Red Tide Research Articles

الآثار البيئية والاقتصادية والاجتماعية لظاهرة المد الأحمر على مجتمع الصيادين في ولاية بركاء بسلطنة عمان

Red tide is not a recent phenomenon. Rather, it is linked to the development and bloom of plankton and phytoplankton that accompanied ancient geological times and climate changes. Japan is the first country that was able to monitor this phenomenon more than 300 years ago, while its appearance in the countries of the Arabian Peninsula was in 1976 in the Sultanate of Oman. Natural and human factors contribute to the growth of harmful algae, which is the main cause of red tide, especially Dinotlagellates, which represents 78% of the samples analyzed in the Sultanate of Oman. Red tides damage ecosystems and coastal communities. This study mainly aims to highlight the economic, social and environmental impacts of the red tide phenomenon on the fishing community in the Wilayat of Barka in the Sultanate of Oman, and to develop appropriate solutions for fishing communities to mitigate the negative effects of this phenomenon. The study relied in its methodology on a review of previous studies, a field study, and direct interviews with fishermen in Barka State, in addition to questionnaires distributed to 120 fishermen using a random sampling method. One of the most prominent findings of this study is that red tide directly causes air pollution through the spread of unpleasant odors in the region, according to 99% of the sample population. However, what should be noted is that fishermen are completely unaware of the effects of red tide on public health related to the possibility of fish poisoning. As to the economic impacts, 94% of the study population pointed out to cost of cleaning equipment used in the fishing process. The problem was compounded by expatriate workers exploitation of situation by raising the costs of cleaning. Among the most prominent recommendations that came out of the study: conducting further studies and research, raising awareness on negative impacts of red tide and establishing fishermen associations to mitigate the effects of red tide.

Estimates of Western Atlantic Goliath Grouper (Epinephelus Itajara) Bycatch Mortality in Commercial Fisheries of the Southeastern United States From 2002 to 2022

The Atlantic Goliath Grouper (_Epinephelus itajara_) in the southeastern United States is in decline due to increasingly large and persistent red tides, loss of juvenile habitat, and severe cold-weather events. In this paper, we address another source of mortality -- bycatch, focusing on data from NOAA Fisheries logbooks for commercial fisheries operating between 2002 to 2022. We calculate capture related mortality based on known patterns of depth-related barotrauma drawn from the literature and assume that all fish captured at depths greater than 30 m died if unvented prior to release. The overall result suggests that 75% (14,124 of 18,770) of Goliath Grouper captures died from barotrauma, as they either hemorrhaged or were unable to return to the bottom because of increased buoyancy due to expanded gas trapped in the swim bladder. While fishers currently use self-reporting to document these mortalities, this approach often results in biases toward lower capture and a higher survival rate. Thus, we strongly urge the Florida Fish and Wildlife Conservation Commission and the National Oceanic and Atmospheric Administration to quit using logbook data and instead require that fishers use paid observers and remote electronic monitoring on all commercial and charter vessels to ensure more effective, timely and reliable bycatch data for this and other protected species.

A Chlorophyll-a Concentration Inversion Model Based on Backpropagation Neural Network Optimized by an Improved Metaheuristic Algorithm

Chlorophyll-a (Chl-a) concentration monitoring is very important for managing water resources and ensuring the stability of marine ecosystems. Due to their high operating efficiency and high prediction accuracy, backpropagation (BP) neural networks are widely used in Chl-a concentration inversion. However, BP neural networks tend to become stuck in local optima, and their prediction accuracy fluctuates significantly, thus posing restrictions to their accuracy and stability in the inversion process. Studies have found that metaheuristic optimization algorithms can significantly improve these shortcomings by optimizing the initial parameters (weights and biases) of BP neural networks. In this paper, the adaptive nonlinear weight coefficient, the path search strategy “Levy flight” and the dynamic crossover mechanism are introduced to optimize the three main steps of the Artificial Ecosystem Optimization (AEO) algorithm to overcome the algorithm’s limitation in solving complex problems, improve its global search capability, and thereby improve its performance in optimizing BP neural networks. Relying on Google Earth Engine and Google Colaboratory (Colab), a model for the inversion of Chl-a concentration in the coastal waters of Hong Kong was built to verify the performance of the improved AEO algorithm in optimizing BP neural networks, and the improved AEO algorithm proposed herein was compared with 17 different metaheuristic optimization algorithms. The results show that the Chl-a concentration inversion model based on a BP neural network optimized using the improved AEO algorithm is significantly superior to other models in terms of prediction accuracy and stability, and the results obtained via the model through inversion with respect to Chl-a concentration in the coastal waters of Hong Kong during heavy precipitation events and red tides are highly consistent with the measured values of Chl-a concentration in both time and space domains. These conclusions can provide a new method for Chl-a concentration monitoring and water quality management for coastal waters.

