Selective Removal of Chlorophyll and Isolation of Lutein from Plant Extracts Using Magnetic Solid Phase Extraction with Iron Oxide Nanoparticles.

In recent years, there has been a growing interest in plant pigments as readily available nutraceuticals. Photosynthetic pigments, specifically chlorophylls and carotenoids, renowned for their non-toxic antioxidant properties, are increasingly finding applications beyond their health-promoting attributes. Consequently, there is an ongoing need for cost-effective methods of isolation. This study employs a co-precipitation method to synthesize magnetic iron oxide nanoparticles. Scanning electron microscopy (SEM) coupled with energy dispersive spectrometry (EDS) confirms that an aqueous environment and oxidizing conditions yield nanosized iron oxide with particle sizes ranging from 80 to 140 nm. X-ray photoelectron spectroscopy (XPS) spectra indicate the presence of hydrous iron oxide FeO(OH) on the surface of the nanosized iron oxide. The Brunauer-Emmett-Teller (BET) surface area of obtained nanomaterial was 151.4 m2 g-1, with total pore volumes of pores 0.25 cm3 g-1 STP. The material, designated as iron oxide nanoparticles (IONPs), serves as an adsorbent for magnetic solid phase extraction (MSPE) and isolation of photosynthetic pigments (chlorophyll a, lutein) from extracts of higher green plants (Mentha piperita L., Urtica dioica L.). Sorption of chlorophyll a onto the nanoparticles is confirmed using UV-vis spectroscopy, Fourier transform infrared photoacoustic spectroscopy (FT-IR/PAS), and high-performance liquid chromatography (HPLC). Selective sorption of chlorophyll a requires a minimum of 3 g of IONPs per 12 mg of chlorophyll a, with acetone as the solvent, and is dependent on a storage time of 48 h. Extended contact time of IONPs with the acetone extract, i.e., 72 h, ensures the elimination of remaining components except lutein, with a spectral purity of 98%, recovered with over 90% efficiency. The mechanism of chlorophyll removal using IONPs relies on the interaction of the pigment's carbonyl (C=O) groups with the adsorbent surface hydroxyl (-OH) groups. Based on molecular dynamics (MD) simulations, it has been proven that the selective adsorption of pigments is also influenced by more favorable dispersion interactions between acetone and chlorophyll in comparison with other solutes. An aqueous environment significantly promotes the removal of pigments; however, it results in a complete loss of selectivity.

Mechanisms of cadmium mitigation in tomato plants under orthophosphate and polyphosphate fertilization regimes.

Cadmium (Cd) is one of the most toxic elements in soil, affecting morphological, physiological, and biochemical processes in plants. Mineral plant nutrition was tested as an effective approach to mitigate Cd stress in several crop species. In this regard, the present study aimed to elucidate how different phosphorus (P) fertilization regimes can improve some bio-physiological processes in tomato plants exposed to Cd stress. In a hydroponic experiment, the impact of two phosphorus fertilizer forms (Polyphosphate (poly-P): condensed P-form with 100% polymerization rate and orthophosphate (ortho-P): from orthophosphoric acid) on the photosynthetic activity, plant growth, and nutrient uptake was assessed under three levels of Cd stress (0, 12, and 25 µM of CdCl2). The obtained results confirmed the negative effects of Cd stress on the chlorophyll content and the efficiency of the photosynthesis machinery. The application of poly-P fertilizer significantly improved the chlorophyll stability index (82%) under medium Cd stress (Cd12), as compared to the ortho-P form (55%). The analysis of the chlorophyll α fluorescence transient curve revealed that the amplitude of Cd effect on the different steps of electron transfer between PSII and PSI was significantly reduced under the poly-P fertilization regime compared to ortho-P, especially under Cd12. The evaluation of the RE0/RC parameter showed that the electron flux reducing end electron acceptors at the PSI acceptor side per reaction center was significantly improved in the poly-P treatment by 42% under Cd12 compared to the ortho-P treatment. Moreover, the use of poly-P fertilizer enhanced iron uptake and its stoichiometric homeostasis in the shoot tissue which maintained an adequate absorption of iron under Cd stress conditions. Findings from this study revealed for the first time that inorganic polyphosphate fertilizers can reduce Cd toxicity in tomato plants by enhancing photosynthesis activity, nutrient uptake, plant growth, and biomass accumulation despite the high level of cadmium accumulation in shoot tissues.

