Dissolved Inorganic Nutrient Biogeochemistry in an Urbanized Coastal Region: A Study of Dapeng Cove, Shenzhen

Abstract

Dissolved inorganic nutrients are pivotal in maintaining the material and energy balance of marine ecosystems, impacting the survival and dynamic succession of marine organisms. To gain a deeper understanding of the source and sink characteristics of dissolved inorganic nutrients in bays affected by human activities and to elucidate the processes involving filter-feeding shellfish in relation to these nutrients, this study investigated the source and sink dynamics of dissolved inorganic nutrients in the Dapeng Cove sea area of Shenzhen. Over the past decade, a significant change in the N/P ratio within the survey area has been observed, suggesting a shift in nutrient limitation from nitrogen to phosphorus or phosphorus–silicon limitation. This induced change in the N/P ratio, along with Si/N and Si/P ratios, may facilitate the growth of cyanobacteria and, subsequently, alter the proportions of diatoms, dinoflagellates, and cyanobacteria. Seasonal fluctuations in human disturbance intensity and precipitation determine the seasonal and spatial distribution of nutrients in the bay, thereby influencing the bay ecosystem metabolism. The Land–Ocean Interactions in the Coastal Zone (LOICZ) model analysis revealed that the bay represents a major source of inorganic nitrogen and a source of phosphate in spring, summer, and autumn, while acting as a sink for phosphate in winter. Furthermore, rivers and groundwater represent the primary sources of phosphate and inorganic nitrogen in the bay. The bay exhibits an annual net ecosystem metabolic rate of 7.06 mmol C/m²/d, with denitrification dominating the nitrogen cycle at 12.65 mmol C/m²/d. Overall, the Dapeng Cove ecosystem displays net production exceeding respiration, classifying it as an autotrophic system. Additionally, the nitrogen cycle in the sea area is predominantly driven by denitrification. The analysis also revealed that the impact of oyster proliferation on the physical and chemical factors in the surveyed area is relatively weaker than that of surface runoff and groundwater inputs.

1. Introduction

Inshore marine ecosystems are commonly identified as the areas that experience the most significant impacts from human activities, including aquaculture, pollutant emissions, overfishing, and the influence of climate change [1,2]. The rapid urbanization and industrialization processes have significantly escalated the utilization and release of carbon (C), nitrogen (N), and phosphorus (P) elements [3]. The excessive discharge of nutrients from terrestrial sources into offshore waters surpasses the ecological capacity of offshore ecosystems [2], thereby becoming a principal contributor to ecological risks in offshore marine environments. These risks include eutrophication, red tides, hypoxia in benthic habitats, declines in biological resources, and reductions in habitat diversity [3,4,5]. Consequently, the impacts of human activities on offshore habitats have become research hotspots in recent decades. Worldwide, countries with coastal regions have also enacted environmental protection legislation to restrict human activities and mitigate the deterioration of offshore ecological conditions [6,7,8].

Despite increasing awareness of the importance of safeguarding water environments and significant efforts directed toward enhancing the sustainability of urban rivers, the rapid urbanization process inevitably leads to the degradation of surface runoff and groundwater quality due to heightened sewage discharges and coastal construction projects [9,10]. Furthermore, the surge in human activities on land and at sea may result in a marked increase in nitrogen and phosphorus inputs into bays [11]. While the implementation of policies banning phosphorus use in the late 1990s and improvements in factory wastewater treatment systems have led to a gradual reduction in phosphorus transported from rivers to the ocean [12], other factors such as groundwater recharge, coastal discharges, atmospheric deposition, ocean circulation, and particle deposition in sediments also exert influence on the sources and inputs of nutrients [13]. These patterns of sources and sinks determine the spatial and temporal distribution and trends of nutrients [14]. Shenzhen Dapeng Cove waters represent highly urbanized semi-closed bays [15] that have been affected by issues including eutrophication, red tides, and environmental degradation problems, affecting fishery resources in recent years [16]. Water nutrients exert a direct influence on the health of the marine ecological environment [17,18]. However, the biogeochemical cycle of inorganic nutrients in this area has not been comprehensively investigated, constraining precise nutrient management and ecosystem health assessment in the bay.

This paper employs the eutrophication potential, trophic state, and Land–Ocean Interactions in the Coastal Zone (LOICZ, https://loicz.org/ (accessed on 1 September 2023)) model to examine the water and nutrient budget in coastal water bodies. Indeed, investigating the stoichiometric ratios of elements in seawater is essential to comprehend the involvement of primary producers in the biogeochemical cycle. The assessment criteria for potential eutrophication expose the nutrient limitations within the studied area. Furthermore, the LOICZ model primarily assesses material (physical, chemical, and biological) fluxes from river basins to marine environments, enabling the identification and characterization of key processes controlling these fluxes to develop a model that can predict changes in water nutrient fluxes in response to future environmental alterations [19]. The model has been employed to describe the seasonal variations in total alkalinity (Talk) and dissolved inorganic carbon (DIC) from the Hugley Estuary to the Bay of Bengal, quantifying carbon flux variations from the estuary to the ocean and assessing the estuary impact on inorganic and organic loads in the northern section of the same bay [20]. Yan et al. (2021) [1] utilized the LOICZ model to quantitatively establish that dissolved inorganic nitrogen (DIN) and active phosphate (soluble reactive phosphorus (SRP)) primarily originate from Shenzhen Bay. These excessive nutrient loads represent potential sources of eutrophication in Shenzhen Bay. Biogeochemical analyses of dissolved inorganic nutrients in the coastal culture area of the North Yellow Sea, based on the LOICZ model, have indicated that human activities play a significant role in the biogeochemistry of DIN and dissolved inorganic phosphorus (DIP) in the North Yellow Sea. Moreover, large-scale scallop cultivation has been found to transform substantial amounts of dissolved inorganic nutrients absorbed by primary producers into seafood and other organic matter [21].

Previous studies have primarily examined the bays of expansive regions, neglecting investigations into smaller bays. However, the scarcity of research on these smaller urban bays is concerning, as they are more susceptible to human disturbances. Consequently, the repercussions of such disturbances extend beyond the immediate bay environment and impact the broader Gulf ecosystem. This study harnessed data from the 2020 annual marine environment survey in the Dapeng Cove sea area to better understand the role of nutrient fluxes in ecosystem metabolism in this area. We examined the income and expenditure of inorganic nutrients in the survey area through the LOICZ budget model and eutrophication assessment tool. Additionally, we explored the distribution, seasonal variations, and influencing factors of dissolved inorganic nutrients in this region and assessed the net ecosystem metabolism (NEM) and its sensitivity to climate and anthropogenic pressures. This study provides valuable insights for the restoration of coastal ecosystems and the promotion of sustainable fishery production.

