Spatiotemporal dynamics of phytoplankton community structure in freshwater reservoir and its relationship with environmental factors

Lushan West Reservoir is a typical deep-water reservoir in the southern mountainous and hilly region. As an artificial freshwater reservoir system with a storage capacity of 7.92 billion cubic meters, the relationship between its internal environmental factors and the structure of the biological community is of great significance for maintaining ecological balance, ensuring water quality security, and promoting sustainable development of water ecology. This study selected 20 sampling points in the Jinkou and Sima areas of the Lushan West Reservoir and conducted monthly dynamic monitoring from May 2022 to April 2023 to analyze the spatiotemporal variation characteristics of the phytoplankton community structure and its relationship with environmental factors. The research results show that: (1) There are a total of 116 species of phytoplankton at eight phylum levels in the Lushan West Reservoir, mainly belonging to the Chlorophyta (43.97%) and Bacillariophyta (28.45%). The community density and biomass show significant seasonal differences, with the highest values in summer (7.86 × 10 6 cells/L) and the lowest values in winter (1.72 × 10 6 cells/L). Cyanophyta and Bacillariophyta show alternating dominance, with Pseudanabaena sp., Anabeana sp., and Synedra acus being the main dominant species throughout the year. (2) Redundancy analysis indicates that water temperature, transparency, total nitrogen, and total phosphorus are the key factors driving the changes in community structure. Among them, the increase in nutrient load in summer is significantly correlated with the dominance of Cyanophyt a, while a low-temperature and high-transparency environment promotes the growth of Bacillariophyta. (3) Niche analysis shows that the niche width of Bacillariophyta is relatively large (B i = 1.75–2.54), while Cyanophyta maintains its competitive advantage through optimized resource utilization. This study reveals the seasonal succession pattern and environmental driving mechanism of the phytoplankton community in the Lushan West Reservoir, providing a scientific basis for water ecology protection and water quality management in deep-water reservoirs in southern China.

Phytoplankton, as key primary producers in aquatic ecosystems, play a critical role in shaping community dynamics through their responses to ecosystem functions. Owing to their short life cycles, they rapidly form new assemblages following reservoir impoundment, making them highly effective bioindicators for aquatic ecological assessments (Baho et al., 2020). Relevant studies indicate that phytoplankton communities are influenced by environmental factors in a multidimensional manner, with their horizontal distribution shaped by seasonal and spatial variations in these factors (Zhu et al., 2021). Moreover, their temporal dynamics are primarily governed by hydrological parameters, water quality, and nutrient concentrations (Liao et al., 2023). As demonstrated by the correlation analysis conducted by Nogueira et al. (2010), elevated water temperatures and increased nutrient levels significantly promote phytoplankton proliferation, thereby contributing to reservoir eutrophication. Liu et al. (2023), using Mantel tests, identified significant correlations between phytoplankton community diversity and key environmental variables, including dissolved oxygen and nitrogen-phosphorus nutrient factors. Additionally, Mingming et al. (2013), through redundancy analysis (RDA), elucidated the pronounced influence of chlorophyll-a (Chla) on the long-term successional patterns and intrinsic mechanisms of phytoplankton dynamics.

Furthermore, phytoplankton community structures exhibit significant variation across different types of water bodies. Reservoir systems, influenced by dam construction, water level regulation, and anthropogenic activities, are characterized by unstable flow velocities, fluctuating discharge rates, and altered distributions of dissolved oxygen and nutrients, leading to distinct environmental fluctuations within their ecosystems (Szoszkiewicz et al., 2006). For instance, Rangel et al. (2012) observed that periodic water level fluctuations induce niche differentiation in both the littoral and pelagic zones of aquatic systems, thereby influencing phytoplankton distribution. During periods of stable water levels, phytoplankton communities in reservoirs remain relatively stable, whereas pronounced fluctuations trigger community reorganization and short-term variability. Typically, phytoplankton biomass and density in the main reservoir area exceed those in tributary regions, exhibiting a spatial pattern of upstream < midstream > downstream (Shan et al., 2023; Zhao et al., 2024; Lian et al., 2024). Similarly, phytoplankton communities in lakes and reservoirs display distinct seasonal dynamics. In eutrophic lakes and reservoirs during summer and autumn, Cyanobacteria and Chlorophyta dominate; in contrast, oligotrophic systems are primarily characterized by Chlorophyta and Bacillariophyta. During winter and spring, Bacillariophyta and Cryptophyta tend to prevail (Ge et al., 2015; Wang et al., 2022). Phytoplankton density and biomass generally follow a seasonal sequence of summer>autumn>spring>winter (Zhang et al., 2019; Zuo et al., 2015; Angel et al., 2012). The structural composition and biomass of phytoplankton communities in reservoirs are shaped by a combination of water body physicochemical properties and seasonal drivers.

Although existing research has explored the relationship between phytoplankton communities and environmental factors, several knowledge gaps remain, particularly for deep-water reservoir systems. First, most studies in China have focused on shallow eutrophic lakes or large river-connected lakes, whereas deep-water reservoirs—characterized by complex thermal stratification, pronounced water-level regulation, and distinct longitudinal environmental gradients—remain comparatively understudied. In particular, Lushan West Reservoir, a typical deep-water reservoir in the southern mountainous-hilly region of China, lacks any systematic baseline survey of its phytoplankton community structure. Second, many prior investigations rely on a limited number of sampling sites or short-term snapshots, which are insufficient to resolve the coupled spatial heterogeneity and seasonal dynamics of phytoplankton communities in regulated reservoir systems. Third, while multivariate ordination methods (e.g., RDA, CCA) have been widely applied to identify environmental correlates, few studies integrate quantitative niche analysis (niche breadth and niche overlap) with these approaches to elucidate the competitive mechanisms underlying seasonal succession.

