Lianzhou Bay, one of the five largest bays in the Guangxi Zhuang Autonomous Region of China, spans 215 km2 ( Figure 1A ). The study area is characterized by shallow water depths (average depth of 5 m) and is strongly influenced by tidal dynamics. Tidal currents dominate water movement within the bay, with a primary pattern of reversing tidal flows (Sun et al., 2014). Under the influence of the East Asian monsoon, the study region is dominated by the southwest monsoon in spring and summer, while the northeast monsoon prevails in autumn and winter. The ecological environment of Lianzhou Bay is impacted by the economic activities of approximately 320,000 residents within the Nanliu River basin (Li et al., 2017). As the largest freshwater river discharging into the ocean in Guangxi Zhuang Autonomous Region, the Nanliu River exhibits distinct seasonal flow patterns, characterized by maximum discharge during the summer months (June-August) (Li et al., 2017), followed by a dry season with markedly reduced flow from October through May of the subsequent year. The upper reaches of the Nanliu River are primarily used for agriculture, while areas near the coast are used for aquaculture. Sediments from the Nanliu River are the primary source of material for Lianzhou Bay (Zhang et al., 2022).

Furthermore, the bay provides a diverse habitat for various aquatic organisms, encompassing biological resources such as mangroves (Liu et al., 2024). The bay also supports numerous aquaculture farms of varying scales, with the main cultivated species being bivalves such as oysters, clams, and scallops ( Figure 1B ).

The field survey was conducted in Lianzhou Bay during July (wet season) and November (dry season) of 2016, with 13 sampling stations established for phytoplankton photosynthetic pigment collection. Among these, Stations 3, 6, and 12 were located within aquaculture areas ( Figure 1B ). Surface seawater samples (3 L) were collected using a Niskin bottle for photosynthetic pigment analysis.

Seawater temperature, salinity and dissolved oxygen (DO) were measured in situ using a YSI EXO2 multi-parameter water quality sonde (YSI Inc., Ohio, USA). Transparency was measured using the Secchi disk method. A 0.5 L seawater sample was filtered through a pre-cleaned 0.45 μm cellulose acetate membrane and stored at 4°C. Nutrient analysis was performed immediately upon return to the laboratory. Concentrations of ammonia nitrogen (NH₄ ⁺-N), nitrate nitrogen (NO₃ ⁻-N), nitrite (NO₂ ⁻-N), phosphate (PO₄ ³⁻), and silicate (SiO₃ ²⁻) were determined using the colorimetric method specified in the “Specification for Oceanographic Survey Part 4: Investigation of Chemical Elements in Seawater” (General Administration of Quality Supervision, Inspection and Quarantine of the People’s Republic of China, 2007). Dissolved inorganic nitrogen (DIN) was calculated as the sum of NH₄ ⁺-N, NO₃ ⁻-N, and NO₂ ⁻-N. The precipitation data were obtained from the Asia-Pacific Data-Research Center (APDRC) with a spatial resolution of 1°×1°.

Photosynthetic pigment samples were stored in a cool, dark place after collection and were immediately filtered upon return to the laboratory. Water samples (2–3 L) were collected on 0.7 μm GF/F filters, with a filtration negative pressure of less than 0.6 atm (1 atm = 101325 Pa). The filters were folded and placed in aluminum foil bags and stored in liquid nitrogen. The filters were thawed between filter papers, and excess water was absorbed. 2 mL of N, N-dimethylformamide (DMF) was used as the extraction solvent. The samples were placed in the dark at -20°C for 2 hours to fully extract the pigments. After thorough mixing, the samples were centrifuged (5 min, 4 kg, -4°C), and the supernatant was collected. The supernatant was filtered through a 13 mm syringe filter (Millipore) with a GF/F filter, and the filtrate (2 mL) was collected in a brown chromatographic vial. The entire process was conducted under low light intensity and low-temperature conditions to minimize pigment degradation.

Mapping was performed using ODV 5.3.0, Surfer 16.0 and Excel 2016. Pearson correlation heatmaps were generated using the pheatmap package in R statistical software.