2. Materials and Methods

2.1. Study Area

The study was conducted in the sea area of Dapeng Cove in the eastern part of Shenzhen. It is now understood that this semi-closed bay, depicted in Figure 1, experiences the influence of the subtropical monsoon. It covers an approximate area of 10 km² and is subject to the northeast monsoon from October to April of the following year, followed by the dominance of the southwest monsoon from May to September. The annual average tidal range is 0.49 m. The water velocity in the sea area is relatively low, measuring 26 cm/s, and it is predominantly influenced by two types of seasonal circulation: cyclonic circulation in the summer and anticyclonic circulation in the autumn, winter, and spring [22]. The bay maintains an annual average sea surface temperature of 28.0 °C and a variable water depth of 1 to 9 m, with an average depth of 5 m. While the bay was once rich in mangroves, oyster reefs, coral reefs, and other habitats, urbanization has transformed the surrounding areas into coastal resorts. Notably, the Daya Bay Nuclear Power Station is located northeast of the bay, with its two units in operation since 1994 and 2002 [23]. The bay is primarily affected by seasonal runoff from the Wangmu River, Longqi River, and Nan Chong River, with a 2 km² oyster breeding area located in the southern part of the bay. Tides in this area flow from the north side of the bay and then follow a counterclockwise path to the south side of the bay. Consequently, the nutrients transported by these three rivers traverse the entirety of Dapeng Cove bay with the influence of the tide, potentially impacting nutrient flux in the adjacent sea area.

2.2. Sample Collection and Analysis

This study was conducted from November 2020 to August 2021, spanning four voyages in spring (May), summer (August), autumn (November), and winter (February). As depicted in Figure 1, the survey stations cover the entire Dapeng Cove area, totaling 18 sampling sites, each separated by approximately 600 m. Niskin samplers were used to collect water samples at each station, with surface water samples collected due to the shallow nature of the bay (average 5 m). Following collection, each water sample (about 1000 mL) was filtered using a 0.45 μm pore-sized Whatman GF/F filter, pre-cleaned, and pre-combusted at 500 °C for 5 h. The resulting filtrate was collected in pre-washed 500 mL polyethylene bottles and transported to the laboratory for nutrient analysis.

A portable chlorophyll a (Chla) fluorescence tester (Aquafluor, Turner Designs, USA) and a portable CTD (CastAway, YSI, OH, USA) were used for the measurement of sea water surface temperature (SST), sea water bottom temperature (BST), salinity (S), and depth. Sea water turbidity (NTU) was analyzed with a portable turbidimeter (WZB-175, Leici, Shanghai, China), and pH and dissolved oxygen (DO) were determined using a portable water quality analyzer (6600 EDSJ YSI, OH, USA). Nutrient analysis included the determination of ammonium nitrogen (NH₄⁺), nitrate nitrogen (NO₃⁻), nitrite nitrogen (NO₂⁻), silicate (SiO₃²⁻), chemical oxygen demand (COD), and soluble reactive phosphate (SRP), with detection limits of 0.0007 mg/L, 0.0007 mg/L, 0.0003 mg/L, 0.1 μmol/L, 0.15 mg/L, and 0.02 μmol/L, respectively. A spectrophotometer was used following the methods outlined in Part 4 of the Marine Monitoring Code: Seawater Analysis (GB 17378.4-2007) [24] and Ocean Survey Code Part 4: Investigation of Chemical Elements in Seawater (GBT 12763.4-2007) [25]. Each sample was analyzed thrice, and the relative standard deviation (RSD) for repeated samples was less than 5%.

Surface sediment samples (0–10 cm) were collected from each station in triplicates using a grab sediment sampler (Van Veen, OSIL, Hants, UK). The sediment samples were screened with a 2 mm net to remove stones and plant roots and sealed in aseptic plastic bags [26]. Total organic carbon (TOC) in the sediment was determined using the potassium dichromate oxidation–reduction volumetric method, total nitrogen (TN) was determined via Kjeldahl titration, total phosphorus (TP) was determined using spectrophotometry, and sulfide was analyzed by methylene blue spectrophotometry. Heavy metals (Cu, Pb, Zn, As, Hg, and Cd) in the sediments were evaluated using atomic absorption spectrophotometry (Z-2010, Hitachi, Tokyo, Japan), and As and Hg were determined using atomic fluorescence spectrophotometry (AFS-8520, Beijing Haiguang, Beijing, China). The collection, preservation, transportation, and testing of sediment samples followed the guidelines set in the Marine Monitoring Code Part 5: Sediment Analysis (GB 17378.5-2007) [27].

2.3. Trophic Status Assessment

2.3.1. Potential Eutrophication Index

Current evidence suggests that, in seawater, phytoplankton absorb nutrients according to the Redfield ratio, and any excess nitrogen or phosphorus that remains unabsorbed and unutilized can be considered as potential eutrophication [21]. To highlight the nutrient limitation characteristics, this study employed DIN and SRP as evaluation parameters and utilized a eutrophication model to assess the trophic status of the study area (

Table 1. The eutrophication evaluation standards.

Grade	Nutrient Level	DIN (mg/L)	SRP (mg/L)	N/P
I	Oligotrophic level	<0.20	<0.030	8–30
Ⅱ	Moderate-level nutrient	0.20–0.30	0.030–0.045	8–30
Ⅲ	Eutrophication	>0.30	>0.045	8–30
IVp	Phosphate-limiting moderate-level nutrient	0.20–0.30	/	>30
Vp	Phosphate moderate limiting potential eutrophication	>0.30	/	30–60
VIp	Phosphate-limiting potential eutrophication	>0.30	/	>60
IVN	Nitrogen-limiting moderate-level nutrient	/	0.030–0.045	<8
VN	Nitrogen moderate limiting potential eutrophication	/	>0.045	4–8
VIN	Nitrogen-limiting potential eutrophication	/	>0.045	<4

).

2.3.2. Life Cycle Assessment

This potential eutrophication index can be compared with the same record through a life cycle assessment (LCA). The life cycle impact assessment (LCIA) method identifies the eutrophication impact of contaminant emissions using the Redfield ratio [28]. Taking into account N and P losses from the system, we calculated the aquatic eutrophication potential (AEP). To characterize different emissions of pollutants or nutrients, we use the following basic approach [29]:

$$AEP=EPi\times {\sum }_{i}Mi$$

(1)

where AEP is the aquatic eutrophication potential, i is the impact category aquatic eutrophication (mg i), and EPi is the characterization factor of the emission i based on the Redfield ratio.

