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Red tide causes significant damage to marine resources such as aquaculture and fisheries in coastal regions. Such red tide events occur globally, across latitudes and ocean ecoregions. Satellite observations can be an effective tool for tracking and investigating red tides and have great potential for informing strategies to minimize their impacts on coastal fisheries. However, previous satellite-based red tide detection algorithms have been mostly conducted over short time scales and within relatively small areas, and have shown significant differences from actual field data, highlighting a need for new, more accurate algorithms to be developed. In this study, we present the newly developed normalized red tide index (NRTI). The NRTI uses Geostationary Ocean Color Imager (GOCI) data to detect red tides by observing in situ spectral characteristics of red tides and sea water using spectroradiometer in the coastal region of Korean Peninsula during severe red tide events. The bimodality of peaks in spectral reflectance with respect to wavelengths has become the basis for developing NRTI, by multiplying the heights of both spectral peaks. Based on the high correlation between the NRTI and the red tide density, we propose an estimation formulation to calculate the red tide density using GOCI data. The formulation and methodology of NRTI and density estimation in this study is anticipated to be applicable to other ocean color satellite data and other regions around the world, thereby increasing capacity to quantify and track red tides at large spatial scales and in real time.

Red tide events are increasingly impacting economies, public health, ecosystems, and aquaculture worldwide, with China experiencing particularly severe effects. This study investigates the changes of red tide events in the Northern South China Sea (NSCS) from 1998 to 2018, focusing on frequency, composition, and environmental drivers. A total of 278 red tide events were reported, with peak in 2003 with 19 events, followed by 14 events in 2004, 9 in 2005, and 7 in 2023. The results indicate that Daya Bay (DYB) is a hotspot for red tide occurrences, with 166 events predominantly caused by Phaeocystis globosa and Noctiluca scintillans . Factors such as thermal discharge and nutrient-rich effluents contribute to the high frequency of red tides in DYB. Other significant locations include Zhanjiang Port (ZJP) with 48 events, Qinzhou Bay (QZB) with 31 events, and Qianjiang Bay (QJB) with 21 events. In contrast, Hongsha Port (HSP) recorded the fewest events, with only 12. The study identified a total of 33 algal species, revealing changes in species composition over the study period. Shifts in dominant species are linked to changing environmental conditions, including rising seawater temperatures and increased nutrient availability. A potential correlation between red tide events and the Nino 3.4 index suggests that global climate patterns may influence red tide occurrences in the NSCS. Additionally, anthropogenic activities, such as industrial wastewater discharge, contribute to the prevalence of red tide events. The study highlights the complex interactions driving red tide blooms in the NSCS and underscores the need for effective management strategies to mitigate their impacts. Highlights 278 red tide events occurred from 1998 to 2018, with a peak in 2003. Daya Bay was the major hotspot. High red tide frequency in Daya Bay is linked to thermal discharge, nutrient-rich effluents, and shifts in algal species due to changing environmental conditions. Potential correlation with the Nino 3.4 index suggests global climate patterns influence red tides, with anthropogenic activities also playing a role.

The recent rise of red tide harmful algal blooms has induced ecosystem degradation, economic losses, and aquaculture damage, yet little is known on prevention and mitigation of red tides. Actual control methods involve physical, chemical, and biological processes, with varying success. Here, we review physical, chemical, and biological control methods applicable to red tide species in marine and estuarine water bodies. We discuss mechanisms of algal blooms outbreak and their applications to prevent outbreaks.