Algae development in rivers with artificially constructed weirs: Dominant influence of discharge over temperature.

Algal blooms contribute to water quality degradation, unpleasant odors, taste issues, and the presence of harmful substances in artificially constructed weirs. Mitigating these adverse effects through effective algal bloom management requires identifying the contributing factors and predicting algal concentrations. This study focused on the upstream region of the Seungchon Weir in Korea, which is characterized by elevated levels of total nitrogen and phosphorus due to a significant influx of water from a sewage treatment plant. We employed four distinct machine learning models to predict chlorophyll-a (Chl-a) concentrations and identified the influential variables linked to local algal bloom events. The gradient boosting model enabled an in-depth exploration of the intricate relationships between algal occurrence and water quality parameters, enabling accurate identification of the causal factors. The models identified the discharge flow rate (D-Flow) and water temperature as the primary determinants of Chl-a levels, with feature importance values of 0.236 and 0.212, respectively. Enhanced model precision was achieved by utilizing daily average D-Flow values, with model accuracy and significance of the D-Flow amplifying as the temporal span of daily averaging increased. Elevated Chl-a concentrations correlated with diminished D-Flow and temperature, highlighting the pivotal role of D-Flow in regulating Chl-a concentration. This trend can be attributed to the constrained discharge of the Seungchon Weir during winter. Calculating the requisite D-Flow to maintain a desirable Chl-a concentration of up to 20 mg/m3 across varying temperatures revealed an escalating demand for D-Flow with rising temperatures. Specific D-Flow ranges, corresponding to each season and temperature condition, were identified as particularly influential on Chl-a concentration. Thus, optimizing Chl-a reduction can be achieved by strategically increasing D-Flow within these specified ranges for each season and temperature variation. This study highlights the importance of maintaining sufficient D-Flow levels to mitigate algal proliferation within river systems featuring weirs.

Effect of salinity stress and surfactant treatment with zinc and boron on morpho-physiological and biochemical indices of fenugreek (Trigonella foenum-graecum).

Micronutrient application has a crucial role in mitigating salinity stress in crop plants. This study was carried out to investigate the effect of zinc (Zn) and boron (B) as foliar applications on fenugreek growth and physiology under salt stress (0 and 120 mM). After 35 days of salt treatments, three levels of zinc (0, 50, and 100 ppm) and two levels of boron (0 and 2 ppm) were applied as a foliar application. Salinity significantly reduced root length (72.7%) and shoot length (33.9%), plant height (36%), leaf area (37%), root fresh weight (48%) and shoot fresh weight (75%), root dry weight (80%) and shoot dry weight (67%), photosynthetic pigments (78%), number of branches (50%), and seeds per pod (56%). Fenugreek's growth and physiology were improved by foliar spray of zinc and boron, which increased the length of the shoot (6%) and root length (2%), fresh root weight (18%), and dry root weight (8%), and chlorophyll a (1%), chlorophyll b (25%), total soluble protein content (3%), shoot calcium (9%) and potassium (5%) contents by significantly decreasing sodium ion (11%) content. Moreover, 100 ppm of Zn and 2 ppm of B enhanced the growth and physiology of fenugreek by reducing the effect of salt stress. Overall, boron and zinc foliar spray is suggested for improvement in fenugreek growth under salinity stress.

Knowledge-guided mixture density network for chlorophyll-a retrieval and associated pixel-by-pixel uncertainty assessment in optically variable inland waters.

Machine learning has been increasingly used to retrieve chlorophyll-a (Chl-a) in optically variable waters. However, without the guidance of physical principles or expert knowledge, machine learning may produce biased mapping relationships, or waste considerable time searching for physically infeasible hyperparameter domains. In addition, most Chl-a retrieval models cannot evaluate retrieval uncertainty when ground observations are not available, and the retrieval uncertainty is crucial for understanding the model limitations and evaluating the reliability of retrieval results. In this study, we developed a novel knowledge-guided mixture density network to retrieve Chl-a in optically variable inland waters based on Sentinel-3 Ocean and Land Color Instrument (OLCI) imagery. The proposed method embedded prior knowledge derived from spectral shape classification into the mixture density network. Compared to another deterministic model, the knowledge-guided mixture density network outputted the conditional distribution of Chl-a given an input spectrum, enabling us to estimate the optimal retrieval and the associated uncertainty. The proposed method showed favorable correspondence with the field Chl-a, with root mean square error (RMSE) of 6.56 µg/L, and mean absolute percentage error (MAPE) of 43.64 %. Calibrated against Sentinel-3 OLCI spectrum, the proposed method also performed well when applied to field spectrum (RMSE = 4.58 µg/L, MAPE = 72.70 %), suggesting its effectiveness and good generalization. The proposed method provided the standard deviation of each estimated Chl-a, which enabled us to inspect the reliability of the estimated results and understand the model limitations. Overall, the proposed method improved the Chl-a retrieval in terms of model accuracy and uncertainty evaluation, providing a more comprehensive Chl-a observation of inland waters.