2.3.3. Trophic Index

The trophic index (TRIX) is a comprehensive metric that integrates commonly used indicators for eutrophication assessment [30]. The TRIX method is widely employed to evaluate the trophic status of water bodies, encompassing a range of nutritional conditions from nutrient scarcity to eutrophication. It simplifies comparing nutritional states in different temporal and spatial contexts in coastal waters. The index is calculated using the following formula:

$$\mathrm{T}\mathrm{R}\mathrm{I}\mathrm{X}=[{\mathrm{l}\mathrm{o}\mathrm{g}}_{10}\left(\mathrm{D}\mathrm{I}\mathrm{N}\times \mathrm{D}\mathrm{I}\mathrm{P}\times \mathrm{C}\mathrm{h}\mathrm{l}\mathrm{a}\times \mathrm{D}\%{\mathrm{O}}_2\right)-(-1.5\left)\right]/1.2$$

(2)

where DIN, DIP, and Chla represent the concentrations of dissolved inorganic nitrogen, dissolved inorganic phosphorus, and chlorophyll a, respectively [31]. The values 1.5 and 1.2 represent the proportional coefficients [32].

2.3.4. Calculation of Trophic Income and Expenditure

The study employed the LOICZ model to investigate nutrient inflow and outflow in the sea area. Prior to applying the model, it was assumed that the research system was in a stable state and the latter was considered a fully mixed system. The model incorporated the following inputs: land runoff, groundwater, atmospheric deposition, sediment–water exchange, and oyster–water nutrient exchange. The Redfield ratio (C:N:P = 106:16:1) was used to estimate NEM as well as nitrogen fixation and denitrification in the LOICZ model [1]. The calculation formula is as follows [33]:

$$\mathsf{\Delta }\mathrm{DIX}=-(\sum \mathrm{DI}{\mathrm{X}}_{\mathrm{output}}-\sum \mathrm{DI}{\mathrm{X}}_{\mathrm{input}})$$

(3)

where ΔDIX represents the source or sink of nutrient elements, DIX_output indicates the nutrients discharged from the system, and DIX_input represents the nutrients imported into the system from external sources.

Based on the urban meteorological monitoring report of Shenzhen City, annual rainfall in the surveyed area was determined to be 1520.9 mm, with evaporation estimated at 1339.6 mm. The average daily flow of the three rivers in the study area was 81.22 × 10³ m³/d, and the annual average concentration of DIN discharged into the bay was 10.7 mg/L, while the annual mean value of SRP concentration was 0.25 mg/L. The determination of internal sediment fluxes was based on the study by Zhang et al. (2019), who provided data on the salt fluxes. In summer, winter, spring, and autumn, DIN values were 547 ± 292, 402 ± 792, 349 ± 597, and 214 ± 870 μmol/(m²d), respectively. The SRP values in summer, winter, spring, and autumn were 22.5 ± 16.8, 6.2 ± 8.6, 20.3 ± 112.0, and 1.0 ± 51.2 μmol/(m²d), respectively. Groundwater flux, nutrient content of precipitation, and the nutrient budget of oysters were determined based on prior literature [23,34].

2.3.5. Data Processing

Actual water depth at the sampling stations was used to simulate underwater topography through spatial interpolation provided by QGIS 3.26.3 (QGIS Development Team, 2022 QGIS, http://qgis.osgeo.org (accessed on 1 September 2023)). Physical and chemical parameter contours (including temperature, salinity, dissolved oxygen, Chla, NO₃⁻, etc.) were generated using the inverse distance weighting method in QGIS interpolation. Significance tests and correlation analyses between physical and chemical factors were conducted and calculated using Origin software (Origin Laboratories, version 2022, USA).

3. Result

3.1. Seasonal Variation Characteristics of Physical and Chemical Factors in the Sea Area

Statistical analyses of the data from the four voyages in this study revealed significant differences in the physical and chemical factors of seawater among seasons (Table S1). Among the investigated sediment factors, only TN exhibited a significant difference among seasons, while the contents of TOC, TP, and sulfide did not show significant seasonal variations. Figure 2a,b demonstrates significant seasonal differences in both bottom water temperature and surface water temperature in the surveyed sea area (p < 0.001).

During the investigation period, salinity exhibited significant seasonal differences (p < 0.001). The highest average salinity was recorded in spring, while the lowest was observed in winter (31.80 ± 0.12 PSU). The seasonal fluctuation in dissolved oxygen (DO) was less pronounced compared to temperature and salinity. DO content peaked in winter (8.46 ± 0.33 mg/L) and was lowest in summer (7.06 ± 0.57 mg/L). The mean chemical oxygen demand (COD) content in surface seawater ranged from 0.60 ± 0.21 mg/L to 1.61 ± 0.27 mg/L. The average COD content was significantly higher in autumn compared to other seasons. Conversely, the average COD content was the lowest in summer, significantly lower than in autumn and winter (p < 0.001). The highest average chlorophyll a content was observed in autumn, significantly exceeding that recorded in spring and winter (p < 0.001).

The seasonal distribution of nitrogen, phosphorus, and silicate exhibited variations within the surveyed area. The average concentration of NH₄⁺ was significantly higher in winter compared to other seasons (p < 0.001). Conversely, the average NH₄⁺ concentration in autumn was significantly lower than that recorded in other seasons (p < 0.001). A significant seasonal difference was also observed in the concentration of NO₂⁻, with the average concentration in summer (0.92 ± 0.16 μg/L) being significantly higher than that recorded in other seasons. However, NO₂⁻ content in autumn and winter fell below the detection limit. The highest average NO₃⁻ concentration was recorded in autumn, significantly exceeding that recorded in summer and winter (p < 0.001). In summer, the concentration was at its lowest (0.06 ± 0.02 mg/L), markedly lower than that documented in other seasons. The composition of dissolved inorganic nitrogen in the sea area was primarily influenced by NH₄⁺ content, which reached its highest average concentration in winter (0.25 ± 0.02 mg/L), significantly higher than that recorded in other seasons (p < 0.001). The content in summer and autumn was significantly lower than in spring and winter (p < 0.001). In autumn, DIN was primarily affected by NO₃⁻, which accounted for 66.7% of the DIN components. The average concentration of SRP was highest in autumn, significantly exceeding that recorded in other seasons, and lowest in summer, being significantly lower than that found in autumn and winter.

