Eutrophication Level Research Articles

Spatiotemporal Dynamic Analysis of Eutrophication Status Based on Machine Learning-Based Retrieval Algorithm: Case Study in Liangzi Lake, Hubei, China

The routine monitoring of eutrophication is an important measure for observing the variation in water quality and protecting the ecological health of lakes. However, in situ information reflects eutrophication levels within a limited distance and period. In this study, we retrieved the trophic level index (TLI) based on Landsat 8 remote sensing images and using a machine learning (ML) method in Liangzi Lake in Hubei Province, China. The results showed that random forest (RF) outperformed other ML algorithms in estimating the TLI, evaluated by its higher fitness through the Monte Carlo method (median values of R2, RMSE, and MAE are 0.54, 0.047, and 0.037, respectively). In general, 8% of the areas of Liangzi Lake presented an increasing eutrophication level from 2014 to 2022, and 20.1% of the areas reached a mild eutrophication level in 2022. In addition, we found that temperature and anthropogenic activities may impact the eutrophication conditions of the lake. This work uses remote sensing imagery and a ML method to monitor the dynamics of the lake’s eutrophication status, thereby providing a valuable reference for pollution control measures and enhancing the efficiency of water resource management.

Manganese(III) dominants the mobilization of phosphorus in reducing sediments: Evidence from Aha reservoir, Southwest China

Eutrophication has become one of the greatest threats to aquatic ecosystems. The release of phosphorus (P) from sediments exerts a critical role on eutrophication level. Both manganese (Mn) and iron (Fe), sensitive to redox conditions, own strong affinity for P. Numerous works have demonstrated that Fe was a key factor to drive P cycle in sediments. However, the role of Mn on P mobilization remains largely unexplored. Herein, the mechanism of P mobilization driven by Mn were investigated in a seasonal anoxic reservoir. Diffusive gradients in thin films (DGT) results, from both field investigations and laboratory incubations, showed P was synchronously distributed and significantly positive correlated (r2 ≥ 0.40, p < 0.01) with Mn, suggested that P cycle was associated with Mn. X-ray photoelectron spectroscopy (XPS) results showed that in the outer layers at the top 1 cm sediment pellet the contents of Mn and P occurred significantly synchronize changed, while that of Fe remains virtually unchanged when oxygen conditions changed. This demonstrated that Mn is likely to be the key factor affect P cycle. Most importantly, the relative content of Mn(III) changed the most (≈20 %) interpreted that Mn(III) is the key Mn species dominants the P mobilization. Furthermore, Dual-Beam scanning electron microscope (DB-SEM) maps clearly showed the co-enrichment of P and Mn in oxic sediments, confirmed P was mainly hosted by Mn minerals. In contrast, the random distributions and weak or negative correlations between P and Fe implied that P cycle was decouple with Fe, this resulted from that Fe was almost deposited as inert Fe fractions (>99.2 %) in reducing sediments. This study significantly expanded our knowledge on the geochemical behavior of P influenced by Mn in aquatic sediments.

Climate Warming and Mismanagement Drive the Shift of Fish Communities in the Wadi El-Rayan Arid Lakes

The Wadi El-Rayan lakes are important aquatic environments located at the border of the great North African Sahara. Quantifying the temporal changes in these lakes due to natural and/or anthropogenic stressors is critical when assessing potential impacts on aquatic ecosystem health and the sustainability of fisheries. To detect the changes in fish communities and their drivers, the landing composition of the Wadi El-Rayan lakes over the past 30 years was quantitatively analyzed. The areas of the lakes dramatically decreased from 110 km2 in 1991 to 73 km2 in 2019. The loss of the lake area was attributed to climate warming, where the evaporation rate exceeded the volume of recharge and the recharge decreased due to an increase in agriculture and aquaculture. The total landing significantly increased in the past three decades due to an increase in the fishing effort (number of licensed boats). Nile tilapia, mullet, and grass carp dominated the landings. The pelagic-to-demersal ratio indicated a shift in the fish community composition towards demersal species. This shift was attributed to an increase in the eutrophication level. The fish communities of the landing data were clustered into four distinct groups. These clusters were significantly differentiated (p &lt; 0.001) in both a PERMANOVA test and a PCA plot. There was a gradual replacement of the dominant species among these clusters. The most recent cluster (2018–2019) was characterized by rare species dominating the community. This shift in species composition suggests that target taxa may have been overexploited. The total landing also decreased, which may have been a result of climate warming. Furthermore, the presence of alien and warm-water species significantly increased. The fish community structure and composition shift could be attributed to anthropogenic (mismanagement) and natural climatic changes (warming).