Past environmental changes: using sedimentary photosynthetic pigments to enhance subtropical reservoir management.

The historical impacts of eutrophication processes were investigated in six subtropical reservoirs (São Paulo, Brazil) using a paleolimnological approach. We questioned whether the levels of pigment indicators of algal biomass could provide information about trophic increase and whether carotenoid pigments could offer additional insights. The following proxies were employed: organic matter, total phosphorus, total nitrogen, photosynthetic pigments (by high-performance liquid chromatography), sedimentation rates, and geochronology (by 210 Pb technique). Principal component analysis indicated a gradient of eutrophication. In eutrophic reservoirs (e.g., Rio Grande and Salto Grande), levels of lutein and zeaxanthin increased over time, suggesting growth of Chlorophyta and Cyanobacteria. These pigments were significantly associated with algal biomass, reflecting their participation in phytoplankton composition. In mesotrophic reservoirs, Broa and Itupararanga, increases and significative linear correlations (r > 0.70) between pigments and nutrients are mainly linked to agricultural and urban activities. In the oligotrophic reservoir Igaratá, lower pigment and nutrient levels reflected lesser human impact and good water quality. This study underscores eutrophication's complexity across subtropical reservoirs. Photosynthetic pigments associated with specific algal groups were informative, especially when correlated with nutrient data. The trophic increase, notably in the 1990s, may have been influenced by neoliberal policies. Integrated pigment and geochemical analysis offers a more precise understanding of eutrophication changes and their ties to human factors. Such research can aid environmental monitoring and sustainable policy development.

What drives the changing characteristics of phytoplankton in urban lakes: Climate, hydrology, or human disturbance?

Phytoplankton in shallow urban lakes are influenced by various environmental factors. However, the long-term coupling effects and impact pathways of these environmental variables on phytoplankton remain unclear. This is an emerging issue due to high urbanization and the resultant complex climate, lake hydrology and morphology, human interference, and water quality parameter changes. This study used Tangxun Lake, the largest urban lake in the Yangtze River Economic Belt, as an example to assess for the first time the individual contributions and coupled effects of four environmental variables and fourteen indicators on chlorophyll-a (Chla) concentrations under two scenarios from 2000 to 2019. Additionally, the influence pathways between the environmental variables and Chla concentration were quantified. The results indicated that the Chla concentration was most affected by lake hydrology and morphology, as were the total nitrogen, total phosphorus, and transparency. Especially after urbanization (2015-2019), the coupling effect of human interference, lake hydrology and morphology, and water quality parameters was strongest (18%). This is mainly due to fluctuations in the lake water level and an increase in the shape index of lake morphology, large amounts of nutrients were input, which reduced lake transparency and indirectly changed the Chla content. In addition, due to the rapid development of Wuhan city, the expansion of construction land has led to an increase in impervious surface area and a decrease in lake area. During periods of intense summer rainfall, a substantial amount of pollutants entered the lakes through surface runoff, resulting in decreased lake transparency, and elevated concentrations of nitrogen and phosphorus, indirectly increasing the Chla content. This study provides a scientific basis for aquatic ecological assessment and pollution control in urban shallow lakes.

Modification of trophic level index with the contribution of macrophyte and its usage to classify trophic state of shallow lakes.