The annual mean value of N/P in the sea area was 73.44, which was six times the Redfield ratio (16:1). The average value was highest in spring, significantly surpassing other seasons, and lowest in autumn (Figure 2l). The average value of Si/N in spring and summer was the highest, significantly exceeding that recorded in autumn and winter (p < 0.001). The change trend exhibited by the average value of Si/P was virtually the same as that of Si/N. The change in sediment nutrient content was not as significant as that in the water. The average content of TN (0.05 ± 0.04%) in the spring was significantly lower than that recorded in other seasons (p < 0.001) (Figure 2p).

The PCA results (Figure 3) revealed that the dominant physical and chemical factors of seawater exhibited substantial variation across seasons (p < 0.001). PC1 and PC2 accounted for 70.7% of the annual variation. PC1 mainly reflected the effects of water temperature, salinity, NO₃⁻, NO₂⁻, SRP, and SiO₃²⁻. PC2 mainly reflected the effects of DO, DIN, NH₄⁺, and Chla. The above findings, along with the results of statistical analyses, revealed that the survey area was primarily influenced by SiO₃²⁻ and SRP in spring.

3.2. Spatial Distribution Characteristics of Physical and Chemical Factors in the Sea Area

The spatial distribution of BST exhibited significant seasonal differences (19.85~29.48 °C) (Figure S1a). In spring, the lowest surface seawater temperature was found in the southern part of the bay, gradually increasing from south to north. In summer and autumn, SST was lower at the estuaries of the three rivers but higher in the middle of the bay (Figure S1b). The spatial distribution of salinity indicated lower values in the south and higher values in the north during spring, autumn, and winter (31.51~34.16 PSU). However, in summer, the salinity around the bay was generally lower than in the middle of the bay (Figure S1c). DO levels were generally lower in the southern part of the bay, higher near the outer sea junction in the spring, higher in the middle of the bay in summer, lower in the north and south, and higher in the northeast corner of the bay in autumn (Figure S1i). In spring, DO concentrations decreased from south to north (ranging from 0.06 μg/L to 2.12 μg/L). The highest Chla content was recorded at station 18 at the Nanao River estuary. In summer, Chla content was higher at the estuaries of the three rivers (Figure S1k), with the lowest value recorded at station 11 in autumn and the highest value recorded at station 12 near the Longqi River estuary in winter (ranging from 0.03 mg/L to 0.19 mg/L) (Figure S1k).

NH₄⁺ concentrations in spring decreased from north to south, being lower near the Wangmu River estuary and higher near the Jiaochangwei resort (Figure S1d). The annual variation range of NO₃⁻ was 0.03 mg/L to 0.11 mg/L. The lowest value throughout the year was documented at station 14 at the bay mouth in summer, while the highest values were recorded at stations 6 and 14 in autumn. In spring, NO₃⁻ content was generally low near the coast and higher in the middle. In summer, the spatial distribution trend decreased from the western coast to the eastern bay mouth and decreased from the southeast to the northwest in autumn (Figure S1e). The annual variation range of DIN was 0.11 mg/L to 0.28 mg/L (Figure S1f). Due to the high proportion of NH₄⁺ in its components, its spatial distribution was generally consistent with that of NH₄⁺. The annual variation range of SRP was 2.79 μg/L to 14.26 μg/L. The lowest value for the entire year was recorded at station 10 in the summer, and the highest value was recorded at station 14 in the autumn. In spring, it decreased from the bay mouth towards the bay. In summer, it decreased from south to north. In autumn, SRP was higher at Nanchong Estuary, Wangmu Estuary, and the bay mouth, and higher at Nanchong Estuary and Wangmu Estuary in winter. The content of SiO₃²⁻ varied from 0.01 mg/L to 0.24 mg/L throughout the year (Figure S1h). The lowest value was recorded at station 9 in autumn, and the highest was recorded at station 9 in spring. SiO₃²⁻ content was higher in the southeast in spring and lower near the Wangmu River in the west, becoming higher in the northwest in summer. In autumn, SiO₃²⁻ content decreased from south to north, while in winter it decreased from east to west. The annual variation range of N/P was 23.78 to 124.05. The overall spatial distribution indicated that N/P was higher in the southern oyster proliferation area in spring and winter, higher in the southeast in autumn, and lower in the bay mouth area. The Si/N spatial distribution correlated with SiO₃²⁻. The spatial distribution of Si/P was similar to that of SiO₃²⁻ in spring, summer, and winter, with some influence from the SRP of the Wangmu River in autumn, showing a decreasing trend from southeast to northwest (Figure S1g).

The spatial distribution of nutrients in the sediments of the surveyed sea area displayed significant variation. Although there were weak seasonal changes, the TOC content in the sediments ranged from 0.14% to 1.93% (Figure S1p), with a decrease from southeast to northwest throughout the four seasons. The TN content ranged from 0.10% to 2.51% (Figure S1q), and the overall trend was similar to that of TOC, with increased sediment concentrations near the western coast in summer. TP content ranged from 0.68% to 5.08% (Figure S1r), showing different spatial distributions in different seasons. In spring, TP content was higher in the middle of the bay area. In summer, TP content was higher at the eastern bay mouth and in the southern coastal waters. In autumn, it decreased from southeast to northwest. In winter, TP content was higher in the middle of the bay area and lower in the north and south. Sulfide content in the sediments of the sea area exhibited a wide range of variation, from 0.50 mg/kg to 298.00 mg/kg (Figure S1s). In spring, sulfide content decreased from west to east, especially near the Wangmu River. However, it decreased from southeast to northwest in summer, autumn, and winter. The spatial variation of C/N in sediments ranged from 1.41 to 57.62 (Figure S1t). The variation trend of C/N in summer, autumn, and winter was consistent with that of TOC, but its value was higher in the southern and western coastal areas in spring. The variation range of N/P in sediments was 0.06 to 2.45 (Figure S1u), with the primary spatial distribution following the pattern of TN in spring and winter. In summer and autumn, N/P was influenced by the TP content in sediments, displaying a decreasing trend from west to east.

Although the spatial distribution of each physical and chemical factor varied, the results of cluster analysis, based on Spearman’s correlation analysis of seawater physical and chemical factors at each station (Figure 4), revealed that the 18 stations in the survey area could be mainly divided into four types. The first type included stations S9, S10, S11, S14, S15, and S16 at the bay mouth. The second type consisted of coastal stations, including S1, S2, S3, S4, and S12. The third type comprised stations S6, S7, S8, S17, and S18 in the oyster proliferation area. Finally, the river estuary stations, S5 and S13, were clustered together.