Long-term monitoring of water quality and phytoplankton community structure of Lake Manzala, Mediterranean Coast of Egypt

Coastal wetlands play a crucial role in supporting biodiversity, providing valuable ecosystem services, and contributing to the resilience of coastal ecosystems, making the preservation and restoration of these wetlands essential for sustainable development in coastal regions. This study focuses on Lake Manzala, a coastal wetland located on the Mediterranean Coast of Egypt, highlighting the significance of conserving and managing this unique environment. The objective of this research was to evaluate the water quality and phytoplankton structure of Lake Manzala and establish an updated long-term ecological database for the region, specifically evaluating the effectiveness of development plans that were carried out in 2017. Surface water samples were collected seasonally at eleven sites between 2010 to 2022. The findings revealed that prior to the development plans, the phytoplankton abundance in Lake Manzala exhibited high levels of eutrophication, characterized by increased abundance and species richness. The dominant phytoplankton classes in Lake Manzala were Bacillariophyceae, Chlorophyceae, and Cyanophyceae. Prior to development plans, they accounted for 46.5% and 45.0% respectively. Post-development, Bacillariophyceae increased to 62.8%, while Chlorophyceae decreased to 25.1%. Dinophyceae increased from 1.3% to 9.04%, while Cyanophyceae decreased from 6.1% to 1.6%. Based on the Trophic State Index for chlorophyll a, Lake Manzala underwent a shift from predominantly hypertrophic to eutrophic conditions. The study explored the relationship between biological factors and environmental conditions using principal component analysis, cluster analysis, and the modified water quality index (WQI). The results indicated positive signs of improvement in Lake Manzala during the post-development phase, as it transitioned from a poor to a moderate state. This research emphasizes the need for integrated land and water management approaches. By informing policy direction and development, this research underscores the importance of preserving and restoring ecosystems for the long-term well-being of both local communities and the global environment.

Macrogenomics Reveals Effects on Marine Microbial Communities during Oplegnathus punctatus Enclosure Farming.

(1) Background: Laizhou Bay is an important aquaculture area in the north of China. Oplegnathus punctatus is one of the species with high economic benefits. In recent years, the water environment of Laizhou Bay has reached a mild eutrophication level, while microorganisms are an important group between the environment and species. In this study, we evaluated alterations in environmental elements, microbial populations, and antibiotic resistance genes (ARGs) along with their interconnections during Oplegnathus punctatus net culture. (2) Methods: A total of 142 samples from various water layers were gathered for metagenome assembly analysis. Mariculture increases the abundance of microorganisms in this culture area and makes the microbial community structure more complex. The change had more significant effects on sediment than on seawater. (3) Results: Certain populations of cyanobacteria and Candidatus Micrarchaecta in seawater, and Actinobacteria and Thaumarchaeota in sediments showed high abundance in the mariculture area. Antibiotic resistance genes in sediments were more sensitive to various environmental factors, especially oxygen solubility and salinity. (4) Conclusions: These findings highlight the complex and dynamic nature of microorganism-environment-ARG interactions, characterized by regional specificity and providing insights for a more rational use of marine resources.