Accordingly, this study selected Lushan West Reservoir as the research object and conducted consecutive monthly dynamic monitoring from May 2022 to April 2023 across 20 spatially distributed sampling sites. This study aims to: (1) clarify the spatiotemporal variation characteristics of phytoplankton community structure in a deep-water reservoir; (2) identify the key environmental driving factors through redundancy analysis; and (3) reveal the competitive mechanisms underlying seasonal succession via quantitative niche analysis. The findings are expected to provide a scientific basis for water ecological protection and water quality management of similar deep-water reservoir systems in southern China.

Study area

As a representative river-connected lake in the eastern plain lake region of China, Poyang Lake is characterized by abundant lake and reservoir resources as well as rich aquatic biodiversity within its watershed (Liu et al., 2015; Dai et al., 2015; Wang et al., 2014; Zheng et al., 2014). Lushan West Reservoir is a typical deep-water reservoir located in the northwest of Yongxiu County, Jiangxi Province, at the boundary between Yongxiu and Wuning counties (115°04’ – 115°40’E, 29°03’ – 29°18’N). Situated in the southern mountainous-hilly region of China, it is characterized by complex basin topography and significant water depth, making it a representative system for studying phytoplankton community dynamics in deep-water reservoirs. The water surface covers an area of 308 km 2, with a north–south extent of 15.53 km and an east–west span of 44 km. The average water depth in the lake reaches 18.59 m, with a maximum depth of 45 m and a total storage capacity of 7.92 billion m 3. The lake basin exhibits complex and diverse topography, predominantly surrounded by medium-to-low mountains with elevations ranging from 300 to 500 meters. The terrain gradually slopes from west to east and from north and south toward the center, forming an overall arc-shaped enclosure. This configuration reflects a typical deep-water lake-reservoir topographic pattern characteristic of southern mountainous and hilly regions, commonly described as “two gorges with one valley”. This makes it an ideal area for studying the spatiotemporal relationship between environmental factors and phytoplankton community structure.

Sample collection and analysis

In accordance with the Technical Guidelines for National Surveys of Freshwater Biological Species Resources (Trial Implementation), a total of 20 sampling sites were established within the Lushan West Reservoir (Figure 1). From May 2022 to April 2023, monthly sampling was conducted with seasonal divisions defined as follows: spring spanning February to April, summer from May to July, autumn from August to October, and winter from November to January.

Qualitative analysis

The phytoplankton samples were collected in accordance with the investigation method stipulated in “Research Methods of Freshwater Plankton” (Manickam et al., 2018). A plankton net with a pore size of 64 μm and a No.25 was used to scoop water samples at a depth of 0.5 m for 8 to 10 min. Pour the water sample into a 500 mL specimen bottle, add 10 mL Lugol’s solution for fixation and seal it with a label. After bringing it back to the laboratory, let it stand for sedimentation for 48 h. Then, discard the upper clear liquid and retain about 30 mL of concentrated liquid. Take 0.1 mL aliquot of the concentrated liquid to make 5 temporary slides and identify the species of phytoplankton under an optical microscope, recording the morphological characteristics and cell structure.

Quantitative analysis

Three water samples were collected from the upper (0.5 m below the water surface), middle (at half the water depth), and lower (0.5 m above the sediment surface) layers of the water column using a 2,500 mL organic glass water sampler during each sampling event. The collected samples were mixed in equal volumes to form an integrated water-column sample for each site, and a 1,000 mL aliquot was transferred into a polyethylene bottle. Subsequently, 20 mL of Lugol’s solution was added to the aliquot for fixation. Following 36 h of sedimentation under laboratory conditions, the samples were concentrated via siphoning to a final volume of approximately 30 mL. A 0.1 mL subsample of the concentrated solution was transferred using a pipette into a 25 × 16 grid counting chamber. Phytoplankton cells were enumerated under an optical microscope across 10 randomly selected fields of view. When cell density was low, the entire chamber surface was counted. Each sample was analyzed in duplicate or triplicate, with the mean value calculated and the counting error maintained below 15% (Li, 2015).

Environmental factor determination

Water temperature, pH, dissolved oxygen, and conductivity were measured using a multiparameter portable water quality analyzer, while turbidity was determined with a digital portable turbidimeter calibrated with zero turbidity water after a 30-min warm-up period. Sampling time, location, and water depth were recorded during collection. Water samples were preserved at 4 °C and transported to the laboratory within 24 h. Laboratory analyses were conducted in accordance with the “Water and Wastewater Monitoring and Analysis Methods”: permanganate index was determined by the acidified potassium permanganate method, chemical oxygen demand by the dichromate method, biochemical oxygen demand by the dilution and inoculation method, ammonia nitrogen by Nessler’s reagent colorimetry, total phosphorus by the ammonium molybdate spectrophotometric method, and total nitrogen by the alkaline potassium persulfate digestion-UV spectrophotometric method.

Data statistics and analysis

Analysis of dominance and diversity of phytoplankton communities

Utilize dominance index (Lampitt et al., 1993) (Y) (Equation 1) to determine the dominant species of phytoplankton: To mitigate potential biases stemming from reliance on a singular diversity index (Equation 2), the Shannon-Wiener diversity index (H′) and the Pielou evenness index (J) (Equation 3) were employed to assess the phytoplankton diversity.

In the given formula: N denotes the aggregate count of all individual organisms within the sample; n i signifies the abundance of individuals belonging to the ith species in the sample; f i represents the frequency of occurrence of the ith species across various samples; S indicates the total number of species present; when the value of Y ≥ 0.02, it designates the species as dominant, whereas a Y > 0.1 classifies the species as absolutely dominant (Guo et al., 2016).

Niche analysis

The niche breadth was calculated using the modified Levins’ index (Equation 4) (Xu et al., 2012): In this formula, B i denotes the proportion of individuals of the i-th species observed at the j-th sampling point relative to the total population of the species; r represents the total number of sampling points.

Ecological niche overlap among dominant species was quantified using Pianka’s (1973) niche overlap index (Equation 5):

In the formula: P ij and P kj represent the proportions of individuals of species i and species k at the j -th sampling site, respectively; r is the total number of sampling sites; k denotes a phytoplankton species different from species i; and O ik is [0, 1].

