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This paper concerns a discrete-time phytoplankton–zooplankton model in which the effects of toxin produced by phytoplankton and refuges provided for phytoplankton on the interactions between phytoplankton and zooplankton are considered. We first discuss the existence and stability of fixed points. When two parameters change, it is shown that there exist some codimension-two bifurcations, including fold-flip bifurcation and strong resonance bifurcations. Moreover, we give the corresponding bifurcation diagrams, phase diagrams and maximum Lyapunov exponent diagrams. The results show that phytoplankton toxin and refuges play important roles in the occurrence and termination of algal blooms in freshwater lakes. [ABSTRACT FROM AUTHOR]

Management of water resources in the Murray-Darling Basin has historically focussed on water security and the allocation of water for users with competing needs. This focus was reflected in the seminal paper on multiple risks to shared water across the basin by the Commonwealth Scientific and Industrial Research Organisation 15 years ago. That paper captured key concerns that were at the forefront for decision-makers, managers and policy-makers who were, at that time, experiencing the early impacts of the Millennium Drought. Water quality, then, was secondary to the issues of water security. Across the following years, new water quality risks have emerged along with a more nuanced understanding of the complex interplay between climate, floodplain/catchment vegetation, hydrology, and water quality. Critically, this improved understanding applies to the systemic shocks of extreme events, such as the 2020 bushfires and hypoxic blackwater events, as well as the variability, duration and volumes of natural and regulated river flows. In this paper, we explore the key water quality issues that currently face the Basin, and reframe water quality as an integral rather than incidental component of the risks to shared water in the Basin, with the associated implications for policy development that this implies. [ABSTRACT FROM AUTHOR]

Populations are generally censused daily, weekly, monthly or annually. In this paper, we introduce a discrete-time nutrients-phytoplankton-oysters (NPO) model that describes the interactions of nutrients, phytoplankton and oysters in a bay ecosystem. We compute the threshold parameter $ \mathcal {R}_N $ R N for persistence of phytoplankton with or without oysters. When $ \mathcal {R}_{N} \lt 1 $ R N < 1 , then both phytoplankton and oysters populations go extinct. However, when $ \mathcal {R}_N \gt 1 $ R N > 1 , we show that the model may exhibit two scenarios: (1) a locally asymptotically stable equilibrium with positive values of nutrients and phytoplankton with oysters missing, and (2) a locally asymptotically stable interior equilibrium with positive values of nutrients, phytoplankton and oysters. We use sensitivity analysis to study the impact of human and environmental factors on the model. We use examples to illustrate that some human activities and environmental factors can force the interior equilibrium to undergo a Neimark–Sacker bifurcation which generates phytoplankton blooms with oscillations in oysters population and nutrients level. [ABSTRACT FROM AUTHOR]

The application of machine learning (ML) techniques for understanding and predicting organic matter (OM) and harmful algal blooms (HABs) in freshwater systems has increased significantly with the availability of abundant data and advanced monitoring technologies. However, there is a lack of comprehensive reviews concentrating on practical applications and delving into the potential risks associated with misrepresentation or inflation in constructing ML models. This review aims to bridge these gaps by providing a comprehensive overview of various aspects of ML applications in the context of OM and HABs in freshwater systems. It covers practical ML applications for rapid assessment, early warning, and driver analysis, highlighting the diverse range of techniques employed in these areas. Furthermore, it discusses the challenges and considerations associated with data handling, including using in situ and remote sensing data and the importance of appropriate data-splitting techniques to avoid data leakage. To ensure unbiased and reproducible results, this review offers recommendations for model improvement, such as utilizing explainable ML techniques to gain insights into model behavior and avoiding overreliance on a single ML algorithm. It also emphasizes the significance of deploying ML models through user-friendly interfaces, enabling non-experts in ML to effectively utilize these models in real-world water environments. [ABSTRACT FROM AUTHOR]