Globally, climate change impacts on marine ecosystems are evident in physical, chemical, and biological processes, and are generally more extensive in faster warming regions. China makes the largest contribution of any country to global fisheries production and has experienced severe declines in marine health and biodiversity, and so the current and potential impacts of marine climate change are a large concern for both fisheries and biodiversity. China also has marine regions warming in the top 10% globally, necessitating a thorough understanding of how marine systems are changing so that appropriate corresponding countermeasures can be identified and prioritized. Here, we review and collate what is currently understood about documented and projected responses of marine systems to climate change in Chinese coasts and oceans, from physical, biological, and ecological perspectives, through to impacts on key ecosystems. Our results show extensive change attributed to climate change throughout Chinese marine systems, including red tide bloom events that have been recorded an order of magnitude more frequently in recent decades. Ocean acidification has led to the increased mortality of marine calcifying organisms through effects on the biomineralization process and physiological functions. Moreover, many species have been documented undergoing extensive changes in geographic distribution, with potential implications for species interactions and trophic food webs, as well as important habitats like coral reefs, seagrass, and mangroves. Some constructive laws and actions have been introduced in response to these climate-driven changes, such as actions to reduce pollution and increase artificial propagation and replanting of habitat species, however, addressing the impacts of marine climate change remains a considerable and escalating challenge.

Ichthyotoxic red tide is a problem that the world is facing and needs to solve. The use of antialgal compounds from marine macroalgae to suppress ichthyotoxic red tide is considered a promising biological control method. Antialgal substances were screened and isolated from Bangia fusco-purpurea, Gelidium amansii, Gloiopeltis furcate, Hizikia fusifarme, Laminaria japonica, Palmaria palmata, and Sargassum sp. to obtain new materials for the development of algaecides against ichthyotoxic red tide microalgae using bioactivity-guided isolation methods. The fractions of seven macroalgae exhibited selective inhibitory activities against Amphidinium carterae and Karenia mikimotoi, of which the ethyl acetate fractions had the strongest and broadest antialgal activities for the two tested red tide microalgae. Their inhibitory effects on A. carterae and K. mikimotoi were even stronger than that of potassium dichromate, such as ethyl acetate fractions of B. purpurea, H. fusifarme, and Sargassum sp. Thin-layer chromatography and ultraviolet spectroscopy were further carried out to screen the ethyl acetate fraction of Sargassum sp. Finally, a new glycolipid derivative, 2-O-eicosanoyl-3-O-(6-amino-6-deoxy)-β-D-glucopyranosyl-glycerol, was isolated and identified from Sargassum sp., and it was isolated for the first time from marine macroalgae. The significant antialgal effects of 2-O-eicosanoyl-3-O-(6-amino-6-deoxy)-β-D-glucopyranosyl-glycerol on A. carterae and K. mikimotoi were determined.

Breaking‐wave induced bioluminescence is a critical component of the biogeochemical process in the ocean. Understanding bioluminescence is important for monitoring red tides caused by bioluminescent microorganisms. In this study, we present the first numerical effort to quantify bioluminescent light intensity based on high‐fidelity direct numerical simulations of breaking waves and a quantitative bioluminescent model. The dynamics of breaking waves are extensively validated through comparison with existing studies. We find that the time‐averaged and Lagrangian‐averaged shear stress saturates as surface tension effects decrease and wave steepness increases. The spatial distribution of light intensity correlates with the wave crest overturning and air bubbles generated in plunging breakers. Furthermore, we observe that the maximum light intensity asymptotically approaches the emission of single cells, suggesting the potential for cost‐effective prediction models in future studies. Plain Language Summary Marine microorganisms, such as dinoflagellates, flash when stimulated by mechanical forces caused by breaking waves. Understanding this phenomenon, also known as the ‘blue tears’ of ocean, is helpful for predicting ‘red tides’, a hazardous algal blooms caused by dinoflagellates. We use computer simulations to determine how much light is emitted when breaking waves stimulates bioluminescence. Our analysis show that there is an upper limit for the level of the mechanical force in breaking waves. We also find that the maximum bioluminescence light intensity is similar to that emitted by a single cell. Key Points A numerical framework is developed to quantify bioluminescence stimulated by ocean surface breaking waves The time‐averaged and Lagrangian‐averaged shear stress saturates as surface tension effects decrease and wave steepness increases Maximum bioluminescent light intensity asymptotically approaches single cell emission at the time of flashing

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.