Trophic state index (TSI) only considers the influence of phytoplankton excluding that of macrophytes. It is necessary to combine the contribution of macrophytes into trophic classification systems in waters with extensive growths of macrophytes. A novel trophic level index (TLIECa) combined both trophic level index (TLI) and the TSI based on equivalent chlorophyll a (TSIECa) with the Chl a of submerged macrophytes as an addition in Chl a was developed to assess the spatial trophic state of 15 lakes and annual trophic state of four lakes in China. TLIECa obtained different but significantly correlated results as those of the traditional TLI, concerning the influences of both phytoplankton and macrophytes. The result of TLIECa indicated that the trophic state of the 15 lakes varied from mild-eutrophic to moderate-eutrophic. Small particles were the dominant factor for the trophic state of most sampling sites in the 15 lakes. Total phosphorus was the dominant factor for the trophic state for most time of the year in Lake Jinniu. Both small particles and total phosphorus were the dominant factors for the annual trophic state of Lake Taihu, Lake Xuanwu, and Lake Baijia.

Anoxia begets anoxia: A positive feedback to the deoxygenation of temperate lakes.

Declining oxygen concentrations in the deep waters of lakes worldwide pose a pressing environmental and societal challenge. Existing theory suggests that low deep-water dissolved oxygen (DO) concentrations could trigger a positive feedback through which anoxia (i.e., very low DO) during a given summer begets increasingly severe occurrences of anoxia in following summers. Specifically, anoxic conditions can promote nutrient release from sediments, thereby stimulating phytoplankton growth, and subsequent phytoplankton decomposition can fuel heterotrophic respiration, resulting in increased spatial extent and duration of anoxia. However, while the individual relationships in this feedback are well established, to our knowledge, there has not been a systematic analysis within or across lakes that simultaneously demonstrates all of the mechanisms necessary to produce a positive feedback that reinforces anoxia. Here, we compiled data from 656 widespread temperate lakes and reservoirs to analyze the proposed anoxia begets anoxia feedback. Lakes in the dataset span a broad range of surface area (1-126,909 ha), maximum depth (6-370 m), and morphometry, with a median time-series duration of 30 years at each lake. Using linear mixed models, we found support for each of the positive feedback relationships between anoxia, phosphorus concentrations, chlorophyll a concentrations, and oxygen demand across the 656-lake dataset. Likewise, we found further support for these relationships by analyzing time-series data from individual lakes. Our results indicate that the strength of these feedback relationships may vary with lake-specific characteristics: For example, we found that surface phosphorus concentrations were more positively associated with chlorophyll a in high-phosphorus lakes, and oxygen demand had a stronger influence on the extent of anoxia in deep lakes. Taken together, these results support the existence of a positive feedback that could magnify the effects of climate change and other anthropogenic pressures driving the development of anoxia in lakes around the world.

The influence mechanism of water level operation on algal blooms in canyon reservoirs and bloom prevention.

The water level operation of reservoirs affects the spatiotemporal patterns of water quality, light-heat, hydrodynamics and phytoplankton, which have implications for algal bloom prevention. However, the theoretical analysis and practical applications of related research are limited. Based on prototype observations and numerical modeling, data on algae, water level operation and environmental factors in the Zipingpu Reservoir from April and September in 2015 to 2017 and 2020 to 2022 were collected. An in-depth analysis of the causal mechanisms between algal blooms and water level operation was performed, and prevention strategies with practical application assessments were developed. Water level operation control in the reservoir from April to September can be divided into five stages (falling-rising-oscillating-falling-rising), with algal blooms occurring only in the second stage. The rising water level with inflow into the middle layers shapes a closed-loop circulation in the surface waters. This distributes the nutrients that were trapped in the surface layer during the first stage, helping algae avoid to phosphorus limitation and thrive in the closed loop circulation, leading to algal blooms (chlorophyll-a exceeding 10 mg/m3). There is a significant positive correlation (p < 0.05) between algal blooms and the rapid rise in water levels in the second stage, occurring within a span of three days. To contain the algal bloom, a water level operation limit of rising waters on the third day after a two-day consecutive rise in water level was examined. This was found to be effective after its practical application to the case reservoir in 2022, with chlorophyll-a concentrations consistently below 10 mg/m3. This study unveils the mechanisms through which water level operation affects algal blooms and presents a successful case of bloom prevention. Furthermore, it serves as a valuable reference for the management of canyon reservoirs.

Spatio-temporal variation and environmental drivers of chlorophyll a concentration and diatom community in four small urban lakes of Kunming, China.

