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Cyanobacterial harmful algal blooms in freshwater systems can produce cyanotoxins, such as microcystins (MCs) and nodularins (NODs), presenting serious threats to human health and ecosystems. Required routine monitoring of cyanotoxins in water samples, as posed by U.S. EPA drinking water contaminant candidate list 5 (CCL5), demands for cost-effective, reliable and sensitive MCs/NODs detection methods. We report the development of a colorimetric paper-based immunochip assisted by nanozyme catalysis with a smartphone readout system for rapid detection of cyanotoxins in water. We show that the introduction of biorthogonal click reaction enables in situ facile self-assembly of multi-layers of peroxidase-like nanozyme onto the anti-MCs/NODs monoclonal antibody. We can detect 13 variants of MCs/NODs even in the sub-microgram per liter range with detection limit of below 0.7 μg/L and satisfactory recovery percentages between 88 and 120% in different water matrices. Our technology shows a good correlation with the well-developed ELISA technology, demonstrating its great potential applications in resource-limited or less-developed regions for on-site and large-scale screening of cyanotoxins in water environment. [Display omitted] • A paper-based biochip with high sensitivity and throughput for cyanotoxins. • A layer-by-layer bioorthogonal click reaction for nanozyme amplification. • Limit of detection below 0.7 μg/L towards 13 variants of cyanotoxins. • Satisfactory recoveries in various water environments. • An entire detection cycle time of less than 60 min. [ABSTRACT FROM AUTHOR]

Microcystins (MCs) are toxins produced by cyanobacteria commonly found in harmful algal blooms (HAB) occurring in many surface waters. Conventional methods for removing MC-LR such as membrane filtration and activated carbon are only phase change removal methods and are often expensive in operation and maintenance. It is urgent to develop a rapid, easy-to-use, and cost-effective method for the degradation of MC-LR. In this study, a novel Au-decorated Ni-metal-organic framework (Au/Ni-MOF) was newly developed on a hydrophilic carbon fiber paper (2 cm × 2 cm) using an air spraying method. The Au/Ni-MOF was then applied for the photodegradation of MC-LR in water under UV–Vis. The addition of Au onto the surface of the Ni-MOF resulted in a nearly fivefold enhancement in the reaction rate coefficient (k), reaching a value of 0.0599 min−1 for the photodegradation of MC-LR (initial concentration of 20 ppb). It was found that 94.2% of MC-LR removal was attributed to photodegradation, with the remaining 5.8% from adsorption. The rate coefficient of 20 ppb of MC-LR in the surface water sample (pH 6.0) was 0.06 min−1 likely due to the presence of other contaminates including scavenger agents within the sample which inhibits the degradation reaction of the MC-LR. Overall, this study demonstrated the potential for the novel Au/Ni-MOF to effectively reduce the concentration of the MC-LR toxin in the contaminated water. [Display omitted] • Au/Ni-MOF showed surface functionalization with excellent light absorption properties. • MC-LR photodegradation was increased with the addition of Au on the Ni-MOF. • Au/Ni-MOF was successfully applied to a real lake water sample. [ABSTRACT FROM AUTHOR]

Green tide disasters have been occurring along the Qinhuangdao coastal area for several years since 2015. This study investigated the interannual changes of green tides in Qinhuangdao from 2018 to 2020 and found that the green algae biomass was significantly reduced in 2020. The peak biomass of the green tide in July was only 151.5 g m−3, which is significantly lower than 7789.4 g m−3 in July 2018 and 5873.9 g m−3 in July 2019. Further comparative analysis showed that the decrease in nutrients, reduction in the density of Ulva microscopic propagules, and low biomass of attached macroalgae on the seaweed beds along the Jinmenghaiwan bath coastal area were the main causes for the decrease in the scale of green tides in Qinhuangdao in 2020. This paper also summarizes the factors of green tide formation in Qinhuangdao and proposes relevant prevention and control suggestions for the local governments based on the previous research. • First, this paper investigated the inter annual changes of green tides in Qinhuangdao from 2018 to 2020 and found that the scale of green tides in Qinhuangdao was significantly reduced in 2020. • Second, this paper showed that the decrease in nutrients, reduction in the number of green algae micro-propagules, and low biomass of macroalgae attached to the benthic substrate in coastal waters of Jinmenghaiwan bath were the main causes for the decrease in the scale of green tides in Qinhuangdao in 2020. [ABSTRACT FROM AUTHOR]

There is a significant concern about the accessibility of uncontaminated and safe drinking water, a fundamental necessity for human beings. This concern is attributed to the toxic micropollutants from several emission sources, including industrial toxins, agricultural runoff, wastewater discharges, sewer overflows, landfills, algal blooms and microbiota. Emerging micropollutants (EMs) encompass a broad spectrum of compounds, including pharmaceutically active chemicals, personal care products, pesticides, industrial chemicals, steroid hormones, toxic nanomaterials, microplastics, heavy metals, and microorganisms. The pervasive and enduring nature of EMs has resulted in a detrimental impact on global urban water systems. Of late, these contaminants are receiving more attention due to their inherent potential to generate environmental toxicity and adverse health effects on humans and aquatic life. Although little progress has been made in discovering removal methodologies for EMs, a basic categorization procedure is required to identify and restrict the EMs to tackle the problem of these emerging contaminants. The present review paper provides a crude classification of EMs and their associated negative impact on aquatic life. Furthermore, it delves into various nanotechnology-based approaches as effective solutions to address the challenge of removing EMs from water, thereby ensuring potable drinking water. To conclude, this review paper addresses the challenges associated with the commercialization of nanomaterial, such as toxicity, high cost, inadequate government policies, and incompatibility with the present water purification system and recommends crucial directions for further research that should be pursued. [Display omitted] • Qualitative and quantitative assessment of emerging micropollutants in aquatic systems • Sources and toxicity of various emerging micropollutants in aquatic ecosystem • Nanotechnology-based approaches exhibit the potential to remove emerging micropollutants • Toxicity, cost, disposal methods and regulatory policies are major hurdles in commercialising nanomaterials [ABSTRACT FROM AUTHOR]