Identifying factors influencing reservoir eutrophication using interpretable machine learning combined with shoreline morphology and landscape hydrological features: A case study of Danjiangkou Reservoir, China

Reservoir nearshore areas are influenced by both terrestrial and aquatic ecosystems, making them sensitive regions to water quality changes. The analysis of basin landscape hydrological features provides limited insight into the spatial heterogeneity of eutrophication in these areas. The complex characteristics of shoreline morphology and their impact on eutrophication are often overlooked. To comprehensively analyze the complex relationships between shoreline morphology and landscape hydrological features, with eutrophication, this study uses Danjiangkou Reservoir as a case study. Utilizing Landsat 8 OLI remote sensing data from 2013 to 2022, combined with a semi-analytical approach, the spatial distribution of the Trophic State Index (TSI) during flood discharge periods (FDPs) and water storage periods (WSPs) was obtained. Using Extreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP), explained the relationships between landscape composition, landscape configuration, hydrological topography, shoreline morphology, and TSI, identified key factors at different spatial scales and validated their reliability. The results showed that: (1) There is significant spatial heterogeneity in the TSI distribution of Danjiangkou Reservoir. The eutrophication levels are significant in the shoreline and bay areas, with a tendency to extend inward only during the WSPs. (2) The importance of landscape composition, landscape configuration, hydrological topography, and shoreline morphology to TSI variations during the FDPs are 25.12 %, 29.6 %, 23.09 %, and 22.19 % respectively. Besides shoreline distance, the Landscape Shape Index (LSI) and Hypsometric Integral (HI) are the two most significant environmental variables overall during the FDPs. Forest and grassland areas become the most influential factors during the WSPs. The influence of landscape patterns and hydrological topography on TSI varies at different spatial scales. At the 200 m riparian buffer zone, the increase in cropland and impervious areas significantly elevates eutrophication levels. (3) Morphology complexity, shows a noticeable threshold effect on TSI, with complex shoreline morphology increasing the risk of eutrophication.

Effects of storm events on nutrient characteristics in a stratified drinking water reservoir: Behavior, transmission pathways and management strategy

Storm events result in nutrient fluctuations and deterioration of reservoir water supply quality. Understanding of nutrient dynamics (e.g., concentration, composition, loads and transport pathways) and adoption of effective management strategies are critical for safeguarding water quality. A comprehensive monitoring was conducted for three storm events during the rainy season in 2023. Results showed nitrogen (N) and phosphorus (P) dynamics demonstrate a significant response to hydrological process. Rainfall resulted in the highest event mean concentrations (EMCs) of total nitrogen (TN), nitrate nitrogen (NO3−-N), ammonia nitrogen (NH4+-N), total phosphorus (TP), and particulate phosphorus (PP) in the runoff being 1.97, 2.15, 2.30, 44.17, and 62.38 times higher than those observed in baseflow. On average, NO3−-N/PP accounted for 82 %/96 % of N/P exports. Hysteresis analyses reveal that NH4+-N and PP were mainly transported by surface runoff from over-land sources, whereas TN and NO3−-N were primarily delivered by subsurface runoff. Additionally, nutrient concentrations were significantly higher in the intrusive layer in reservoir compared to the pre-storm period, which gradually decreased from the tail to the head as particulate sedimentation and water column mixing occurred. Water-lifting-aerators (WLAs) were employed to alter the reservoir thermal stratification regime via artificial mixing to affect the intrusive layer of storm runoff. Comparison of the intrusive layer for three storms reveals that WLAs triggers the storm runoff to form an underflow via increasing the reservoir bottom water temperature above that the runoff, ensuring that water quality at the intake position remains unaffected by inflows. These findings serve as a reference for the response of reservoir eutrophication levels to storm events and present practical engineering experience for enhancing water quality safety during the rainy season.

Spatial-temporal distribution and eutrophication evaluation of nutrients and trace metals in summer surface seawater of Yantai Sishili Bay, China