Chlorophyll a (Chla) and diatom community structure are two indicators of lake water quality. In this study, we investigated the environmental parameters, chlorophyll a, and diatom community of four small urban lakes in Kunming (Beitan, Beihu, Nanhu and Longtan lakes in the campus of Yunnan Normal University) between March 2017 and December 2019. The results showed that the concentrations of total nitrogen (TN), total phosphorus (TP), and Chla in the four lakes showed significant seasonal fluctuation. The Chla concentration in Nanhu Lake, which had the highest nutrient level among the four lakes, was significantly higher than that in the other three lakes and largely affected by TN. In comparison, water temperature significantly contributed to the increases in Chla concentration in the other three lakes. Water temperature and TN were significantly correlated with Chla across the four lakes. Diatom assemblages in Beitan, Nanhu, and Longtan lakes were dominated by planktonic diatoms, and benthic diatoms were dominant in the shallowest lake Beihu, suggesting that water depth significantly affected the proportion of planktonic diatoms and dominant taxa. Water depth, TN, TP, transparency, and water temperature affected the spatio-temporal changes of diatom community structure, with water temperature as the major factor in causing the seasonal variation in diatom community, and TN and TP as the major drivers for community variation among lakes within the same season.

Trophic status and lake depth play important roles in determining the nutrient-chlorophyll a relationship: Evidence from thousands of lakes globally.

A fundamental problem in lake eutrophication management is that the nutrient-chlorophyll a (Chl a) relationship shows high variability due to diverse influences of for example lake depth, lake trophic status, and latitude. To accommodate the variability induced by spatial heterogeneity, a reliable and general insight into the nutrient-Chl a relationship may be achieved by applying probabilistic methods to analyze data compiled across a broad spatial scale. Here, the roles of two critical factors determining the nutrient-Chl a relationship, lake depth and trophic status, were explored by applying Bayesian networks (BNs) and a Bayesian hierarchical linear regression model (BHM) to a compiled global dataset from 2849 lakes and 25083 observations. We categorized the lakes into three groups (shallow, transitional, and deep) according to mean and maximum depth relative to mixing depth. We found that despite a stronger effect of total phosphorus (TP) and total nitrogen (TN) on Chl a when combined, TP played a dominant role in determining Chl a, regardless of lake depth. However, when the lake was hypereutrophic and/or TP was >40 µg/L, TN had a greater impact on Chl a, especially in shallow lakes. The response curve of Chl a to TP and TN varied with lake depth, with deep lakes having the lowest yield Chl a per unit of nutrient, followed by transitional lakes, while shallow lakes had the highest ratio. Moreover, we found a decrease of TN/TP with increasing Chl a concentrations and lake depth (represented as mixing depth/mean depth). Our established BHM may help estimating lake type and/or lake-specific acceptable TN and TP concentrations that comply with target Chl a concentrations with higher certainty than can be obtained when bulking all lake types.

Prediction and sensitivity analysis of chlorophyll a based on a support vector machine regression algorithm.

Outbreaks of planktonic algae seriously affect the water quality of rivers and are difficult to control. Based on the analysis of the temporal and spatial variation characteristics of environmental factors, this study uses a support vector machine regression (SVR) algorithm to establish a chlorophyll a (Chl-a) prediction model and conduct Chl-a sensitivity analysis. In 2018, the average Chl-a content was 126.25 ug/L. The maximum total nitrogen (TN) content was 16.68 mg/L and high year-round. The average NH4+-N and total phosphorous (TP) contents were only 0.78 and 0.18 mg/L. The content of NH4+-N was higher in spring and increased significantly along the water flow, while TP decreased slightly along the water flow. We used a radial basis function kernel SVR model and tenfold cross-validation method to optimize parameters. The penalty parameter c was 1.4142, the kernel function parameter g was 1, and the training and verification errors were only 0.032 and 0.067, respectively, indicating a good model fit. Based on a sensitivity analysis of the SVR prediction model, the maximum sensitivity coefficients of Chl-a to TP and WT were 0.571 and 0.394, respectively, and the contributions were 33% and 22%, respectively. The next highest sensitivity coefficients were those of DO (0.28, 16%) and pH (0.243, 14%). The sensitivity coefficients of TN and NH4+-N were the lowest. According to the current water environment pollution conditions, TP is the limiting factor of Chl-a in the Qingshui River, and it is also the main prevention and control factor of phytoplankton outbreak.

Effects of benthic fish and light regimes on water quality and the growth of Vallisneria natans with two sediment types.

