**Spatiotemporal Variation in Phytoplankton Community Driven by Environmental Factors in the Northern East China Sea**

**Yejin Kim 1, Seok-Hyun Youn 2, Hyun Ju Oh 2, Jae Joong Kang 1, Jae Hyung Lee 1, Dabin Lee 1, Kwanwoo Kim 1, Hyo Keun Jang 1, Junbeom Lee <sup>1</sup> and Sang Heon Lee 1,\***


Received: 13 July 2020; Accepted: 24 September 2020; Published: 26 September 2020

**Abstract:** The East China Sea (ECS) is the largest marginal sea in the northern western Pacific Ocean. In comparison to various physical studies, little information on the seasonal patterns in community structure of phytoplankton is currently available. Based on high performance liquid chromatography (HPLC) pigment analysis, spatiotemporal variations in phytoplankton community compositions were investigated in the northern ECS. Water temperature and salinity generally decreased toward the western part of the study area but warmer conditions in August led to strong vertical stratification of the water column. In general, major inorganic nutrient concentrations were considerably higher in the western part with a shallow water depth, and consistent with previous results, had no discernable vertical pattern during our observation period except in August. This study also revealed PO4-limited environmental conditions in May and August. The monthly averaged integral chlorophyll-a concentration varied seasonally, highest (35.2 <sup>±</sup> 20.22 mg m−2) in May and lowest (5.2 <sup>±</sup> 2.54 mg m<sup>−</sup>2) in February. No distinct vertical differences in phytoplankton community compositions were observed for all the sampling seasons except in August when cyanobacteria predominated in the nutrient-deficient surface layer and diatoms prevailed at deep layer. Canonical correlation analysis results revealed that nutrient distribution and the water temperature were the major drivers of the vertical distribution of phytoplankton communities in August. Spatially, a noticeable difference in phytoplankton community structure between the eastern and western parts was observed in November with diatom domination in the western part and cyanobacteria domination in the eastern part, which were significantly (*p* < 0.01) correlated with water temperature, salinity, light conditions, and nutrient concentrations. Overall, the two major phytoplankton groups were diatoms (32.0%) and cyanobacteria (20.6%) in the northern ECS and the two groups were negatively correlated, which holds a significant ecological meaning under expected warming ocean conditions.

**Keywords:** East China Sea; phytoplankton; HPLC; diatoms; cyanobacteria

#### **1. Introduction**

Phytoplankton communities play an important role in marine ecosystems, affecting carbon and nutrient cycling, the structure and efficiency of the food web, and the flux of particles to deep waters [1–3]. Phytoplankton show a clear variation in community structure and abundance in response to environmental changes, so the phytoplankton community structure can be used as a useful indicator of ecosystem and water quality characteristics [4–6]. Therefore, in order to understand the structure and function of the ecosystem, it is necessary to monitor the spatiotemporal changes in the phytoplankton community [7]. Various methods such as microscopy, flow cytometry, and pigment analysis have been used to quantitatively analyze phytoplankton community structure. Traditionally, microscopic methods have been the most commonly used to assess biomass and community structure [8]. Microscopes can provide detailed information on species and size, but this method requires taxonomic expertise and very considerable time. Furthermore, microscopic methods fall short when identifying small organisms such as some of picophytoplankton and nano flagellates [9], and the structure of fragile cells of many species can be altered during the process of fixation in Lugol's solution, formaldehyde, glutar-aldehyde, and similar fixatives [10,11]. Flow-cytometric analysis has been developed for providing more rapid and automated method for identification of communities of smaller phytoplankton. Flow-cytometric analysis requires a full understanding of the optical characteristics of the species and can mainly separate phytoplankton communities into picoplanktonic prokaryotes, picoeukaryotes, and nanoeukaryotes [12–14]. High performance liquid chromatography (HPLC) was used for this study because HPLC method can be used to measure the concentration of each pigment separately, and possible to determine the clustering of phytoplankton using the extracted marker pigments [15]. In particular, this method can provide useful information on nanoand pico-sized phytoplankton communities that are difficult to distinguish based on microscopic observations [16].