Here a nonlinear mathematical model for an aquatic ecosystem containing both non-toxic and toxin-producing algal blooms is formulated and analyzed. The presence of harmful algae impacts the aquatic population, subsequently affecting the human population that relies on zooplankton (fish, crabs, etc.). It also deteriorates the water quality, and it is advisable not to use water from lakes containing harmful algae. Here, our focus is to understand the dynamics of aquatic ecosystems when we have both types of algae, one that is non-toxic and acts as food to zooplankton, and another that is toxin-producing algae that causes death to zooplankton. The predation of zooplankton on algae influences the growth of the algae population. First, we consider a deterministic model, and later, this model is extended to stochastic model to check whether it has any impact on the dynamics of the populations under consideration. Various equilibria of the proposed model are derived, and the local stability of these equilibria is thoroughly examined. The existence of Hopf-bifurcation is also demonstrated for a suitable set of parameters. The results of deterministic and stochastic models are compared using numerical simulation. Upon examining our results and simulation data, it is evident that modifying specific key parameters, such as the growth rate of non-toxic algae due to nutrient intake and the parameter associated with the predation of non-toxic algae by zooplankton, has a substantial impact on algal bloom dynamics. Minor adjustments to these parameters can result in an augmented presence of non-toxic algae and a simultaneous decrease in toxin-producing algae, aligning with the primary objectives set by policymakers. [ABSTRACT FROM AUTHOR]

The use of algicidal bacteria has gained prominence as natural solution to control the worrying increase of harmful algal blooms worldwide. However, although cyanobacterial blooms (cyanoHABs) often dominate freshwater bodies, recent reviews on the subject have addressed cyanobacteria in the second place and focused more on bacteria-algae interactions. This article provides a critical review of the fundamental aspects of searching for, isolating and assaying candidate algicidal bacteria targeting cyanobacteria. Possible species-specific interactions and the different modes of action of bacteria against different species of cyanobacteria are also discussed. It has been observed that there is a clear bias in the literature toward the genus Microcystis, being by far the most studied and reviewed to date. This contrasts with the numerous studies showing cyanobacterial blooms dominated by other harmful species, such as the genera Planktothrix, Aphanizomenon or Raphidiopsis. To add new knowledge to the lack of current studies on these genera, a separate experimental section has been included in this review with research results on the sensitivity of nine harmful freshwater cyanobacteria and two green algae to different bacteria and algicidal compounds. Finally, certain ecological and biosafety risks that must be taken into account when applying algicidal bacteria as a bioaugmentation strategy are also highlighted. Overall, this review is presented as an attempt to outline the knowledge gathered over the last thirty years of research, while raising new questions and debates on key issues that remain poorly understood. [ABSTRACT FROM AUTHOR]

The Earth's oceans are home to a diverse array of life, from large marine mammals to microscopic organisms. Among the most important are the marine phytoplankton, which comprise the basis of marine food webs, and also produce a large percentage of the Earth's oxygen through photosynthesis. Although the vast majority of phytoplankton are essential to ocean health, several dozen species produce potent toxins, and can form what are called Harmful Algal Blooms (HABs). This science activity focuses on the importance of HABs, as well as the types of data scientists collect to understand blooms. In the classroom exercises, students will calculate the proportional abundance (% contribution) of five HAB species present in water samples, and use these data to create pie graphs to depict species composition. Students will then compare these results with levels of HAB toxins in water samples collected over the same time period. Thought questions challenge students to develop hypotheses regarding how changes in the HAB community may relate to observed trends in toxin concentrations. This activity was successfully taught to visually impaired students who were able to complete the pie charts and answer the thought questions. [ABSTRACT FROM AUTHOR]

As filter feeders, mollusks' growth is completely reliant on the natural environment. This leaves clam aquaculture, and more generally molluskan aquaculture, highly susceptible to environmental risks such as harmful algal blooms (HABs) and low salinity events. As marine environments change, whether due to climatic or nutrient related variations, there may be new risk combinations that farmers have yet to encounter. To analyze the financial effects of environmental risks on clam farmers in the Gulf of Mexico, we conducted a Monte–Carlo experiment, varying risk combinations and correlations among scenarios. Simultaneous stressors showed a significant impact on individual firms, decreasing average profit by 71% and internal rate of return (IRR) by 83% when compared to best case baseline scenarios without environmental risk, indicating a potential need for risk mitigation strategies. While our analysis focuses on Florida Gulf of Mexico clam farmers, the model presented is applicable to molluskan aquaculture globally. [ABSTRACT FROM AUTHOR]

