Shifting of phytoplankton assemblages in a regulated Chinese river basin after streamflow and water quality changes

Decoding phytoplankton quality in the waterways of the Sundarbans mangrove forest of Bangladesh

Phytoplankton, as primary producers and bioindicators, are vital for assessing aquatic ecosystem health. This study developed a Phytoplankton Quality Index (PQI) to evaluate the ecological health of Bangladesh's Sundarbans estuarine zones, using data from 24 stations across the Pashur River and estuaries in Bagerhat, Khulna, and Satkhira regions during the winter of 2021. Thirty-two variables were incorporated into a comprehensive multivariate and index-based framework, including ten heavy metals, eight phytoplankton indices, eight physicochemical, and four nutrient parameters. Diatoms dominated the phytoplankton community (93.38 %), followed by Dinoflagellates, Chlorophyta, and Charophyta together accompanying high abundance, richness and diversity in estuarine regions and high dominance in upstream regions with varying level of evenness throughout the study area. Moderate pollution was indicated by the Heavy Metal Evaluation Index (HEI = 6.24) in Satkhira and Nemerow's Pollution Index (NPI = 1.65) in Bagerhat. Normality (P > 0.05) and multicollinearity tests (Variance Inflation Factor < 10) finalized fifteen variables for Redundancy Analysis (RDA) and Canonical Correspondence Analysis (CCA), which identified temperature (23.85 ± 1.36 °C), pH (8.04 ± 0.08), nitrate (0.612 ± 0.15 ppm), HEI (5.14 ± 1.48), and ORP (285.11 ± 34.86 miliVolts) as key drivers for Diatoms, while ammonia (0.203 ± 0.105 ppm) and phosphate (0.096 ± 0.05 ppm) favored Chlorophytes and Charophytes. Further PQI was calculated using Principal Component Analysis (PCA) integrating the varimax method ensuring Measure of Sampling Adequecy (MSA > 0.5) for all variables. Results revealed significant spatial variability in phytoplankton quality with poor PQI in the upstream (20 %) and downstream (18 %) sections of the Pashur River driven by metal pollution and nutrient imbalances. Estuarine zones showed good quality (76 %) with localized poor-quality areas were linked to pollution and restricted water circulation. The study introduces a novel framework to identify PQI integrating multiple ecological metrics to assess the health of mangrove estuarine ecosystems. This tool is essential for monitoring ecosystem conditions, detecting pollution hotspots, and supporting sustainable management strategies globally.

Land use types, basin characteristics and water quality together shape riverine phytoplankton community composition and diversity

Exploring the combined effects of basin characteristics, land use types, and human activities on phytoplankton biomass, community composition and diversity is important for developing effective river protection strategies. In the present study, 182 phytoplankton samples were collected in the Hanjian and Danjiang River basins and the explanation rate of the above factors was analyzed. Water quality was the primary factor affecting riverine phytoplankton biomass, with an explanation rate to Chl a reaching 59.8%. Water quality was also the primary factor affecting phytoplankton diversity but the contribution of land use types and basin characteristics was also high. In addition to affecting phytoplankton communities and diversity by affecting water quality, diverse land use can increase the taxa of algae discharged through soil erosion processes. Elevation and slope were the main basin characteristics regulating phytoplankton community and diversity because they can determine the retention time of phytoplankton in rivers. The results also showed that land use types were the primary factor affecting the critical relative abundance of extinction (a), competition coefficient (k), environmental taxa capacity (N), but water quality was the primary factor affecting Shannon index, Simpson index, and Pielou index. This difference indicated that index a, k, and N could reflect specific characteristics of phytoplankton diversity that were not reflected by the latter indices. Our results implied that land use types and basin characteristics affected the discharge of exotic algal taxa, retention time, and other factors, thereby influencing the composition and diversity of riverine phytoplankton communities.

A new approach combining principal component factor analysis and K-means for identifying natural background levels of NO3-N in shallow groundwater of the Huaihe River Basin

Establishing natural background levels (NBLs) of nitrate‑nitrogen (NO3-N) is crucial for groundwater resource management and pollution prevention. Traditional statistical methods for evaluating NO3-N NBLs generally overlook the hydrogeochemical processes associated with NO3-N pollution. We propose using a method that combines principal component factor analysis and K-means clustering (PCFA-KM) to identify NO3-N anomalies in three typical areas of the Huaihe River Basin and evaluate the effectiveness of this method in comparison with the hydrochemical graphic method (Hydro) and the Gaussian mixture model (GMM). The results showed that PCFA-KM was the most robust and effective for identifying NO3-N anomalies caused by human activities. This method not only considers the data's discreteness but also combines the influencing factors of NO3-N pollution to identify anomalies, thus avoiding the influence of non-homogeneous hydrogeological conditions. Moreover, 70 % of the identified anomalies were explained by sampling survey data, geochemical ratios, and pollution percentage indices, confirming the method's effectiveness and reliability. The upper limits of NO3-N NBLs obtained by PCFA-KM were 12.97 mg/L (CUs-I), 4.42 mg/L (CUs-V), and 5.57 mg/L (CUs-VI). This study provides a new approach for NO3-N anomaly identification, which can guide future NO3-N NBLs assessments and pollution prevention and control efforts.