The East China Sea (ECS) is the largest marginal sea in the northern west Pacific and approximately 70% of the area is made up of a wide continental shelf. ECS is one of the most productive areas and possible sinks of carbon dioxide [17]. Furthermore, it is considered one of the most important marine fishing grounds in China [18]. Various water masses affect in the ECS, such as the Yellow Sea bottom cold water (YSCW) from the north, Changiiang diluted water (CDW) from the world's largest Yangtze river from the west, Kuroshio water (KW) from the east and Taiwan current warm water (TCWW) from the south [19–22]. Generally, the environmental conditions vary from the eastern part to the western part in the ECS. This complex topography and various water masses cause show heterogeneous and complex environmental characteristics seasonally and spatially [23]. Previous studies for phytoplankton community in the northern ECS are quite limited and most of the studies have focused on the Yangtze River estuary and adjacent waters [24–26]. Three different phytoplankton communities in the Yangtze River estuary have been identified according to water mass [27–29]. Diatoms are generally the most dominant groups in this area [27–31]. In the northern ECS near Korea, several previous studies focused on the phytoplankton community were carried out in spring [32] and summer [33,34] and mostly conducted over one season. In addition, most of the studies have focused on the spatial distribution of diatoms and dinoflagellates which can be identified under the microscope. To date, little information on the seasonal patterns in community structure that is inclusive of all phytoplankton is currently available in the northern ECS. Therefore, the present study aimed to investigate spatiotemporal changes in composition and distribution of phytoplankton community structure in the northern ECS that is possible using pigment analysis through HPLC.

#### **2. Materials and Methods**

#### *2.1. Sampling Site and Water Sampling*

Four cruises were carried out in the northern ECS from 1–9 February, 30 April–10 May, 2–10 August, and 7–17 November in 2018, as representatives for winter, spring, summer, and autumn, respectively (Figure 1; Table 1). Water samples were collected from three light depths (100%, 30%, and 1% penetration of surface irradiance, PAR) using a CTD/rosette sampler fitted with Niskin bottles. The light depths were determined by a Secchi disk. Phytoplankton pigments and physicochemical parameters (temperature, salinity, and major nutrients; N, P, and Si) were analyzed in samples drawn from the three light depths. The vertical temperature and salinity were measured by SBE9/11 CTD (Sea-Bird Electronics, Bellevue, WA, USA) sensors.

**Figure 1.** Sampling stations in the northern East China Sea, 2018. The major currents in the northern East China Sea are based on [19].


**Table 1.** Description of sampling stations in the northern East China Sea for each cruise period, 2018.

#### *2.2. Phytoplankton Pigment Analysis*

Water samples for photosynthetic pigment analysis were filtered through 47 mm GF/F filters (Whatman, Maidstone, UK; 07 μm), and then stored in a freezer at −80 ◦C to avoid degradation. Pigments were extracted in 100% acetone (5 mL) with cantaxanthin (100 μL) as an internal standard for 24 h in the dark at 4 ◦C and placed in an ultra-sonic bath to disrupt a cell [35,36]. An aliquot water of 1 mL was passed through a 0.45 μm PTFE syringe filter to rid the samples of particles. After the extracts were centrifuged for 10 min at 3500 rpm to remove cellular debris and glass fibers. All procedures were carried out under low light conditions to minimize pigment degradation. Pigments were analyzed using a HPLC (Agilent Infinite 1260, Santa Clara, CA, USA), and the separation of pigments was performed using a slightly modified method of [37] and [38]. The peaks were identified based on their retention time compared with those of pure standards (chlorophyll a, chlorophyll b, β-carotene, fucoxanthin, prasinoxanthin, 19 -hexanoyloxyfucoxanthin, diadinoxanthin, 19 -butanoyloxy-fucoxanthin, peridinin, alloxanthin, neoxanthin, violaxanthin, prasinoxanthin, lutein, and zeaxanthin obtained from DHI, Denmark). The concentrations of pigments in samples were calculated as following equation. Standard response factor (Rf) was calculated based on the standard pigment and dividing the concentration of the standard by the measured peak area [38].