Analysis of the spatiotemporal variations of environmental factors and phytoplankton community structure

Seasonal variations among environmental factors were analyzed using Student’s t -test implemented in the stats package (version 4.4.1) of R (version 4.4.1; R Core Team, Vienna, Austria). Non-metric Multidimensional Scaling (NMDS) ordination and Analysis of Similarities (ANOSIM) were performed using the vegan package (version 2.6–4) in R. All statistical visualizations were generated using the ggplot2 package (version 3.5.1). All analyses were conducted in the RStudio IDE (version 2024.04.2 + 764; Posit Software, PBC, Boston, MA, United States).

Analysis of driving mechanisms for phytoplankton community structure using multivariate statistics in Canoco 5.0

The Canoco5.0 software (Microcomputer Power, Ithaca, NY, United States) was used to conduct Detrended Correspondence Analysis (DCA) on the data of dominant phytoplankton species. When the DCA result is greater than 4, Canonical Correspondence Analysis (CCA) should be chosen to explain the relationship between dominant phytoplankton and environmental factors; when the DCA result is less than 3, Redundancy Analysis (RDA) should be selected; when the DCA result is between 3 and 4, both analysis models can be used. The results of the DCA analysis in this study indicated that the maximum gradient lengths of the four ordination axes were all less than 3. Therefore, RDA was selected as the tool to analyze the relationship between dominant phytoplankton species and the environment. The RDA analysis utilized the “vegan” package (version 2.6–4) in R language to screen the environmental factors influencing the phytoplankton community structure. Before the RDA analysis, all environmental factor variables except pH were transformed by lg(x + 1) to meet the requirements of normality and homoscedasticity. The explanatory ratios of each explanatory variable were calculated using “rdacca (version 1.0–1)” in R to eliminate the collinearity effect among variables.

Statistical analyses

This study utilized Excel 2022(Microsoft Corporation, Redmond, WA, United States) and Origin 2021(Origin Lab Corporation, Northampton, MA, United States) for basic data processing, statistical analysis, and graphical representation. Spatial distribution maps of sampling sites and phytoplankton cell abundance were generated using ArcGIS 10.8.2(Esri, Redlands, CA, United States), while significance analysis was conducted with IBM SPSS Statistics 26(IBM Corporation, Armonk, NY, United States).

Dynamic characteristics of environmental factors

In terms of hydrochemical characteristics, the water body of Lushan West Reservoir is characterized by neutral to weakly alkaline conditions, with a pH ranging from 7.02 to 7.26 and a mean of 7.15. Water temperature (TW) varies between 12.68 and 28.42 °C, averaging 20.77 °C. Dissolved oxygen (DO) concentrations range from 6.78 to 7.79 mg/L, with a mean of 7.31 mg/L. Secchi disk depth (SD) ranges from 262.67 to 320.55 cm, averaging 280.75 cm. Electrical conductivity (EC) values fall within 95.46 to 101.15 μS/cm, with a mean of 97.74 μS/cm. The permanganate index (COD Mn) ranges from 1.13 to 1.98 mg/L, with an average of 1.56 mg/L. Chemical Oxygen Demand (COD) levels ranged from 11.68 to 13.23 mg/L, with a mean of 12.29 mg/L. Five-day Biochemical Oxygen Demand (BOD 5) concentrations ranged from 1.12 to 1.78 mg/L, averaging 1.50 mg/L. Ammonia Nitrogen (NH 3 -N) concentrations varied between 0.06 and 0.08 mg/L, with a mean of 0.07 mg/L. Total Phosphorus (TP) levels ranged from 0.02 to 0.22 mg/L, with an average of 0.07 mg/L. Total Nitrogen (TN) concentrations ranged from 0.44 to 1.29 mg/L, with a mean of 0.68 mg/L.

Seasonal variations in water temperature (TW), electrical conductivity (EC), permanganate index (COD Mn), five-day biochemical oxygen demand (BOD 5), and total nitrogen (TN) were statistically significant across seasons (p < 0.05), with TW showing highly significant differences among seasons (p < 0.01). In contrast, other physicochemical parameters exhibited relatively stable seasonal patterns, as illustrated by total phosphorus (TP), which showed no significant seasonal variation (p > 0.05). Water transparency displayed marked seasonal fluctuations, particularly during the spring–summer transition, while remaining stable in other periods. Similar trends were observed in the concentration dynamics of total nitrogen and total phosphorus. The permanganate index decreased during summer, whereas electrical conductivity exhibited an opposite seasonal trend, showing an increase (Table 1). According to the GB 3838–2002 “Environmental Quality Standards for Surface Water” concentrations of COD Mn, COD, BOD 5, and NH 3 -N consistently met Class I water quality criteria across all seasons. Total phosphorus (TP) complied with Class III standards in summer and primarily met Class I standards during the remaining seasons. Total nitrogen (TN) satisfied Class I standards in winter and spring, but exceeded these thresholds in summer and autumn. From a habitat perspective, no significant differences were detected among the various environmental factors.

In terms of hydrological characteristics, the water level of Lushan West Lake showed distinct seasonal fluctuations during the study period, ranging from 60.25 m to 65.18 m, with an annual mean of 62.74 m. The lowest monthly mean water level occurred in June (60.25 m) during the pre-flood regulation period, while the highest value was recorded in November (65.18 m) after post-flood impoundment. The seasonal variation of water level was closely coupled with regional rainfall patterns and artificial dam operation schedules, representing a typical hydrological feature of large multi-purpose reservoirs.