Due to coastal development expansion, an increasing influx of pollutants enters the sea through riverine input and land runoff, threatening coastal ecosystems and posing a risk of eutrophication. In this study, trace metals (Fe, Mn, Cu, and Zn), and nutrients (constituents of N, P, and Si) were assessed in the summer surface seawater of Yantai Sishili Bay (YSB), Northern China focusing on the determination of concentration, spatial-temporal distribution and sources identification, while exploring their correlations. It also aimed to clarify the eutrophication status and evaluate the linear relationships between eutrophication, trace metals, and nutrients in YSB. Over three years (2021–2023), the total dissolved concentrations of Fe, Mn, Cu, and Zn ranged from 4.79–26.71, 0.19–6.41, 0.26–1.53, and 0.74–13.12 µg/L, respectively. Concurrently, nutrient concentrations including NO2-, NO3-, NH4+, PO43-, and DSi exhibited a range of 0.37–11.66, 2.04–178.30, 1.69–70.01, 0.02–16.68, and 0.02–0.71 µg/L respectively. These concentrations revealed a gradual decrease from nearshore to offshore and the temporal variation also showed significant patterns from year to year, indicating distinct regional variations. The primary contributors to the trace metals and nutrients in the study region were recognized as external contributions stemming from natural, anthropogenic, and atmospheric deposition through correlation and principal component analysis. More specifically, riverine input and coastal farming contributed large amounts of nutrients to coastal waters, threatening a potential risk of eutrophication. The eutrophication evaluation expressed below the mild eutrophication level and was far lower than the other global and Chinese bays. The linear correlation between eutrophication and trace metals revealed a weak positive correlation but a significant correlation with nutrients. Despite the absence of significant eutrophication in the bay, potential risks were identified due to identifiable sources of nutrient and trace metal inputs. The findings provided insights to guide efforts in preventing and mitigating coastal eutrophication, as well as nutrient and trace metal pollution, in coastal cities.

Forms and Migration Mechanisms of Phosphorus in the Ice, Water, and Sediments of Cold and Arid Lakes.

Phosphorus (P) is a crucial nutrient in lake ecosystems and organic phosphorus (Po) is a significant component. However, the distribution characteristics and migration behaviour of Po in ice-water-sediment systems under freezing and thawing conditions in cold and arid regions remain unclear. This study aims to investigate the forms of Po and its contribution to endogenous P pollution. We selected three lakes (Dai, Hu, and Wu Lake) and employed phosphorus nuclear magnetic resonance (31P-NMR) techniques to analyse the following: (1) The total phosphorus (TP) content, which was the highest in the water from Dai Lake (0.16 mg/L), with substantial seasonal variation observed in Wu Lake, where P content was four times higher in summer than in winter because of farmland drainage. (2) Eutrophication analysis, which indicated that Dai Lake had significantly higher eutrophication levels than Wu Lake, with P being the controlling factor in Dai Lake and both N and P in Wu Lake. The proportion of Po in the TP content was 90%, 70%, and 55% for Wu, Dai, and Hu Lake, respectively, indicating that Po was the main component of eutrophic lakes. (3) 31P-NMR, which revealed that orthophosphate (Ortho-P) and monoester phosphate (Mon-P) were the main P components in the winter, with a higher P content in Dai Lake. Ortho-P has a higher content in ice, indicating that inorganic phosphorus (Pi) migration is the main factor in ice-water media. Mon-P showed multiple peaks in Dai Lake, indicating a complex composition of adenosine monophosphate and glucose-1-phosphate. (4) The ice-water phase change simulation experiments, which showed that phosphate was the least repelled in ice, while pyrophosphate (Pyro-P) and macromolecular P were more repelled. Adding sediment enhanced the migration of P but did not change the repulsion of macromolecular P, suggesting the molecular structure as the main influencing factor. These results provide important scientific evidence for the quantitative analysis of Po pollution in lake water environments, aiding in P load reduction and risk prevention and control.

Quantitative Effects of Anthropogenic and Natural Factors on Heavy Metals Pollution and Spatial Distribution in Surface Drinking Water Sources in the Upper Huaihe River Basin in China.

