Phytoplankton Community Diversity and Its Environmental Driving Factors in the Northern South China Sea

Abstract

The South China Sea (SCS) plays an important role in global marine ecology. Studies of phytoplankton diversity promote the sustainable utilization of resources in the SCS. From July to August 2020, the phytoplankton community structure at 47 stations in the northern SCS was investigated. Species composition and distribution of phytoplankton, water quality, diversity index, main influencing factors, and succession characteristics of the community structure were analyzed in combination with the survey results from previous years. A total of 332 separate taxa from 83 genera and three phyla were identified, including 142 species and 45 genera of Bacillariophyta, 188 species and 36 genera of Dinophyta, and two species and two genera of Chrysophyta. Average phytoplankton cell abundance was 649.97 cells/L. Nitzschia spp., Thalassionema nitzschioides, and Scrippsiella spp. were the dominant species. Scrippsiella spp. was found for the first time as a dominant species in the northern SCS. Meanwhile, Nitzschia spp. was associated with organic-polluted water. The high-value areas of Nitzschia spp. also indicated eutrophication, and water was slightly polluted. The Shannon–Weiner diversity index of the surface layer was 0.99–4.56 (with a mean of 3.57), and the evenness index was 0.23–0.96 (with a mean of 0.83). The phytoplankton community structure in the northern SCS was deemed to be stable. Pearson correlation analysis showed that the sum of nitrate and nitrite was significantly negatively correlated with the abundance of dinoflagellate, which indicated restrictions as a result of the sum of nitrate and nitrite, with no significant correlation between ammonium salt and various groups. Small- and medium-sized phytoplankton are usually dominant in the SCS, where nitrogen is limited.

1. Introduction

Phytoplankton are the most crucial primary producers in the ocean, accounting for approximately 95% of the primary productivity of the ocean [1,2] and approximately half of the global net primary productivity [3]. Phytoplankton convert inorganic matter into organic matter through photosynthesis and promote the absorption of nutrients dissolved in seawater above the euphotic layer, which introduces energy and substances into the food chain and transfers them to a higher trophic level that opens a series of marine food webs [2,4]. The active vertical movement of phytoplankton is critical for carbon storage and flux, as well as marine biological resources [5]. Environmental factors have had a dynamic impact on biological communities. Changes in physical and chemical factors in the ocean can directly influence the physiological characteristics of phytoplankton [6], thereby altering their community structure [7]. Therefore, by studying the changes in phytoplankton community structure, we can understand the environmental changes in the local sea area better, which is of great significance in the study of marine ecology.

The South China Sea (SCS) is one of three marginal seas in China. It has a monsoon climate that includes tropical and subtropical climatic zones. The northern SCS is connected to the East China Sea in the north and is affected by Pacific water in the east, while the continental shelf in the west is greatly affected by land sources. The Pearl River and other rivers carry large amounts of nutrients and other substances from their estuaries. During the summer, the northern SCS is affected by the interactions between circulation, coastal currents, and upwelling in the SCS [8]. In addition, the internal waves in the northern SCS are the largest reported in the global ocean [9]. Many ocean currents cause seasonal changes in the phytoplankton community structure.

The water quality directly affects the abundance, community structure and diversity of phytoplankton. Human activities, such as the rapid development of tourism and sewage discharge, can all contribute to poor water quality, which endangers the health of the ecosystem [10,11]. Eutrophication is a typical example, which is usually caused by hypoxia and an increasein the number of algae [12]. At present, eutrophication has become a global problem, which has brought serious negative impacts to the marine ecosystem.

Previous studies of the South China Sea have focused on coastal bays or aquaculture waters, and less attention has been paid to the large surface stations in the northern SCS. Few studies have evaluated the water quality in the northern SCS. In this study, based on an analysis of water-collected phytoplankton samples from 47 large surface stations in the northern SCS, the species composition, cell abundance, dominant population, and diversity index of phytoplankton were systematically studied in order to clarify the diversity of phytoplankton in the SCS and reflect the eutrophication of the sea area. Based on this, the water quality of the investigated area was analyzed. In comparison with historical data, we discussed the changes in the phytoplankton composition in the northern SCS in recent years. Simultaneously, ecological statistics were used to correlate the phytoplankton with environmental factors, and the environmental factors driving the change in phytoplankton community structure were discussed. This study provides a basis for studying the response of the phytoplankton community structure in the northern SCS to global environmental changes and human activities on a large temporal scale, and it assessed water quality in the northern SCS with the aim of better introducing relevant measures for management.