Dynamic causes contribute to the increasing trend of red tides in the east China sea during 2020–2022

Red tide is a marine phenomenon caused by the excessive growth of microscopic algae in the ocean. This study aims to analyze the development trends of red tides in the past 20 years and the dynamic external causes that induce red tides based on existing satellite remote sensing and numerical simulation data. And the changes in dominant species of red tides in different seasons are analyzed. The results show significant temperature fluctuations within the week before the red tide occurs, with an average increase of 1.42 °C. In contrast, the change in salinity is relatively small. Meanwhile, ocean fronts are areas in the ocean where different water masses meet and form boundaries. The average strength of ocean fronts increased by 3.7%, indicating enhanced ocean mixing over a short period of time. Under the combined influence of these factors, the probability of a red tide outbreak in the East China Sea increases rapidly. Therefore, this study has important reference value for further research on the causes of red tides and their response to ocean dynamic changes.

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.

Red Tide and the Anthropological Divide at Lake Merritt in Oakland, California

Red Tide and the Anthropological Divide at Lake Merritt in Oakland, California

Survival of red knots in the northern Gulf of Mexico

Highly migratory shorebirds are among the fastest declining avian guilds, so determining causes of mortality is critically important for their conservation. Most of these species depend on a specific geographic arrangement of suitable sites that reliably provide resources needed to fuel physiologically demanding life histories. Long-term mark-resight projects allow researchers to investigate specific potential sources of variation in demographic rates between populations. Red Knots (Calidris canutus) occur in three relatively distinct regions across the northern Gulf of Mexico, and two of these areas have been experiencing episodic harmful algal blooms (red tide) with increased frequency in recent decades. Since knots are mostly molluscivorous during the nonbreeding season in the Gulf, they are potentially exposed to red tide toxins at high concentrations via their filter-feeding prey. We used long-term mark-resight data from Texas, Louisiana, and Florida (USA) to estimate apparent survival, and to assess the effects of red tides on survival of Red Knots. We also assessed effects of tracking devices deployed in conjunction with the projects over the years. While overall apparent annual survival rates were similar across the three locations (0.768 – 0.819), several red tide events were associated with catastrophically low seasonal (fall) survival in Florida (as low as 0.492) and Texas (as low as 0.510). Leg-mounted geolocators, but not temporary glued-on VHF tags, were associated with a reduction in apparent survival (~8%/year). Movement of knots between the three areas was rare and site fidelity is known to be high. Harmful algal blooms are predicted to increase in frequency and severity with climate change and increased anthropogenic degradation of coastal habitats, which may further endanger these as well as other shorebird populations around the world.

What's in a name? Political and economic concepts differ in social media references to harmful algae blooms

Policies and management decisions in the marine environment are driven in part by public sentiment which can grow more intense during hazard events like Harmful Algae Blooms (HABs). The public conversations on social media sites like Twitter (before X) reveal the polarized nature of HABs through nuanced language and sentiment. This article uses mixed methods of machine learned topic modeling and inductive qualitative coding to describe the ways the long-term 2017–2019 Karenia brevis “red tide” bloom were politicized across Florida's South West coast. It finds that there are topical differences in keywords related to place (e.g. beach, Florida, coast), agent (individual or organization), and epistemic values (reliance on scientific and/or media reports). These topical differences demonstrate different levels of politicization and partisanship in qualitative analysis. Conceptually, this research demonstrates the ways different dimensions of a long-duration marine hazard can be polarized. Regarding management, this research provides insights to political and organizational stakeholders and the gaps in the discourse shaping marine hazards which can be used to strategically guide future social media engagement to manage politicization.What if all the careful work that resource and environmental managers do can be undone by simple, seemingly uncontroversial words? In an era of increased environmental and marine distress—coupled with short format communication—the ways environmental managers choose their words is crucial, even between ostensibly inconsequential nouns like “red tide” or “algae bloom.” Policies and management decisions in the marine environment are driven in part by public sentiment which can grow more intense during hazard events like Harmful Algae Blooms (HABs). The public conversations on social media sites like Twitter (before X) reveal the polarized nature of HABs through nuanced language and sentiment. This article relies on mining social media posts, and uses mixed methods of machine-learned topic modeling and human-driven inductive qualitative coding to describe the ways the long-term 2017–2019 Karenia brevis “red tide” blooms were politicized across Florida's South West coast. It finds that there are topical differences in keywords related to place (e.g. beach, Florida, coast), agent (individual or organization), and epistemic values (reliance on scientific and/or media reports). These topical differences demonstrate different levels of politicization and partisanship in qualitative analysis. Conceptually, this research demonstrates the ways different dimensions of a long-duration marine hazard can be polarized. Regarding management, this research provides insights to political and organizational stakeholders and the gaps in the discourse shaping marine hazards which can be used to strategically guide future social media engagement to manage politicization.