The water quality of sources in the Huaihe River Basin significantly affects the lives and health of approximately 16.7% of China's population. Identifying and quantifying pollution sources and risks is essential for effective water resource management. This study utilized Monte Carlo simulations and Geodetector to assess water quality and eutrophication, as well as to evaluate the sources of heavy metals and the associated health risks for both adults and children. The results showed that eutrophication of water sources in Huaihe River was severe, with an overall EI value of 37.92; 67.8% of the water sources were classified as mesotrophic and 32.2% classified as eutrophic. Water quality and eutrophication levels in the southern mountainous regions were better than those in the densely populated northern areas. Adults were found to have a higher carcinogenic risk than children, whereas children faced a higher noncarcinogenic risk than adults. Cr presented the highest carcinogenic risk, affecting more than 99.8% of both adults and children at levels above 1 × 10-6 but not exceeding 1 × 10-4. The noncarcinogenic risk from metals did not surpass a level of 1, except for Pb. As was primarily influenced by agricultural activities and transportation, whereas Cd, Cr, and Pb were mainly affected by industrial activities, particularly in local textile industries such as knitting and clothing manufacturing. The analysis demonstrated that the influence of anthropogenic factors on heavy metal distribution was significantly enhanced by indirect natural factors. For example, the explanatory power of Precipitation and Road Network Density on As was 0.362 and 0.189, respectively, whereas their interaction had an explanatory power as high as 0.673. This study indicates that the geodetector method is effective in elucidating the factors influencing heavy metal distribution in water, thereby providing valuable insights into pollution sources in global drinking water.

Ocean water colour retrieval method based on directional polarimetric camera

ABSTRACT Chlorophyll-a (Chl-a) concentrations serve as a pivotal metric for assessing the biological content and eutrophication levels of waterbodies. In optical remote sensing, empirical and semi-analytical methods are commonly employed for Chl-a retrieval. Leveraging the Level-1B remote sensing data from the Directional Polarimetric Camera (DPC) aboard the Terrestrial Ecosystem Carbon Inventory Satellite (TECIS), this study amalgamates empirical algorithms (OC2, OC3, Aiken-P, and Aiken-C) and look-up-table (LUT) techniques to estimate Chl-a in open water. Test data acquired from DPC on 20 August 2022, are validated against the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on the Terra satellite and AERONET-Ocean Color water-leaving radiance data for the same area and date. The results reveal that among the tested algorithms, particularly in the log10 scale space, the Aiken-P algorithm demonstrates the highest correlation coefficient (R2 = 0.6333), with the lowest bias of 1.0366 and a minimum mean absolute error (MAE) of 1.2097. This underscores the suitability and accuracy of the Aiken-P algorithm for water colour retrieval based on DPC-derived data, highlighting its practical applicability.

Research on the Inversion of Chlorophyll-a Concentration in the Hong Kong Coastal Area Based on Convolutional Neural Networks

Chlorophyll-a (Chl-a) concentration is a key indicator for assessing the eutrophication level in water bodies. However, accurately inverting Chl-a concentrations in optically complex coastal waters presents a significant challenge for traditional models. To address this, we employed Sentinel-2 MSI sensor data and leveraged the power of five machine learning models, including a convolutional neural network (CNN), to enhance the inversion process in the coastal waters near Hong Kong. The CNN model demonstrated superior performance with on-site data validation, outperforming the other four models (R2 = 0.810, RMSE = 1.165 μg/L, MRE = 35.578%). The CNN model was employed to estimate Chl-a concentrations from images captured over the study area in April and October 2022, resulting in the creation of a thematic map illustrating the spatial distribution of Chl-a levels. The map indicated high Chl-a concentrations in the northeast and southwest areas of Hong Kong Island and low Chl-a concentrations in the southeast facing the open sea. Analysis of patch size effects on CNN model accuracy indicated that 7 × 7 and 9 × 9 patches yielded the most optimal results across the tested sizes. Shapley additive explanations were employed to provide post-hoc interpretations for the best-performing CNN model, highlighting that features B6, B12, and B8 were the most important during the inversion process. This study can serve as a reference for developing machine learning models to invert water quality parameters.

Evidence of comammox bacteria playing a dominant role in Lake Taihu sediments based on metagenomic analysis