Harmful algal blooms (HABs) can be a natural hazard unlike anything else. Whereas a hurricane or tornado has a sudden and devastating impact to an area, an HAB can slowly impact people and the environment over the course of weeks, even months. Karenia brevis, more commonly known as red tide, can have this effect along the Gulf Coast of Florida, lasting for many weeks in a row, causing large-scale deaths in fish and other marine life, and respiratory issues in humans. These harmful effects can effect tourism, as visitors are not able to enjoy the coastlines Florida is famous for. We test a 6 county region, from Pinellas County, FL down to Collier County, FL, to determine the magnitude with which an additional day of red tide affects tourism-related revenues. Using a spline regression approach, we find that an additional day of red tide in a month with 17 days or more of red tide drives monthly lodging sector sales down by 1–2%, and restaurant sector sales down by 0.5–1%. As these blooms are increasing in frequency and persistency, it becomes of great importance to counties and effected businesses to control and mitigate red tide blooms as soon as possible. If not, losses and harmful effects will only continue to grow and become detrimental to the environment and economy.

Red tides sometimes impact the aquaculture industry worldwide, resulting in mass fish mortalities. It is known empirically that their effects can be mitigated by cessation of feeding. However, specific methods to maximize this technique’s effectiveness and provide physiological support remain limited. In the present study, we investigated the effects of the feeding‐cessation period on a fish’s resistance to a harmful red‐tide microalga, the Chattonella marina complex (“ Chattonella ”), using yellowtail ( Seriola quinqueradiata ) of two ages and body weights: juveniles (74 days after hatching and ~15 g) and young (201 days after hatching and ~860 g). The fish mortality by Chattonella is thought to be associated with gill damage. Thereby, we measured oxygen consumption to consider plankton contact with the gills. Our results showed that feeding cessation for 4 or more days significantly increased survival, regardless of size. Body weight decreased with longer feeding cessation, but survival rates were not affected by body weight. To test red‐tide resistance, juvenile yellowtail were treated by feeding cessation for 1, 2, and 4 days, and young yellowtail for 1, 4, and 8 days. In the juveniles, a longer feeding pause also reduced oxygen consumption. Moreover, histological examination of the juveniles showed that a longer feeding pause reduced damage to the secondary lamellae of the gills. We propose that gill damage was mitigated by reducing the interaction between Chattonella cells and the gill lamellae, likely as a result of decreased oxygen consumption. These results indicate that feeding cessation for a specific period of time physiologically improves red‐tide resistance in yellowtail.

Long-term trends of bottom-water concentrations of dissolved oxygen (DO), total nitrogen, and total phosphorus at 42 sites in Tokyo Bay were analyzed using monthly data from 1983 to 2018 measured by local government agencies. The results were visualized as spatial distribution maps. Bottom-water DO concentrations varied seasonally. The area of hypoxic bottom water (DO < 2 mg L −1 ) was greatest in September of every year. Examination of interannual variations of the spatial distribution of bottom-water DO concentrations in September revealed that along the eastern side of the bay, hypoxic zones have been shrinking since the mid-2000s, but along the western side of the bay, the bottom water closest to shore is hypoxic in September even today. The areal percentage of hypoxic bottom water during September within inner Tokyo Bay has declined from 30% around 2007 to < 15% around 2015 and has not changed since then. A comparison of the spatial distributions of the frequencies of occurrence of red tides (chlorophyll- a concentrations ≥ 50 μg L −1 ) and hypoxic water masses during 8-year intervals revealed that areas with high percentages of red tides coincided with areas with high percentages of hypoxic bottom water. The implication is that the reduction of the size of the hypoxic zones along the eastern side of the bay was due to less frequent occurrence of red tides there. Reducing the inputs of nutrients to the bay as a result of policies aimed at reducing water pollution has, therefore, contributed to the mitigation of the hypoxia problem.