3.3. Correlation between Physical and Chemical Factors in the Sea Area

To investigate the influence of salinity, Chla, and DO on the trophic dynamics of the area, this study examined the correlation among nutrients in the sea area. As depicted in Figure 5, significant correlations were observed. Notably, a significant negative linear relationship was found between surface seawater salinity and NO₃⁻, DIN, and SRP, respectively (p < 0.001, R = −0.39; p = 0.0017, R = −0.36; p < 0.001, R = −0.71). Conversely, there was a significant positive linear relationship between salinity and SiO₃²⁻ (p < 0.001, R = 0.53), while a negative linear relationship with NH₄⁺ was observed, though it was not statistically significant.

Furthermore, a significant negative linear relationship was identified between Chla and NH₄⁺, DIN, and SiO₃²⁻, respectively (p < 0.001, R = −0.62; p < 0.001, R = −0.64; p < 0.001, R = −0.44), although there was no significant linear relationship between NO₃⁻ and SRP in the surface water.

Additionally, a significant positive linear relationship was detected between DO and NH₄⁺, DIN, and SRP, respectively (p < 0.001, R = 0.49; p < 0.001, R = 0.61; p < 0.001, R = 0.38), but the linear relationship with NO₃⁻ and SiO₃²⁻ was not statistically significant.

3.4. Eutrophication Assessment Model and Nutrition Index

According to the criteria in Table 1, the average DIN concentrations in spring and winter were 0.20 ± 0.01 mg/L and 0.25 ± 0.02 mg/L, respectively, with corresponding N/P ratios of 97.28 ± 9.40 and 73.89 ± 10.14. Consequently, spring and winter were categorized as phosphorus-limited moderately eutrophic water bodies. In contrast, during summer and autumn, the mean values of DIN in the sea area were lower than 0.2 mg/L, and SRP was lower than 0.03 mg/L, classifying it as an oligotrophic water body.

When considering the assessment criteria for primary productivity constraints in coastal waters, the following inferences can be made, as proposed by Justić and colleagues. If Si/P > 22 or N/P > 22, phosphate will be a limiting factor; if N/P < 10 or Si/N > 1, nitrogen becomes the limiting factor; if Si/P < 10 or Si/N < 1, silicon becomes the limiting nutrient [35]. In this study, N/P values in all four seasons exceeded 22, with Si/P ratios higher than 22 in spring, summer, and winter. Therefore, the sea area was identified as phosphorus-limited during these seasons. However, in autumn, Si/P was 4.10 ± 2.80, and Si/N was 0.10 ± 0.05, indicating silicon limitation during that season. The AEP results show that the AEP(P) in the four seasons was between 1.4 and 2.7 times greater than AEP(N). This is consistent with the potential eutrophication index, with the exception of the autumn.

The range of TRIX variation in the surveyed bay spanned from 3.68 to 5.21, with an annual average of 4.45. Seasonal differences were less pronounced than single-nutrient assessments (Figure 6). The average TRIX in spring (4.24 ± 0.29) was significantly lower than that in autumn (p < 0.01) and winter (p < 0.05), but there was no statistically significant difference between spring and summer (4.47 ± 0.28). Based on TRIX evaluation results, all four seasons in the sea area fell into the category of medium productivity water bodies (

Table 2. General ranking for TRIX evaluation.

Grade	TRIX Value	Trophic Status	Condition
I	0–4	Oligotrophic	Water poorly productive
Ⅱ	4–5	Mesotrophic	Water moderately productive
Ⅲ	5–6	Mesotrophic to eutrophic	Water moderately to highly productive
Ⅳ	6–10	Eutrophic	Water highly productive

).

TRIX displayed distinct distribution patterns among survey stations (Figure 7). In spring, the highest TRIX values were observed near the Wangmu River, with a decreasing trend from the Wangmu Estuary in the southwest to the northeast. According to the TRIX evaluation criteria, the sea area near the Wangmu River was classified as a mesotrophic water body, while the northern area was categorized as oligotrophic. The highest TRIX values in summer were also recorded in the vicinity of the Wangmu River estuary, with a similar decreasing trend from the southwest to the northeast, except for an increase near the Longqi River estuary. The sea area near the Wangmu River was considered mesotrophic, while the northern area remained oligotrophic. In autumn, TRIX values decreased from the eastern bay mouth towards the west, declined near the Nanchong River and the Longqi River estuary, and increased near the Wangmu River estuary. The overall trend in the sea area shifted from high productivity in the west to low productivity in the east. The highest TRIX value for the entire year was observed at station 3 in winter, decreasing from the western coast to the eastern bay mouth. The areas near stations 3 and 7 were characterized as high and medium-to-high productivity water bodies, whereas those near station 17 were categorized as low productivity water bodies.

3.5. Nutrient Budget Based on LOICZ Model

When ΔDIX is less than 0, it indicates that the bay system serves as a sink for that particular nutrient. The present study employed the water–salt balance module of the LOICZ model to calculate the flushing time of the bay. The flushing times for spring, summer, autumn, and the entire year were found to be 1.09 days, 0.91 days, 1.74 days, and 1.71 days, respectively. The bay exhibited the fastest water cycle in summer and the slowest in autumn.

Figure 8a presents the annual phosphate budget in the bay. Overall, the annual average river input of phosphate was 21.74 kg/d, and the annual groundwater input was 6.16 kg/d. It was found that winter is the only season when phosphate acts as a sink throughout the year, while the other three seasons function as sources of phosphate in the bay. Autumn exhibited the highest phosphate output, with an average of 57.06 kg/d, while winter stood as the sole sink. The average annual net phosphate import into the bay was 10.64 kg/d, with rivers serving as a major phosphate source. During summer, the three rivers contributed the most phosphate to the bay, averaging 7.93 kg/d, while in winter, they became sinks, with an average of 10.64 kg/d. Using the Redfield stoichiometric ratio, the NEM of the bay was highest in autumn, with an average of 2328.78 kg C/d. In contrast, the lowest NEM was recorded in winter, with an average of 515.52 kg C/d. The annual NEM was 847.12 kg C/d, and, when standardized to a unit area, it equated to 7.06 mmol C/m²/d.