The nitrification process plays an important role in the nitrogen cycle, in which the ammonia-oxidation process mediated by microorganisms is the rate-limiting step. Environmental factors can affect the distribution and activity of ammonia-oxidizing microorganisms (AOM), including ammonia-oxidizing bacteria (AOB), ammonia-oxidizing archaea (AOA), and complete ammonia oxidizer (comammox Nitrospira). At present, most studies have used amoA as a marker gene for the ammonia oxidation process to analyze the differences among AOM community composition and abundance in the environment. In this study, metagenomic sequencing was used to study the differences in community composition and functional gene distribution of nitrifying microorganisms in the sediments of Lake Taihu with different eutrophication levels. It was found that comammox Nitrospira and typical nitrite oxidizer NOB Nitrospira, which belong to Nitrospirota, had higher relative abundance at most sites compared to AOB and AOA. Furthermore, the network analysis of genes related to nitrogen cycle showed that the main survival mode of nitrogen metabolizing microorganisms was mutualism. Besides, the microbial genomes in the sediments of Lake Taihu were reconstructed by metagenomic binning, which showed that among the 167 bins obtained, 2 bins (bin 9 and bin 32) were annotated as comammox Nitrospira, and had high abundance in the macrophytes-dominated lakes (such as South Lake Taihu and West Coast). In addition, bin 9, which belongs to comammox Nitrospira, annotates amoA genes associated with ammonia oxidation, and other genes associated with urea decomposition and transport, suggesting functional diversity. Overall, these findings suggest that AOM have different distribution characteristics, among which comammox Nitrospira has high diversity and may be potentially dominant in macrophytes-dominated lakes.

Updating the breeding sites of Aedes aegypti (Diptera: Culicidae) in Camagüey, Cuba

Mosquito-borne diseases continue to be of significant public health concern in various parts of the world, facilitated by the adaptations that certain species, such as Aedes aegypti, have managed to develop. In order to update the bioecological knowledge of A. aegypti populations in a Health Area of Camagüey Province, Cuba, a comprehensive entomological survey was conducted both indoors and outdoors, covering the entire urban population, encompassing a total of 36,584 households. Aedes aegypti colonized 52 types of breeding sites, of which 15 were found to be permanent and suitable (29.0%), contributing 82.0% of the positivity. Low tanks were particularly prominent (43.0%). Positivity in natural breeding sites remained low (0.11%). Larvae were collected in habitats with high levels of eutrophication (17.30%), grouped in 28 positive breeding sites, accounting for 3.32% of the total number of positive sites. No differences were observed in the total number of positive breeding sites and capture locations between climatic seasons, indicating a consistent pattern of positivity throughout the study year, during which six types of breeding sites exceeded a 70% monthly repetitiveness. These results underscore the importance of vigilance and control measures to be undertaken by residents in their respective households.

Factors of macrozoobenthos formation in low-mountain lakes of the Russian Altai

The current state of macrozoobenthos of six low-mountain lakes of the Russian Altai was studied in different hydrological seasons (May, July, September) 2022: Aya (Aiskoe), Beloe, Kireevo, Kolyvanskoe, Koksha, and Svetloe. The aim of the article is to study the factors of formation of benthic invertebrate communities of foothill lakes of the Russian Altai. In total 156 species from 9 classes of invertebrates were identified in the zoobenthos of the studied lakes, the highest percentage of occurrence was recorded for chironomids and oligochaetes. According to the taxonomic composition of macrozoobenthos, most of the studied lakes of the Russian Altai (Aya, Beloe, Kireevo and Kolyvanskoe) were close to flatland lakes. Two lakes (Koksha and Svetloe) combined characteristics of both flatland and highland lakes. The abundance and biomass of zoobenthos in lakes Aya and Kireevo corresponded to the oligotrophic level, in lakes Beloe and Kolyvanskoe to the mesotrophic level, and in lakes Koksha and Svetloye to the eutrophic level. The structural characteristics of macroinvertebrates are indicators of the state of lake ecosystems. Therefore, in order to maintain the health of lake ecosystems, it is important to determine the limiting factors for macroinvertebrate community composition and structure. The influence of environmental factors on the composition and structure of macrozoobenthos of foothill lakes of the Russian Altai was studied. The relationship of 10 main indicators of zoobenthos structure with 30 hydro physical and hydrochemical indicators was analyzed. Using principal component analysis, multiple regression method, correlation and canonical analyses, it was revealed that the greatest influence on the development of benthic invertebrate communities in the studied lakes of the Russian Altai was exerted by nutrients, permanganate oxidability and soil character and water temperature.