$$\text{Concentration} = \text{Area} \times \text{Rf} \times \text{(Ve/Vs) [ngL}^{-1}\text{]} \tag{1}$$

Area = area of the peak in the sample [area] Rf = standard response factor [ngL−<sup>1</sup> area<sup>−</sup>1] Ve = AIS/(peak area of IS added to sample) × (Volume of IS added to sample) [L] Vs = volume of filtered water sample [L] AIS = peak area of IS when 1 mL IS is mixed with 300 μL of H2O IS = Internal Standard

The CHEMTAX program was used to estimate the contribution of the different phytoplankton community structure to the total chlorophyll a [15,16]. The contribution of diatoms, dinoflagellates, prymnesiophytes, chlorophytes, chrysophytes, cryptophytes, cyanobacteria and prasinophytes were calculated based on the program. Twelve pigments and initial pigment ratios for around the Korean peninsula were used for this study [38]. In the following CHEMTAX, to derive the most accurate phytoplankton groups, data was binned according to sampling month and three light depths (100%, 30% and 1% penetration of surface irradiance, PAR) [39,40].

#### *2.3. Dissolved Inorganic Nutrient Concentration*

An aliquot of water (100 mL) was filtered onboard through GF/F filters (Whatman, Maidstone, UK; 07 μm) for dissolved inorganic nutrient concentrations (NH4, NO2, NO3, PO4, and SiO2) and kept frozen (−20 ◦C) until further analysis. Concentrations of nutrients were determined in an automatic analyzer (Quaatro, Bran + Luebbe, Germany) belonging to the National Institute of Fisheries Science (NIFS), Korea. Dissolved inorganic nitrogen (DIN) concentrations were calculated as the sum of NH4, NO2 and NO3.

For verifying P-limited water conditions, Excess Nitrate (ExN), which is calculated as ExN = DIN-(R\*PO4) (R = Redfield N:P ratio of 16), was used in this study [41–43]. ExN values of <0 indicate PO4-enriched condition, while ExN > 0 indicates the converse condition [41–43].

#### *2.4. Statistical Analysis*

Canonical correspondence analysis (CCA) was performed using "past 3" software to explain the relationship between environmental parameters and phytoplankton community structure [44]. Temperature, salinity, depth, DIN, PO4, SiO2, and ExN were include for the environmental parameters.

#### **3. Results**

#### *3.1. Physical Environments*

Seasonal distribution patterns of temperature and salinity during the four cruises are summarized in Table 1. The average temperature was lowest in February (winter) at 13.7 ± 2.9 ◦C and gradually increased to highest in August (summer) at 24.2 ± 4.7 ◦C. The average salinity was highest at 34.1 ± 0.6 in February and lowest at 32.3 ± 0.7 in August. In February, the water temperature decreased toward the western part from the eastern part in the study area and the salinity showed the same trend as the water temperature (Table 1). The water temperature and salinity in May (spring) were also relatively higher in the eastern part and lower in the western but the difference in water temperature was smaller in May compared to that in February. On the other hand, the water temperature and salinity were inversely spatially distributed in August with low in the eastern and high in the western parts and the differences were smallest during the observation period. Vertically, the temperature increased with depth in August, which resulted in a strong stratification (Figure 2). In November (autumn), the patterns in water temperature and salinity were similar to those in February and May.

**Figure 2.** Vertical profiles of temperature and salinity in the northern East China Sea, 2018. (**a**) February, (**b**) May, (**c**) August, and (**d**) Nov for temperature; and (**e**) February, (**f**) May, (**g**) August, and (**h**) November for salinity.