Figure 8b shows the annual N budget of the bay. It was concluded that the bay represented the source of N throughout the year, with an annual output of 1920.39 kg/d, of which the highest output was 2625.29 kg/d in spring and the lowest was 1358.89 kg/d in winter. The three rivers had the most N source in the bay in spring, which was 1227.57 kg/d, and the lowest in winter, which was 421.98 kg/d. The model estimated that the annual N denitrification in the bay was −1771.21 kg/d, converted to a unit area of −12.65 mmol/m²/d.

4. Discussion

4.1. Factors Influencing Temporal and Spatial Variations in Nutrients and Eutrophication Index

The biogeochemical and ecosystem metabolism in the investigated bay is strongly influenced by seasonal variations in climate and terrestrial runoff [36]. Despite the subtropical location of the study area, water temperature displays clear seasonal differences due to the direct impact of climatic factors. Spatial variations in water temperature are primarily attributed to water depth, hydrodynamic characteristics, runoff, seabed sediment, and human activities [21]. Water temperature is critical in nutrient circulation, eutrophication occurrence, and aquatic organism metabolism in the sea area [16]. In the present study, the northern part of the bay is adjacent to the Daya Bay nuclear power station, making it susceptible to the influence of cold source inlets, thermal discharges from the nuclear plant, and tidal flow direction and velocity. The increase in seawater temperature near the thermal discharge area might contribute to blooms caused by Creseis acicula [16]. Higher bottom water temperatures in the northern spring could be attributed to sediment composition, presence of coral rubble, gravel, and extended sunshine hours in the southern region with shallow water depths, facilitating sun radiation penetration and bottom water mixing, resulting in higher temperatures in the spring [37]. The influence of three rivers, running from the north, west, and south, divides the sea water temperature distribution into three distinct regions. As the runoff from these rivers varies across different seasons, the impact of runoff on sea water temperature also varies. During the alternating seasons of winter and spring, the underlying water temperatures rise, facilitating the rapid diffusion of nutrients from the seabed. In winter and spring, this process can potentially lead to the occurrence of red tides [38].

Salinity gradients are distinct characteristics of estuaries and bays, setting them apart from the ocean and river waters [39]. Ocean salinity is primarily affected by water temperature, rainfall, evaporation, runoff, and ocean current exchange. Average sea surface salinity varies seasonally, with winter experiencing lower values due to cooling air temperatures and shallower water depths. In winter, a combination of factors leads to lower salinity near the coast, in contrast to deeper offshore waters [40]. Notably, the strong seasonal variability in temperature and salinity should be emphasized, as this not only influences the energy metabolism of marine resources like fish and oysters [41,42], but also has a significant impact on the oxygen consumption and calcification rate of the dominant phytoplankton species, Creseis acicula, in this area. Interestingly, salinity impacts oxygen consumption more than temperature for this species [16].

The phytoplankton biomass in estuaries and bays is primarily regulated by river nutrient input, growth rates, and predation effects [43]. In the present study, chlorophyll-a content was lowest in winter, consistent with the seasonal distribution of Chla observed in Lianyungang [44]. Studies have suggested that shellfish farming can mitigate eutrophication by removing chlorophyll and improving water transparency [45,46]. Since the 1980s, Portuguese oysters (Crassostrea angulata) have been introduced for farming [15]. The content of Chla in the southern oyster breeding area was lower than in other areas of the bay in summer, but the decrease in Chla in the oyster breeding area was not statistically significant in other seasons. This phenomenon can be attributed to oysters selectively filtering plankton, allowing certain plankton species to dominate [45,47]. Chla increased notably in the estuary during spring and summer, confirming that the Chla concentration in the sea area was influenced by the rapid changes in the estuarine environment and time-lag effects. These spatial and temporal variations were dynamic in nature [11,48].

As per the grade seawater quality standard (GB 3097-1997, 1997) [49], the average values of dissolved inorganic nitrogen and soluble reactive phosphorus in each season met the first-class seawater standards. The measured sediment indexes were consistent with the first-class sediment standard of ‘Marine Sediment Quality’ (GB 18668-2002) [50]. NH₄⁺ was found to be the primary component of DIN in the surveyed bay, consistent with the general characteristics of DIN components in the continental shelf of the South China Sea [40]. The composition of DIN resembled that of DIN in the subtropical Gulf of Brazil (Santa Catarina Bay) [36]. However, in contrast to the north temperate zone of Laizhou Bay and Lianyungang, the main component of DIN in those regions was NO₃⁻ [14,44]. In addition, in the surveyed area, NO₃⁻ was the primary source of DIN in autumn, with the average NO₃^– content in spring being equivalent to that of NH₄⁺. It is widely thought that NO₃^– in the bay mainly originates from surface runoff and groundwater input, while NH₄⁺ is primarily sourced from the respiratory metabolism of marine organisms in aquaculture, the decomposition and death of algae cells, and bacteria-mediated remineralization of dissolved organic nitrogen [51]. Studies have demonstrated that when NO₃⁻ is the dominant species in DIN it favors the development of red tides dominated by diatoms [52], whereas when NH₄⁺ is the primary component of DIN it promotes red tides dominated by pico-cyanobacteria [53]. The findings of this study suggest that the investigated sea area is more likely to develop cyanobacteria red tides.

The correlation analysis of salinity, Chla, and DO with DIN revealed significant patterns. DIN content decreased significantly with increasing salinity in the sea area, consistent with the trend of decreasing from the estuary to the open sea. Furthermore, as Chla concentration increased, DIN in the sea area decreased significantly, indicating substantial absorption by phytoplankton with respect to DIN (R = −0.64) [44]. There was also a positive linear correlation between DO and DIN, likely because increasing DO promoted the remineralization of organic nitrogen in the sea area [54]. These results illustrate that the composition of DIN in the survey area resulted from the combined effects of the aforementioned factors, shaping the seasonal and spatial variation characteristics of DIN components. SRP exhibited a significant negative linear relationship with salinity and a significant positive linear relationship with DO, mirroring trends observed in DIN and suggesting that SRP, much like DIN, is substantially influenced by estuarine and nutrient remineralization. Despite the higher river input water flow in summer, SRP levels were significantly lower during that season than in autumn and winter, indicating rapid SRP removal and/or consumption from the water column [40].

In autumn, the silicate content was significantly lower than in other seasons, while the Chla content during the same period was significantly higher than in spring and winter. Spatially, the peak silicate concentration in autumn appeared in areas with lower Chla. Correlation analysis also revealed a significant negative correlation between Chla and silicate. Additionally, the seawater NO₃⁻ content was higher during this period, promoting diatom growth [55]. During this period, the rapid proliferation of phytoplankton in the sea area consumed a significant amount of silicate, leading to decreased silicate content in autumn, consistent with recent survey results in the Lianyungang sea area [44].