Since 2018, severe and recurrent copepod depletions have been observed in Belgian coastal waters. These depletions have been described as temperature-induced mass mortality events. This paper confirms the relation of copepod abundance anomalies with periods of high temperature based on new data. Although severe, the effects, consequences and implications of this depletion remain unknown. Our study suggests that the absence of zooplanktonic predators in autumn, together with the availability of nutrients discharged via the Scheldt estuary, allowed a bloom of the diatom Bellerochea , in a season otherwise characterised by low phytoplanktonic activity. Although the bloom reaches high abundances, its effects on the marine environment are not yet visible. The enormous abundances are likely to induce small-scale oxygen depletions which might further translate to the environment. Communities of Calanoida, Canuelloida and Cyclopoida tend to recover from the annual autumn depletion, although the typical autumn peak is entirely missing in the years subject to severe heat waves and associated high water temperatures. As a result, copepod dynamics have drastically changed since the first observed depletion and associated bloom of Bellerochea in 2018. • Bellerochea blooms emerged in the Belgian part of the North Sea (BPNS) due to temperature-induced copepod depletion. • It is the first documented bloom of Bellerochea in the BPNS • Image-based datasets allow retrospective analysis of unchanged samples, revealing ecosystem changed without decay. • Copepod depletion and Bellerochea blooms intensified, wiht longer durations observed in 2022 compared to 2018. •. Copepod depletion and Bellerochea blooms may reduce oxygen, impacting thropic levels, larval fish and zooplankton in the BPNS ecosytem. • Recurrent copepod depletions and Bellerochea blooms pose challenges to predict ecosystem responses, intensified by global warming and associated heatwaves. • Since 2018, copepod dynamics have shifted, potentially favoring more temperature-resilient species in the ecosystem. [ABSTRACT FROM AUTHOR]

In this paper, we propose a class of resource-based growth models with delays in algal digestion and detritus-nutrient recycling, and investigate the model based on two different survival scenarios of algae during nutrient transformation. One scenario considers the survival rates of algae during nutrient uptake, while the other overlooks this factor. We find a significant difference in the estimated time window required for clearing the lake of detritus between the two models, and both are longer compared to the model without algal digestion delay. Moreover, the internal equilibria of both scenarios undergo an infinite number of stability switches, however, the key parameters leading to these stability switches differ. Notably, in the model accounting for algal death during nutrient uptake, there exists a safe zone where the stability of the internal equilibrium remains unaffected by the detritus-nutrient recycling delay, provided that the algal digestion delay falls within a suitable range. The findings derived from this study can provide valuable insights for the development of efficacious approaches in safeguarding the ecological integrity, managing algal blooms, facilitating sustainable fishery practices, and fostering favorable economic outcomes within the realm of water resources advancement. • Models with algal digestion and detritus-nutrient recycling delays. • Detritus clearance time variations under different algae survival scenarios. • Infinite stability switches in internal equilibria. • Safety zone identified in the model with algal death during nutrient uptake. • Insights for algal bloom management, fisheries, and water resource enhancement. [ABSTRACT FROM AUTHOR]

We present AquaNutriOpt, a user-friendly Python package designed to tackle a complex combinatorial optimization problem aimed at optimizing nutrient management for the control of harmful algal blooms. This optimization process involves the identification of optimal Best Management Practices (BMPs) and Treatment Technologies (TTs). AquaNutriOpt is constructed based on a novel integer programming model, which we present in this paper. The package can accommodate various user inputs, automatically transforming them into an optimization model, and then solving it using a free solver. To demonstrate AquaNutriOpt's efficacy, we conduct a series of experiments on two watersheds around Lake Okeechobee in Florida, USA. These experiments illustrate that the optimal BMPs/TTs obtained by AquaNutriOpt can significantly reduce Phosphorus loads into the lake across various budget scenarios. We validate the results by running simulations with the process-based Watershed Assessment Model (WAM), confirming that the estimated percentage reductions closely align with the reports from WAM. • We study controlling harmful algal blooms (HABs) through nutrient optimization. • We develop a novel mathematical optimization model for nutrient optimization. • We develop a software package in Python based on the proposed model. • We show the efficacy of the package in a case study in Lake Okeechobee in Florida. [ABSTRACT FROM AUTHOR]

Electrophysiological techniques, by measuring bioelectrical signals and ion channel activities in tissues and cells, are now widely utilized to study ion channel-related physiological functions and their underlying mechanisms. Electrophysiological techniques have been extensively employed in the investigation of animals, plants, and microorganisms; however, their application in marine algae lags behind that in other organisms. In this paper, we present an overview of current electrophysiological techniques applicable to algae while reviewing the historical usage of such techniques in this field. Furthermore, we explore the potential specific applications of electrophysiological technology in harmful algal bloom (HAB) research. The application prospects in the studies of stress tolerance, competitive advantage, nutrient absorption, toxin synthesis and secretion by HAB microalgae are discussed and anticipated herein with the aim of providing novel perspectives on HAB investigations. [ABSTRACT FROM AUTHOR]

Harmful algal blooms is a global problem of water pollution causing great economic losses to countries. Microcystis aeruginosa , as a dominant algal species in cyanobacterial blooms, has attracted extensive attention. However, most of the current studies on the treatment of alga-containing waters focus on the removal of algal cells or microcystins, lacking the exploration of the degradation pathways and analyses of the toxicity of the products. In this paper, we constructed a photo-Fenton system using Fe(III)-EDDS (EDDS: Ethylenediamine-N,N'-disuccinic acid) complex as an iron source for the simultaneous removal of Microcystis aeruginosa as well as microcystin-LR (MC-LR). The results showed that adding 0.1 mM of Fe(III)-EDDS complex and 1.0 mM of H 2 O 2 achieved 83.3% algal cell removal in 240 min under neutral pH conditions and also degraded 72.5% of MC-LR. Moreover, the degradation products of MC-LR and EDDS were analyzed by LC-MS, which showed that the toxicity of the MC-LR molecule was greatly reduced by benzene ring removal and decarboxylation of partial amino acids, while its degradation resulted from the destruction of amino acids in the MC-LR molecule. The toxicity analyses provide a basis for the practical application of the system, hence consideration can be given to combining or improving it with the existing UV disinfection technologies in water supply plants for potential algal bloom outbreaks. This study was the first time to apply the Fe(III)-EDDS system to the field of microalgae removal and MC-LR detoxication, aiming to provide new development ideas for water purification and photochemical algae removal technology. [Display omitted] • Simultaneous removal: algal cells and MC-LR via Fe(III)-EDDS photo-Fenton system. • System oxidative activity: hydroxyl radicals attacks both algal cells and MC-LR. • Mechanistic reveal: changes in physiological indexes of algal cells are monitored. • Further analysis: degradation pathways of MC-LR and toxicity of products. [ABSTRACT FROM AUTHOR]

• The oceanographic conditions before El Niño 2015–16 favored the generation of events. • Significative differences between species and ENOS conditions were detected in HAB duration. • The upwelling relaxing condition favors the retention of HABs while the upwelling produces the dispersion. • The simulations explain the low connectivity between bays. The bays of Tongoy and Guanaqueros are located in the Humboldt Current system, where Argopecten purpuratus has been the subject of intense aquaculture development. These bays lie in one of the most productive marine ecosystems on Earth and are dominated by permanent coastal upwelling at Lengua de Vaca Point and Choros Point, one of the three upwelling centers on the Chilean coast. Significantly, this productive system experiences a high recurrence of harmful algal bloom (HAB) events. This paper examines 9-year (2010–2018) samples of three toxic microalgal species collected in different monitoring programs and research projects. During this period, nine HAB events were detected in Guanaqueros Bay and 14 in Tongoy Bay. Among these, three HAB events were produced simultaneously in both bays by Pseudo-nitzschia australis , and two events produced simultaneously were detected in one bay by Alexandrium spp. and the other by Dinophysis acuminata. Before El Niño 2015–16, there were more HAB events of longer duration by the three species. Since El Niño, the number and duration of events were reduced and only produced by P. australis. HAB events were simulated with the FVCOM model and a virtual particle tracker model to evaluate the dynamics of bays and their relationship with HAB events. The results showed retention in bays during the relaxation conditions of upwelling and low connectivity between bays, which explains why almost no simultaneous events were recorded. [ABSTRACT FROM AUTHOR]