Ecological patterns of phytoplankton across lake cross-section: insights into co-evolution of physicochemical conditions in Chashma Lake on Indus River

Physicochemical properties of water influence planktonic diversity and distribution, which is essential in obtaining basic knowledge of aquatic biodiversity. Thus current study aims to investigate the spatiotemporal diversity, abundance ratio, and distribution of phytoplankton species and their association with water quality parameters of Chashma Lake, Pakistan. During the study period from 2018 to 2019, we measured 13 physicochemical parameters across three selected sampling sites (S1, S2, and S3) in Chashma Lake, revealing both spatial and temporal variability. Dissolved oxygen (DO) was higher in S3, while S1 exhibited higher alkalinity levels, carbon dioxide, phosphorus, and chloride levels. The study identified 77 phytoplankton species grouped into five taxonomic categories, with Cyanobacteria dominating (39.90%), followed by Chlorophyta (33.4%) and Bacillariophyta (24.88%). Euglenozoa and Ochrophyta were less abundant (1.3% and 0.41%, respectively). Spatial variations in phytoplankton distribution were noted, with Chlorophyta being more abundant at S2, Bacillariophyta and Cyanobacteria at S1, and Euglenozoa dominating at S3. Canonical Correspondence Analysis (CCA) revealed the influence of various physicochemical parameters on phytoplankton distribution. This comprehensive study provides valuable insights for the ecological assessment and monitoring of water bodies. It is recommended that continuous monitoring is required to capture long-term trends, further explore the specific environmental drivers impacting phytoplankton dynamics, and consider management strategies for maintaining water quality and biodiversity in Chashma Lake.

Damming exacerbates the discontinuities of phytoplankton in a subtropical river in China

Phytoplankton is sensitive to changes in river ecosystems. Increasing dams disrupt the continuity of river ecosystems. However, the spatial impacts of dams on phytoplankton have not been well documented. In this study, using multiple statistical analyses, the relationships between environmental drivers and phytoplankton community structures in natural background reaches, reservoirs, and corresponding post-dam reaches were explored in the Jiulong River with multiple cascaded dams, which encountered eutrophication and algal blooms in the past 15 years. Results illustrated that damming exacerbated longitudinal discontinuities of phytoplankton communities. The relative abundance of phytoplankton varied in three types of river sections. The average phytoplankton abundance in the reservoirs (1.62 × 105 cell·L-1) was higher than those in the natural background reaches (5.15 × 104 cell·L-1) and the corresponding downstream reaches (4.55 × 104 cell·L-1). The total β diversity ranged from 0.38 to 0.89 with an average of 0.64 and dominated by species replacement and least by species richness. The water environmental factors and hydraulic parameters rather than nutrients were more attributable to phytoplankton community variability in three river sections. These findings facilitate the management of rivers with multiple cascade dams by releasing environmental flows, jointly operating cascade hydropower stations, and developing nutrient reduction schemes to mitigate the negative impacts of damming in the river.

Phytoplankton functional groups as indicators of environmental changes in weir and non-weir sections of the lower Nakdong River, Republic of Korea

The Nakdong River underwent water impoundment after eight weirs were constructed as part of South Korea's Four Major River Restoration Project from 2009 to 2012. In this study, we aimed to confirm whether the assemblage of phytoplankton based on phytoplankton functional groups (PFGs), could indicate environmental changes in the weir section (WS) and non-weir section (NWS) of the lower Nakdong River after the construction of the weir. Thus, we examined the relationships between PFGs and gradients in environmental drivers, such as physicochemical, meteorological, and hydrological variables. Environmental gradients were observed between the WS and NWS in dissolved oxygen (DO), electric conductivity (EC), biochemical oxygen demand (BOD), chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP), dissolved total nitrogen (DTN), dissolved total phosphorus (DTP), ammonia nitrogen (NH3-N), nitrate nitrogen (NO3-N), and phosphorus (PO4-P), which were relatively higher in the WS. Seventeen PFGs were identified (A, B, C, D, E, F, G, H1, J, LM, LO, MP, P, T, W1, X1, and X2). Additionally, the LM and P groups, preferring an enriched lentic system more than other groups, were found to be the dominant PFGs that led the succession of assemblages. Traditional nutrients (N, P) and organic pollutants (BOD, COD) primarily affected the autochthonous growth of the most dominant PFGs in the WS as HRT (hydraulic retention time) increased. Furthermore, the hydrological variables associated with meteorological conditions have a synergistic effect on the composition of the major PFGs and chemical and physical variables in the WS. In other words, the WS may be a new source of inoculum that primarily determines the occurrence and maintenance of phytoplankton in the immediate downstream region (NWS). In particular, group LM (mainly potentially toxic Microcystis) developing in the upper weir impoundment is transported downstream, resulting in a high inoculation effect on further growth in the NWS during the summer monsoon season.