The distribution of Tchl-a concentration in the waters of Lianzhou Bay exhibited distinct seasonal and spatial variations ( Table 4 ; Figures 5A, E ). During the wet season, Tchl-a concentrations showed significant fluctuations, with a peak value of 13.34 μg/L observed only at Station 13 in the estuarine zone, while concentrations at most other stations remained below 3.00 μg/L. Specifically, the mean Tchl-a concentration in the estuarine zone was 3.92 μg/L, decreasing to 0.93 μg/L in the offshore area. Similarly, the mean concentration in non-fishing zones was 3.02 μg/L, whereas it declined to 0.95 μg/L in fishing zones. During the dry season, elevated Tchl-a concentrations were predominantly concentrated in the estuarine zone and the southeastern inlet, with concentrations in the central and western parts of the study area remaining below 1.50 μg/L. Consistent with the wet season, Tchl-a concentrations in the estuarine zone remained higher than those in the offshore area, while fishing zones exhibited significantly lower concentrations compared to non-fishing zones ( Table 4 ).

According to HPLC analysis, 14 pigments were detected during the high-water period, but 19-butfu and DV-chl a were not detected, and perid was not observed in the estuary. During the low-water period, 19 pigments were detected, but DV-chl a was not detected, and perid was not observed in the estuary.

Chl-b was the most abundant pigment during the high-water period, with a total concentration ranging from 0.13 μg/L to 2.34 μg/L. The spatial distributions of chl-b, fucox, zeax, allox, and perid were similar to that of Tchl-a, reaching a peak at station 13 in the estuary ( Figure 5 ). High concentrations of pras appeared at station 9, with the second highest value detected in the central part of the surveyed sea area. Unlike all characteristic pigments, the concentration distribution of 19-hexfu showed a trend of increasing from the estuary to the sea. Compared with the high-water period, the spatial distribution of each characteristic pigment during the low-water period was significantly different ( Figure 5 ). Chl-b was also the most abundant pigment, with a concentration range of 0.19 μg/L to 1.26 μg/L, mainly concentrated in the estuary. The spatial distribution of fucox was similar to that of Tchl-a, with higher concentrations in the estuary and the southeastern sea inlet. Similar to the distribution of chl-b, the concentration distribution of pras showed a decreasing trend towards the sea. High concentrations of allox and perid were concentrated in the northern coastal area and the southwestern part of the surveyed sea area. The concentration distribution of zeax showed a decreasing trend from northwest to southeast, while the concentration distribution of 19-hexfu showed a decreasing trend from the estuary to the sea.

CHEMTAX analysis revealed fluctuations in phytoplankton community composition between the two seasons ( Figure 6 ). During the wet season, diatoms, cyanobacteria, prasinophytes, chlorophytes, and cryptophytes contributed over 99.0% of the Tchl-a concentration. The average contributions of diatoms, cyanobacteria, prasinophytes, chlorophytes, and cryptophytes were 35.0%, 21.0%, 13.0%, 19.0%, and 11.0%, respectively. The contribution of three phytoplankton groups, including chlorophytes, cryptophytes, and dinoflagellates, to Tchl-a decreased from the estuarine to the offshore region. Conversely, the contributions of diatoms, cyanobacteria, and chrysophytes to Tchl-a showed an increasing trend towards the sea. Diatoms and chlorophytes exhibited the greatest variability, with diatoms increasing from 20.0% in the estuarine region to 52.0%, and chlorophytes decreasing from 31.0% in the estuarine region to 4.0% in the offshore region. The contribution of prasinophytes to Tchl-a did not change between the estuarine and offshore regions ( Figure 6A ). During the dry season, diatoms, prasinophytes, cyanobacteria, and cryptophytes contributed over 98% of the Tchl-a concentration. The average contributions of diatoms, prasinophytes, cyanobacteria, and cryptophytes were 62.0%, 18.0%, 12.0%, and 7.0%, respectively. The contribution of prasinophytes and chlorophytes to Tchl-a decreased from the estuarine to the offshore region, while the contribution of diatoms to Tchl-a increased from the estuarine to the offshore region. The contributions of cyanobacteria and cryptophytes to Tchl-a did not differ between the estuarine and offshore regions ( Figure 6B ).

It is evident that diatoms and chlorophytes exhibited the greatest variability between the two periods. From the wet season to the dry season, diatoms increased from 31.95% to 62.0% of the Tchl-a concentration, while chlorophytes decreased from 14.51% to 0.89%.