Forecasting harmful algal blooms (HABs) is an important part of marine environmental monitoring. Algae bloom observation channels includes satellite remote sensing and maritime station monitoring (MSM). Compared with satellite remote sensing image, MSM can collect more accurate data, which includes various seawater inorganic salt content related to the HABs. However, the measured data of MSM is easily affected by regional sediment content and seawater dynamic field, which leads to lack the accurate forecasting models. Therefore, this paper proposed a local spatio-temporal HABs forecasted model (STHFM) based on few impact factors in MSM. The advantage of this model is to first use principal component analysis to select main environment factors (MEFs) related to HABs. Then, this model distinguishes multiple warning levels of HABs in spatio-temporal according to the algae growth rate. Finally, this paper generates continuous MEFs time series information based on the Autoregressive Integrated Moving Average (ARIMA) model in the high-level warning area. And an improved LSTM network with MEFs time series as input is established to forecast HABs in future. The proposed model is tested on the NOAA website public dataset, which contains historical harmful algae Alexandrium data on the East Coast of US. The experimental shows that our model has good HABs monitoring performance. Under the public NOAA Alexandrium dataset, the proposed model can achieve the highest prediction accuracy of 82.1%, and has a small prediction error. • The coupling relationship between HABs and major environmental factors were investigated. • The changes of algae were successfully predicted by using the few major influencing factors. • The use of space–time clustering in combination with forecasting is recommended. • Better prediction of HABs by combining ARIMA with deep LSTM network. [ABSTRACT FROM AUTHOR]

• Reports of BHAB species and related harmful events in South America (SA) were reviewed. • Greater diversity of toxigenic species found in equatorial/tropical areas of the continent. • Prorocentrum lima complex is the most frequent and widespread BHAB taxon in SA. • Ciguatera events reported in Colombia and Venezuela since the 1970s and 80s. • Enhanced analytical capacity and BHAB monitoring are necessary in most parts of SA. Public awareness about Benthic Harmful Algal Blooms (BHABs) and their negative impacts has increased substantially over the past few decades. Even so, reports of BHABs remain relatively scarce in South America (SA). This paper provides a comprehensive overview of the current state of knowledge on BHABs in the continent, by integrating data from published articles, books, and technical reports. We recorded ∼300 different occurrences of potentially toxic BHAB species over the Caribbean, Atlantic and Pacific coasts, mostly in marine (>95%) but also in estuarine areas located from 12⁰36′ N to 54⁰53′ S. Over 70% of the data was published/released within the past 10 years, and ∼85% were concentrated in Brazil, Venezuela, Ecuador and Colombia. Benthic species were mainly associated with macroalgae, seagrass and sediment. Incidental detection in the plankton was also relevant, mainly in places where studies targeting BHAB species are still rare, like Argentina, Uruguay, Chile and Peru. The study listed 31 infrageneric taxa of potentially toxic benthic dinoflagellates and eight of estuarine cyanobacteria occurring in SA, with the greatest species diversity recorded in the equatorial-tropical zone, mainly in northeastern Brazil (Atlantic), Venezuela and Colombia (Caribbean), and the Galapagos Islands, Ecuador (Pacific). Local strains of Amphidinium, Gambierdiscus, Coolia and Prorocentrum spp. produced toxic compounds of emerging concern. Prorocentrum lima species complex was the most common and widely distributed taxon, followed by Ostreopsis cf. ovata. In fact, these two dinoflagellates were associated with most BHAB events in SA. Whereas the former has caused the contamination of multiple marine organisms and cases of Diarrhetic Shellfish Poisoning in subtropical and temperate areas, the latter has been associated with faunal mortalities and is suspected of causing respiratory illness to beach users in tropical places. Ciguatera Poisoning has been reported in Colombia (∼240 cases; no deaths) and Venezuela (60 cases; two deaths), and may be also a risk in other places where Gambierdiscus spp. and Fukuyoa paulensis have been reported, such as the Galapagos Islands and the tropical Brazilian coast. Despite the recent advances, negative impacts from BHABs in SA are intensified by limited research/training funding, as well as the lack of official HAB monitoring and poor analytical capability for species identification and toxin detection in parts of the continent. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel framework is proposed to assess the risks of algal blooms in lakes. • Vine Copula was used to integrate the quantity-distribution of algal blooms. • The framework was used effectively in risk assessment of Chaohu Lake, China. • The framework can handle the problem of spatio-temporal dynamics in risk assessment. Algal blooms threaten water safety and quality, particularly in lakes with vulnerable environment and advanced urbanization. Due to low water exchange rate and multiple human activity influences, algal blooms in inland lakes display highly dynamic spatio-temporal distributions. This paper proposes a comprehensive framework for risk assessment of algal bloom coupling quantity and distribution based on remote sensing observations. The framework comprises algal bloom recognition, spatial zonation, quantity-distribution multivariate joint distribution construction, and risk assessment. The framework was applied to China's giant shallow and algae-prone lake, Chaohu Lake, to assess the annual algal bloom risk from 2000 to 2021. The results showed that this proposed method could achieve a more comprehensive and objective risk assessment by coupling the quantity and distribution of algal blooms. Furthermore, the internal dependence of algal bloom fluctuation in different zones was explicitly presented. This framework promotes systematic integration of algal bloom risk assessment, taking into account its highly spatio-temporal dynamic feature. It creates a quantitative approach to gain insights into the evolution of quantity and distribution in various environmental assessments. [ABSTRACT FROM AUTHOR]