Spatio-temporal dynamics of phytoplankton in a diversion reservoir and the major influencing factors: taxonomic versus functional groups classification

Identifying factors affecting phytoplankton dynamics is crucial to the management of aquatic ecosystems. A lot of scholars have conducted intensive studies on phytoplankton in lake or reservoirs, but not many studies have been conducted on diversion reservoirs. To explore the seasonal and spatial variation of phytoplankton communities and their relationship with environmental factors in the context of water diversion, a case study was carried out at XiKeng (XK) reservoir in South China. In this study, month-by-month water samples and phytoplankton were collected from this reservoir from December, 2021, to July, 2022. The results showed that the phytoplankton community was characterized by significant spatial and temporal variations. There were significant differences in phytoplankton abundance and structure in the reservoirs in terms of time. The abundance of phytoplankton cells and the proportion of Cyanobacteria in the reservoir showed a trend of increasing from autumn to spring and then decreasing from spring to summer, while the functional group evolved from S1 in autumn to SN in spring and summer. The abundance of phytoplankton was influenced by the dynamic water division and the characteristics of the reservoir itself, resulting in a spatial distribution characteristic of AIII > AII > AI. Water temperature (WT) and nutrients were the key factors driving the changes in phytoplankton abundance and community structure in the reservoir. These findings will deepen our understanding of the spatial and temporal dynamics of phytoplankton community structure in diversion reservoirs and provide a basis for freshwater water ecological management strategies.

Rotifer distribution patterns in relation to dissolved organic matter in the middle reaches of Huai River Basin during the dry season

Increased dissolved organic matter (DOM) may induce water browning and affect zooplankton communities by changing photochemical environment, microbial food web, and bioavailability of organic carbon supply. However, little is known about the relationship between DOM components and rotifers in natural rivers, relative to the cladocerans and copepods. Here, we investigated the spatial patterns of rotifer distribution in relation to DOM by collecting forty-four water samples from four areas in the middle reaches of Huai River Basin. Results revealed that DOM was described by two humic-like and two protein-like components. There were significant differences in the composition and diversity of rotifer communities among areas, which might be related to autochthonous and allochthonous DOM as well as geographical distances. Specifically, rotifer communities were mainly related to molecular weight, substituents on the aromatic ring, humification level, and protein-like materials. Autochthonous and fresh DOM was positively associated with rotifer abundance and richness, and terrigenous humic-like substances were positively associated with rotifer diversity and evenness. There was a reciprocal effect between rotifer and DOM. Our findings will contribute to the understanding of the possible effects of water browning on rotifer communities, providing new insights into the key role of DOM and rotifer in the energy transfer of aquatic systems.

Impacts of land uses on spatio-temporal variations of seasonal water quality in a regulated river basin, Huai River, China

Land use impacts from agriculture, industrialization, and human population should be considered in surface water quality management. In this study, we utilized an integrated statistical analysis approach mainly including a seasonal Mann-Kendall test, clustering analysis, self-organizing map, Boruta algorithm, and positive matrix factorization to the assessment of the interactions between land use types and water quality in a typical catchment in the Huai River Basin, China, over seven years (2012-2019). Spatially, water quality was clustered into three groups: upstream, midstream, and downstream/mainstream areas. The water quality of upstream sites was better than of mid-, down-, and mainstream. Temporally, water quality did not change significantly during the study period. However, the temporal variation in water quality of up-, down-, and mainstream areas was more stable than in the midstream. The interactions between land use types and water quality parameters at the sub-basin scale varied with seasons. Increasing forest/grassland areas could substantially improve the water quality during the wet season, while nutrients such as phosphorus from cropland and developed land was a driver for water quality deterioration in the dry season. Water area was not a significant factor influencing the variations of ammonia nitrogen (NH₃-N) and total phosphorus (TP) in the wet or dry season, due to the intensive dams and sluices in study area. The parameters TP, and total nitrogen (TN) were principally linked with agricultural sources in the wet and dry seasons. The parameters NH₃-N in the dry season, and chemical oxygen demand (COD_Cr) in the wet season were mainly associated with point source discharges. Agricultural source, and urban point source discharges were the main causes of water quality deterioration in the study area. Collectively, these results highlighted the impacts of land use types on variations of water quality parameters in the regulated basin.