Spatiotemporal variation characteristics of phytoplankton community structure

Species composition

A total of 116 phytoplankton species spanning 8 phyla were identified, with the community structure demonstrating significant seasonal variations in species composition and abundance distribution. Throughout the year, Chlorophyta dominated the taxonomic composition (51 species, 43.97%), followed by Bacillariophyta (33 species, 28.45%) and Cyanophyta (20 species, 17.24%). The remaining phyla-Dinophyta (4 species, 3.45%), Cryptophyta (5 species, 4.31%), Haptophyta (1 species, 0.86%), Euglenophyta (1 species, 0.86%), and Chrysophyta (1 species, 0.86%)—collectively represented 9.48% of the total species count. Significant deviations were observed in both abundance distribution and species composition: Cyanophyta dominated throughout the year, accounting for 67.50–94.72% of relative abundance in winter (November to January) and 48.64–62.26% in spring (February to April). The relative abundance of Bacillariophyta peaked in February (41.80%) and reached its lowest levels in winter (11.50% in March and 3.19% in November). Although Chlorophyta constituted 43.97% of the total species richness, its abundance exceeded 10% only in March (12.50%) and April (13.32%), declining to 1.58–3.35% during winter. Cryptophyta were detected exclusively in the colder months, with presence recorded only in November (0.28%), December (0.09%), and January (0.07%) (Figure 2).

Community structure characteristics

Phytoplankton cell density in Lushan West Reservoir exhibited pronounced seasonal fluctuations (Figure 3a). In early summer (May), cell density remained at a relatively high level of 7.86 × 10 6 cells/L, but declined sharply to 1.08 × 10 6 cells/L in June, coinciding with the pre-flood discharge period. A gradual recovery was observed thereafter, with densities increasing to 1.92 × 10 6 cells/L in July and 2.46 × 10 6 cells/L in August. The annual peak density was recorded in September at 9.98 × 10 6 cells/L. Following this peak, cell density declined markedly during winter, dropping to 1.72 × 10 6 cells/L in December—approximately 17.2% of the September maximum. Spring densities were generally low: a slight rebound to 1.67 × 10 6 cells/L occurred in March, while densities in February and April remained below 1.00 × 10 6 cells/L.

In terms of phytoplankton biomass, the highest value was recorded in May 2022, with Cyanophyta dominating (0.42 mg/L, accounting for 70% of total biomass), followed by Bacillariophyta (0.03 mg/L, 18% of total biomass); all other phyla contributed relatively little. Significant spatial variability in biomass was observed among sampling sites, with comparatively lower levels at sites SW2, SW4, SW13, SW15, and SW19. Overall, phytoplankton density and biomass were strongly correlated with seasonal fluctuations in physicochemical factors, whereas spatial variations reflected the heterogeneity of aquatic physicochemical characteristics across sampling locations (Figures 3b,c).

Key species assessment

Dominant species and ecological niche

This study examined seasonal variations in dominant species within Lushan West Reservoir, uncovering notable differences in ecological niche breadth and dominance indices among species. Cyanobacteria exhibited distinct seasonal patterns, with Y1 (Pseudanabaena sp.) displaying consistently high dominance across all seasons, achieving the peak dominance index of 1.1268 in autumn, accompanied by a niche breadth of 2.78. In contrast, Y2 (Anabaena sp.) demonstrated its highest dominance (0.2631) during summer, with a relatively narrower niche breadth of 1.27, which underscores its pronounced seasonal growth advantage. Other cyanobacteria species, such as Y3 (Raphidiopsis sinensis) and Y4 (Raphidiopsis sp.), demonstrated notable dominance in both spring and autumn, with ecological niche breadth values of 0.58 and 1.81, respectively. These values suggest a more restricted ecological niche and a limited seasonal growth window for these species. In contrast, Chlorophyta species exhibited relatively lower dominance overall, with Y7 (Ankistrodesmus spiralis) showing a pronounced dominance in spring (0.0125). Despite its relatively higher dominance, the ecological niche breadth of Y7 (1.37) indicated a stronger capacity for environmental adaptability. Similarly, Y8 (Quadrigula chodatii) and Y9 (Oocystis sp.) displayed relatively lower dominance in autumn, with ecological niche breadth values of 1.46 and 1.58, respectively, both of which suggest a more limited ecological adaptation range (Table 2).

The ecological niche breadth of Bacillariophyta species exhibits substantial variation, with Synedra acus (Y12) demonstrating particularly pronounced dominance during summer months (0.2030) and an ecological niche breadth of 2.13, indicative of robust seasonal adaptability. Melosira granulata (Y11) an d Aulacoseira sp. (Y13) display relatively stable dominance indices, with ecological niche breadths of 1.75 and 2.54, respectively, suggesting their capacity to adapt to seasonal environmental fluctuations. Conversely, species within the Chrysophyta and Cryptophyta consistently exhibit lower dominance indices. Dinobryon sp. (Y14) achieves a dominance of 0.0686 during spring, accompanied by an ecological niche breadth of 1.46, while Cryptomonas sp. (Y15) exhibits a dominance of 0.0135 during summer with an ecological niche breadth of 1.01, reflecting their constrained growth potential during specific seasonal periods (Figure 4).

Spatiotemporal variability in phytoplankton assemblages and their relationship influenced by environmental factors

Assessment of the relationship between spatiotemporal variations in phytoplankton community composition and environmental variables

The research findings demonstrate that seasonal variations exert significant influences on multiple facets of aquatic ecosystems, revealing complex interactions between environmental factors and the spatiotemporal dynamics of phytoplankton community structure. During spring, water temperature (WT) exhibits a significant positive correlation with the Shannon-Wiener diversity index (H′) of phytoplankton communities (R 2 = 0.382, p < 0.05), indicating that elevated water temperatures promote enhanced phytoplankton species diversity. In addition, both water temperature and pH show significant positive correlations with the phytoplankton community evenness index (J) (WT: R 2 = 0.315, p < 0.05; pH: R 2 = 0.297, p < 0.05). Concurrently, a significant positive correlation exists between phytoplankton biomass (10 −3 mg/L) and chemical oxygen demand (COD) (R 2 = 0.421, p < 0.05), implying an intrinsic linkage between biomass proliferation and increased organic pollution loading within the water body.