It is widely acknowledged that nutrients in seawater ensure plankton growth, and different nutrient ratios influence plankton species composition [56]. Therefore, studying the stoichiometric ratios of elements in seawater is crucial to understand the involvement of primary producers in biogeochemical cycles. The assessment criteria for potential eutrophication unveiled nutrient limitations in the surveyed sea area. Based on the assessment results, the investigated sea area was classified as a phosphorus-limited moderately eutrophic water body in spring and winter, while it was categorized as an oligotrophic water body in summer and autumn. Additionally, based on the criteria for primary productivity constraints in coastal waters, the surveyed area exhibited phosphorus limitation in spring, summer, and winter, while it was characterized by silicate limitation in autumn. The results from both assessments were consistent. The annual mean N/P ratio in the sea area was 73.44, which is six times the Redfield ratio (16:1). The annual variation range was 23.78~124.05, resembling that of Bohai Bay (20–133) [57]. This situation is comparable to Xiamen Bay, which may be influenced by the high N/P ratio in urban sewage discharges, leading to an imbalance between phosphorus and nitrogen in the water bodies receiving these discharges (reclaimed water) [58]. The potential eutrophication results in Daya Bay from 2009 to 2015 were mostly lower than 16, suggesting a change in N/P in the sea area in recent years. Coastal areas with significant terrestrial input may shift from nitrogen limitation to phosphorus limitation or phosphorus–silicate limitation [59]. This anthropogenic shift in N/P, along with Si/N and Si/P, can further alter the proportion of diatoms, dinoflagellates, and cyanobacteria by promoting cyanobacterial growth [59].

TRIX provides an effective indicator for the assessment of the trophic status of coastal waters [60]. Initially developed for Italian coastal waters, it has been used in numerous sea areas worldwide [31,36]. In the surveyed bay, TRIX exhibited a variation range of 3.68~5.21, with an average of 4.45. The overall evaluation results in this study resembled those from the Gulf of California [31], but were better than the trophic status of Magdalena Bay in Mexico and Nha Trang Bay in Vietnam [61,62]. Seasonal differences in TRIX were less significant than the differences in nutrient ratios among seasons. TRIX values were relatively high during summer. The average TRIX in spring was significantly lower than that recorded in autumn or winter, though the difference between spring and summer was not statistically significant. Moreover, the variation among summer, autumn, and winter was not substantial. Eutrophication in the study area exhibited no significant link to seasonality. According to the TRIX results, the sea area was categorized as a moderately productive water body in all four seasons. Spatially, high productivity water bodies were mainly found in areas near the estuary and sewage outlet. In spring and summer, the Wangmu River exerted significant influence, resulting in high water nutrient levels. The Wangmu River flows through industrial and residential areas with large populations along its banks, strongly affecting the eutrophication assessment of the bay [21].

4.2. Analysis of the Characteristics of Nutrient Balance in Dapeng Cove

Seasonal and spatial distribution of DIN, SRP, and SiO₃²⁻ concentrations varied due to differences in nutrient sources and consumption in the survey. Nutrient sources in the Dapeng Cove sea area encompass rivers, groundwater input, atmospheric deposition, input from adjacent sea areas, and biological input. In contrast, large algae are rare in the sea areas surrounding Dapeng Cove. Therefore, the absorption of dissolved nutrients results from phytoplankton and bacterial activity, as well as from oyster harvesting. The study area is home to three small seasonal rivers distributed along the coastline from north to south. Plume outlets are located near sampling points 2, 6, and 7. The daily average discharge from these rivers is approximately 881.22 × 10³ m³/d, accounting for about 0.15% of the total water volume of Dapeng Cove. This discharge plays a crucial role in the geochemical nutrient cycle of surface water, as nutrient content in river water entering the sea far exceeds that of seawater. As a result, it contributes significantly to environmental pressures in the bay and elevates the risk of coastal bays and adjacent sea areas experiencing eutrophication [62,63,64].

It has been reported that the average residence time of surface seawater in Daya Bay is 3.2 days [34]. In the present study, according to LOICZ model calculations, the average annual flushing time in the bay was 1.26 days. During the summer, due to factors such as elevated water temperature, increased river discharge into the sea, higher rainfall, and seasonal seawater circulation, the water cycle was at its fastest. The entire bay took approximately one day to complete a water cycle. Research has demonstrated that when seawater exchange between the inner and outer bays strengthens the physico-chemical characteristics of the water body change significantly, transitioning from high temperature and low salinity to low temperature and high salinity. Robust water exchange can also alter the spatial distribution of seawater physicochemical factors and impact plankton community structure [65]. Longer water exchange times during autumn may result in a limited exchange between the inner and outer bays, leading to water retention in certain areas, often corresponding to sediment organic content [66]. These factors might explain the significantly higher sulfide, TOC, and TN content in the sediments of stations 17 and 18 southeast of the bay compared to other regions. Weak water circulation during autumn potentially exacerbates eutrophication. TRIX results also demonstrate that the mean TRIX value was highest in autumn, indicating significantly higher potential eutrophication levels than those in spring and winter.

Further examination of the results revealed that winter acted as a phosphate sink, while the bay served as a phosphate source during the other three seasons, with autumn exhibiting the highest phosphate output. The daily average discharge of SRP into the bay stood at 21.74 kg/d, lower than that of Shenzhen Bay and Pernambuco, Brazil [1,67]. Additionally, the annual groundwater input of SRP in the study area was 6.16 kg/d [34], surpassing the amount of SRP discharged into the bay via surface rivers in winter. Similarly, the annual DIN input from groundwater was 1290.55 kg/d, surpassing the DIN input from surface runoff, aligning with observations near the Ma’ao Port in the Balearic Islands and Lianjiang in Fujian [68,69]. This highlights the significant impact of human activity on the delicate groundwater quality by altering recharge conditions and rates [70]. In addition to surface runoff, groundwater also transports considerable nutrients to the surveyed bay, potentially influencing the ecology of coastal waters. The groundwater flux in this sea area was 6.77 × 10⁶ m³/d, and studies have linked the frequent occurrence of harmful algal blooms in the area to the input of substantial groundwater-related nutrients [34,71].