Analysis of water quality indexes and their relationships with vegetation using self-organizing map and geographically and temporally weighted regression

Natural vegetation has been proved to promote water purification in previous studies, while the relevant laws has not been excavated systematically. This research explored the relationships between vegetation cover and water quality indexes in Liaohe River Basin in China combined with self-organizing map (SOM) and geographically and temporally weighted regression (GTWR) innovatively and systematically based on the distributing heterogeneity of water quality conditions. Results showed that the central and northeast regions of the study area had serious organic and nutrient pollution, which needed targeted treatment. And SOM verified that high vegetation coverage with retention potential of organic and inorganic pollutants as well as nutrients improved water quality to some degree, while the excessive discharges of pollutants still had serious threats to nearby water environment despite the purification function of vegetation. GTWR indicated that the waterside vegetation was beneficial for dissolved oxygen increasing and contributed to the decreasing of organic pollutants and inorganic pollutants with reducibility. Natural vegetation also obsorbed nutrients like TN and TP to some degree. However, the retential potential of nitrogen and organic pollutants became not obvious when there were heavy pollution, which demonstrated that pollution sources should be controlled despite the purification function of vegetation. This study implied that natural vegetation purified water quality to some degree, while this function could not be revealed when there was too heavy pollution. These findings underscore that the pollutant discharge should be controlled though the natural vegetation in ecosystem promoted the purification of water bodies.

Ecological health evaluation of rivers based on phytoplankton biological integrity index and water quality index on the impact of anthropogenic pollution: A case of Ashi River Basin

Based on the phytoplankton community matrices in the Ashi River Basin (ASRB), Harbin city, we developed an evaluation method using the phytoplankton index of biotic integrity (P-IBI) to evaluate ecological health while investigating the response of P-IBI to anthropogenic activities. We compared the effectiveness of P-IBI with that of the water quality index (WQI) in assessing ecological health. Between April and October 2019, phytoplankton and water samples were collected at 17 sampling sites in the ASRB on a seasonal basis. Our results showed that seven phyla were identified, comprising 137 phytoplankton species. From a pool of 35 candidate indices, five critical ecological indices (Shannon–Wiener index, total biomass, percentage of motile diatoms, percentage of stipitate diatom, and diatom quotient) were selected to evaluate the biological integrity of phytoplankton in the ASRB. The ecological status of the ASRB as measured by the P-IBI and WQI exhibited a similar spatial pattern. It showed a spatial decline in ecological status in accordance with the flow of the river. These results highlighted that P-IBI was a reliable tool to indicate the interaction between habitat conditions and environmental factors in the ASRB. Our findings contribute to the ecological monitoring and protection of rivers impacted by anthropogenic pollution.

Evaluation of water quality using a Takagi-Sugeno fuzzy neural network and determination of heavy metal pollution index in a typical site upstream of the Yellow River

Assessment of river water quality is very important for understanding the impact of human activities on aquatic ecosystems. As the second-largest river in China, the Yellow River's water environment is closely related to the social development and water security of northern China. The Huangshui River is a major tributary of the upper Yellow River, and it supplies water to cities in the lower reaches. In this study, a Takagi-Sugeno (T-S) fuzzy neural network was used to evaluate water quality of the Huangshui River, and pollutant sources were analyzed. The heavy metal pollution index (HPI) was calculated to assess the heavy metal pollution level, and the health risks posed by heavy metal elements were assessed. The results indicated that the main contaminants in the Huangshui River were ammonia nitrogen (NH₃-N) and total phosphorus (TP), which was affected by various activities of industry, agriculture, and urbanization, and the maximum concentration of NH₃-N and TP was 5.90 mg/L and 0.36 mg/L, respectively. The T-S evaluation results of some points in the middle reaches were 3.317 and 3.197, which belonged to Level Ⅳ and the water quality was poor. The concentrations of Cu, Zn and Cr in the river were 0.57-44.58 μg/L, 10-122.50 μg/L and 2-28.67 μg/L, respectively, and they were relatively large. The T-S fuzzy neural network could evaluate water quality, avoiding extreme evaluation results by using fuzzy rules to reduce the influence of pollutant concentrations that are too high or too low. In addition to qualitative categorization of water quality, this approach can also quantitatively assess water quality within a single category. The results of water quality assessment could provide a scientific data support for river management.