#### *3.2. Dissolved Inorganic Nutrient Concentrations*

Inorganic nutrient concentrations at the three light depths for each cruise are summarized in Table 2. DIN and PO4 concentrations were highest in February and remained low in other seasons, whereas SiO2 tended to increase from May to August and November. In February, the ranges of DIN, PO4 and SiO2 concentrations from surface to 1% light depths were 5.3–14.1 μM, 0.3–0.6 μM, and 6.0–16.8 μM, respectively. There were no distinct vertical patterns, but in the horizontal direction, DIN, PO4, and SiO2 tended to increase from the northeast to the southwest stations. In May, the ranges of DIN, PO4, and SiO2 concentrations were 2.5–12.3 μM, <0.1–0.3 μM, and 3.4–12.4 μM, respectively. No marked vertical patterns in the concentrations were observed but horizontally, DIN and SiO2 showed relatively higher in the western part compared to the eastern part in May. Generally, PO4 concentrations in May

were very low at all the stations with an average of 0.1 μM except for St. 316-21. The ranges of DIN, PO4, and SiO2 concentrations were 1.6–16.9 μM, <0.1–0.5 μM, and 2.1–14.7 μM, respectively, in August. Unlike other seasons, noticeable vertical distributions of nutrients were observed in August with low concentrations at surface but increasing with depth. In November, the ranges of DIN, PO4, and SiO2 concentrations were 2.1–15.9 μM, 0.1–0.6 μM, and 2.0–15.8 μM, respectively. Nutrient concentrations were relatively higher in the western part compared to the eastern part and the differences in the concentrations between the eastern and western parts were largest in November among the four cruises but no vertically distinct distributions were found.


**Table 2.** The dissolved inorganic nutrient concentrations (μM) at the euphotic depths (100%, 30%, and 1%) of water column in the northern East China Sea, 2018.

**Table 2.** *Cont*.


#### *3.3. Phytoplankton Biomass and Community Structure*

The monthly averaged chlorophyll-a concentration integrated from surface to 1% light depth was highest (35.2 <sup>±</sup> 20.22 mg m<sup>−</sup>2) in May and lowest (5.2 <sup>±</sup> 2.54 mg m<sup>−</sup>2) in February (Figure 3). In February, the integral chlorophyll-a concentration was relatively lower in the western part (2.8 mg m<sup>−</sup>2) compared to that in the eastern part (6.7 <sup>±</sup> 2.46 mg m−2) of our study area, which is similar to the temperature distribution. In May, the integral chlorophyll-a concentration was highly variable across the study area with the range of 8.2–70.0 mg m−<sup>2</sup> and the chlorophyll-a concentration was relatively higher in the southern part than in the northern part. In August, no distinct spatial distribution in the chlorophyll-a concentration was observed. In November, the spatial distribution in the integral chlorophyll-a concentration was opposite to that in August, which is similar to the nutrient distribution patterns (Table 2).

**Figure 3.** Horizontal distributions of water column-integrated chlorophyll-a concentration from surface to 1% light depth in the northern East China Sea (**a**) February, (**b**) May, (**c**) August, and (**d**) November.

Generally, no distinct vertical differences in phytoplankton community compositions were observed at 100%, 30%, and 1% light depths for all the sampling seasons except August (Figure 4). The phytoplankton community compositions in August were conspicuously different between 30–100% light depths and 1% light depths. Cyanobacteria predominated, contributing 63.3% to the total phytoplankton biomass and diatoms were the second most abundant group (15.5%) at 100% light depths, whereas diatoms contributed 58.2% followed by dinoflagellates (13.0%) and other classes (<10%) at 1% light depths (Figure 4). Spatially, noticeable differences in phytoplankton community between the eastern and western parts were observed season, especially in November. Diatoms predominated in the western part, contributing 58.6% to the total phytoplankton biomass and cryptophytes were the second most abundant group (27.4%), whereas cyanobacteria predominated (45.0%) in the eastern part followed by cryptophytes (31.0%) in November. These two dominant groups were significantly (*p* < 0.01) correlated with water temperature (Figure 5). The contribution of diatoms was negatively related with water temperature (y = <sup>−</sup>0.0227x + 0.8061, r<sup>2</sup> = 0.7207), whereas the contribution of cyanobacteria had a positive relationship with water temperature (y <sup>=</sup> 0.0309x <sup>−</sup> 0.3506, r<sup>2</sup> <sup>=</sup> 0.824).