New insights on the spatial and temporal distribution characteristics of Chinese marine environmental quality and its driving factors from 2003 to 2021

As land and sea integration continues to accelerate, it will inevitably have an effect on the marine ecological environment. However, the study on spatial and temporal distribution characteristics of Chinese marine environmental quality and its driving factors was lacking. This paper employs Regression Analysis, Spearman Correlation Analysis, Canonical Correlation Analysis, Boston Consulting Group Matrix and Environmental Kuznets Curve to examine the spatial–temporal distribution characteristics and correlation factors of Chinese jurisdictional sea areas environmental quality. The environmental quality of the waters under China's jurisdiction improved on average from 2003 to 2021, the area of sea with excellent water quality increased by 7.21 × 104 km2. The spatial distribution showed “South superior, North inferior” trend. The accumulated red tide area is 2.01 × 105 km2, and the green tide has the average maximum area of distribution is 3.13 × 104 km2. The marine dumping area's volume of waste has a three stages of slow rise (2003–2007), steady (2008–2014) and rapid rise (2015–2021). The average percentage of seawater bathing areas with good water quality is 82.10 %. Urban Environmental Infrastructure Investment and Urban Drainage Construction Investments are positively correlated with excellent water quality and negatively correlated with light-sewage water quality. The typical correlation for the group “Environmental Quality/Environmental Governance” is 0.911, and the strongest correlation is between excellent water quality and urban drainage construction investment. The typical correlation coefficient for the “Environmental Quality/Socioeconomic” group is 0.960, and the strongest correlation is between excellent water quality and per capita GDP. The Gross Ocean Product, Per Capita GDP, Proportion of Non-agricultural Industries, Year-end Resident Population, and excellent water quality are positively correlated whereas light-sewage water quality is negatively correlated. Liaoning, Tianjin, Shandong and Guangdong shift from high-pollution-low-investment to low-pollution-low-investment model. Shanghai, Zhejiang, Fujian and Hainan maintain high-pollution-low-investment model, Hainan maintains high-pollution-high-investment model. Jiangsu maintains low-pollution-low-investment model. Hebei and Guangxi shift from low-pollution-low-investment to low-pollution-high-investment model. Liaoning, Hebei, Tianjin, Shandong, Guangxi and Shanghai show inverted “N” shape, Jiangsu shows positive “N” shape, Zhejiang and Fujian show monotonic decline shape, Guangdong and Hainan show positive “U” shape. The results could provide valuable suggestions for coastal provinces to accomplish economic development and environmental improvement, which to prevent the old way of “pollution first and treatment later”.

The toxigenic red-tide-forming dinoflagellates Alexandrium leei and Alexandrium catenella differ in terms of the sensitivity to strong light and low temperature of their photosynthetic machinery

Alexandrium leei and Alexandrium catenella are noxious dinoflagellates that form red tides but the two species differ substantially in optimal growth conditions. For formation of blooms in natural environments, A. leei favors moderate temperatures (around 20 °C) while A. catenella favors much lower temperatures (around 10 °C). We examined the effects of temperature and light on cell proliferation and photosynthesis in cell cultures of the two species. Under light at 100 μmol photons m−2 s−1, the growth rate of both species was highest at 20 °C. At 25 °C, A. leei continued to proliferate but A. catenella did not survive. Conversely, at lower temperatures, namely, 12 °C and 15 °C, the growth rate of A. leei was very low while that of A. catenella remained high. The net photosynthetic activity, as determined in terms of oxygen evolution, was highest at 20 °C in A. leei. By contrast, it was highest at 15 °C in A. catenella. Illumination of cells with strong light at 1000 μmol photons m−2 s−1 decreased the activity of photosystem II (PSII), as determined in terms of Fv/Fm, in both species. In A. leei, the activity of PSII declined more rapidly at 12 °C and 15 °C than at 20 °C and 25 °C under strong light. In A. catenella, the activity of PSII declined more rapidly at 20 °C than at 12 °C and 15 °C. Thus, A. catenella appeared to be more resistant to photoinhibition of PSII at low temperatures than A. leei. In addition, the ability to repair photodamaged PSII at 12 °C and 15 °C was greater in A. catenella than that in A. leei. Thus, the tolerance of PSII to strong light and low temperatures might determine the range of temperatures that supports the formation of blooms of the two Alexandrium species.