2. Materials and Methods

From 19 July to 10 August 2020, 47 stations were investigated in the northern SCS (15–22° N, 114–120° E) (Figure 1) and 270 bottles of samples were collected in total. Approximately 2000 mL of water samples were collected at water depths of 0 (surface), 30, 50, 75, 100, and 150 m using a Conductivity Temperature Depth water sampler mounted on a Seabird 911 Plus CTD (Seabird Electronics Inc., Bellevue, WA, USA). Among them, the S1 station only collected samples at water depths of 0 and 30 m, the S2 station collected samples at 0, 30 and 50 m, samples with water depths of 75 m and above were collected at the S3 and S4 stations, and the samples at 150 m were collected at the S5 station. Then, 2% Lugol’s iodine solution was added to the water samples for fixation. In the laboratory, we concentrated 2000 mL samples to X mL samples, respectively (the range of X is 100–300), so that we could classify and identify phytoplankton more easily. We evenly took out B mL samples from X mL samples and poured them into a Hydro-Bio counting chamber (Hydro-Bios; Kiel, Germany) for 24 h. The magnification of the microscope eyepiece was 10× and the microscope objective was 20× or 40×. The total magnification was 200× or 400×. The Utermöhl method was used to analyze the phytoplankton [13,14,15]. Phytoplankton cells were counted and identified using a Nikon TS100 inverted microscope (Nikon Corporation of Japan, Tokyo, Japan), and we consulted relevant books for their identification [16,17,18,19].

Temperature, salinity, and nutrient data (NH4-N, NO2-N, NO3-N, PO4-P, and SiO3) were obtained from the First Institute of Oceanography, and were determined by the SEAL-AA3 Auto Continuous Flow Analytical System. Wherein, NO3-N and NO2-N adopted the diazotization-coupling method (NO3-N Zn-Cd reduction); NH4-N, PO4-P and SiO3 used the sodium salicylate method, phosphorus molybdenum blue method, and silicomolybdic blue method, respectively.

The calculation formula of phytoplankton abundance was as follows [14,15]:

$$\mathrm{Phytoplankton} \mathrm{abundance}=\frac{A}{B}\ast \frac{X}{2} \mathrm{cells/L}$$

where, A is the quantity of certain phytoplankton in the Hydro-Bio counting chamber, B is the volume of the sample in the Hydro-Bio counting chamber, and X is the volume after concentration.

The Shannon–Wiener index (H′) [20] was used to determine phytoplankton biodiversity, and was calculated as:

$$H^{\prime }=-{\displaystyle \sum _{\mathrm{i}=1}^{S}Pi{\log }_2}Pi$$

(1)

The evenness of the phytoplankton samples was calculated by Pielou’s index (J’) [21]:

$$J=H^{\prime }/{\log }_{2}S$$

(2)

The dominance index (Y) was used to determine the dominant species, where Y > 0.02 indicated the dominant species [22]:

$$Y=n_i/N\times f_i$$

(3)

Pi shows the significance probability for all species. Where Pi = ni/N, ni is the number of individuals of the ith species, N is the total number of phytoplankton cells, S is the number of identified species in a sample, and f_i is the frequency of occurrence of the ith species in each sample.

We used R software (version: 4.2.0) to analyze the relationship between variables and the strength of the relationship and visualized the results. We used Primer software (Primer 6) to do hierarchical clustering and made comparisons of the clusters with ANOVA. Surfer software (version: 26.0) was used to draw plane and section distribution maps, and ArcGis (version: 10.2) was used to draw the map of sampling stations.

3. Results

3.1. Environment of the Investigated Sea Area in the Northern South China Sea

The plane distribution of temperature (Figure 2a) and salinity (Figure 2b) in the investigated sea area is shown in Figure 2. The temperature varied from 15.4 °C to 31.9 °C, with an average of 25.1 °C. The salinity was 31.91–34.69, with an average of 34.32. In general, the temperature decreased with the depth, and the salinity distribution was relatively uniform There was little difference among water layers.