Correlation analysis was performed between water salinity and transparency, DO, and various nutrients during the survey period ( Figure 7 ). The results showed that during the wet season, salinity and transparency were significantly positively correlated, and significantly negatively correlated with PO₄ ³⁻, SiO₃ ²⁻, DIN, NO₂ ⁻-N, and NO₃ ⁻-N. During the dry season, salinity was also significantly positively correlated with transparency, and negatively correlated with SiO₃ ²⁻, DIN, N/P, NH₄ ⁺-N, NO₃ ⁻-N, and NO₂ ⁻-N.

Correlation analysis was performed between Tchl-a, major characteristic pigments, and environmental factors such as salinity ( Figure 7 ). The results revealed that during the wet season, Tchl-a, chl-b, and zeax exhibited significant correlations with NH₄ ⁺-N concentration. Pras showed positive correlations with both NH₄ ⁺-N concentration and seawater temperature. Allox concentration was closely associated with the N/P ratio, while perid demonstrated significant relationships with both the N/P ratio and NH₄ ⁺-N concentration. Notably, 19-hexfu displayed distinct coastal population characteristics, with its concentration showing significant positive correlations with salinity and transparency, but negative correlations with nutrient concentrations ( Figure 7A ). During the dry season, negative correlations were observed between Tchl-a, fucox, allox, and seawater temperature. The chl-b concentration exhibited typical estuarine population characteristics, being associated with low salinity, low transparency, and high nutrient conditions. In contrast, 19-hexfu displayed clear coastal population features, correlating with high salinity, high transparency, and low nutrient concentrations. This indicates that chl-b and 19-hexfu occupy completely opposite ecological niches. The ecological niche of pras was similar to that of chl-b, showing negative correlations with salinity and transparency but positive correlations with PO₄ ³⁻ and NH₄ ⁺-N concentrations ( Figure 7B ).

During the rainy season, significant rainfall transports accumulated sediments from the dry season into the Nanliu River (Tao et al., 2020), leading to a direct decrease in water transparency ( Table 3 ; Figure 7A ). Throughout our study, we observed a gradient in water transparency, which increased from the northern nearshore region towards the open sea. Analysis using SPSS revealed that the primary factor contributing to reduced transparency was the input of freshwater runoff, regardless of whether it was the wet or dry season ( Figure 7 ). As a result, the estuarine region exhibited the lowest transparency values across the entire study area. In contrast, the southeastern part of the bay showed the highest transparency, likely due to the dynamics of water movement within the bay. The water body of Lianzhou Bay is predominantly shaped by the interaction between tidal currents and coastal currents, with the latter introducing “new” water into the southern part of the bay, which is subsequently brought into the bay during the next high tide. This interplay between tidal and coastal currents facilitates a gradual northwestward movement of water within the bay, which is then replenished by “new” water from the southeast (Sun et al., 2014).

Lianzhou Bay receives a substantial influx of organic matter from the Nanliu River, the largest river in Guangxi (Li et al., 2017; Zhang et al., 2022). During the wet season, the DO concentration at most stations within the bay fell below 6 mg/L, which is lower than the levels recorded in other estuarine waters (Córdoba-Mena et al., 2020). The quality of water is influenced by organic matter from various sources (Rashed-Un-Nabi et al., 2011), including domestic, agricultural, and industrial effluents, which are the primary pollutants of the Nanliu River (Li et al., 2017; Chen et al., 2022; Wei et al., 2024). The lowest DO values were noted along the coast of Beihai City, where urban sewage discharge has a significant impact. Additionally, the detritus food chain within the mangrove ecosystem contributes to the presence of dissolved organic matter in the estuary of the Nanliu River (Holmer and Olsen, 2022).