With harmful algal blooms, marine food poisoning caused by marine biotoxins frequently occurs and is life-threatening if severe. However, the conventional detection methods of marine toxins have a few limitations: low sensitivity and high-cost. Therefore, it is necessary to establish a fast and sensitive on-site detection method for real seafood sample. Biosensors based on aptamers, antibodies, and cells have been applied in marine toxins monitoring. This review presents the classification and toxic effects of marine toxins, and recent biosensor for marine toxin detection. In addition, we have compared the superiority and limitation of these biosensors. Finally, challenges and opportunities of biosensors in food safety detection were discussed. Considering the excellent results achieved by the aptasensor in the field of detection, it seems ready to be put into practical applications. [ABSTRACT FROM AUTHOR]

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Ulva prolifera blooms have occurred every summer in the South Yellow Sea since 2008. U. prolifera blooms appeared in the area near the Jiangsu shoal and then were driven to the Shandong Peninsula by the prevailing summer winds. The blooms covered a maximum area of more than 50000 km2 and had an aggregate estimated biomass of 3.64 × 105 tons. Large number of U. prolifera dissipation in the natural degradation and this cause a serious impact on the marine environment. We used MODIS, HJ-1A/B and GF-1 remote sensing image data to conduct large-scale monitoring of U. prolifera. Combined with sea surface monitoring station data from Haiyang city, Shandong province, we analyzed the impact of U. prolifera death on the coastal sea environment of Haiyang city from 2012 to 2016 using multiple regression analysis. It showed that chlorophyll-a concentration was related to sea surface temperature (SST), salinity, dissolved inorganic nitrogen (DIN) and phosphate (R2 = 0.50, P < 0.001). Among these, DIN and phosphate were important factors affecting chlorophyll-a concentration. There was a significant positive correlation between chlorophyll-a concentration and DIN, but a significant negative correlation between chlorophyll-a concentration and phosphate. The nutrients released by the decomposition of U. prolifera enhanced the growth of planktonic microalgae, and increased the mean chlorophyll-a concentration from 1.398 μmol/L to 2.819 μmol/L during May to August in the study area. This increased the Level of eutrophication in the coastal area and contributed to blooms of secondary algae such as red tides. [ABSTRACT FROM AUTHOR]

Water color is a crucial optical indicator of water quality, polluted water bodies often show water color anomalies. To comprehensively understand the occurrence of water color anomalies in inland lakes, an integrated method was designed using the hue angle based on the Forel-Ule Index (FUI) model, and other remote sensing indices, including the Turbid Water Index (TWI), Floating Algae Index (FAI), and Cyanobacteria and Macrophytes Index (CMI). Based on all available Landsat-8 OLI images from 2013 to 2020, continuous monitoring was conducted in three different lakes in the middle of the Yangtze River, China. The results demonstrated that: (1) The proposed method can accurately identify algal blooms, high sediment loads, and eutrophication from the abnormal water color areas; (2) The calculated hue angles of sediment-dominated water were significantly higher than those of algal blooms and aquatic vegetation, providing a noticeable visual discoloration of water; (3) These water color anomalies exhibited significant correlations with the water quality and environmental conditions. This study serves as an example for accurate and spatially continuous assessment of water color anomaly and supports practical information to facilitate local water environment conservation. [ABSTRACT FROM AUTHOR]