In shal low eutrophic lakes, submersed macrophytes are essential for maintaining a clear water state and they are significantly affected by benthic fish disturbance, light availability, and sediment types. We conducted a mesocosm experiment with benthic fish (Misgurnus anguillicaudatus), two light regimes, and submerged macrophyte (Vallisneria natans) growing in two sediment types to investigate the ecological effects of benthic fish and light regimes on water quality and the growth of submersed macrophyte. Our findings indicated that the benthic fish increased the concentrations of total nitrogen, total phosphorus, and total dissolved phosphorus in the overlying water. The effects of benthic fish on ammonia-nitrogen (NH4+-N) and chlorophyll a (Chl-a) contents were related to light regimes. Fish disturbance indirectly promoted the growth of macrophytes growing in sand by increasing NH4+-N content in overlying water. However, the increasing Chl-a content stimulated by fish disturbance and high light regime reduced the growth of submersed macrophytes growing in clay due to shading. Macrophytes with different sediments had different strategies coping with light. Plants growing in sand responded to low light mainly by adjusting the leaf and root biomass allocation, whereas plants growing in clay responded to low light by physiologically adjusting the soluble carbohydrate content. The findings of this study might help restore lake vegetation to some degree, and using nutrient-poor sediment might be an appropriate method to avoid the detrimental effects of fish-mediated disturbances on the growth of submerged macrophytes.

[Analysis of Influencing Factors of Chlorophyll-a in Lake Taihu Based on Bayesian Network].

Global warming has aggravated the problem of lake eutrophication. As a typical large, eutrophic, shallow lake in China, the issue of cyanobacterial harmful algal blooms (cyanoHABs) was particularly prominent in Lake Taihu. We took Lake Taihu as the study area, using the meteorological (temperature, wind speed, rainfall, and sunshine hours), water quality (total nitrogen, total phosphorus, conductivity, pH, and chemical oxygen demand), and biological (chlorophyll-a in phytoplankton) monitoring data from 1992 to 2020. We built a simulation model of chlorophyll-a based on the Bayesian network model with continuous variables to study the chlorophyll-a level of Lake Taihu under different meteorological and water quality conditions. The 75th percentile of chlorophyll-a concentration was used as the threshold to judge the risk of cyanobacterial bloom. When the probability of chlorophyll-a concentration below this threshold was greater than 75%, it was regarded as "low risk" of cyanobacterial bloom outbreak. The results showed that the average level of "temperature wind ratio" (ratio of air temperature to wind speed) in spring was 6.67℃·s·m-1, and the probability of high chlorophyll-a was less than 75% when the total phosphorus concentration was less than 0.130 mg·L-1. The average "temperature wind ratio" level in summer was 10.52℃·s·m-1, and the probability of high chlorophyll-a was less than 75% when the total phosphorus concentration was less than 0.257 mg·L-1. The average level of total phosphorus concentration in autumn was 0.154 mg·L-1, and the probability of high chlorophyll-a was less than 75% when the "temperature wind ratio" was less than 6.30℃·s·m-1. Based on the above research, the chlorophyll-a model constructed by the Bayesian network model with continuous variables was further used to simulate the nutrient control objectives under different climate change backgrounds. In order to control chlorophyll-a in Lake Taihu at the:"low risk" level of cyanoHABs, the target concentration thresholds of total phosphorus needed to be controlled under the climate level background from 1992 to 2000, 2001 to 2010, and 2011 to 2020 were given. From 1992 to 2000, the threshold value of total phosphorus concentration was 0.135 mg·L-1 in spring, 0.174 mg·L-1 in summer, and 0.171 mg·L-1 in autumn. From 2001 to 2010, the threshold value of total phosphorus concentration was 0.115 mg·L-1 in spring, 0.164 mg·L-1 in summer, and 0.162 mg·L-1 in autumn. From 2011 to 2020, the threshold value of total phosphorus concentration was 0.059 mg·L-1 in spring, 0.145 mg·L-1 in summer, and 0.145 mg·L-1 in autumn. The results showed that the control of cyanoHABs in eutrophic lakes required more stringent nutrient control strategies with global warming. It provided a reference for preventing and controlling cyanoHABs and eutrophication in Lake Taihu. Previous studies have used multiple regression models, hydrodynamic numerical models, and other methods to predict chlorophyll-a concentrations or cyanobacterial blooms in lakes. However, there has been no study on the prediction of cyanoHABs in lakes based on the Bayesian network model with continuous variables and the "dynamic" evaluation of nutrient thresholds. Therefore, based on the seasonal meteorological, water quality, and biological monitoring data of Lake Taihu from 1992 to 2020, the chlorophyll-a model of Lake Taihu was constructed for the first time based on the Bayesian network model with continuous variables to simulate the chlorophyll-a concentration of Lake Taihu under different climate indicators and total phosphorus concentrations. The weight of its influencing factors was also analyzed, and the nutrient control objectives under different climate scenarios were "dynamically" evaluated.