• Climate or physiographic patterns often induce non-stationarity for extreme values. • pML methods require subjective decisions which could lead to some biases. • npML methods are compared to commonly used pML method to estimate conditional density. • npML should be prioritized if there is no a priori knowledge of the non-stationary form. • Random forest for CDE is a promising tool when fitted with several covariates. Besides the complex effect of global warming on extreme events, spatiotemporal variability of natural phenomena often carries the legacy of anthropogenic activities. Moreover, any feedback induced by these activities on climate brings additional complexity when modelling natural events. For extreme values, climate or physiographic patterns often induce non stationarity, or long-term changes. In this context, parametric models may become inadequate given the complexity of the studied phenomena and their systematic changes through space and time. In this paper, we assess the use and ensuing efficiency of nonparametric machine learning (npML) methods to estimate and predict extreme values associated with natural events. These npML methods are compared to a commonly used parametric machine learning (pML) approach, the nonstationary frequency analysis model. We use a historical database compiling the frequency of harmful algal blooms (HAB) in Québec, Canada. Results show that a 19-covariate RFCDE model leads to the best mean estimate among the considered models. However, for low and large quantiles, the 4-covariate RCDE model provides better agreement between observed and simulated bloom frequencies. The models may be used to assess the effects of climate change and anthropogenic developments on the frequency of HAB. They may also be leveraged to measure the efficiency of mitigation scenarios and to identify priority areas for restoration plan strategies. Recommendations are finally made regarding the estimation of the conditional density to predict extreme values associated with natural events. [ABSTRACT FROM AUTHOR]

Climate change is an issue that is causing a wide range of impacts along Australian coastlines including sea level rise, density of development and infrastructure, exposure to extreme weather, algal blooms, oil spills, availability of affordable property insurance, governmental policies, and regulations. Solutions will require the navigation of complex inter-relationships to facilitate the building of effective policy. Development of effective communications is essential to deployment of effective adaptations. This paper reports the results of a narrative review on how to communicate climate change impacts to marine and coastal communities. Results show communications must be tailored to the right audience at the right time and delivered by trustworthy messengers. A best practice communications strategy is suggested. • Communicating climate change in coastal and marine contexts has specific challenges. • Two-way communications must be tailored to the right audience. • Climate communications need to deliver the right messages. • Climate change communications need delivery by trusted messengers. [ABSTRACT FROM AUTHOR]

With the increasing problem of eutrophication, lacustrine ecosystem can undergo complex changes, often resulting in a shift from a clear macrophyte-dominated state to a turbid phytoplankton-dominated state. However, it's not clear how lake transitions occur at regional and global scales. This is due to a lack of long-term monitoring and an effective algorithm that can distinguish floating/emergent aquatic vegetation (FEAV), submerged aquatic vegetation (SAV) and algal bloom (AB). This paper presents a novel three-step classification algorithm based on Landsat imagery, (ie., vegetation and bloom indices (VBI) algorithm): (1) to distinguish between aquatic vegetation (AV) and non-aquatic vegetation (non-AV) extents by an aquatic vegetation index (AVI) derived from tasseled cap transformation; (2) to identify FEAV and SAV within AV extent by using the normalized difference vegetation index (NDVI), and (3) to extract AB from non-AV extent with floating algae index (FAI). The performance of the VBI algorithm was validated using 1307 field samples collected across 22 lakes in the middle and lower reaches of the Yangtze River (MLY) in China, with a pooled overall accuracy of 84.49%. Finally, the VBI algorithm was applied to Landsat data from 1985 to 2021 to quantify the temporal changes of FEAV, SAV and AB in large lakes (i.e., > 50 km2) along the MLY. Within these lakes, AV showed a significant decrease over the past 37 years, mainly due to the decrease of SAV; while AB occurred with higher frequency and in more lakes. The transition from a macrophyte-dominated state to a phytoplankton-dominated aquatic systems is still ongoing in the MLY area. This study shows outstanding innovation in the construction of a new classification index (i.e., AVI), and the method of calculating the adaptive threshold, which makes VBI algorithm have great potential in mapping long-term changes and capturing transformation between lake communities on a global scale. • A novel Landsat-based algorithm was developed for quantifying aquatic communities. • An index for aquatic vegetation (AV) was proposed to classify AV and non-AV. • Long-term algal blooms and AV (floating/emergent/submerged) in MLY lakes were mapped. • AV decreased while algal blooms increased in most MLY lakes from 1985 to 2021. • Shift from macrophyte- to phytoplankton-dominated state is ongoing in MLY lakes. [ABSTRACT FROM AUTHOR]

This paper presents Lake Operation Optimization of Nutrient Exports (LOONE), a Python-based model with three coupled modules: 1) a water balance module to simulate hydrology and operations, 2) a nutrient module to simulate phosphorus dynamics in the water column, and 3) an optimization tool to design optimal reservoir releases. We applied the model to Lake Okeechobee (Florida, USA), a shallow subtropical lake receiving and exporting excessive amounts of nutrients, while providing water supply, recreation, and flood control. We evaluated LOONE under historical operation schedules for model verification, and then designed optimal releases that minimized phosphorus exports into the two main distributaries of Lake Okeechobee. We found that P loads could decrease by 12–33% under optimal operations. The software package could be used to evaluate management decisions to help control water quality issues such as high nutrient exports and harmful algal blooms in Lake Okeechobee and reservoirs worldwide. • We developed a model to manage operations of nutrient impaired reservoirs. • The model includes dynamic phosphorus balance coupled with an optimization algorithm. • The model was evaluated to minimize phosphorus release from Lake Okeechobee. [ABSTRACT FROM AUTHOR]

This paper estimates beachgoers' preferences for beach quality, including avoidance of harmful algal blooms and bacterial warnings. Following a stratified random sampling schedule, data was collected via interviews conducted at 28 public beaches from Eastern Ohio to Northern Lake St Clair. Randomly selected visitors were interviewed and sent a follow-up choice experiment survey, which measured preferences for beach attributes. We find the average respondent is willing to drive 260 and 266 miles to avoid sites with either current HAB or bacterial warnings, and find a negative stigma effect that remains at least 6 days post-warning. While respondents' aversion to active HAB and bacterial warnings are not statistically different, this aversion decreases more slowly after a bacterial warning; respondents are willing to drive 77 miles to avoid a site with a bacterial warning lifted 6 days earlier, but only 31 miles to avoid a site with a HAB warning lifted 6 days earlier. To test our findings' validity, we used the choice model estimates to simulate responses to contingent behavior questions from the follow-up. Although framed differently, the elicitation formats yield concordant findings. Results indicate that cost-benefit analysis which doesn't evaluate the stigma effect of recently-lifted warnings may understate their costs. • Beachgoers are significantly averse to current and recent HAB & bacterial warnings. • The mean beachgoer is willing to drive up to 260 miles to avoid sites with either warning. • This aversion remains for up to six days after warnings are lifted. • Aversion to bacterial warnings persists longer than aversion to HAB warnings. • This "lag effect" has implications for the accurate measurement of warning costs. [ABSTRACT FROM AUTHOR]