3.2. Species Composition, Cell Abundance, and Ecological Type of Phytoplankton

A total of 332 species (including varieties and forms) belonging to 83 genera in three phyla were identified (Appendix A). Among these, 142 species and 45 genera of Bacillariophyta were identified, accounting for 42.77% of the total species. The main genus of Bacillariophyta was Chaetoceros spp., accounting for 39 species and 27.46% of the diatom species. There were 188 species belonging to 36 genera in Dinophyta, accounting for 56.63% of the total species. Among them, 33 were Neoceratium spp., accounting for 17.55% of the total dinoflagellate species. There were 29 species of Protoperidinium spp., accounting for 15.43% of the total. In addition, two species from the two Chrysophyta accounted for 0.60%of the total species. Ceratocorys horrida and Ornithocercus steinii were also found northeast of the survey area. These oceanic species are widely distributed from the warm temperate zone to the tropical ocean and the Kuroshio area of the East China Sea. Therefore, they can be used as indicator species for the Kuroshio invasion [23].

The total abundance of phytoplankton in the survey area was 0.38 × 10⁵–400.24 × 10⁵ cells/L, with an average of 6.50 × 10⁵ cells/L. Diatom abundance was 0.03 × 10⁵–92.55 × 10⁵ cells/L, with an average of 5.33 × 10⁵ cells/L, accounting for 82.03% of the total cell abundance, which indicated dominance. Dinoflagellate abundance was 0.04 × 10⁵–8.02 × 10⁵ cells/L, with an average of 1.15 × 10⁵ cells/L, accounting for 17.66% of the total cell abundance. The average cell abundance of Chrysophyceae was 0.02 × 10⁵ cells/L, accounting for 0.31% of the total cell abundance. The ecological types of phytoplankton in this survey were mainly eurythermic and widespread species, such as Nitzschia spp. and Thalassionema nitzschioides, as well as coastal and warm-water species, such as Pseudo-nitzschia delicatissima and Chaetoceros constrictus, and the distribution of offshore species was low.

3.3. Plane Distribution of Phytoplankton

The plane distribution of phytoplankton in each water layer in the investigated sea area is shown in Figure 3. The layers with the highest cell abundance of phytoplankton(Figure 3a), diatoms(Figure 3b), and dinoflagellates(Figure 3c) were 30, 30, and 50 m, respectively. In the surface layer, the abundance of phytoplankton cells was 62–4066 cells/L, with an average of 512 cells/L. Most of the areas with high phytoplankton cell abundance were located at the SCS43 station in the north of the survey area and the S1 station near the coast of Guangdong. Overall, the distribution gradually decreased from north to south and from west to east. The cell abundance of diatoms was 3–9255 cells/L, with an average of 352 cells/L. Cell abundance reached its highest value in the north of the survey area and gradually decreased from north to south. The abundance of dinoflagellates was 30–331 cells/L, with an average of 159 cells/L. The highest value was at the S2 station near the coast of Guangdong, and the abundance of Scrippsiella spp. was high. In general, dinoflagellate abundance was distributed in patches.

The total abundance of phytoplankton in the 30 m layer was 73–40,024 cells/L. The highest phytoplankton cell abundance in this survey was 40,024 cells/L at the S1 station, and the abundance of Nitzschia spp. was high. The average phytoplankton cell abundance at stations other than S1 was 482 cells/L. The cell abundance of diatoms in the 30 m layer was 15–397,552 cells/L, reaching the highest value of 39,752 cells/L at the S1 station near the shore. The average diatom cell abundance at all stations (except S1) was 297 cells/L. The highest abundance of dinoflagellates was 27–494 cells/L at in the 50 m layer, with an average of 155 cells/L. At the SCS19 station in the south of the survey area, a high-value area was found, which was jointly distributed by Scrippsiella spp. and Gyrodinium spp., and showed a distribution of low abundance in the north and south, and a higher abundance in the east than in the west.