In contrast, summer observations reveal a significant positive correlation between water transparency and both the evenness index (J) (R 2 = 0.406, p < 0.05) and phytoplankton biomass (R 2 = 0.359, p < 0.05), suggesting that improved light penetration is closely associated with increased community evenness and biomass accumulation. Additionally, COD maintains a positive correlation with biomass (10 −3 mg/L) (R 2 = 0.374, p < 0.05), further evidencing the persistent influence of organic loading on biomass enhancement within the aquatic system.

During autumn, water temperature, pH, and turbidity exhibited significant positive correlations with the Shannon-Wiener diversity index (H ′) (WT: R 2 = 0.443, p < 0.05; pH: R 2 = 0.328, p < 0.05; turbidity: R 2 = 0.301, p < 0.05), indicating that these environmental parameters exert significant influences on biodiversity. Furthermore, these environmental indicators were significantly positively correlated with the evenness index (J), suggesting they contribute substantially to ecosystem evenness. In winter, ammonia nitrogen (NH 3 -N) demonstrated a significant positive correlation with the evenness index (R 2 = 0.289, p < 0.05; Figure 5).

RDA analysis

DCA analysis revealed that the maximum gradient axis length of phytoplankton density in Lushan West Reservoir reached 0.977, indicating a linear distribution pattern of community structure. Accordingly, RDA analysis based on a linear model was conducted to explore the relationship between phytoplankton community density and environmental factors. After excluding variables with variance inflation factor (VIF) greater than 20, the final RDA model was constructed, with an overall adjusted R 2 of 0.624 (p = 0.002), indicating that the selected environmental factors explained 62.4% of the total variation in phytoplankton community structure. The first two ordination axes explained 41.8 and 15.7% of the community variation, respectively, cumulatively accounting for 57.5% of the total variance (Figure 6).

Redundancy Analysis (RDA) indicated that transparency (conditional R 2 = 0.182, p < 0.01) and water temperature (conditional R 2 = 0.147, p < 0.05) were the most influential driving factors for phytoplankton community structure across all four seasons. Conversely, nutrient concentrations (TN, TP) and the permanganate index (COD Mn) consistently exhibited inhibitory effects on community diversity. Species-specific seasonal responses further elucidated these patterns: in spring, Granoreticella (Bacillariophyta) exhibited a significant positive correlation with transparency (R 2 = 0.296, p < 0.01), while Pseudanabaena (Cyanophyta) displayed a significant positive relationship with water temperature (R 2 = 0.241, p < 0.05). During summer, Scenedesmus bispinosus (Chlorophyta) demonstrated a strong positive association with transparency (R 2 = 0.312, p < 0.01), whereas Cryptomonas sp. showed a significant positive correlation with water temperature (R 2 = 0.228, p < 0.05). In autumn, the positive relationships between Granoreticella and transparency, along with Pseudanabaena and water temperature (R 2 = 0.205, p < 0.05), corresponded to those observed in spring. However, in winter, no significant correlations were detected between specific algal taxa and environmental variables, attributable to the suppressed metabolic activity under low temperatures.

Succession patterns of phytoplankton community structure

The phytoplankton community structure in large and medium-sized reservoirs within the Poyang Lake basin displays both shared and distinct regional characteristics, primarily governed by reservoir topography, hydrological conditions and anthropogenic regulation (Costantini et al., 2018). Compared to morphologically similar reservoirs, Lushan West Reservoir exhibits a unique phytoplankton succession pattern shaped by the combined effects of thermal stratification and seasonal water level fluctuations. As a typical deep-water reservoir (mean depth: 18.59 m) within a mountainous region, its water level presents clear seasonal variation driven by dam operation and regional rainfall: the reservoir implements pre-flood drawdown from April to June to reserve flood control capacity, resulting in the lowest annual water level and frequent hydrological disturbance during the early flood season; from September to November, post-flood impoundment raises the water level to the highest annual level, which remains relatively stable throughout the winter. In summer, pronounced thermal stratification limits vertical nutrient exchange under relatively low water level conditions, while periodic water level fluctuations induce mild sediment resuspension, rendering endogenous phosphorus release an important driver of cyanobacterial dominance. Under elevated summer temperatures (28.42 °C) and heightened nutrient concentrations (TN: 1.29 mg/L, TP: 0.22 mg/L), cyanobacteria, particularly filamentous taxa such as Pseudanabaena and Anabaena, experience rapid proliferation. The temporary decline of phytoplankton density in June is closely associated with enhanced discharge during pre-flood regulation, which shortens hydraulic retention time and exerts a dilution effect on phytoplankton populations.

Conversely, winter diatoms adapt to low-temperature, high-transparency conditions under stable high water levels through enhanced silicon metabolism, resulting in distinct seasonal dominance patterns. This hydrological-driven succession pattern is consistent with the viewpoint that periodic water level fluctuations induce niche differentiation of phytoplankton in reservoir ecosystems (Rangel et al., 2012), and further confirms that artificial water level regulation is a key differentiating factor shaping phytoplankton community structure in reservoirs compared to natural lakes. This model contrasts markedly with canyon-type deep-water reservoirs like the Three Gorges Reservoir (Li et al., 2009), where frequent and drastic water level fluctuations intensify hydrodynamic disturbance, favoring year-round dominance by flow-adapted diatoms. Compared to shallow lakes such as Taihu Lake (Ji et al., 2024) (mean depth: 1.9 m), Lushan West Reservoir’s complex island topography creates hydrological barriers, prolonging local water retention times and fostering microhabitats conducive to nitrogen-fixing cyanobacteria (Shen et al., 2021). In contrast, Taihu Lake exhibits spatially homogeneous cyanobacterial distribution and persistent dominance, attributable to intense wind-wave disturbance, high external nutrient loading, and short hydraulic retention time. This comparative analysis reveals that regional phytoplankton distribution patterns and seasonal succession dynamics are determined by differences in topography, hydrological regimes, and nutrient sources.