• Microalgae identification to solve the issues of harmful algae blooms. • The classification of potential algae strains for valuable bioactive compounds. • Machine learning and deep learning techniques for smart algae identification. • Image acquisition with consideration of robust dataset to enhance accuracy. • Incorporate various image pre-processing module to improve classification results. The identification of microalgae species is an important tool in scientific research and commercial application to prevent harmful algae blooms (HABs) and recognizing potential microalgae strains for the bioaccumulation of valuable bioactive ingredients. The aim of this study is to incorporate rapid, high-accuracy, reliable, low-cost, simple, and state-of-the-art identification methods. Thus, increasing the possibility for the development of potential recognition applications, that could identify toxic-producing and valuable microalgae strains. Recently, deep learning (DL) has brought the study of microalgae species identification to a much higher depth of efficiency and accuracy. In doing so, this review paper emphasizes the significance of microalgae identification, and various forms of machine learning algorithms for image classification, followed by image pre-processing techniques, feature extraction, and selection for further classification accuracy. Future prospects over the challenges and improvements of potential DL classification model development, application in microalgae recognition, and image capturing technologies are discussed accordingly. [ABSTRACT FROM AUTHOR]

[Display omitted] • Current land management can lead to more severe BAP conditions. • Regulating fertilizer application rate can offset HAB risks from extreme climate. • Regulating P was more effective in reducing HAB risks in freshwater watersheds. • Regulating N was more effective in controlling HAB downstream of watershed. This paper was aimed at assessing the risk of HAB occurrence in a highly cultivated watershed and evaluating the effectiveness of N and P fertilizer reduction practices in mitigating this risk under future climate projections. To achieve this objective, a modelling framework was developed for HAB risk assessment under different environmental stressors including climate changes and different land management practices. The modelling framework used a fully distributed physical-based hydrologic model, MIKE SHE, and a hydrodynamic river model, MIKE 11, coupled with ECO-Lab to simulate the fate and transport of different forms of N and P in the Upper Sangamon River Basin (USRB), a highly cultivated watershed in central Illinois. Three different land management scenarios based on the N and P reduction target in "The Gulf Hypoxia Action Plan" were simulated to assess the P nonpoint source behavior and HAB risk level in the USRB from 2020 to 2050 under extreme climate projections. Our results predicted that the HAB risk in USRB is relatively low even with increased bioavailable P (BAP) concentration and longer duration with high BAP concentration due to low water temperature. Reducing N or P application rates by 50% was able to offset the negative effects on HAB occurrence from extreme climate projections apart from spring. Within P and N, regulating P was found to be more effective in reducing HAB risks in the USRB while regulating N was more effective in controlling HAB downstream. Understanding the dynamics of N and P in causing the occurrence of HAB was expected to improve the mitigation measures that we implement at the field level. [ABSTRACT FROM AUTHOR]

• A regional model for algal bloom frequency under a non-stationary framework. • A model to project bloom scenarios in response to anthropogenic developments. • A model to test the effects of mitigation scenarios on bloom frequency. • Case studies testing model capacity to foresight climate change impacts on blooms. • Projections showing doubling of bloom frequency in a eutrophic lake over next 80 years. There are significant social, economic and environmental costs related to phytoplankton blooms, particularly when they are dominated by cyanobacteria. However, the climatic, physiographic and morphological drivers involved in bloom phenology create complex spatiotemporal patterns in biomass and taxonomic composition, making monitoring and forecasting challenging. This complexity also limits the ability of process-based algorithms to model bloom phenology. Stochastic approaches and predictive modelling are valuable risk management tools for natural events. This paper presents a novel model to estimate the conditional density of phytoplankton blooms based on environmental covariates, namely the physiography and climate descriptors of lake watersheds. The goal was to provide a tool to project future scenarios of bloom phenology in response to climate change and anthropogenic developments, and to test the efficiency of mitigating approaches. Specifically, we developed a non-stationary regional model to estimate the probability of bloom occurrence in 580 lakes in Quebec, Canada, and to study the impact of physiographic or climate changes over our reference period and future horizons. Results show that the regional model is more precise and accurate than local models, which are usually used in frequency analyses of extreme values. Simulations conducted for different climatic and physiographic scenarios on the watershed of Lake Brome indicate a 65% increase in bloom frequency on the horizon of years 2080–2100. The model also evaluates the effects of different environmental disturbances on bloom phenology, such as agriculture or settlement increase in the watershed. Disturbance case studies were carried out on lakes with different trophic levels, physiographic and climatic characteristics. Simulations indicate that bloom frequency in a highly urbanized meso-eutrophic lake (Lake Brome) and a eutrophic lake with a watershed dominated by agriculture (Missisquoi Bay) would be more responsive to changes in climate rather than land cover, although physiographic disturbances would still generate considerable effects. A meso-eutrophic lake with a watershed dominated by forest (Lake Aylmer) would neither respond to increases in agriculture nor settlement but would be most affected by increases in degree days. Another scenario focused on a highly forested oligo-mesotrophic lake (Lake St. Jean). Bloom phenology in this lake was most affected by disturbances in agriculture or settlement land use. Overall, these results suggest that lakes with a high level of eutrophication are the least responsive to the pressures resulting from land cover changes. [Display omitted] [ABSTRACT FROM AUTHOR]

This paper analyzed the long-term variations in nutrients in Liaodong Bay and their potential influencing factors based on historical data from 1978 to 2019. Under the influence of both human activities and natural changes, the concentration of DIN increased approximately 4-fold from the end of the 1990s to the mid-2010s, while DIP and DSi concentrations decreased from the beginning to the end of the 1980s and have since increased again. Asynchronous changes in nutrient levels have led to changes in the nutrient composition, which has caused a series of ecological effects. The total phytoplankton abundance decreased from the 1980s to the end of the 1990s and then increased again. Additionally, the phytoplankton composition shifted from a diatom-dominated to a dinoflagellate-dominated system, and the dominant species of zooplankton changed. Harmful algal blooms (HABs) rarely occurred before the 1980s but have frequently occurred since the end of the 1990s. • Long-term changes of nutrients in Liaodong Bay during the past 40 years • Transport fluxes of nutrients from different sources affected by human activities in Liaodong Bay • Ecological effects caused by nutrient changes in Liaodong Bay [ABSTRACT FROM AUTHOR]

The prediction of algal bloom is one of the important links in eutrophication prevention. Chlorophyll a concentration is the indicating variable of algal bloom, and its time series is non-stationary and non-linear, which brings challenges to its effective prediction. Although the current algae growth model (AGM) can directly describe the algal bloom dynamics, the fixed parameters limit the adaptability of the model. If the fixed parameters are dynamically adjusted, the trend of chlorophyll a concentration can be better captured. Therefore, the adaptive dynamic programming (ADP) approach is used to optimize the parameters of the AGM. The ADP contains an action network and a critic network by echo state network, where the action network is used to output the increment value of the fixed parameters, and the critic network is used to approximate the performance index function. In this paper, the input of the action network uses the time series features extracted by the relevant variables, so that the time-varying parameters of the AGM have better dynamic characteristics. We verify the effectiveness of the proposed model through the dataset of the North Canal and Taihu Lake, and the convergence analysis proves the theoretical reliability. In this way, the improved mechanism model with time-varying parameters not only maintains the better interpretability of the original AGM, but also further enhances the prediction accuracy and adaptability by extracting inherent interactive features from the relevant variables. • A time-varying algae growth model (TAGM) is proposed for algal bloom prediction. • CMA-ES is used to estimate the fixed parameters. • Adaptive dynamic programming with ESN is used to solve the incremental parameters. • Time series feature is employed to enhance the prediction accuracy. • TAGM is adopted to the actual lakes with better interpretability and precision. [ABSTRACT FROM AUTHOR]