Estimates of Atlantic Goliath Grouper (Epinephelus Itajara) Bycatch Mortality in Commercial Fisheries of the Southeastern Us From 2002 to 2022

Atlantic Goliath Grouper _Epinephelus itajara _is experiencing a population decline in the southeastern United States currently due to a combination of factors, including increasingly large and persistent red tides, loss of juvenile habitat, severe cold-weather events, and bycatch, the unintended capture by commercial and recreational fishers. In this paper, we review the extent of bycatch in the southeastern United States from 2002 to 2022 resulting from commercial fishing only based on data from NOAA Fisheries logbooks. We calculated depth-of-capture-related mortality based on known patterns of depth-related barotrauma and assumed that all captures deeper than 30 m that were unvented prior to release died based on observations of other researchers. The overall result is that 75% (14,124 of 18,770) _Epinephelus itajara_ captures died from both barotrauma and from inability of the fish to return to the bottom due to trapped swim bladder gas.

Preliminary investigation on the causes of red tides in Qinhuangdao coastal areas in 2022.

To explore the causes of red tides in Qinhuangdao coastal water, we conducted surveys on both water quality and red tides during April to September of 2022 and analyzed the relationships between main environmental factors and red tide organisms through the factor analysis and canonical correspondence analysis. The results showed that there were eight red tides along the coast of Qinhuangdao in 2022, with a cumulative blooming area of 716.1 km2. The red tides could be divided into three kinds based on the major blooming organisms and occurrence time, Noctiluca scintillans bloom, diatom-euglena (Skeletonema costatum, Eutreptiella gymnastica, Pseudo-nitzschia spp.) bloom, and dinoflagellate (Scrippsiella trochoidea and Ceratium furca) bloom. Seasonal factor played roles mainly during July to September, while inorganic nutrients including nitrogen and phosphorus influenced the blooms mainly in April and July. The canonical correspondence analysis suggested that N. scintillans preferred low temperature, and often bloomed with high concentrations of ammonium nitrogen and dissolved inorganic phosphorus. S. costatum, E. gymnastica, and Pseudo-nitzschia spp. could tolerate broad ranges of various environmental factors, but favored high temperature and nitrogen-rich seawater. C. furca and S. trochoidea had higher survival rate and competitiveness in phosphate-poor waters. Combined the results from both analyses, we concluded that the causes for the three kinds of red tide processes in Qinhuangdao coastal areas in 2022 were different. Adequate diet algae and appropriate water temperature were important factors triggering and maintaining the N. scintillans bloom. Suitable temperature, salinity and eutrophication were the main reasons for the diatom-euglena bloom. The abundant nutrients and seawater disturbance promoted the germination of S. trochoidea cysts, while phosphorus limitation caused the blooming organism switched to C. furca and maintained the bloom hereafter.

Organismal responses to deteriorating water quality during the historic 2020 red tide off Southern California

In April and May of 2020, a large phytoplankton bloom composed primarily of the dinoflagellate Lingulodinium polyedra reached historic levels in geographic expanse, duration, and density along the coast of southern California, United States, and Baja California Norte, Mexico. Here, we report the water quality parameters of dissolved oxygen and pH over the course of the red tide, as measured by multiple sensors deployed in various locations along San Diego County, and document the extent of mass organism mortality using field surveys and community science observations. We found that dissolved oxygen and pH corresponded with bloom dynamics, with extreme hypoxic and hyperoxic conditions occurring at multiple locations along the coast, most notably within select estuaries where dissolved oxygen reached 0 mg L−1 and hypoxia occurred for up to 254 consecutive hours, as well as along the inner shelf of the open coast where dissolved oxygen dropped as low as 0.05 mg L−1. Similarly, pH ranged widely (6.90–8.79) across the bloom over both space and time, largely corresponding with dissolved oxygen level. Extreme changes in dissolved oxygen and pH, in addition to changes to other water parameters that affect organismal health, ultimately led to documented mortalities of thousands of demersal and benthic fishes and invertebrates (primarily within estuarine and inner-shelf environments), and long-term surveys within one lagoon showed protracted changes to benthic infaunal density and species composition. In addition to field observations, we also quantified water quality parameters and organism mortalities from four local aquarium facilities, with varying levels of filtration and artificial oxygenation, and documented the morphological changes in the gills of captive-held Pacific sardine in response to the red tide. We show that multiple factors contributed to organismal stress, with hypoxia likely being the most widespread, but not the only, cause of mortality.