Noctiluca scintillans (Macartney) Kofoid and Swezy, 1921 contributes ∼ 85% of the total biomass of heterotrophic plankton in Crimean coastal waters. Data for the retrospective analysis come from a 20-year sampling (in 2000s) across the Crimean shelf and in adjacent open sea waters. Samples were collected onboard research vessels, in the upper 150 m layer, by Juday nets (vertical hauls) fitted with 145 µm mesh. These data were compared to field surveys of the 1960s. Seasonal blooms of Noctiluca were pronounced during summer time, with the peak of abundance in June. The mesoscale spatial distribution of Noctiluca abundance was most heterogeneous in June as well. The annual concentration of cells in coastal waters exceeded that of the open sea by four times. The coefficient of Noctiluca seasonal abundance variation in coastal waters was 1.5 times higher than that of the open sea. The Principal Component Analysis implied that the seasonal variation of the Noctiluca abundance offshore was modulated by coupling of the atmospheric precipitation, sea surface temperature, photosynthetically active radiation, euphotic depth, chlorophyll-a concentration, Noctiluca abundance in coastal waters, mesoscale eddies and wind stress. A general decline of Noctiluca abundance and biomass was observed in coastal waters, from the 1960s to the present. [ABSTRACT FROM AUTHOR]

The eutrophication of lake ecosystems due to anthropogenic activities has impacted lakes worldwide and shallow lakes are particularly vulnerable. The retention of phosphorus (P) in lake sediments and its subsequent release to the water column is often a key factor in degraded water quality, algal blooms and delayed responses to lake restoration efforts. Despite this link between sedimentary P and poor ecosystem outcomes, a limited amount of research has been conducted on P dynamics in New Zealand's lakes. In this study, sediments in six shallow lakes across the country were analysed for geochemistry and P fractionation. Total sedimentary P content varied widely and was related to inflow concentrations and hydrological retention times. The P binding capacity of the sediments was related to iron (Fe) and aluminium (Al) concentrations, while the Fe:P ratio was correlated to the release of P under anoxic conditions. P fractions and release rates were poorly correlated with traditional water quality parameters, however the mobile-PSL and reducible-P fractions were strongly correlated with the frequency of summertime algal blooms. This relationship may provide an indicator to assess harmful algal bloom frequency in unmonitored lakes, and a valuable tool to assess internal loading risk and inform lake restoration methods. [ABSTRACT FROM AUTHOR]

Short-term changes in red tide characteristics are very helpful in monitoring the larger change progress and associations with environmental factors. We conducted an experiment to collect data on short-term changes in noctilucent algae blooms in the Bohai Sea, on 14 June 2015. The performance of three classic indices (OC2, OC3G and YOC) for noctilucent algae surveying was compared based on the measured remote sensing reflectance (Rrs(λ)) and Chl_a (chlorophyll a). OC2 was finally selected here. We established two thresholds: α (Rrs(745)/ Rrs (865)) and ε (Lc(745)/ Lc(865)), based on the measured reflectance and the Geostationary Ocean Colour Imager (GOCI) images corrected by Rayleigh scattering, respectively. These two thresholds were subsequently used in Management Unit Mathematics Models (MUMM), which were embedded in the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Data Analysis System (SeaDAS), for atmospheric correction of the selected GOCI images. Based on the correlation between phytoplankton cell density and Chl_a, we defined the threshold (6.5 μg L−1) of Chl_a concentration as a proxy of noctilucent algae blooms. Finally, we determined the temporal and spatial variations of the noctilucent algae bloom waters in the Bohai Sea, on 14 June 2015. The changing pattern demonstrated a general acknowledgement of phototropic vertical migration of the algae over the course of the day. Our results also demonstrated the utility of GOCI images, with MUMM atmospheric correction for short-time monitoring of noctilucent algae blooms. [ABSTRACT FROM AUTHOR]

Iron plays an important role in physiological processes of microalgae and also affects the absorption of other nutrients by algae cells. Therefore, iron is one of the important controlling factors for algae bloom formation. This study investigated the effect of four kinds of complex iron (EDTA-Fe, ferric humate, ferric oxalate and ferric ammonium citrate) on the phosphorus absorption by two freshwater algae (Scenedesmus quadricauda and Anabaena flos-aquae). The results showed that the species and concentration of complex iron had a significant effect on the phosphorus uptake rate of S. quadricauda, but had only a slight effect on that of A. flos-aquae. The former exhibits positive influences on phosphorus absorption and was in the following order: ferric oxalate and EDTA-Fe > ferric humate and ammonium ferric citrate, and these effects depended on whether the presence of complex iron constitutes an environmental pressure for the growth of algal cells. [ABSTRACT FROM AUTHOR]