. Harima-nada sea suffers from oriogotrophication/nori damages due to diatom bloom • 4 type phytoplankton were modeled in the benthic-pelagic ecosystem model • The model reproduced the lifecycle and blooms of harmful diatoms in Harima-nada • The physical-chemical-biological causes of blooms were revealed by the model • This phytoplankton modelling approach enables to apply harmful bloom problems Harmful diatom (Coscinodiscus waillesi and Eucampia zodiacus) blooms frequently occur in the western coastal area of Japan from late autumn to early spring, causing discoloration of edible seaweed nori (Pyropia yezoensis). One of the causes of the discoloration is thought to be nutrient depletion (oligotrophication) due to nutrient uptake by diatoms. The goal of our study was to elucidate the mechanisms underlying phytoplankton blooms and the effects of such blooms on comprehensive nutrient cycles in the benthic-pelagic ecosystem. We developed a new ecosystem model, EMAGIN-L.P., simultaneously representing phytoplankton life cycle and the benthic-pelagic ecosystem. The life cycles of four types of phytoplankton—dinoflagellates (DFL), small diatoms (SDA), Coscinodiscus wailesii (CDW), and Eucampia zodiacus (EZ)—were numerically modeled and incorporated into an existing ecosystem model, ECOHYM (Sohma et al., 2008a), representing the food web among the benthic and pelagic systems and carbon-nitrogen-phosphorus-oxygen-coupled cycles driven by biogeochemical and physical processes. The model was applied to the Harima-Nada Sea where the discoloration of nori frequently occurs. The model reproduced the differences in timing and scale of the four phytoplankton blooms, and each bloom could be explained by a combination of temperature suitability, light availability, nutrient limitation, and vertical mixing within the water column. Furthermore, through a sensitivity analysis, competition for nutrient uptake among different types of phytoplankton was observed in the model. That is, from June to October, when DFL and SDA blooms occur, the SDA nutrient uptake rate is high and SDA suppresses the DFL bloom, while from November to March, when CDW and EZ blooms occur, the nutrient uptake rate of EZ is high and the CDW bloom is slightly suppressed. The developed model representing the phytoplankton bloom mechanisms in the whole benthic-pelagic coupled ecosystem will be a useful tool for revealing the mechanisms underlying the nutrient cycle and the contribution of harmful diatom blooms to the discoloration of nori. The modeling approach presented in this paper (i.e., categorizing different types of major phytoplankton and incorporating their life cycle into the entire benthic-pelagic coupling ecosystem) can be an effective method to understand, predict, and manage the problems caused by harmful diatom blooms across different damage types, harmful diatom species, and ocean areas. [ABSTRACT FROM AUTHOR]

High frequency water quality data measured by in-situ sensors allowed the development of auto-calibration methods for water quality simulation programs. However, these methods consider static parameter values, which may be unrealistic for microorganism activities. An alternative technique is to use data assimilation methods. This paper presents a first application of a particle filter that assimilates dissolved oxygen (DO) data into the hydro-ecological model ProSe. It demonstrates the capability of the approach for simulating DO concentrations and characterizing time-varying physiological properties of living communities in contrasted trophic contexts. DO concentrations are better estimated, especially during algal bloom when phytoplankton physiological parameters match the ones reported in the literature. Despite the simulation capabilities related to phytoplankton, further improvements related to low flow periods can still be achieved, especially concerning the heterotrophic bacteria properties as well as a finer description of the biodegradable component of the organic matter flux at the system's boundaries. • A particle filtering method is applied for the first time in the Seine River system. • The filter improves significantly the simulation of oxygen and algae dynamics. • The filter can capture time-varying phytoplanktonic parameters during algal blooms. • The description of BDOM data need to be further investigated for low flow periods. [ABSTRACT FROM AUTHOR]

• The continental margin off SE Spain is sediment-starved and submarine canyons incised into it show low particle fluxes. • Off-shelf particle export following occasional river discharge is determined by storms and modulated by oceanographic conditions. • Canyon head incision and distance to the shoreline play a key role in particle trapping capability by submarine canyons. • Bottom trawling impacts particle fluxes in some of the investigated canyons (i.e. the Garrucha-Almanzora Canyon System). • Few terrestrial-sourced particles reach the deep basin off the Gulf of Vera. Investigating the transfer of particulate matter from the continental shelf to the deep basin is critical to understand the functioning of deep sea ecosystems. In this paper we present novel results on the temporal variability of particle fluxes to the deep in three physiographic domains of a 240 km long margin segment and nearby basin off Murcia and Almeria provinces in the SW Mediterranean Sea, which are submarine canyons forming a rather diverse set (namely Escombreras, Garrucha-Almanzora and Almeria), the adjacent open slope and the deep basin. This margin is located off one of the driest regions in Europe and, therefore, its study may help understanding how mainland aridity translates into the export of particles to deep margin environments. Five mooring lines equipped with currentmeters, turbidity-meters and sediment traps were deployed for one entire annual cycle, from March 2015 to March 2016. We combine oceanographic, hydrological and meteorological data with grain size and bulk elemental data (organic carbon, opal, CaCO 3 , lithogenic) from the collected sinking particles to understand what drives particle transfers in such an under-studied setting, and to quantify the resulting fluxes and assess their spatio-temporal variability. Weighted total mass fluxes in canyons range from 1.64 g m−2 d−1 in Almeria Canyon to 7.33 g m−2 d−1 in Garrucha-Almanzora Canyon system, which are rather low values compared to other submarine canyons in the Western Mediterranean Sea. This results from the absence of extreme wind-storm events during the investigated time period combined with the reduced sediment input to the inner shelf by river systems in the study area. Our results also show that wind-storms are the main trigger for off-shelf particle transport to the deep margin, both within submarine canyons and over the open slope. The most significant transfer period is associated to a set of north-eastern storms in early spring 2015, when the off-shelf transport likely was promoted by storm-induced downwelling. However, the prevailing oceanographic conditions restricts the advection of water down the canyon heads to a few hundred meters, thus promoting a bottom-detached transport of particles seaward. Overall physiography, canyon head incision into the continental shelf and the distance of the canyon head to the shoreline (e.g. very short in Garrucha Canyon) play a key role in particle trapping capability and, therefore, in easing downslope particle transport. Further, bottom trawling activities around the Garrucha-Almanzora Canyon system, feed a nepheloid layer at depths in excess of 400 m, subsequently enhancing particle fluxes throughout the study period. In contrast, maximum particle fluxes in the deep basin respond to seasonal phytoplankton blooms. Our study shows that particle export from the shallow inner margin to the deep outer margin in sediment-starved settings, even if limited, does occur as dominated by atmosphere and ocean driven short-lived events. However, that export does not reach too far as at several tens of kilometres from the shelf edge advective fluxes are replaced by vertical ones impelled by phytoplankton dynamics. [ABSTRACT FROM AUTHOR]