**Figure 5.** Relationships between contributions of two major phytoplankton communities and water temperature for all the cruise period, 2018. (**a**) Diatom (**b**) Cyanobacteria.

Overall, the major phytoplankton community in the study site was diatoms with a contribution more than 30% although it varied seasonally from 9.8% (November) and 50.0% (February) (Figure 6). Cyanobacteria were the second highest contributors ranging from 0% to 38.3% during our study period. Cyanobacteria were not appeared in February but their contribution increased steadily from May to November. The contributions of cryptophytes ranged from 7.8% to 30.7%. The contributions of prymnesiophytes were 5.4–7.6%, with a similar contribution for each cruise. Chlorophytes contributed 0.5–16.1%, with the highest contribution in February and were hardly observed in May and November (0.5% and 0.8%, respectively). Chrysophytes had the contributions of 0.6–14.0%, showing their highest contribution in February. Dinoflagellates showed their contributions of 0–17.4% and their highest contribution was in August. In the case of prasinophytes, they showed the contributions ranging from 0% to 14.2% and the highest contribution was in May (Figure 6).

**Figure 6.** Seasonal contributions of phytoplankton communities averaged from all the stations for each cruise period in the northern East China Sea, 2018.

#### *3.4. Canonical Correspondence Analysis (CCA)*

CCA results between phytoplankton community and environmental parameters for each season are presented in Figure 7. In February, diatoms and chryptophytes showed negative correlations with temperature and salinity and positive correlations with nutrients, whereas chrysophytes and chlorophytes had positive correlations with temperature and salinity. In May, diatoms had no significant correlation with any environment parameter, whereas cyanobacteria and chrysophytes had negative correlations with nutrients and cyanobacteria had positive correlations with temperature and salinity. In August, cyanobacteria had a positive correlation with temperature and negative correlations with nutrients and depth. In comparison, diatoms had significantly positive correlations with nutrients and depth in August. Similarly, cyanobacteria showed a strong positive correlation with temperature and negative correlations with depth and nutrients in November. In comparison, diatoms had negative correlations with temperature and depth, and positive correlations with nutrients in November.

169

East China Sea (**a**) February (**b**) May (**c**) August (**d**) November.

#### **4. Discussion**

The northern ECS is a typical temperate water seasonally affected mainly by four different water masses. The CDW, TCWW, KW, and YSCW, but their influence can vary seasonally [45,46]. Mixed waters were mainly distributed in our study area in February but YSCW was found at the most western stations (Sts. 315-21, 316-21, and 317-21) in May based on T-S diagrams. Low temperature, strong winds, and vigorous vertical mixing are generally observed in February during the Northeast Monsoon [47,48]. Weak surface stratification begins May and the water column was well stratified in August with TCWW mainly distributed at surface layer whereas the YSCW is mainly distributed at bottom layer (73 m). Normally, the surface layer in summer has a low density due to a high temperature and low salinity water from the CDW and the lower layer forms a strong stratification due to the distribution of the low temperature water from the YSCW and high salinity water from the TCWW [49]. In the northern ECS, the runoff from the Changjiang river is maximum in summer and minimum in winter [50]. According to a previous study, CDW is a main source of fresh water input in the ECS, increasing from spring to summer [51]. In November, the water masses were relatively well mixed (Figure 2).