The air temperature change effect on water quality in the Kvarken Archipelago area.

The Kvarken Archipelago is Finland's World Heritage site designated by UNESCO. How climate change has affected the Kvaken Archipelago remains unclear. This study was conducted to investigate this issue by analyzing air temperature and water quality in this area. Here we use long-term historical data sets of 61 years from several monitoring stations. Water quality parameters included chlorophyll-a; total phosphorus; total nitrogen; coliform bacteria thermos tolerant; temperature; nitrate as nitrogen; nitrite-nitrate as nitrogen, and Secchi depth and correlations analysis was conducted to identify the most relevant parameters. Based on the correlation analysis of weather data and water quality parameters, air temperature showed a significant correlation with water temperature (Pearson's correlations = 0.89691, P < 0.0001). The air temperature increased in April (R2 (goodness-of-fit) = 0.2109 &P = 0.0009) and July (R2 = 0.1207 &P = 0.0155) which has indirectly increased the chlorophyll-a level (e.g. in June increasing slope = 0.39101, R2 = 0.4685, P < 0.0001) an indicator of phytoplankton growth and abundance in the water systems. The study concludes that there might be indirect effects of the likely increase in air temperature on water quality in the Kvarken Archipelago, in particular causing water temperature and chlorophyll-a concentration to increase at least in some months.

Sediments are important in regulating the algae-derived off-flavor (ß-cyclocitral) in eutrophic lakes.

In recent years, due to global warming and water eutrophication, cyanobacterial blooms have occurred frequently worldwide, resulting in a series of water quality problems, among which the odor problem in lakes is one of the focuses of attention. In the late stage of the bloom, a large amount of algae accumulated on the surface sediment, which will be a great hidden danger to cause odor pollution in lakes. ß-Cyclocitral is one of the typical algae-derived odor compounds that cause odor in lakes. In this study, an annual survey of 13 eutrophic lakes in the Taihu Lake basin was investigated to assess the effects of abiotic and biotic factors on ß-cyclocitral in water. Our results showed that high concentrations of ß-cyclocitral in the pore water (pore-ß-cyclocitral) were detected in the sediment and far exceeded that in the water column, with an average of about 100.37 times. Structural equation modeling indicated that algal biomass and pore-ß-cyclocitral can directly regulate the concentrations of ß-cyclocitral in the water column, and total phosphorus (TP) and temperature (Temp) promoted the algal biomass which further enhanced the production of ß-cyclocitral both in the water column and pore water. It was worth noting that when Chla ≥30 µg/L, the effects of algae on pore-ß-cyclocitral were significantly enhanced, and pore-ß-cyclocitral played a major role in the regulation of ß-cyclocitral concentrations in water column. Overall, our study facilitated a comprehensive and systematic understanding of the effects of algae on odorants and the dynamic regulatory processes in complex aquatic ecosystems, and revealed a long-neglected process, that was, the important contribution of sediments to ß-cyclocitral in the water column in eutrophic lakes, which would conduce to a more accurate understanding of the evolution of off flavors in lakes and also useful for the management of odors in lakes in the future.

Assessing chlorophyll-a and water quality dynamics in arid-zone temporary pan systems along a disturbance gradient.

Temporary pans are susceptible to various anthropogenic effects such as pollution, resource extraction, and land use intensification. However, given their small endorheic nature, they are almost entirely influenced by activities close to their internally drained catchments. Human-mediated nutrient enrichment within the pans can lead to eutrophication, resulting in increased primary productivity and decreased associated alpha diversity. The Khakhea-Bray Transboundary Aquifer region and the pan systems that characterise the area are understudied area with no records available of the biodiversity therein. Additionally, the pans are a major water source for the people in these areas. This study assessed differences in nutrients (i.e., ammonium, phosphates) and their effect on chlorophyll-a (chl-a) concentrations in pans along a disturbance gradient in the Khakhea-Bray Transboundary Aquifer region, South Africa. Physicochemical variables, nutrients, and chl-a were measured from 33 pans representing variable anthropogenic exposure during the cool-dry season in May 2022. Five environmental variables (i.e., temperature, pH, dissolved oxygen, ammonium, and phosphates) showed significant differences between the undisturbed and disturbed pans. The disturbed pans generally had elevated pH, ammonium, phosphates and dissolved oxygen compared to the undisturbed pans. A strong positive relationship was observed between chl-a and temperature, pH, dissolved oxygen, phosphates and ammonium. Chlorophyll-a concentration increased as surface area, and the distance from kraals, buildings and latrines decreased. Anthropogenic activities were found to have an overall effect on the pan water quality within the Khakhea-Bray Transboundary Aquifer region. Therefore, continuous monitoring strategies should be established to better understand the nutrient dynamics through time and the effect that this may have on productivity and diversity in these small endorheic systems.