While rivers and groundwater contribute relatively modestly to the bay, atmospheric deposition emerges as another source of SRP and DIN. However, relevant studies have indicated that the input of ammonium nitrogen from the atmosphere in the Yellow Sea exceeds that from rivers. Atmospheric deposition, being a significant nutrient source, exerts a profound impact on local biogeochemical cycles [72,73]. This study estimated the nutrient flux into the bay through atmospheric deposition, which was higher in summer and lower in winter. As a phosphorus-limited water body, differences in nutrients due to atmospheric wet deposition could prompt the transition from picophytoplankton dominance to microphytoplankton [74]. Atmospheric deposition alters the N/P ratio in certain sea areas and significantly impacts the dynamic changes of heterotrophic bacteria and autotrophic organisms [75,76,77].

Within the survey area, a 2 km² raft oyster culture accounted for 20% of the study area surface. The filter-feeding effect of oysters inevitably influences the concentration and spatial distribution of nutrients in the sea. The impact of the oyster culture on nutrients in the sea area and the exchange of nutrients in sediments were calculated as endogenous nutrient fluxes. The average annual oyster yield in the survey bay amounted to 1.82 × 10⁴ t, removing a total of 75.89 t N and 12.85 t P from the bay annually [78]. The average ammonia excretion rate of oysters was 122.50 μg/h/g, while the average phosphorus excretion rate was 18.89 μg/h/g [79]. Based on the oyster yield and metabolic rate, the net metabolic rate of nitrogen was −61.32 kg/d, and the net metabolic rate of phosphorus was −12.60 kg/d. Oyster harvesting can thus eliminate a substantial amount of N and P from the sea area.

The circulation, transfer, and storage of dissolved inorganic nutrients and soluble reactive phosphate at the sediment–seawater interface play a pivotal role in the ecosystem. The flux of DIN and SRP is influenced not only by the nutrient concentration gradient between the overlying water and pore water, but also by factors such as the content and composition of organic matter, oxygen concentration, infiltration depth of bottom water, and the activities of benthic organisms and bacteria [80,81]. The range of variation in sediment nutrient flux of DIN and SRP in the studied sea area was within an order of magnitude of that recorded in the northern continental shelf of the East China Sea [82], but lower than that observed in the Strait of Lauren in eastern Canada [80].

NEM is a fundamental indicator of quality and energy balance, offering a comprehensive measure of ecosystem status [83]. It reflects the disparity between the contributions of primary production and respiration processes within the sea area. The annual net metabolic rate of the ecosystem in the surveyed area was determined to be 7.06 mmol C/m²/d using the Redfield molar ratio between phosphorus and carbon, indicating that total production dominates over ecosystem respiration, resulting in an autotrophic system [84]. This value is comparable to the Seto Inland Sea of Japan (6.67 mmol C/m²/d) [85], but it is lower than that found in the Beibu Gulf coast in China (8.6 mmol C/m²/d) [86]. In winter, the net metabolic value in the study area is negative, signifying that respiration prevails over production, a phenomenon which may be attributed to factors such as nutrient input limitations, sea circulation models, water temperature, and bacterial activity [87,88,89].

Denitrification, a pivotal process to improve water quality, control trophic states, and regulate nutrient cycling in bays, is essentially a bacterial-mediated nitrification and denitrification process that removes bioavailable nitrogen from the water column and releases it into the atmosphere in the form of molecular nitrogen. This phenomenon has been observed in numerous estuaries and bays worldwide [90]. It has been established that the LOICZ model calculates nitrogen fixation and denitrification in the sea area based on mass balance and CNP stoichiometry. The model determined that denitrification dominates in the surveyed area, with a denitrification rate of 12.65 mmol/m²/d, higher than that in the Seto Inland Sea in Japan and lower than that in the Wamy Estuary in Tanzania during the dry season [85,91]. Denitrifying nitrogen constitutes over 90% of the total DIN load in the survey area, possibly due to factors such as shallow water depth, high annual average water temperature, high nitrogen–phosphorus ratio, and slow current velocity in the study area. Excess nitrogen that cannot be consumed by primary production is released into the atmosphere in nitrogen form, highlighting the role of coastal ecosystems in local, regional, and global biological cycles and their response to excessive nitrogen outside the dissolved inorganic nutrient cycle [5].

5. Conclusions

Urban estuary basin bays face substantial human-activity-related pressures and are particularly susceptible to eutrophication due to factors such as wastewater runoff and thermal discharge from power plants. As per the TRIX assessment results, all four seasons in this study fall within the category of medium productivity water body. The potential eutrophication level in the bay is high during summer and autumn, with high productivity water areas primarily concentrated near the estuary and sewage outlet. These conditions are linked to rainfall, surface runoff, and groundwater input. The findings from the eutrophication model align with those from the trophic index method. Over the past decade, the N/P ratio in the surveyed sea area has experienced significant changes, potentially shifting from nitrogen to phosphorus or phosphorus–silicon limitations. This artificial alteration of N/P ratios, combined with Si/N and Si/P dynamics, may lead to changes in the proportions of diatoms, dinoflagellates, and cyanobacteria by promoting cyanobacterial growth. Seasonal effects, including climate variations, ocean circulation patterns, human disturbances, and rainfall events, drive the seasonal and spatial distribution of nutrients in the bay, subsequently affecting the ecosystem metabolism within the bay. The annual net ecosystem metabolic rate in the bay is 7.06 mmol C/m²/d, with total ecosystem production exceeding respiration, resulting in the bay being classified as an autotrophic system. The results obtained from the LOICZ evaluation indicate that the nitrogen cycle in the surveyed area is dominated by denitrification, with a denitrification rate of 12.65 mmol/m²/d. Overall, our findings suggest that oyster proliferation has a weaker impact on the physical and chemical properties of the surveyed waters than surface runoff and groundwater input. There used to be wetland ecosystems such as oyster reefs, coral reefs, and mangroves; however, the development of coastal zone and other anthropogenic disturbances brought certain environmental pressures, causing the coastal habitats to degrade rapidly. This also reduces the conditional capacity of the cove with respect to the nutrient load. The frequency of blooms has also increased in recent years. If the coastal development and the nutrients discharged in the bay continue to increase, great damage will be caused to the marine ecology and the fishing industry; for example, shellfish cultures enrich harmful phycotoxins through an enrichment effect, which would be ultimately harmful to human health. We could further investigate corrective actions to reduce the risk of eutrophication through the following measures: increasing plant biomass in water bodies, building artificial oyster reefs, limiting the export load of nitrogen and phosphorus, and building wetlands downstream of agricultural catchment. Additionally, maintaining an input–output balance would be possible by reducing nitrogen and phosphorus diffusion and leaching from fertilizers.