Rate-induced tipping can trigger plankton blooms

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

Fusing remote sensing data with spatiotemporal in situ samples for red tide (Karenia brevis) detection.

We present a novel method for detecting red tide (Karenia brevis) blooms off the west coast of Florida, driven by a neural network classifier that combines remote sensing data with spatiotemporally distributed in situ sample data. The network detects blooms over a 1-km grid, using seven ocean color features from the MODIS-Aqua satellite platform (2002-2021) and in situ sample data collected by the Florida Fish and Wildlife Conservation Commission and its partners. Model performance was demonstrably enhanced by two key innovations: depth normalization of satellite features and encoding of an in situ feature. The satellite features were normalized to adjust for depth-dependent bottom reflection effects in shallow coastal waters. The in situ data were used to engineer a feature that contextualizes recent nearby ground truth of K. brevis concentrations through a K-nearest neighbor spatiotemporal proximity weighting scheme. A rigorous experimental comparison revealed that our model outperforms existing remote detection methods presented in the literature and applied in practice. This classifier has strong potential to be operationalized to support more efficient monitoring and mitigation of future blooms, more accurate communication about their spatial extent and distribution, and a deeper scientific understanding of bloom dynamics, transport, drivers, and impacts in the region. This approach also has the potential to be adapted for the detection of other algal blooms in coastal waters. Integr Environ Assess Manag 2024;00:1-15. © 2024 SETAC.

Efficient Adsorption of Nitrogen and Phosphorus in Wastewater by Biochar.

Nitrogen and phosphorus play essential roles in ecosystems and organisms. However, with the development of industry and agriculture in recent years, excessive N and P have flowed into water bodies, leading to eutrophication, algal proliferation, and red tides, which are harmful to aquatic organisms. Biochar has a high specific surface area, abundant functional groups, and porous structure, which can effectively adsorb nitrogen and phosphorus in water, thus reducing environmental pollution, achieving the reusability of elements. This article provides an overview of the preparation of biochar, modification methods of biochar, advancements in the adsorption of nitrogen and phosphorus by biochar, factors influencing the adsorption of nitrogen and phosphorus in water by biochar, as well as reusability and adsorption mechanisms. Furthermore, the difficulties encountered and future research directions regarding the adsorption of nitrogen and phosphorus by biochar were proposed, providing references for the future application of biochar in nitrogen and phosphorus adsorption.

Photoacclimation in the kleptoplastidic ciliate Mesodinium rubrum and its cryptophyte prey Teleaulax amphioxeia: phenotypic variability and implications for red tide remote sensing

Abstract Mesodinium rubrum is a kleptoplastidic ciliate that sequesters the chloroplasts and nuclei of cryptophyte algae to perform photosynthesis. Blooms of M. rubrum can cause red tides in coastal oceans worldwide. Such red tides are detectable by remote sensing, and studying M. rubrum pigments and optical properties is a crucial step toward characterizing its blooms using satellite observation. Previous studies have shown that M. rubrum photoacclimates, modifying its pigment content depending on irradiance. Using cultures at different irradiance levels, we observed that photoacclimation in M. rubrum closely resembles that of its cryptophyte prey Teleaulax amphioxeia, leading to substantial phenotypic variability. In both species, phycoerythrin 545 cellular concentrations increased 3-fold between the highest and lowest irradiance, suggesting a major role in photoacclimation. Absorption cross-section decreased, and pigment-specific absorption coefficients increased with irradiance at the peak absorption wavelengths of chlorophyll a and phycoerythrin 545. After assessing the variability of absorption properties in M. rubrum, we combined field measurements and high-resolution Sentinel-2 satellite images to estimate chlorophyll a concentration of a coastal red tide and document small-scale spatio-temporal features. This work provides an overview of pigment photoacclimation in a peculiar phytoplankter and suggests guidelines for future studies of M. rubrum blooms.