Analysis of the eutrophication in a wetland using a data-driven model.

Eutrophication is a major problem in the international Anzali wetland (northern Iran). The present research initially aimed to determine the trophic state index (TSI) in ten sampling sites in the main parts of the Anzali wetland (western, eastern, central, and Siahkeshim parts). After determining the TSI in the wetland, a data-driven method (classification tree model with a J48 algorithm) was implemented to predict the trophic condition in the wetland based on a set of water quality and physical-structural variables. One hundred twenty samples related to chlorophyll-a (the model's output) and environmental variables (the model's inputs) were measured monthly during 1-year study period (2017-2018). Based on the TSI calculation, the western, Siahkeshim, eastern, and central parts of the wetland are classified as eutrophic, super-eutrophic, hyper-eutrophic, and hyper-eutrophic, respectively. When all environmental variables were introduced to the model (with five-time randomization effort, pruning confidence factor = 0.01, and seven-fold cross-validation), eight variables (bicarbonate, pH, water temperature, electric conductivity, dissolved oxygen, total phosphorus, water depth, and water turbidity) were predicted by the model. The model predicted that an increase in total phosphate, water turbidity, and electric conductivity concentration may contribute to the hyper-eutrophic state of the wetland. In contrast, the hyper-eutrophic of the wetland is associated with a decrease in water depth, dissolved oxygen, and pH concentration. According to ANOVA test, the trophic condition in the wetland can be affected by spatial and temporal patterns. Anthropogenic pressures such as the influx of chemicals particularly the nutrients (phosphorus and nitrogen) are the main cause of water enrichment (eutrophication problem) in main parts of the Anzali wetland ecosystem.

The impacts of nanoplastic toxicity on the accumulation, hormonal regulation and tolerance mechanisms in a potential hyperaccumulator - Lemna minor L.

Plastic pollution, which is currently one of the most striking problems of our time, raises concerns about the dispersal of micro and nano-sized plastic particles in ecosystems and their toxic effects on living organisms. This study was designed to reveal the toxic effects of polystyrene nanoplastic (PS NP) exposure on the freshwater macrophyte Lemna minor. In addition, elucidating the interaction of this aquatic plant, which is used extensively in the phytoremediation of water contaminants and wastewater treatment facilities, with nanoplastics will guide the development of remediation techniques. For this purpose, we examined nanoplastic accumulation, oxidative stress markers, photosynthetic efficiency, antioxidant system activity and phytohormonal changes in L. minor leaves subjected to PS NP stress (P-1, 100 mg L-1; P-2, 200 mg L-1 PS NP). Our results showed no evidence of PS NP-induced oxidative damage in P-1 group plants, although PS NP accumulation reached 56 µg g-1 in the leaves. Also, no significant changes in chlorophyll a fluorescence parameters were observed in this group, indicating unaffected photosynthetic efficiency. PS NP exposure triggered the antioxidant system in L. minor plants and resulted in a 3- and 4.6-fold increase in superoxide dismutase (SOD) activity in the P-1 and P-2 groups. On the other hand, high-dose PS NP treatment resulted in insufficient antioxidant activity in the P-2 group and increased hydrogen peroxide (H2O2) and lipid peroxidation (TBARS contents) by 25 % and 17 % compared to the control plants. Furthermore, PS NP exposure triggered abscisic acid biosynthesis (two-fold in the P-1 and three-fold in the P-2 group), which is also involved in regulating the stress response. In conclusion, L. minor plants tolerated NP accumulation without growth suppression, oxidative stress damage and limitations in photosynthetic capacity and have the potential to be used in remediation studies of NP-contaminated waters.