3.4. Vertical Distribution of Phytoplankton

As seen in Figure 1, the survey was divided into four longitudinal sections and one section from northwest to southeast. Figure 4 shows the distribution of phytoplankton in each section. In Section A, the distribution of phytoplankton and diatoms was consistent. The maximum cell abundance in this survey appeared at the 30 m layer of the S1 station near the shore, and the dominant species was Nitzschia. The diatom cell abundance was concentrated nearshore, mainly in the 30 m and 50 m layers, while offshore, it was mostly in the 50 m and 75 m layers. The distribution of cell abundance decreased from coastal to offshore areas, which is consistent with the distribution of nutrients. The patch distribution of dinoflagellates was obvious and was mainly distributed in the water above the 75 m layer.

Sections B, C, D, and E are four north–south sections arranged in parallel from west to east. Diatoms accounted for a large proportion of the total abundance of phytoplankton; therefore, the distribution of phytoplankton was similar to that of diatoms. The high abundance of phytoplankton and diatom cells in Section B was mainly located at the 75 m water layer of the S5 station near the shore, and the dominant species was C. curvisetus. The high diatom cell abundance area was mainly located in the 100 m layer, and dinoflagellates were densely distributed offshore. In Section C, the patch distribution of phytoplankton and diatoms was clear, and high-value areas appeared from the nearshore to the far sea. The distribution of phytoplankton and diatoms in Section D first increased and then decreased with the increase in water depth. The 30 m layer of the SCS15 station in the south of the survey area had the greatest abundance, with many Nitzschia spp. and C. curvisetus. Dinoflagellates were distributed in high-abundance areas from the nearshore to the far sea, and most were located above the 75 m layer. In Section E, the abundance of phytoplankton in the north was higher than that in the south. The high-value area of diatoms was mainly distributed in the 50 m layer, while dinoflagellates often appeared in the high-value area on the surface. Generally, areas with a high abundance of phytoplankton cells were distributed in the 30 m layer near the shore, whereas those in the open sea were mainly concentrated in the 75 m layer.

3.5. Dominant Species of Phytoplankton and Their Horizontal Distribution

Nitzschia spp., Thalassionema nitzschioides, and Scrippsiella spp. were the dominant phytoplankton species in the northern SCS during the summer. Nitzschia spp. was the dominant species in this survey, with a frequency of 94.4%. Scrippsiella spp. was the only dominant dinoflagellate species with a frequency of 68.1%, second only to Nitzschia spp. (Figure 5). The high-value area of Nitzschia spp. (Figure 5a) in the surface layer was mainly located at the S1 station near the shore and the SCS43 station near the intersection of the Taiwan Strait and SCS. Nitzschia spp. appeared less frequently in the south and northeast regions of the survey area. The Nitzschia spp. in the 30 m layer were mostly distributed near the S1 station, where the highest abundance of Nitzschia spp. cells in this survey was 26,313 cells/L. Overall, cell abundance showed a decreasing trend from the S1 station to the surroundings, with a high value at the SCS15 station in the south. The high-abundance area of Thalassionema nitzschioides (Figure 5b) in the surface layer was located at stations S1 and S2 near the shore and decreased to the east and south of the investigation area. The cell abundance of Thalassionema nitzschioides was the highest in the 30 m layer, and the high-value areas were mostly concentrated near the shore, whereas their distribution in the open sea was lower. This indicates cold and warm changes in paleotemperature in the northern SCS [24]. The area with a high abundance of Scrippsiella spp. (Figure 5c) in the 0 m water layer was mainly located near the shore and in the middle of the survey area. The abundance was highest in the 50 m layer, and appeared more frequently in the southwestern part of the survey area. In general, cell abundance in the southern sites was higher than that in the northern sites.

3.6. Diversity and Evenness Index of the Phytoplankton Community

Shannon–Wiener diversity (Figure 6a) and Pielou evenness indices (Figure 6b) were used to measure the stability of the phytoplankton community structure. The Shannon–Weiner diversity index of surface phytoplankton in the investigated sea area was 0.99–4.56, with an average of 3.57, and the evenness index was 0.23–0.96, with an average of 0.83. The average value of the diversity and evenness indices was the highest in the 75 m layer, whereas the Shannon–Weiner diversity index was 3.08–5.02, with an average of 4.39, and the evenness index was 0.72–0.93, with an average of 0.85.