Characteristics of phytoplankton assemblages and their relationship with environmental factors in the Qiongzhou Strait, China

The characteristics and influencing factors of phytoplankton assemblages were analyzed in July (rainy season) and November (dry season) 2022 in the Qiongzhou Strait, China. A total of 68 species of phytoplankton belonging to 33 genera and 3 phyla were recorded. Diatom was the most dominant group. The broad-temperature widespread species were the most abundant. The dominant species in the rainy season were Skeletonema costatum, S. tropicum, Chaetoceros preseudocurvisetus and Thalassionema nitzschioides while those in the dry season were T. frauenfeldii, T. nitzschioides and Coscinodiscus granii. Phytoplankton cell abundance was significantly positively correlated with nitrite and total nitrogen concentrations, and negatively correlated with temperature and pH. Red tide algae occurred with high frequency. All sites were at eutrophic level except for 3 sites in the rainy season, which were at mesotrophic level. Therefore, there is a potential risk of red tides in the Qiongzhou Strait, which requires long-term monitoring and precautions.

Analysis of the Spatiotemporal Distribution of Algal Blooms and Its Driving Factors in Chaohu Lake Based on Multi-source Datasets

Eutrophication and harmful algae blooms are one of the common ecological and environmental problems faced by freshwater lakes all over the world. As a typical inland freshwater lake, Chaohu Lake exhibits a high level of eutrophication and algae blooms year-round and shows a spatiotemporal difference in different regions of the lake. In order to understand the basic regularity of the development and outbreak of algal blooms in Chaohu Lake, the data from the comprehensive water observation platform and remote sensing were integrated to obtain the spatiotemporal distribution of algal blooms from 2015 to 2020. Then, an evaluation model based on Boosted Regression Trees (BRT) was constructed to quantitatively assess the importance and interactions of various environmental factors on algal blooms at different stages. The results indicated that:① The occurrence of algal blooms in Chaohu Lake exhibited significant seasonal variations, with the cyanobacteria beginning to recover in spring and bring about a light degree of algal blooms in the western and coastal areas of Chaohu Lake. The density of cyanobacteria reached its maximum in summer and autumn, accompanied by moderate and severe degrees of algal bloom outbreaks. ② During the non-outbreak period, the variation in the cyanobacteria density was greatly affected by physical and chemical factors, which explained 80.3% of the variance in the change in cyanobacteria density. The high concentrations of dissolved oxygen content in the water column and the weak alkalinity (7.2-7.6) and appropriate water temperature (about 3℃) provided a favorable environmental condition for the breeding and growth of cyanobacteria. In addition, the onset of algal blooms was closely related to the air temperature steadily passing through the threshold. According to the statistics, the date of first outbreak of algal blooms in Chaohu Lake was 11 days or so after the air temperature steadily remained above 7℃. ③ During the outbreak period, the occurrence of algal blooms was influenced by the combination of cyanobacterial biomass and meteorological conditions such as temperature, wind speed, and sunshine duration. The cumulative contribution ratio of the four factors was as high as 95%, and each factor had an optimal interval conductive to the outbreak of algal blooms. Furthermore, the results of multi-factor interaction analysis indicated a larger probability of the outbreak of algal blooms in Chaohu Lake under the combined effect of high cyanobacteria density, suitable temperature, and the breeze. This study analyzed and revealed the spatiotemporal characteristics and the dominant influencing factors of algal blooms in Chaohu Lake at different stages, which could provide the scientific basis for the prediction, early warning, and disposal of algal blooms under the context of climate change.

The spatiotemporal variations of microbial community in relation to water quality in a tropical drinking water reservoir, Southmost China.