Throughout the investigation, the concentrations of DIN, PO₄ ³⁻, and SiO₃ ²⁻ exhibited a clear decreasing trend as one progressed from the estuary towards the open sea ( Figure 3 ). During the wet season, the significant rise in river runoff markedly increased the nutrient concentrations within the surveyed marine area, with a notable accumulation of these nutrients occurring primarily near the estuary. The analysis conducted using SPSS revealed a significant correlation between PO₄ ³⁻, SiO₃ ²⁻, and DIN with salinity, highlighting the fact that freshwater runoff serves as the main source of nutrients during this period. In contrast, during the dry season, the reduced river runoff led to a corresponding decline in nutrient concentrations within the surveyed marine area. The SPSS analysis further indicated a significant positive correlation between SiO₃ ²⁻ and DIN with salinity during this phase, thereby confirming that the primary sources of SiO₃ ²⁻ and DIN remain linked to freshwater runoff ( Figure 7B ). Unlike the wet season, the elevated concentrations of DIN and SiO₃ ²⁻ observed during the dry season were predominantly found in the northwestern section of the surveyed area, likely due to intensified coastal currents at this time, which facilitated the movement of water towards the northwest, thereby transporting nutrients into that specific region of the surveyed marine area (Sun et al., 2014). Conversely, the concentration of PO₄ ³⁻ was primarily concentrated in the northeastern part of the surveyed area, with heightened levels noted near the coastline. The SPSS analysis indicated that the relationship between salinity and PO₄ ³⁻ was not statistically significant ( Figure 7B ), suggesting that the sources and exchange processes governing PO₄ ³⁻ are inherently complex. Previous studies have indicated that, in addition to freshwater runoff, phosphorus in the Lianzhou Bay area also originates from urban wastewater and aquaculture effluents (Guo et al., 2024). Furthermore, a critical process in the exchange of phosphorus within coastal regions involves the adsorption and desorption of particulate matter. On one hand, a reduction in DO levels promotes the release of PO₄ ³⁻ from phosphorus-rich sediments (Lønborg et al., 2021), which clarifies the observed correlation between low DO distribution and high PO₄ ³⁻ distribution ( Figures 2H , 3E ). On the other hand, an increase in nearshore salinity may also facilitate the desorption of PO₄ ³⁻ from sediments, consequently elevating the concentration of PO₄ ³⁻ within the water column (Bharathi et al., 2022).

During the investigation period, the distribution of Tchl-a concentrations in Lianzhou Bay showed a significant negative correlation with temperature exclusively during the dry season ( Figure 7 ). In contrast, no statistically significant relationships were detected between Tchl-a and previously identified key environmental drivers, including salinity, nutrient levels, and water transparency. Notably, the observed spatial patterns of salinity, nutrients, and transparency failed to adequately account for the abrupt decreases in Tchl-a concentrations occurring in specific sub-regions. Furthermore, while previous studies (Tan et al., 2025) proposed that the synergistic effects of strong northeast monsoon winds and decreased temperatures during autumn (dry season) would reduce Tchl-a concentrations in Lianzhou Bay, our empirical results demonstrate the opposite trend ( Figure 7B ). These findings suggest that in estuarine ecosystems, Tchl-a distribution patterns are unlikely to be governed by any single dominant environmental factor. Consequently, we postulate that alternative mechanisms, particularly zooplankton grazing pressure and hydrodynamic forcing, may constitute more plausible determinants of Tchl-a spatial variability in Lianzhou Bay.

Lianzhou Bay serves as a major aquaculture area, with bivalve species (e.g., oysters, clams, and scallops) being the primary cultivated organisms. Bivalves predominantly feed by filtering plankton and organic detritus from seawater (Riisgard et al., 2003; Galimany et al., 2021). These filter-feeding bivalves exhibit remarkable water filtration capacity, while their metabolic activities and fecal excretion can influence nutrient concentrations in the water column, subsequently promoting phytoplankton growth (Bacher et al., 1995). Consequently, phytoplankton dynamics in the water are simultaneously regulated by both top-down control through bivalve grazing and bottom-up control via nutrient availability. However, in high-density bivalve aquaculture areas, the top-down control typically outweighs the bottom-up effects. Studies have demonstrated that intensive bivalve cultivation significantly reduces phytoplankton biomass in farming zones (Jiang et al., 2016), leading to rapid declines in Tchl-a concentrations - a phenomenon also observed in other coastal bivalve farming regions in China (Wheat and Ruesink, 2013; Petersen et al., 2019; Hulot et al., 2020). Our investigation revealed consistently lower Tchl-a concentrations in aquaculture areas compared to non-farming zones ( Table 4 ). Since bivalves primarily feed by filtering plankton and organic detritus (Galimany et al., 2021), Tchl-a concentrations at sampling stations, including the outer edges of aquaculture areas, were substantially lower than the survey-wide average. Furthermore, during our dry-season survey, areas with elevated temperatures largely coincided with aquaculture zones. We therefore hypothesize that grazing pressure from bivalves may explain the unexpected decrease in Tchl-a concentrations in these warmer areas. Additionally, intensive phytoplankton predation by zooplankton (e.g., shrimp, prawns, bivalves, and fish larvae) inhabiting the mangrove forests of the Nanliu River estuary constitutes another contributing factor (Farid and Baderan, 2024). This explains why phytoplankton abundance remains low even in nutrient-rich estuarine areas. In summary, the micro-food web within Lianzhou Bay’s mangrove ecosystem and bivalve aquaculture activities effectively reduce the probability of algal blooms by directly decreasing Tchl-a concentrations through phytoplankton consumption. Numerous studies have confirmed that both mangrove ecosystems and bivalve aquaculture can serve as effective measures for improving seawater quality in coastal bays (Zhao et al., 2019; Cubillo et al., 2023).