3.7. Correlation Results

The cell abundance of phytoplankton, diatoms, dinoflagellates, and dominant species were combined with environmental factors (temperature, salinity, phosphate, silicate, ammonium salt, nitrate, and nitrite) for Pearson correlation analysis (Figure 7). The abundance of dinoflagellate cells was positively correlated with temperature, which is consistent with the preference of dinoflagellates for high-temperature living environments. Additionally, the abundance of dinoflagellate cells was negatively correlated with salinity, depth, silicate, phosphate, and the sum of nitrate and nitrite levels. In general, phytoplankton and diatoms did not show a certain correlation with these environmental factors. Among the dominant species, Scrippsiella spp. had a significant negative correlation with temperature, and Nitzschia spp. were greatly affected by salinity. As with the phytoplankton and diatoms, Thalassionema nitzschioides had no correlation with environmental factors. Ammonium salt had little effect on phytoplankton in the northern SCS. Contrary to other nutrients, ammonium salt was positively correlated with depth and negatively correlated with salinity.

3.8. Cluster Analysis of Community Structure

Hierarchical cluster analysis was conducted for each station according to the species and cell abundance of each station (Figure 8). The results showed that the Bray–Curties similarity coefficient between the largest stations was mostly 40–60% in each layer. In the surface, 47 stations were divided into two groups. S1, SCS43, and SCS1 stations, which were located in the north of SCS, were divided into group I. The other stations were divided into group II. The average cell abundance of phytoplankton in group I was 4774 cells/L, which was much higher than that in the group II (221 cells/L). Some nearshore species, such as skeletonema costatum, mostly occurred in group 1, and group II mainly consisted of widespread species and warm-water species. Cluster analysis divided the stations according to their close geographical locations, which indicated that the physical environment was consistent with the biological data.

From the perspective of vertical structure, 30 m and 50 m water layers were relatively similar, and the SCS34 station formed an independent group. It indicated that the environment of the two layers might be similar.

4. Discussion

4.1. Factors Affecting the Distribution of Phytoplankton

In the surface layer, the cell abundance distributions of phytoplankton and diatoms were similar, and most areas with high phytoplankton density were located near the Taiwan Strait. This area is on the east coast of Guangdong, and is greatly affected by freshwater and land-based inputs from the Pearl River. In addition, this area is jointly influenced by the coastal current of Guangdong, summer upwelling, the SCS warm current, and the Kuroshio intrusion current in the summer [25,26], making the nutrient content in the north higher than in the south. The cell abundance of diatoms gradually decreased from north to south, which is consistent with their preference for high-nutrient environments [27]. At the 30 m layer, the highest abundance of phytoplankton and diatom cells in this survey appeared at the S1 station near the coast of Guangdong, where Nitzschia spp. were the dominant species. As the area was affected by freshwater in the Pearl River estuary, the high-abundance area of phytoplankton usually did not appear in the surface water. Instead, it was between the surface and bottom fronts of freshwater and above the vertical pycnocline [28]. Therefore, the 30 m layer may be the location of the pycnocline.

Generally, areas with a high abundance of phytoplankton cells were distributed in the 30 m layer near the shore, whereas those in the open sea were mainly concentrated in the 75 m layer. However, at stations SCS33 and SCS24 in the middle of the survey area, a high-abundance area appeared at the 100 m layer, which may have been due to the high intensity of the current in the sea area, which transports phytoplankton from the upper to the deeper water [25]. A previous study found that the pycnocline in the north of the site was located at a depth of 60–120 m and that the stratification was strong [29], which is consistent with the observation that the high-value area of phytoplankton in the northern SCS often appeared in the 75 m layer in the current study.

The patch distribution of the dinoflagellates was determined based on their physiological characteristics. Many dinoflagellates are heterotrophic organisms that can obtain organic phosphorus by feeding on diatoms, cyanobacteria, and bacteria [30,31]. They are highly competitive in environments with low nutrient concentrations in the open sea [32,33].

In the surveyed sea area, the maximum value layer of nutrients often appeared at 150 m, whereas the high-value phytoplankton layer often appeared above the 100 m layer. This was mainly due to the exponential attenuation of light in the vertical direction when it propagated in water [34]. Therefore, at 150 m and below, light replaced nutrients as the main limiting factor for phytoplankton growth, resulting in a low abundance of phytoplankton cells.