Structures and organizations of PSI–AcpPCI supercomplexes from red tidal and coral symbiotic photosynthetic dinoflagellates

Marine photosynthetic dinoflagellates are a group of successful phytoplankton that can form red tides in the ocean and also symbiosis with corals. These features are closely related to the photosynthetic properties of dinoflagellates. We report here three structures of photosystem I (PSI)-chlorophylls (Chls) a/c-peridinin protein complex (PSI-AcpPCI) from two species of dinoflagellates by single-particle cryoelectron microscopy. The crucial PsaA/B subunits of a red tidal dinoflagellate Amphidinium carterae are remarkably smaller and hence losing over 20 pigment-binding sites, whereas its PsaD/F/I/J/L/M/R subunits are larger and coordinate some additional pigment sites compared to other eukaryotic photosynthetic organisms, which may compensate for the smaller PsaA/B subunits. Similar modifications are observed in a coral symbiotic dinoflagellate Symbiodinium species, where two additional core proteins and fewer AcpPCIs are identified in the PSI-AcpPCI supercomplex. The antenna proteins AcpPCIs in dinoflagellates developed some loops and pigment sites as a result to accommodate the changed PSI core, therefore the structures of PSI-AcpPCI supercomplex of dinoflagellates reveal an unusual protein assembly pattern. A huge pigment network comprising Chls a and c and various carotenoids is revealed from the structural analysis, which provides the basis for our deeper understanding of the energy transfer and dissipation within the PSI-AcpPCI supercomplex, as well as the evolution of photosynthetic organisms.

Predicting brown tide microalgae concentrations using reconstructed fluorescence spectroscopy combined with CNN

The non-destructive and sensitive three-dimensional excitation-emission matrix (3D-EEM) fluorescence spectroscopy shows great potential for real-time monitoring of brown tide, while current methods of 3D-EEM spectra combined with convolutional neural network (CNN) do not take full advantage of its spatial characteristics. To address this issue, we propose a data reconstruction method based on 3D-EEM spectra. By stratifying the 3D-EEM spectra according to fluorescence intensity, we can reconstruct the original two-dimensional data of the spectra into more informative three-dimensional data, then the reconstructed data are enhanced according to the characteristics of the reconstructed data by using the attention mechanism, so as to better utilize the spatial characteristics of the 3D-EEM spectra and to improve the performance of the prediction of microalgae concentration. Experimental result shows a significant improvement in the prediction of microalgae concentration using reconstructed data, the mean squared error (MSE) of the brown tide causal algae Aureococcus anophagefferens is reduced by 85.76%, and the mean squared errors of Chlorella and Synechococcus elongatus is also reduced by 96.52% and 63.76% respectively. This work demonstrates the role of convolutional neural network in 3D-EEM spectral analysis and highlights the feasibility of using 3D-EEM spectral reconstruction data to improve prediction accuracy.

Biogenic element driving mechanism in the occurrence of Chinese coastal eco-environmental disasters and regulation for ecological environment health.

In recent decades, China's coastal ecological environment has undergone significant changes under multiple pressures such as climate change and high intensity of human activities. The occurrence and scale of harmful algal blooms represented by the red tide and the green tide are increasing rapidly. Moreover, environmental problems such as hypoxia and acidification in seawater have become increasingly prominent. It is urgent to find out the occurrence mechanism and prevention measures of marine eco-environmental disasters. Therefore, we explained the connotation of the concept of "marine eco-environmental disaster" for the first time, and systematically interpreted the biogenic element driving mechanisms in the occurrence of eco-environmental disasters in China nearshore area in the aspects of exogenous input of nutrients, the mineralization and decomposition of marine organic matters and nutrient regeneration, as well as the abnormal nutrient structure in offshore waters. We pointed out that the drastic increases of terrigenous nutrient discharge caused by enhancing human activities, together with the complex biogeochemical cycle process after biogenic elements entering the sea, led to the frequent occurrence of coastal eco-environmental disasters. On this basis, combined with the latest research progress in this field, we put forward the regulatory schemes for coastal ecological environment health based on the controlling of seawater biogenic element. That is, based on land-sea integration strategy, the reduction of land-source pollutants, especially inorganic nitrogen from land, coastal zone and into the sea, and the normalization of nutrient structure in coastal seawater through artificial regulation technology, are the key points to reduce and control the occurrence of disasters and improve the quality of the coastal ecosystems.