Seasonal variations in water movement also influenced the temporal and spatial distribution of Tchl-a concentrations in Lianzhou Bay. Previous studies demonstrated a strong correlation between river discharge and Tchl-a in estuaries (Lucas et al., 1999). The inflow of river water drove convective transport towards the sea, potentially at a rate that exceeded phytoplankton growth, thereby inhibiting biomass accumulation during periods of high flow. Consequently, phytoplankton biomass was often negatively correlated with river discharge (Burford et al., 2012). This may also elucidate why Tchl-a concentrations in the estuarine area were lower during periods of increased freshwater discharge compared to those during low flow conditions ( Table 4 ).

In estuarine regions, water transparency and light availability were frequently key factors influencing Tchl-a concentrations (Bharathi et al., 2022). Many estuaries experienced significant mineral sediment deposition from terrestrial runoff, and these sediments remained suspended due to wind and tidal action (May et al., 2003). The turbidity associated with sediments restricted the photic zone to a narrow layer, limiting photosynthesis and hindering phytoplankton from fully utilizing available nutrients. This situation was commonly observed in numerous estuarine areas, which often possessed abundant nutrients, high SPM, and extremely low phytoplankton productivity (Kocum et al., 2002; Mo et al., 2024). During wet seasons, increased runoff from the Nanliu River introduced substantial nutrients into Lianzhou Bay, accompanied by significant sediment loads. Therefore, despite nutrient concentrations being 37.42%-43.26% higher during wet seasons compared to dry seasons, the low transparency resulted in Tchl-a concentrations at most sampling sites being lower than those observed during dry periods. Following a decrease in rainfall, the average transparency of the bay’s water rose to 1.06, with the highest transparency recorded in the southeastern region, where coastal currents frequently exchanged. Phytoplankton flourished and reproduced in the well-lit nearshore areas, resulting in Tchl-a concentrations surpassing those during wet seasons. This suggested that light availability was more critical than nutrient levels in estuarine regions (Bharathi and Sarma, 2019; Mo et al., 2024).

It was noteworthy that during wet seasons, Tchl-a concentrations were concentrated in the northeastern part of the surveyed area, likely due to multiple influencing factors. This region was situated farther from the aquaculture zones and possessed a relatively stable water environment, allowing phytoplankton to remain in nutrient-rich waters for extended periods, thus promoting rapid growth and reproduction. Studies indicated that phytoplankton preferentially absorbed NH₄ ⁺-N from the water, only resorting to nitrate nitrogen when NH₄ ⁺-N concentrations were insufficient (Glibert et al., 2016). Our survey data revealed that at this site, the concentration of DIN reached 1.547 mg/L, but due to rapid consumption by phytoplankton, NH₄ ⁺-N accounted for only 10.86% of the DIN concentration in this area.

Both freshwater and marine organisms experienced significant osmotic stress due to salinity gradients, with salinity posing a lethal barrier for phytoplankton. Different categories of phytoplankton had specific salinity ranges from estuarine to nearshore environments (Kies, 1997). Furthermore, variations in transparency, nutrient concentration, and grazing pressure led to significant differences in phytoplankton growth rates (Lucas et al., 1999). During periods of high water flow, chlorophytes (31.0%) and diatoms (20.0%) dominated in low salinity estuarine areas, while diatoms (52.0%) were more abundant in nearshore regions with medium to high salinity. In dry periods, diatoms (58.0% and 67.0% in estuarine and nearshore areas, respectively) emerged as the only prominent group. This phenomenon, where diatoms dominated during dry periods and were replaced by chlorophytes and other taxa during wet periods, was observed in many estuaries (Naik et al., 2009; Bharathi et al., 2018).