In this study, we found that major inorganic nutrient concentrations were considerably higher in the western part compared to those in the eastern part in February and November during this study (Table 2), which is consistent with previous results [52]. The waters in the western part of the ECS are fully mixed from surface to the bottom because of the shallow water depth (<50 m), but in the eastern part vertical mixings occur only in the upper layer [35]. The noticeable vertical difference in nutrient concentrations were observed in August (Table 2) due to a strong stratified water column (Figure 2) which suppressed the upwelling of nutrients from the bottom layer. In addition, the seasonal average N:P ratios in the study area ranged from 10.5 to 422.9 (55.1 ± 64.6) which are higher than the Redfield ratio of 16 generally found in various oceans. [53] defined nutrient limitations following as; PO4 limitation when Si:P > 22 and DIN:P > 22; N limitation when DIN:P < 10 and Si:DIN > 1; Si limitation when Si:P < 10 and Si:DIN < 1. Various studies suggested that PO4 is a limiting nutrient to phytoplankton growth in the ECS [41,54–56]. This study also verified PO4-limited environmental conditions in May (124.5 ± 91.1) and August (50.3 ± 29.3) (Figure 8). According to [55] a high N:P ratio is related to very low PO4 concentration. Indeed, low PO4 concentrations (approximately 0.1 μM) were observed in May and August. These PO4-limited conditions could have caused the seasonal variation in phytoplankton community in the ECS. According to [57], Diatoms would have a higher phosphorus demand relative to other phytoplankton groups which may be reflected by lower N:P ratios in diatoms compared to those in other groups. Indeed, [43] showed the phytoplankton community in mid-shelf ECS in summer and identified 2 distinct phytoplankton communities under two major water masses with different nutrient conditions: PO4-rich Kuroshio intermediate water (KW) indicated by a low ExN value leading to diatom domination and PO4-limited CDW indicated by high ExN leading to small phytoplankton domination such as chlorophytes and cyanobacteria. However, we did not find the relationships in this study. In spring, diatoms were mostly dominant despite of PO4-limited water conditions. The PO4- limited condition in spring could be due to the spring bloom of diatoms, which is consistent with the results in Chesapeake Bay [58]. Even in our summer cruise period, opposite relationship between diatoms and ExN was observed. This discrepancy between this and previous studies could be caused by several factors. [42] observed pronounced effects of KW and CDW and a large range of PO4 concentration, whereas in this study, TCWW current was largely dominant rather than the KW and CDW and narrow range of PO4 concentration. In addition, the analysis in [42] was performed only in the surface layer, whereas this study was performed within the euphotic layer (surface to 1% light depth). Indeed, we also found a dominance of cyanobacteria in the surface layer with a lack of PO4 and diatoms dominant at the nutrient-rich depths as discussed in detail below.

**Figure 8.** Scatter diagrams of atomic nutrient ratios at the euphotic depths (100%, 30%, and 1%) in the northern East China Sea, 2018.

The distinct vertical difference in dominant phytoplankton communities was observed in our study area in August with cyanobacteria predominated at surface layer and diatoms prevailed at deep layer. A strong water stratification appeared in the study area could have caused the vertical pattern of phytoplankton community [59]. A stratified water column restricts the upward supply of major inorganic nutrients to the upper euphotic surface layer. According to the resource competition theory [60–62], pico-phytoplankton are favored over larger phytoplankton in nutrient-limited conditions because of their higher nutrient affinity associated to their small size [63–65]. Thus, small size cyanobacteria are predominant in the nutrient-deficient surface layer in August. Since zeaxanthin is a marker pigment in cyanobacteria and plays an important role in protecting cyanobacteria against photoinhibition [66], the high concentration of zeaxanthin at surface might be due to much higher photosensitivity than that at the deep water column [67,68]. In addition, the water temperature was approximately 7 ◦C higher at surface than the deep layer in August. Indeed, CCA revealed a positive correlation between cyanobacteria and temperature in this study (Figure 7c). As water temperature exceeds 20 ◦C, the growth rates of eukaryotic phytoplankton usually stabilize or decrease whereas those of many cyanobacteria species increase because of their competitive advantage over high temperature [69–71]. Therefore, the water temperature and nutrient distribution in August had a great influence on the vertical distribution of phytoplankton communities.