Phosphorus (P) scarcity and the environmental hazards posed by P discharges have triggered the development of technologies for P sequestration and removal from waste streams. Agriculture runoff usually has P concentrations high enough to contribute to eutrophication and harmful algal blooms, but they are still too low for successful P removal with conventional technologies commonly applied in wastewater treatment. For this reason, realistic approaches to remove P from agricultural waste streams mainly include natural assimilation and constructed wetlands. Although these technologies have been implemented for some time, P removal is not always achieved to the needed extent and sometimes sufficient surface areas required are unattainable. Phosphorus sorbing materials, especially materials rich in calcium, have emerged to increase the removal potential of runoff treatment wetlands and at the same time sequester P for potential subsequent reuse. This paper analyses the current strategies and technologies for P removal and reuse from agriculture surface runoff streams taking a circular economy approach. It particularly addresses the current state of calcium rich materials commonly used for P removal that have also shown positive results as fertilizers or soil. [ABSTRACT FROM AUTHOR]

The South Shetland Islands, including King George Island (KGI), are located in the northern hydrographic zone on the West side of the Antarctic Peninsula (Northern WAP), which is washed mainly by the Antarctic Circumpolar Current (ACC). Continuous vertical mixing of the water column by strong currents, violent tidal water exchanges in deep fjords and frequent strong winds do not favour the seasonal appearance of large phytoplankton blooms. In contrast, the southern WAP is bound by the continental shelf, and is under the influence of the weaker Antarctic Peninsula Coastal Current (APCC), maintaining seasonal winter sea ice, which provides a shallow mixed layer, which in turn supports high levels of biological production in summer. During the 2009 / 2010 summer, however, a distinctive bloom event (chl-a > 20 μgL−1) was documented for in Admiralty Bay (AB), the largest and deepest fjord in KGI. It commenced in early summer (29 December 2009) at the edge of melting sea ice which had persisted since the preceding cold winter of 2009. The phytoplankton group dynamics, determined using photosynthetic pigment data, and associated changes in nutrient concentration during the bloom, have been described in this paper. The area where the phytoplankton bloom developed coincided with the surface of the brash sea ice cover. The sequence and size of biological and chemical changes recorded within the fjord during the bloom resembled the recurring ice edge blooms which occur in the southern WAP, although they had a much shorter lifespan (< two weeks), which may have been due to the slow SE winds and related surface water movement direction, which hindered vertical mixing and kept the surface water within the fjord. • A distinctive diatom bloom was documented after sea ice melting in Admiralty Bay. • The massive bloom entailed changes in phytoplankton assemblages composition. • The concentration of chl-a has reached an unusually high level. • The phosphates have depleted locally to the values limiting primary production. • The environmental changes during the bloom were similar to those in the southern WAP. [ABSTRACT FROM AUTHOR]

We investigated spatiotemporal variations of nutrients, dissolved organic pools (C, N, P), phosphomonoesterase (PME) and phosphodiesterase (PDE) activities, heterotrophic prokaryotic production and planktonic microorganisms within the mixed layer (ML) in the Eastern Mediterranean Sea. We characterized two contrasted situations: autumn 2018 (highly stratified period, deep chlorophyll maximum within 100 m depth) and winter 2019 (including a bloom period). We compared the distribution of biogeochemical variables within the mixed layer and hydrological vertical structure between the different stations using a principal component analysis. Six groups of stations were identified (one group in autumn, 5 in winter), based on variable physical descriptors but also environmental biogeochemical conditions related to i) the seasonal aspect (for instance, all stations sampled within the Ierapetra anticyclone in autumn clustered in one, single group); ii) transitions between cyclonic and anticyclonic structures with a large range of ML depths (18–269 m) and indications of intense, preceding winter convection events: iii) progression of a high phytoplankton bloom during the winter cruise inferred from a series of observations: a strong nitrate drawdown, important growth of Synechococcus , pico and nano eukaryotes, accumulation of chlorophyll a (>60 mg m−2), primary production rates up to 509 mg C m−2 d−1, changes in the pigments' diversity, increase in biomass-specific ectoenzymatic activities and of heterotrophic prokaryotic production, all in conjunction with the vicinity of the Rhodes gyre. Here, we studied the distribution of biological and biogeochemical properties within the mixed layer, in particular by employing sensitive methods for the detection of low phosphate concentrations and of the labile dissolved organic phosphorus pool. From this data set, we demonstrate that the surface mixed layer classically considered as a P-depleted and uniform layer in the Eastern Mediterranean Sea was highly biologically dynamic, and prone to rapid spatio-temporal changes in phosphatase activities and phytoplankton dynamics. Altogether, these data reveal a strong short-term population dynamics. The results highlight the role of mixing episodes in winter, which provide pulsed supplies of phosphate and/or nitrate from the deeper layer to the euphotic zone, triggering transient blooms that often go undetected by satellites. • Significant role of mixing episodes in winter in eastern Mediterranean Sea. • Meso-scale variability in the mixed layer (P-depleted) affects P cycle and populations. • Phosphomonoesterase and phosphodiesterase kinetics tracers of P availability. • An important, winter phytoplankton bloom evidenced in the vicinity of the Rhodes gyre. • Highest cell specific phosphatases were seen in the Rhodes gyre. [ABSTRACT FROM AUTHOR]

This paper describes the development of a decision support system (DSS) for evaluating membrane restoration strategy. The engine of the DSS is a digital twin (DT), a virtual representation of wear (degradation) and restoration of membrane elements in a reverse osmosis (RO) pressure vessel. The basis of the DT is a mathematical model that describes an RO vessel as a novel multi-component system in which the wear-states of individual elements (components) are quantified and elements can be swapped or replaced. This contrasts with the contemporary presentation in the literature of a membrane system as a single system. We estimate the parameters of the model using statistical methods. We describe our approach in the context of a case study on the Carlsbad Desalination Plant in California, which suffers from biofouling due to seasonal algae blooms. Our results show a good fit between the observed and the modelled wear-states. Competing policies are compared based on risk, cost, downtime, and number of stoppages. Projections indicate that a significant cost-saving can be achieved while not compromising the integrity of plant. [ABSTRACT FROM AUTHOR]