During periods of increased discharge from the Nanliu River, we observed substantial proliferation of non-diatom phytoplankton in the estuarine zone, along with a seaward increase in diatom dominance ( Figure 6A ). While diatoms typically dominate in nutrient-rich waters (Sarthou et al., 2005), their contribution to Tchl-a was lower in the estuary than in coastal waters despite elevated SiO₃ ²⁻ concentrations in the estuarine zone. SPSS analysis revealed no significant correlations between the diatom biomarker pigment fucox and salinity, transparency, or nutrient concentrations, suggesting more complex factors governing diatom distribution ( Figure 7A ). This may indicate their broad tolerance ranges for salinity and light availability to sustain growth. Chlorophytes emerged as the dominant group in the estuary during this period, frequently co-dominating with diatoms in low-salinity estuarine waters (Mo et al., 2024). Due to their limited osmoregulatory capacity, most chlorophytes were restricted to the estuarine zone ( Figure 6 ). SPSS results showed that the distribution pattern of chl-b (associated with chlorophytes) closely mirrored that of Tchl-a, with NH₄ ⁺-N identified as the primary limiting factor. Cyanobacteria, possessing wide ecological niches for temperature, salinity, and nutrients, represented the third dominant group. Their biomarker pigment zeax showed positive correlations with both temperature and NH₄ ⁺-N concentrations ( Figure 7A ). Both cyanobacteria and cryptophytes also dominated during high-flow periods, demonstrating adaptability to low N/P environments through nitrogen storage and utilization capabilities (Rocha et al., 2002). Cryptophytes contributed significantly (16.0%) in the high N/P estuarine zone, likely reflecting their ecological preference for low-salinity, high-nitrogen conditions (Mendes et al., 2013; Zhong et al., 2020). Some researchers suggest that cryptophytes, with their rapid growth rates, tend to proliferate in areas receiving frequent nutrient inputs (e.g., estuaries) (Paerl et al., 2010). This may reflect their competitive advantage in unstable waters, with their dominance serving as an indicator of ecosystem instability (Casotti et al., 2000).

Diatoms constituted the dominant phytoplankton group during the dry season, a phenomenon potentially attributable to favorable light conditions during this period (Pednekar et al., 2011). Notably, similar to Tchl-a, the concentration of fucox-the primary pigment of diatoms-showed significant reductions within and around aquaculture areas. In the absence of morphological identification data, this study could not determine whether the major contributors to fucox were temperature-sensitive species or those with size ranges optimal for bivalve grazing. Previous studies in the Beibu Gulf have identified diatoms (particularly Bacteriastrum sp., Chaetoceros sp., and Thalassionema sp. through microscopic observations) as the predominant phytoplankton group during dry seasons (Xu et al., 2024). The observed decrease in fucox concentrations in aquaculture zones may reflect selective grazing pressure on palatable diatom species (Bharathi and Sarma, 2019). Chlorophytes and cyanobacteria occupied similar ecological niches, as evidenced by the widespread distribution of their biomarker pigments (chl-b and zeax) in low-salinity, low-transparency, and nutrient-rich riverine waters. Their contributions were markedly higher in estuarine areas than in coastal waters. Phytoplankton groups associated with zeax and perid pigments (e.g., cyanobacteria and dinoflagellates) showed no distinct correlations with any environmental parameters, indicating their successful colonization across diverse nutrient regimes in estuarine-coastal gradients. These phytoplankton communities with broad niche widths exhibited more complex distribution patterns (Zhong et al., 2020). For instance, elevated PO₄³⁻ concentrations in coastal waters favored cyanobacterial biomass accumulation (Mo et al., 2024). Furthermore, Synechococcus cyanobacteria possess genetically mediated niche plasticity, enabling proliferation across river plumes, eutrophic coastal areas, and warm offshore waters (Moisan et al., 2010).