Consistent with the seasonal succession pattern documented in Section 3.2, Cyanophyta and Bacillariophyta exhibited cyclic dominance alternation. The underlying mechanism involves temperature-mediated competitive displacement: in summer, elevated water temperature (> 25 °C) coupled with reduced transparency suppresses the photosynthetic efficiency of other algal groups, consolidating cyanobacterial dominance; in winter, lower temperatures (< 13 °C) favor Bacillariophyta due to their enhanced biosilicification efficiency and higher surface-area-to-volume ratios. Concurrently, intensified vertical mixing-mediated nutrient replenishment further amplified this competitive edge.

The mechanism of alternation of dominant species

The seasonal succession of dominant phytoplankton species in Lushan West Reservoir demonstrates distinct regularity, primarily driven by dynamic changes in aquatic environmental factors and the adaptive regulation of algal functional traits. Specifically, various algal taxa utilize species-specific functional traits to acclimate to seasonal environmental variations: Within Cyanobacteria, Pseudanabaena sp. achieves its annual peak dominance (Y = 1.1268) in autumn, a phenomenon closely linked to its adaptation to elevated total phosphorus concentrations, while its filamentous morphology enhances light capture efficiency in low-transparency waters. Conversely, the peak dominance (Y = 0.2030) of the diatom Synedra acus during summer is attributed to the structural properties of its silica frustule, which confers resistance to hydraulic disturbance, thereby promoting its proliferation under conditions of strong turbulence and high turbidity. However, elevated summer temperatures suppress the nitrogen-fixing capacity of Anabaena sp., resulting in a diminished competitive advantage.

Seasonal succession exerts profound influences on ecosystem functioning. The expansion of cyanobacteria in autumn can exacerbate water column stratification and suppress zooplankton communities via the release of algal toxins, thereby diminishing energy transfer efficiency throughout the food web. Conversely, the dominance of diatoms during summer contributes to the stabilization of primary productivity, whereas the deposition of their siliceous shells facilitates nutrient recycling within sediments. Although transient blooms of chlorophytes and narrow-niche species may enhance community diversity to a limited extent, their pronounced population fluctuations can undermine community resilience against perturbations.

The relationship between environmental factors and dominant species of phytoplankton

The proliferation of phytoplankton represents a multifaceted process governed by intrinsic biological attributes and extrinsic environmental determinants, encompassing critical variables such as temperature, nitrogen (N) and phosphorus (P) concentrations, and conductivity. Marked disparities are evident across aquatic environments of varying depths. Results from the redundancy analysis (RDA) conducted in this study demonstrate that environmental factors exert significant seasonal influences on phytoplankton community structure within Lushan West Reservoir. Specifically, water temperature, transparency, and nutrient concentrations exert pivotal influences on phytoplankton distribution and abundance dynamics. Previous research has established that water temperature not only directly regulates phytoplankton physiological metabolic activity and rates, thereby substantially impacting reproductive processes, but also indirectly modulates algal growth by influencing physicochemical processes, such as the decomposition rates of nutrients within aquatic systems (Deng et al., 2023). Furthermore, an increase in water temperature can directly enhance the photosynthetic and respiratory activities of phytoplankton, thereby elevating their growth and reproduction rates (Wang et al., 2015). In particular, the abundance of cyanobacteria such as Y1 (Pseudanabaena), Y2 (Anabaena), Y5 (Microcystis), and Y6 (Planktolyngbya) exhibits a significant positive correlation with rising water temperatures. Conversely, the diatom species Aulacoseira granulata (Y11) demonstrates a negative correlation with water temperature and a positive correlation with water transparency, indicating a stronger adaptability of diatoms under lower temperature conditions. According to the study by Ndungu et al. (2013), in large lakes formed by tectonic movements, such as Yilong Lake, diatoms exhibit a competitive advantage over other phytoplankton in relatively low-temperature environments (12–16 °C). The study also found that dominant diatom species like Aulacoseira granulata tend to be gradually replaced by smaller diatoms as water temperature increases, while they dominate under high-transparency conditions. These findings are consistent with the observations in the water body of Lushan West Reservoir investigated in this study. Similarly, Wong and Zhou (2016) observed in their study of the Qingcaosha Reservoir that both water temperature and transparency exerted significant influences on phytoplankton community structure. Under lower temperature conditions, Bacillariophyta species exhibited greater dominance, whereas elevated water transparency was associated with increased abundance of Bacillariophyta species.

During summer and autumn, Cyanobacteria consistently maintain their dominant position, with total nitrogen and total phosphorus showing a positive correlation with cyanobacterial abundance. It is worth noting that although total phosphorus (TP) concentration showed no statistically significant seasonal variation based on integrated water-column samples (p > 0.05), cyanobacterial dominance exhibited pronounced seasonal patterns. This apparent inconsistency can be attributed to the vertical redistribution of phosphorus and changes in its bioavailability driven by seasonal thermal stratification, rather than changes in the total phosphorus inventory of the whole water column. As a deep stratified reservoir, Lushan West Reservoir forms a stable thermocline in summer, leading to anoxic conditions in the hypolimnion and promoting endogenous phosphorus release from surface sediments. The released phosphorus accumulates in the bottom water, but is restricted from fully mixing with the upper water column by thermal stratification, resulting in non-significant seasonal variation of TP in the integrated water samples. However, the upward diffusion of bioavailable dissolved phosphorus and its rapid internal cycling within the euphotic zone substantially increase the phosphorus supply available for phytoplankton growth in the surface layer. Meanwhile, elevated summer temperatures significantly enhance the phosphorus uptake efficiency and metabolic activity of Cyanobacteria, enabling them to gain competitive dominance under stable total phosphorus conditions. This synergistic mechanism of thermal stratification-driven internal loading and temperature-enhanced nutrient utilization efficiency explains why seasonal Cyanobacterial proliferation occurs in the context of non-significant TP seasonal variation.

