4.6–11) × 109 m3 d−1 (0.18–0.45 m3 m−2 d−1) in the dry season of the CRE. In comparison with the nutrient fluxes from the rivers, the SGD-derived nutrient fluxes may play a vital role in controlling the nutrient budgets and stoichiometry in the study areas. The large amount of dissolved inorganic nitrogen and phosphorus fluxes together with high N: P ratios into the PRE and CRE would potentially contribute to eutrophication and the occurrence of red tides along the adjacent waters.

Ra Tracer‐Based Study of Submarine Groundwater Discharge and Associated Nutrient Fluxes into the Bohai Sea, China: A Highly Human‐Affected Marginal Sea

AbstractNutrient concentrations in coastal bays and estuaries are strongly influenced by not only riverine input but also submarine groundwater discharge (SGD). Here we estimate the SGD and the fluxes of the associated dissolved inorganic nitrogen (DIN), phosphorus (DIP), and silicon (DSi) into the Bohai Sea based on a 226Ra and 228Ra mass balance model. This procedure shows that in the Bohai Sea the average radium activities (dpm 100 L−1) are 42.8 ± 6.3 (226Ra) and 212 ± 41.7 (228Ra) for the surface water and 43.0 ± 6.1 (226Ra) and 216 ± 38.4 (228Ra) for the near‐bottom water. According to the 228Ra/226Ra age model, the residence time in the Bohai Sea is calculated to be 1.7 ± 0.8 yrs. The mass balance of 226Ra and 228Ra suggests that the yearly SGD flux into the whole Bohai Sea is (2.0 ± 1.3) × 1011 m3 yr−1, of which the percentage of submarine fresh groundwater discharge (SFGD) to the total SGD is approximately (5.1 ± 4.1)%. However, the DIN and DSi fluxes from SFGD constitute 29% and 10%, respectively, of the total fluxes from the SGD. Moreover, nutrient loads, which exhibit high DIN/DIP from SGD, especially the SFGD, may substantially contribute to the nutrient supplies, resulting in the occurrence of red tide in the Bohai Sea.

Complex network modeling for mechanisms of red tide occurrence: A case study in Bohai Sea and North Yellow Sea of China

Red tide is an abnormal ecological phenomenon, and it severely affects marine ecosystem, economic growth and human health. The mechanism of red tide occurrence has been studied for many years, and a lot of indicators and techniques have been developed. Although these studies have effectively expanded the knowledge of mechanisms of red tide occurrence, the combination effect of water quality factors of different sea areas on red tide occurrence has not received enough attention. In this paper, a water quality factor dissimilarity network model (WDN), which can systematically reflect water quality of different sea areas, is presented. According to this model, a series of WDN networks are constructed with the data collected from monitoring stations of Bohai Sea and North Yellow Sea, and a novel red tide detection approach based on the outlier analysis of node strengths is proposed. Based on the analysis of the results obtained using this approach, the locality, the seasonality and the alternation of red tide occurrences are revealed. The validation from actual red tide events shows that our model and approach perform effectively and contribute to expanding the knowledge of mechanisms of red tide occurrence.

A new approach for the estimation of phytoplankton cell counts associated with algal blooms

This study proposes a method for estimating phytoplankton cell counts associated with an algal bloom, using satellite images coincident with in situ and meteorological parameters. Satellite images from Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), Operational Land Imager (OLI) and HJ-1 A/B Charge Couple Device (CCD) sensors were integrated with the meteorological observations to provide an estimate of phytoplankton cell counts. All images were atmospherically corrected using the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) atmospheric correction method with a possible error of 1.2%, 2.6%, 1.4% and 2.3% for blue (450–520nm), green (520–600nm), red (630–690nm) and near infrared (NIR 760–900nm) wavelengths, respectively. Results showed that the developed Artificial Neural Network (ANN) model yields a correlation coefficient (R) of 0.95 with the in situ validation data with Sum of Squared Error (SSE) of 0.34cell/ml, Mean Relative Error (MRE) of 0.154cells/ml and a bias of −504.87. The integration of the meteorological parameters with remote sensing observations provided a promising estimation of the algal scum as compared to previous studies. The applicability of the ANN model was tested over Hong Kong as well as over Lake Kasumigaura, Japan and Lake Okeechobee, Florida USA, where algal blooms were also reported. Further, a 40-year (1975–2014) red tide occurrence map was developed and revealed that the eastern and southern waters of Hong Kong are more vulnerable to red tides. Over the 40 years, 66% of red tide incidents were associated with the Dinoflagellates group, while the remainder were associated with the Diatom group (14%) and several other minor groups (20%). The developed technology can be applied to other similar environments in an efficient and cost-saving manner.

Developing a Smart Semantic Web With Linked Data and Models for Near-Real-Time Monitoring of Red Tides in the Eastern Gulf of Mexico

In recent decades, the technology used to detect and quantify harmful algal blooms (commonly known as red tides) and characterize their physicochemical environment has improved considerably. A remaining challenge is effective delivery of the information generated from these advances in a user-friendly way to a diverse group of stakeholders. Based on existing infrastructure, we establish a Web-based system for near-real-time tracking of red tides caused by the toxic dinoflagellate Karenia brevis , which annually threatens human and environmental health in the eastern Gulf of Mexico. The system integrates different data products through a custom-made Web interface. Specifically, three types of data products are fused: 1) near-real-time ocean color imagery tailored for red tide monitoring; 2) K. brevis cell abundance determined by sample analysis; and 3) ocean currents from a nested and validated numerical model. These products are integrated and made available to users in Keyhole Markup Language (KML) format, which can be navigated, interpreted, and overlaid with other products in Google Earth. This integration provides users with the current status of red tide occurrence (e.g., location, severity, and spatial extent) while presenting a simple way to estimate bloom trajectory, thus delivering an effective method for near-real-time tracking of red tides.

Biological responses to nine powerful typhoons in the East China Sea

Using multi-satellite remote sensing and numerical model data, we investigated the biological responses to nine powerful typhoons that affected the East China Sea (ECS) between 2010 and 2013. The spatial distribution patterns of the surface chlorophyll-a (Chl-a) in response to the passage of typhoons were quite different. Some typhoons clearly induced phytoplankton blooms in part of the surface seawater, whereas the Chl-a concentrations were not significantly altered by the other typhoons. In the case that the ocean’s precondition was similar, the pre-typhoon Chl-a concentration and transit time were the main factors that affected the post-typhoon Chl-a concentration. Besides strong vertical mixing and upwelling, the surface current change and heavy precipitation induced by the typhoons also influenced the distribution and growth of phytoplankton in surface seawater after passage of individual typhoons. In addition, the typhoons that directly affected coastal regions increased the nutrient concentrations in these areas, which influenced the occurrence of red tides in the ECS over a long time scale.