It is well-known that water quality has great significance on microbial community composition in aquatic environments. In this study, we detected water column indicates the microbial community composition of nine sampling sites over two seasons using Illumina TruSeq sequencing in Songtao Reservoir, Hainan Province, Southmost China. The study indicated that the dominant phylum was Actinobacteria, Proteobacteria, Bacteroidetes, and Cyanobacteria. The diversity parameters showed that the microbial community composition had significant spatiotemporal variations, including the significantly higher Shannon index and Simpson index upstream than those midstream and downstream. Besides, there were significantly higher Chao1 index, Shannon index, and Simpson index in winter than in summer. Principal coordinates analysis (PCoA) showed the microbial structural composition had significant seasonal differences. The results of microbial community composition further revealed that the eutrophication level upstream was higher than that of midstream and downstream. The redundancy analysis (RDA) diagram indicated that the abundance of microbiology species significantly correlated with temperature, total phosphorus, Se, and Ni. Furthermore, the mantel's test showed that the temperature and total phosphorus significantly affected the community composition of archaea and bacteria. Overall, our finding here partially validated our hypothesis that the spatiotemporal variations of microbial community composition are significantly related to nutrients, physicochemical factors and metals, which has been unknown previously in tropical drinking waterbodies. This study substantially contributed to understanding of the composition of microbial community in tropical drinking water reservoirs and the main environmental driving factors in tropical zones. It also provided a reference for the management of reservoir operation to ensure drinking water safe.

Enabling comprehensive assessment of marine eutrophication impacts and their evaluation against regional safe operating space

PurposeNitrogen emissions from human activities are contributing to elevated levels of eutrophication in coastal ecosystems. Mechanisms involved in marine eutrophication show strong geographical variation. Existing life cycle impact assessment (LCIA) and absolute environmental sustainability assessment (AESA) methods for marine eutrophication do not adequately represent this variability, do not have a full global coverage, and suffer from other limitations, such as poor estimation of coastal residence times. This study aims to advance LCIA and AESA for marine eutrophication.MethodsWe aligned and combined recent advancements in marine eutrophication LCIA and AESA methods into one method. By re-running models underlying the combined methods and incorporating additional data sources, we included marine regions missing in previous methods and improved fate modeling, with the inclusion of denitrification and plant uptake in the air emission-terrestrial deposition pathway. To demonstrate and validate our method, we applied it in a case study.ResultsThe developed method allows the assessment of marine eutrophication impacts from emissions to soil, freshwater, and air at high resolution (0.083° and 2° × 2.5° for inland and air emissions, respectively) and spatial coverage (all ice-free global continents). In the case study, we demonstrate the added value of our method by showing that the now quantified spatial variability within spatial units, e.g., river basins, can be large and have a strong influence on the modeled marine eutrophication from the case study. Compared to existing methods, our method identifies larger occupations of safe operating space for marine eutrophication, mainly due to the high resolution of the coastal compartment, reflecting a more realistic areal extent of marine eutrophication impacts.ConclusionsAlthough limited by factors such as simulations based on a single reference year for modeling inland and air fate, our method is readily applicable to assess the marine eutrophication impact of nitrogen emitted to any environmental compartment and relate it to the safe operating space. With substantial advancement of existing approaches, our method improves the basis for decision-making for managing nitrogen and reducing emissions to levels within the safe operating space.

Comprehensive assessment of eutrophication in Tangxun Lake, a large urban lake in the middle reaches of the Yangtze River

Urban lakes play an important role in supporting the ecological environment and human society, yet increasing pollution poses a threat to water quality. Tangxun Lake, a typical Large urban lake in the middle reaches of the Yangtze River, has experienced cultural eutrophication in recent years; however, few studies have comprehensively examined the water quality of this lake. Therefore, we aimed to evaluate the water quality of the Tangxun Lake Basin using the Nemerow pollution index, principal component analysis (PCA), phytoplankton density and diversity, and the comprehensive trophic level index (TLI). Additionally, we analyzed the main influencing factors to provide a reference for the management of the aquatic environment of Tangxun Lake. The Nemerow pollution index evaluation showed that the annual degree of pollution in Tangxun Lake ranged from mild to heavy. The PCA results showed that the main pollution factors affecting water quality were total phosphorus (TP) and total nitrogen (TN). According to the results of TLI, the water in Tangxun Lake was moderately to severely eutrophic. Evaluation of algal cell density showed that Tangxun Lake was mesotrophic, and the phytoplankton diversity index showed that the eutrophication level was high. The degree of pollution in Tangxun Lake varied seasonally and was in the order of spring > winter > summer > autumn. The pollution in inner Tangxun Lake was relatively serious in spring, summer, and autumn, whereas that in outer Tangxun Lake was more serious in winter. This study provides a scientific basis for the comprehensive management of the ecological environment in the Tangxun Lake Basin.