A study conducted in Lake Taihu (Ji et al., 2024) demonstrated that Cyanobacteria sustain growth through the regeneration of ammonium nitrogen, a mechanism particularly critical during nitrogen-limited summer periods. This indicates that under eutrophic conditions, Cyanobacteria can utilize nitrogen and phosphorus resources more efficiently, thereby enhancing their competitive advantage. Moreover, the positive correlation between water temperature and cyanobacterial abundance further supports their dominance under elevated thermal conditions. In winter, as temperatures decline, metabolic activity across phytoplankton communities generally decreases, resulting in a significant reduction in overall phytoplankton biomass. The relative abundance of dominant species is also lower compared to other seasons. These patterns indicate that fluctuations in water temperature not only directly influence the growth rates and physiological activities of aquatic organisms but also indirectly shape phytoplankton abundance and community structure through complex ecological interactions. Such dynamics underscore the intricate interspecific relationships within aquatic ecosystems and their sensitivity to environmental change (Yue et al., 2024).

Ecological niche analysis of dominant species

This study analyzed the niche breadth of dominant phytoplankton species in Lushan West Reservoir, revealing that Bacillariophyta and Cyanophyta species play a predominant role in the local phytoplankton community, demonstrating strong ecological adaptability. In contrast, Chlorophyta, Chrysophyta, and Cryptophyta species occupy relatively subordinate positions with narrower ecological adaptation ranges. Significant interspecific variations were observed, and seasonal factors exerted considerable influence on the distribution and growth of phytoplankton. These findings align with the investigation by Li et al. (2021) on the phytoplankton community in Ningxia’s Taiyangshan National Wetland Park, which also indicated the dominance of Cyanophyta and Bacillariophyta in terms of niche breadth, while the dominant species in low-altitude reservoirs exhibited distinct seasonal succession patterns. Similarly, Chao et al. (2025) documented a Cyanophyta - Bacillariophyta - Chlorophyta dominated phytoplankton community structure in the lower reaches of the Yarlung Tsangpo River, consistent with the conclusions drawn in this study.

The Cyanobacteria phylum in this study maintained relatively high niche breadth throughout all seasons, yet exhibited pronounced seasonal differentiation. Specifically, both Anabaena and Microcystis demonstrated significant niche contraction during summer, with markedly reduced niche breadths compared to other seasons. This phenomenon may stem from elevated sensitivity to specific environmental factors or adaptive responses to intensified interspecific competitive pressures in summer. A pertinent study (Cao et al., 2024) indicates that Anabaena exhibits significant competitive advantage under nitrogen-limited conditions. However, in the present study area of Lushan West Reservoir, the total nitrogen concentration reached (1.29 ± 0.15) mg/L during summer, substantially exceeding levels in other seasons and surpassing the annual mean by over twofold. This seasonal nutrient surge induces a niche mismatch with the ecological conditions favoring Anabaena ’s competitive dominance, thereby reducing the summer niche breadth of both species. Diatoms exhibited wider ecological niches during spring under relatively low-temperature conditions. Study (Chen et al., 2024) reports that diatom relative abundance in lakes significantly exceeds that in other aquatic ecosystems, with cold environments promoting their competitive dominance. However, Synedra acus displayed markedly reduced niche width in winter over the annual cycle. This pattern may be attributed to the oligotrophic and low-temperature conditions prevailing in Lushan West Reservoir during winter, likely driving Synedra acus toward ecological specialization in resource utilization. This adaptive strategy involves enhanced silicon uptake efficiency to secure dominance along the silicon resource axis, while concurrently reducing physiological flexibility regarding nitrogen-to-phosphorus ratios, light availability, and water temperature (Gao et al., 2009). In contrast, Chlorophyta species generally exhibited lower dominance and narrower niche breadth; however, certain species demonstrated notable ecological adaptability during specific seasons. For example, the dominance of Quadrigula chodatii (Y8) peaked within its cohort in autumn (0.0793), while its niche breadth expanded to 2.2 during winter, indicating an ability to exploit additional resources by tolerating low-temperature and low-light conditions. Species within Chrysophyta and Cryptophyta consistently displayed relatively low dominance, reflecting limited growth potential under seasonally variable environmental conditions.

Impacts of human activities on Lushan west reservoir and recommendations for water quality conservation

Lushan West Reservoir, as a typical large-scale hilly deep-water reservoir in southern China, serves the dual purposes of drinking water source protection and scenic tourism, presenting considerable challenges for aquatic ecological conservation. Analysis based on pollution source census data (Investigation Report on Cyanobacterial Bloom Risk and Aquatic Ecological Security Assessment of Lushan West Reservoir) reveals substantial pollutant loads originating from industrial and domestic sources within the watershed: industrial areas discharge 572.13 tons of COD, 44.43 tons of TN, and 1.11 tons of TP annually; while urban domestic wastewater contributes 4,454.79 tons of COD, 936.15 tons of TN, and 51.33 tons of TP per year. The distribution of domestic pollution sources is closely correlated with population density and built-up land along the eastern and northern shorelines, where most townships and tourism facilities are concentrated; agricultural non-point sources correspond to cultivated land in the western tributary catchments. This spatial mapping ensures that the recommended measures are targeted to the actual source areas rather than being generic. These pollutants enter the lake through both point and non-point sources, posing potential risks to water quality safety. As a vital drinking water source, the ecological and environmental protection and comprehensive management concept for Lushan West Reservoir is established, which centers on safeguarding the aquatic ecosystem health and ensuring the security of drinking water sources. This approach emphasizes the conservation of the lake’s water bodies as its core objective, highlighting the watershed and regional characteristics of the Lushan West Reservoir area (Liu, 2013).