Using integrated models to analyze and predict the variance of diatom community composition in an agricultural area

With the growing demand of assessing the ecological status, there is the need to fully understand the relationship between the planktic diversity and the environmental factors. Species richness and Shannon index have been widely used to describe the biodiversity of a community. Besides, we introduced the first ordination value from non-metric multidimensional scaling (NMDS) as a new index to represent the community similarity variance. In this study, we hypothesized that the variation of diatom community in rivers in an agricultural area was influenced by hydro-chemical variables. We collected daily mixed water samples using ISCO auto water samplers for diatoms and for water-chemistry analysis at the outlet of a lowland river for a consecutive year. An integrated modeling was adopted including random forest (RF) to decide the importance of the environmental factors influencing diatoms, generalized linear models (GLMs) combined with 10-folder cross validation to analyze and predict the diatom variation. The hierarchical analysis highlighted antecedent precipitation index (API) as the controlling hydrological variable while water temperature, Si²⁺ and PO₄-P as the main chemical controlling factors in our study area. The generalized linear models performed better prediction for Shannon index (R² = 0.44) and NMDS (R² = 0.51) than diatom abundance (R² = 0.25) and species richness (R² = 0.25). Our findings confirmed that Shannon index and the NMDS as an index showed good performance in explaining the relationship between stream biota and its environmental factors and in predicting the diatom community development based on the hydro-chemical predictors. Our study showed and highlighted the important hydro-chemical factors in the agricultural rivers, which could contribute to the further understanding of predicting diatom community development and could be implemented in the future water management protocol.

Nuisance phytoplankton transport is enhanced by high flow in the main river for drinking water in Uruguay

Eutrophication, climate change, and river flow fragmentation are the main cause of nuisance algal blooms worldwide. This study evaluated the conditions that trigger the growth and occurrence of nuisance phytoplankton in the Santa Lucía River, a subtropical floodplain lotic system that supplies drinking water to 60% of the population of Uruguay. The main variables that explained phytoplankton biovolume were extracted from generalized linear models (GLM). The potential impact of nuisance organism advection on water utility was estimated by the phytoplankton biovolume transport (BV_TR, m³ day^-1), an indicator of biomass load. Santa Lucía River had a wide flow range (0.7×10⁵-1438×10⁵ m³ day^-1) and eutrophic conditions (median, TP: 0.139 mg L^-1; TN: 0.589 mg L^-1). GLMs indicated that phytoplankton biomass increased with temperature and soluble reactive phosphorus. Contrary to expectations, the presence of cyanobacteria was positively associated with periods of high flow that result in high cyanobacterial biovolume transport, with a probability of 3.35 times higher when flow increased by one standard deviation. The cyanobacterial biovolume transported (max: 9.5 m³ day^-1) suggests that biomass was subsidized by allochthonous inocula. Biovolume from other nuisance groups (diatoms, cryptophytes, and euglenophytes) was positively associated with low-flow conditions and high nutrient concentrations in the main river channel, thereby indicating that these conditions boost eukaryote blooms. The evaluation of BV_TR allows a better understanding of the dynamics of fluvial phytoplankton and can help to anticipate scenarios of nuisance species transport.

Seasonal and spatial distributions of morpho-functional phytoplankton groups and the role of environmental factors in a subtropical river-type reservoir

Phytoplankton is capable of responding to aquatic conditions and can therefore be used to monitor freshwater reservoir water quality. Numerous classification techniques, including morpho-functional approaches, have been developed. This study examined changes in phytoplankton assemblages and water quality, which were sampled quarterly from July 2018 to April 2019. The purpose was to contrast the applicability of three classification approaches (functional, morpho-functional and morphological-based functional groupings) for understanding the spatial and seasonal distribution of the biomass variance in phytoplankton functional groups and their driving environmental factors in the ecological zones of the Shanxi Reservoir through multivariate analysis. The results showed that the phytoplankton biomass was highest in the watercourse zone and lowest in the transition zone. Furthermore, the Shanxi Reservoir was characterized by several cyanobacteria (Microcystis spp.) and numerous bacillariophytes (Asterionella sp., Navicula spp. and Aulacoseira granulata). After evaluating the advantages and disadvantages of morpho-functional classifications, we determined that water temperature appeared to be an essential factor, and the morphology-based functional group approach provided the best results for demonstrating phytoplankton succession, despite having lower sensitivity than the others. Nevertheless, these approaches are all appropriate for identifying and monitoring phytoplankton community structure in aquatic systems of reservoirs with complex terrains.