• Flow pattern of Xiangxi River can be generalized according to the intrusive location of thermal stratified flows. • The effect of typical thermal stratified flows on algae transport process is analyzed. • The superimposed effect of different thermal stratified flow patterns is one reason of multiple algal blooms. • Algal bloom governance proposals under different hydrodynamic conditions are given. After the impoundment of Three Gorges Reservoir (TGR), its tributaries have been frequented by algal blooms, especially the Xiangxi River (XXR). Stratified flow induced by temperature difference often occurs, which likely influences the water exchange and algae transport process between the tributary and TGR. To investigate the variation of flow field and algae concentration in XXR, a 2-dimensional hydrodynamic and water quality model is developed. The simulation results show good agreement with field observed data, reproducing the water exchange and algal bloom process. Notwithstanding the hydrodynamic environment of XXR is complicated, the thermal stratified flows are generalized into six typical patterns in this paper. Subsequently, algae transport processes under the influence of different thermal stratified flow patterns are examined. Thermal stratified flows from upstream and TGR intrude into the bay tributary through different layers with different combinations, resulting in water exchange of XXR is the major cause of algae transport difference. We show that when the mainstream intrusive flow and upstream inflow separately intrude into the XXR through the surface and bottom layer, hydrodynamic environments are favorable to algae transport, with the final chlorophyll- a (Chl-a) concentrations of entire XXR lower than algal bloom threshold value. The worst scenarios occur when the mainstream flow intrudes through middle or bottom layer while the upstream inflow enter through bottom layer, with the final algal bloom coverage rate (R alg) of 82.3% and 78.1%, respectively. In terms of superimposed effect of different flow patterns, when the sequentially thermal stratified flows have different effect on algae transport direction, algae will concentrate in the reach rather than discharged which increase the risk of multiple algal blooms. These findings represent an important step towards understanding the multiple outbreaks of algal bloom in XXR during the spring and provide a new perspective for the research of algal bloom governance. [ABSTRACT FROM AUTHOR]

The central eastern Florida shelf edge is a highly dynamic area that supports an important yet vulnerable deep-sea coral reefs ecosystem, the Oculina Coral Habitat Area of Particular Concern. Rapid and large short-terms (days to weeks) changes of bottom temperature (up to 9 °C) and p CO 2 (up to 180 μatm) were observed at the shelfbreak during a two-month (May 13-July 10, 2017) deployment of a lander package. An analysis suggests that these changes are the combined results of tides, the Gulf Stream meandering, and submesoscale eddies and filaments. The processes responsible for sub-tidal variability may include 1) the Gulf Stream frontal movements, 2) upwelling/downwelling of slope waters in association with the Gulf Stream variability, and 3) submesoscale processes and associated vertical movements. Satellite images also frequently show a narrow plume of elevated chlorophyll concentration that stretches from the coast northward up to >200 km along the Gulf Stream front during late spring and early summer. Our analysis indicates that these phytoplankton blooms in the plume are likely supported by the nutrient supply from the nutrients-rich slope waters to the shelf edge and subsequent local vertical mixing. Carbon export associated with these blooms can be an important food source to the Oculina corals. Upwelling of slope waters, on the other hand, will lead to increased CO 2 and reduced pH and aragonite saturation state along the shelf edge. Therefore, these dynamic processes may have strong impacts on the health and sustainability of the Oculina coral ecosystem. • Rapid short-terms changes of bottom temperature (up to 9 °C) and p CO 2 (up to 180 μatm). • A high chlorophyll plume stretches from the coast northward along the Gulf Stream front. • Short-terms variability are associated with GS meandering and submesoscale features. • The biogeochemical processes may have strong impacts on the deep coral ecosystem. [ABSTRACT FROM AUTHOR]

The density of ice krill (Euphausia crystallorophias), a species of key ecological value, and related environmental factors were observed along two transects in the Amundsen Sea Coastal Polynya (ASCP) in Antarctica. The distribution of ice krill was processed using two-frequency acoustic backscatter data identification, and the target strength of ice krill was calculated via stochastic distorted-wave born approximation based on the ice krill sample. The ice krill density ranged from 0.96 to 11.01 g m−2 for each transect (mean value was 5.77 g m−2 for the entire survey). These results were of a lower order of magnitude than those of a previous study in the same waters, although the ice krill was still the dominant krill specie in this polynya. We contend that the extent of the phytoplankton bloom might be the factor behind this difference, while other hydrographic parameters such as surface temperature and salinity would have some effect on the spatial distribution of ice krill abundance. Meanwhile, the density and height of ice krill abundance suggested that the diurnal effect on the ice krill was almost negligible. According to the fitted results of regression model, the abundance of ice krill in ASCP in 2022 summer was estimated approximately 175,000 tons. • Ice krill density and related factors were observed in the Amundsen Polynya, Antarctica. • The ice krill density ranged from 0.96 to 11.01 g m−2 in two sampled transects. • Ice krill was still the dominant krill species considering previous findings. • The ice krill density, however, distinctly declined compared to the density in 2012. • The phenomenon of ice melting and eutrophication possibly influenced the density. [ABSTRACT FROM AUTHOR]

The spatial and temporal variability of the partial pressure of carbon dioxide (pCO 2) over the northern tropical Indian Ocean was estimated based on satellite-derived sea surface temperature (SST), sea surface salinity (SSS), and chlorophyll concentration (Chl-a). The distribution of sea surface pCO 2 is controlled by various physical processes, such as mixing, entrainment, upwelling, and advection, and by associated biological processes, such as phytoplankton blooms. The results showed lower surface water pCO 2 over the Bay of Bengal (BoB) (< 300 μatm) as compared to the Arabian Sea (AS), which could be attributed to low salinity during the northeast monsoon season (December–January) in the BoB. High pCO 2 values (> 500 μatm) were found near the Somali coast during the southwest monsoon season (June–August) caused by intense coastal upwelling. The pCO 2 over BoB (400–450 μatm) was more than that of the AS in the fall inter-monsoon season (September–November) as a response to the relatively warmer SST over the BoB. The highest spatiotemporal variability of surface pCO 2 was observed in the western AS near to the coast and over the northern BoB as a response to the higher variability in biological productivity and salinity, respectively, over these regions. The effect of tropical cyclones on pCO 2 variability over the BoB was also assessed in this study. The sea surface pCO 2 values were found to be much smaller along the cyclone track after the passage of cyclones because of the strong SST drop and the sudden phytoplankton blooms caused by the entrainment and vertical mixing of subsurface cold and nutrient-rich water with surface water. The cyclone-induced surface cooling and the associated decrease in surface water pCO 2 were found to be higher after the passage of the Madi cyclone compared to the Hudhud cyclone. • The spatiotemporal variability of surface pCO 2 in the BoB is dominated by the influx of riverine freshwater. • SST and chlorophyll are the decisive factors governing the variability of pCO 2 in the AS. • Tropical cyclone induced surface cooling and biogeochemical processes, affecting the pCO 2 distribution in the BoB. [ABSTRACT FROM AUTHOR]