4.2. Comparison with Historical Data

We found that, at the station near the Pearl River Estuary in the northwest of the investigated sea area, the water temperature was low, and the salinity was high at the 30 m and 50 m water layers, this was contrary to previous studies [35]. This survey was conducted from July to August 2020, when, according to the historical data of the China Meteorological Administration, South China suffered multiple rounds of heavy rainfall during this period. The Pearl River Estuary should have therefore had a large runoff, and the lower water temperature in the coastal waters was likely to be closely related to the increased runoff. Studies showed that upwelling existed in the area from the southern Taiwan Strait to the Pearl River estuary in summer [36]. This may be the reason why the salinity in the north of the survey area was slightly higher.

Table 1. Comparison of dominant phytoplankton species composition and historical data in the northern South China Sea.

Sampling Data	Survey Area	Sampling Method	Number of Species	Average Cell Abundance (cells/L)	Average Diversity Index	Dominant Species	Reference
August 2020	15°–22° N 114°–120° E	Water sample	332	649.97	3.95	Nitzschia spp. Thalassionema nitzschioides Scrippsiella spp.	This study
May 2015	19°–23.5° N 110.5°–117.5° E	Net sample	378	762.00	3.99	Rhizosolenia alata Thalassiothrix frauenfeldii Pseudo-nitzschia pungens Eucampia zodiacus Nitzschia lorenziana Rhizosolenia gracillima	[40]
August 2014	18°–22° N 114°–116° E	Water sample	229	16318	2.37	Skeletonema costatum Fragilariopsis spp. Chaetoceros brevis T. nitzschioides Pseudo-nitzschia delicatissima Pseudo-nitzschia pungens Chaetoceros compressus Chaetoceros lorenzianus Chaetoceros pelagicus	[35]
August 2012	11°–22° N 110°–116.5° E	Net sample	206	666.70	2.67	Thalassiothrix frauenfeldii Rhizosolenia alata Thalassionema T. nitzschioides	[41]
October 2010~November 2010	18°–23.5° N 110.5°–118° E	Water sample	204	500.00	3.14	Thalassionema T. nitzschioides Navicula spp. Skeletonema costatum Chaetoceros curvisetus Rhizosolenia stolterfothii Paralia sulcata	[42]
August 2009	18°–22° N 110°–117° E	Water sample	109	819.70	—	Pseudo-nitzschia delicatissima Thalassiothrix frauenfeldii Pseudo-nitzschia pungens Detonula pumila Protoperidinium spp. Asterionella glacialis	[43]
August 2008	18°–23° N 110°–120° E	Net sample	169	180.60	—	Chaetoceros lorenzianus Pseudo-nitzschia delicatissima Thalassionema T. nitzschioides	[44]
August 2007	18°–23° N 110°–120° E	Water sample	216	11,220	2.62	Thalassionema T. nitzschioides Thalassiosira spp. Skeletonema costatum Prorocentrum minimun Gymnodinium spp.	[45]
August 2004–September 2004	18°–22° N 110°–117° E	Water sample	159	115,050	2.08	Pseudo-nitzschia delicatissima Chaetoceros curvisetus Chaetoceros diadema Prorocentrum dentatum Asterionellopsis glacialis Thalassionema T. nitzschioides Chaetoceros lorenzianus Bacteriastrum comosum Emiliania huxleyi	[46]

compares the phytoplankton survey results with historical data for the northern SCS. Similar to previous research, diatoms and dinoflagellates were the main communities in the northern SCS, with diatoms being predominant. A total of 332 species were identified in this survey. Based on long-term monitoring results from 2004 to the present, the number of species show a fluctuating upward trend. The cell abundance has fluctuated substantially, and years with high abundance were up to three orders of magnitude worse than years with low abundance. The diversity index showed a fluctuating upward trend over ten years. In addition to investigating the changes in environmental factors in the sea area, with the continuous development of trade globalization, ship transportation has played a major role in the freight market. Ballast water brings a large amount of marine phytoplankton to all parts of the world. In an appropriate environment, some species settle in the sea, resulting in a gradual increase in species diversity [3]. When compared with previous investigations, the composition of the dominant species was different. From 2008 to 2014, Chaetoceros spp. often appeared as a dominant species in the northern SCS, but in recent years, it had gradually lost its dominant position. As a typical oligotrophic area, the SCS was often limited by phosphorus [37]. In order to adapt to the phosphorus deficiency environment, the phytoplankton population will also change. Species with low phosphorus demand and whose phospholipids in cell membranes are easily replaced by lipids containing sulfur or nitrogen will gradually become dominant species [38]. The growth of Chaetoceros spp. with high phosphorus demand gradually lost its competitive advantage [39].