Recommendations are proposed to address this issue through the following four dimensions: First, urban domestic sewage control (targeting the dominant source): Based on the spatial distribution of population and built-up land in the watershed, we identify the key townships along the reservoir shoreline (e.g., Lixi Town) as primary source areas. Measures include: (i) upgrading existing wastewater treatment plants to meet Class 1A discharge standards or higher; (ii) expanding the sewerage collection network to reduce direct discharge from unsewered areas; and (iii) deploying decentralized treatment systems (e.g., constructed wetlands, septic tank–soil infiltration systems) for scattered rural settlements not connected to the central network. Second, agricultural and rural non-point source control: Targeting cropland and livestock areas identified through land-use analysis, measures include optimized fertilization management, construction of ecological ditches and buffer strips along tributary inflows, and resource utilization of livestock manure. Third, ecological restoration and self-purification enhancement: rehabilitation of riparian ecological buffer zones and replanting of submerged aquatic vegetation in littoral zones, targeting areas with high shoreline development intensity. Fourth, tourism-related pollution control: given that Lushan West Reservoir is also a scenic tourism area, measures include mandatory sewage collection from tour boats and centralized treatment of wastewater from scenic area facilities.

Limitations and future research perspectives

This study systematically revealed the seasonal succession pattern of phytoplankton communities and their environmental driving mechanisms at the whole-reservoir scale in Lushan West Reservoir. However, there are still some limitations in the research design. Given the focus on horizontal spatial coverage and long-term monthly dynamic monitoring across 20 sampling sites, we adopted an integrated water-column sampling strategy by mixing equal volumes of water from the upper, middle, and lower layers, rather than conducting separate stratified analysis for each water layer. As a typical deep-water hilly reservoir, Lushan West Lake develops obvious thermal stratification in summer, which may drive vertical differentiation of phytoplankton community structure and nutrient distribution. The integrated sampling design cannot fully reflect the fine-scale vertical stratification characteristics of phytoplankton, which is an unavoidable limitation of this study.

In future research, we will carry out fine-scale stratified sampling at typical deep-water sites of Lushan West Reservoir, combine high-frequency monitoring of thermal stratification and vertical nutrient profiles, and further explore the vertical distribution pattern of phytoplankton communities and its coupling mechanism with water stratification. This will help to deepen the understanding of phytoplankton ecological processes in deep-water reservoirs, and provide more refined scientific support for water ecological protection and water quality management of such water bodies.

Community composition and seasonal succession

A total of 116 phytoplankton species belonging to 8 phyla were identified in Lushan West Reservoir. Chlorophyta (43.97%) and Bacillariophyta (28.45%) dominated in terms of species richness, whereas Cyanophyta dominated in abundance throughout the year (relative abundance: 48.64–94.72% in winter and spring). The community exhibited a distinct seasonal succession pattern characterized by Cyanophyta – Bacillariophyta alternation: Cyanophyta prevailed in summer (May–July), while the proportion of Bacillariophyta increased in winter (November–January).

Key environmental driving thresholds

Cyanobacterial bloom threshold

When water temperature exceeded 25 °C (maximum 28.42 °C), TP reached ≥ 0.22 mg/L (exceeding the Class III standard of GB 3838–2002), and TN reached 1.29 mg/L, cyanobacterial biomass peaked at 0.42 mg/L and cell density reached a maximum of 9.98 × 10 6 cells/L.

Bacillariophyta dominance threshold

When water temperature was below 13 °C (minimum 12.68 °C) and transparency exceeded 320 cm, the relative abundance of Bacillariophyta reached 41.80%.

Redundancy analysis (RDA) indicated that water temperature, transparency, TN, and TP were the key factors driving community structural changes (water temperature: p < 0.01; transparency: p < 0.01).

Niche differentiation mechanism

Bacillariophyta maintained relatively broad niche widths (B i = 1.75–2.54) and gained dominance in low-temperature, high-transparency environments through silicon metabolism strategies. Cyanophyta exhibited an even wider range of niche widths (B i = 1.25–2.78); among them, Pseudanabaena sp. (B i = 2.78) sustained year-round dominance through broad niche adaptation and efficient resource utilization. In contrast, Chlorophyta occupied narrower niches (B i = 0.40–1.58), resulting in limited competitive capacity.

Management implications

The RDA identified water transparency (conditional R 2 = 0.182, p < 0.01), water temperature (p < 0.01), TN, and TP as the key drivers of phytoplankton community structure. Summer TP exceedance (0.22 mg/L, above the GB 3838–2002 Class III threshold) was significantly associated with cyanobacterial proliferation, while higher transparency favored Bacillariophyta dominance. Pollution source census data further identified urban domestic wastewater as the dominant external nutrient source (936.15 tons TN and 51.33 tons TP annually). Accordingly, management priorities should focus on: (i) reducing external nitrogen and phosphorus inputs, with primary emphasis on urban domestic sewage collection and treatment; and (ii) optimizing water transparency through watershed erosion control and riparian buffer restoration. These measures are expected to suppress excessive cyanobacterial proliferation and promote a more balanced Bacillariophyta-dominated community.

In summary, this study systematically elucidates the seasonal succession patterns of phytoplankton communities in Lushan West Reservoir and their interactive mechanisms with key environmental factors. The findings demonstrate that the synergistic variation of water temperature and nutrient concentration serves as the primary driver of community structural changes. Cyanobacteria maintain their competitive dominance throughout the year through broad niche adaptation, whereas diatoms occupy ecological niches via silicon metabolism strategies in low-temperature, high-transparency environments. The research findings provide a scientific basis for water quality management in deep-water reservoirs located in mountainous and hilly regions. This study provides a scientific basis for water quality management in deep-water reservoirs located in mountainous and hilly regions. It should be noted that this study is based on 12 months of monthly monitoring, which captures a complete seasonal cycle but does not encompass interannual climatic variability (e.g., extreme drought or flood years). Long-term, multi-year monitoring is recommended to validate the robustness of the observed succession patterns.

Future studies should further investigate the impacts of internal phosphorus cycling and seasonal climatic variations on phytoplankton functional groups, thereby offering theoretical support for ecological restoration of deep-water reservoirs.