Widely distributed species such as Thalassionema spp. have been dominant for a long time [35,40,41,42,43,44,45,46] (Table 1). A typical morphological characteristic of Thalassionema spp. is slenderness. This shape increases the surface to volume ratio of the cells and increases the absorption of nutrients. This shape is conducive to the absorption of restricted phosphate, particularly in the oligotrophic sea area of the SCS. Thalassionema spp. often appear in clusters, which increases the cell volume and makes them resistant to sinking, so that the population can stay in the euphotic layer for a longer time to accelerate reproduction. When compared to small-sized phytoplankton living alone, phytoplankton living in groups are not easily eaten by zooplankton, which benefits population reproduction [32].

In this investigation, Scrippsiella spp., a coastal species, was the only dominant dinoflagellate species, which differed from previous studies. The environmental factors in the northern SCS are complex, and dinoflagellates showed a trend of more species observed, yet in lower quantities; therefore, it was difficult to identify a dominant population. Scrippsiella spp. somatic cells are small, and the carbon biomass they convert is relatively low. Because of their flagella and mobility, they suspend more easily in water than diatoms. Therefore, the emergence of Scrippsiella spp. as a dominant species may indicate a reduction in carbon flux in the SCS.

4.3. Assessment of Community Structure Stability and Eutrophication in the Northern SCS

The higher the diversity index, the more uniform the distribution of individuals in the community, and the more stable the community. The diversity index of the upper water body was higher than that of the lower water body. Therefore, the community in the upper water body had higher stability. At the surface, an area with low diversity index appeared in the north of the survey area, which was due to the presence of high-density water masses of Nitzschia spp. In general, the phytoplankton community structure in the northern SCS was relatively stable and was evenly distributed during the survey period. However, in the northern part of the survey area, the diversity and evenness indices were relatively low because of the massive reproduction of Nitzschia spp., and the stability of the community structure was consequently poor. The northern area is close to the shore and is greatly affected by the input of land sources, with more human interference leading to poor stability of the community structure. Nitzschia spp. have an affinity for organic-polluted water [47] and often appear in eutrophic waters [48]. Therefore, the high-value area of Nitzschia spp. in the coastal waters of the study area indicated eutrophication and slightly polluted water. Overall, the water quality in the south of the investigated area was better than that in the north.

4.4. Correlation between Phytoplankton Community Structure and Environmental Factors

Overall, the phytoplankton community in the northern SCS had no significant correlation with ammonium salt, but was negatively correlated with the sum of nitrate and nitrite. In general, among the three DIN types, phytoplankton preferentially absorbed ammonium nitrogen because they require less energy than nitrate-nitrogen [49]. However, the ammonium salt content in the SCS was extremely low [50]. Phytoplankton absorb nitrate- and nitrite-nitrogen to maintain their growth and reproduction. The extensive use of nitrate- and nitrite-nitrogen leads to a decrease in the nitrate/nitrite content and an increase in the number of phytoplankton. Therefore, the number of phytoplankton was negatively correlated with the sum of nitrate and nitrite in the data [51]. The SCS is an oligotrophic sea area, which is often restricted by nitrogen. The nitrogen quota of phytoplankton with large cell volumes is large, and the absorption capacity of phytoplankton with large cell volumes for nitrogen salt is related to its minimum nitrogen quota. Therefore, in the SCS, where nitrogen is limited, small- and medium-sized phytoplankton are usually dominant.

5. Conclusions

In the present study, we analyzed the structure and characteristics of the phytoplankton community in the northern SCS during the summer of 2020. Combined with historical data, we discussed the evolutionary trends of the phytoplankton community and the succession of dominant species. Based on the field survey and detection data, the environmental factors affecting the phytoplankton community structure in the northern SCS were analyzed, and the water quality in the sea area was evaluated. We observed that eutrophication occurred near the shore. As phytoplankton play an important role in the calculation of carbon storage, we will further analyze the change in carbon storage in the SCS and its influencing factors based on long-term data on the changes in the phytoplankton community structure in the SCS.