During the four research periods, spatial difference in phytoplankton community was not significantly high, but in November, there was a clear difference in phytoplankton community between the western and eastern parts. The most predominant phytoplankton communities were diatoms in the western part and cyanobacteria in the eastern part. The cryptophytes were the third dominant species in both western and eastern parts. CCA result showed that cyanobacteria are associated with high temperature, high salinity, low nutrient concentrations, and depth, whereas diatoms are associated with low temperature and high nutrient concentrations in November (Figure 7d). Nutrient concentrations were also horizontally different, gradually decreasing toward the west. In relation to the distribution of these nutrients, zeaxanthin (major pigments of cyanobacteria) showed a negative correlation with nutrients (*p* < 0.01, *t*-test), whereas fucoxanthin (major pigments of diatoms) showed a positive correlation with nutrients (*p* < 0.01, *t*-test). These correlations with the nutrient concentrations indicate that nutrients are a major driver of the spatial difference in phytoplankton community distribution in November. Moreover, there was a significant difference in light condition based on the euphotic depths between in the western and eastern parts. The euphotic layer up to 1% depth was 43 m on average in the eastern part, whereas it was 7 m in the western part. Light can be a limiting factor largely influencing the spatial distribution of picophytoplankton, probably because the decreasing light in water is mostly variable in the water column [72,73]. According to [74], diatoms have high growth efficiency under a low light condition. In comparison to the phytoplankton community in the ECS, several studies in

other oceanic basins influenced by large rivers were compared. Similar to the East China Sea, the Gulf of Mexico is a phosphate-limited environment during summer period [75,76]. These studies showed that diatoms generally predominate and cryptophytes are the second most abundant group in the winter and spring periods and cyanobacteria are most dominant during PO4-limited summer time compared to other seasons in the Gulf of Mexico. The spatiotemporal variations in the region are controlled mainly by river flow runoff, along with other environmental variables such as wind pressure and stratification [75,76]. In contrast, Western Tropical North Atlantic, which is a region largely affected by the Amazon River, is mainly dominated by the diatom-diazotroph associations (DDAs) [43]. In this region, the phytoplankton community structure and distributions are controlled by low concentrations of inorganic nitrite and nitrate (NO2 + NO3) [43].

Based on the four different seasonal observations in this study, the yearly average contributions of different phytoplankton communities were 32.0%, 20.6%, 17.2%, 6.9%, 6.4%, 6.4%, 5.7%, and 5.0% for diatoms, cyanobacteria, cryptophytes, prymnesiophytes, chlorophytes, chrysophytes, dinoflagellates, and prasinophytes, respectively, in the northern ECS. Chlorophyll-a concentrations were highest in May and lowest in February in this study which is consistent with previous results in the ECS [56,77]. Previous studies reported that diatoms are associated with phytoplankton blooms in early spring and that the dominant species in the ECS are mostly chain-forming diatoms such as *Pseudonitzschia delicatissima*, *Thalassionema nitzschioides*, and *Paralia sulcate* [28]. Consistent with previous observations, this study also verified that the dominant species were diatoms during the spring bloom in May.

#### **5. Summary and Conclusions**

There are multiple factors including light intensity, stability of water column, temperature, and nutrient conditions [78] that can cause variations in phytoplankton compositions and spatial distributions. The seasonal variations in the phytoplankton community were distinct in our study area although spatial and vertical variations were observed along the seasons. Diatoms appeared to be dominant in the northern ECS throughout the year in this study. Normally, diatoms are known to be competitive over other species at low water temperatures [79]. Therefore, in February with a low water temperature (Figure 2) and high nutrient concentrations (Table 2), diatoms were most predominated among our study periods. Moreover, diatoms are more efficient at high nutrient concentrations than small phytoplankton [80] and they can quickly respond to nutrient inputs [81]. Contrary to diatoms, cyanobacteria, as the next dominant species, started to appear in May and showed their contribution gradually increased from May to November in this study. According to previous research, water temperature is the main control factor for the distribution of cyanobacteria [82]. In this study, we also found that water temperature is a main factor driving the seasonal variation in the cyanobacteria contribution in the northern ECS throughout the year based on CCA result (Figure 7). Overall, the cyanobacteria contribution was strongly negatively correlated with the diatom contribution in the northern ECS during our study period in 2018 (Figure 6). This result implies an ecologically significant meaning for the marine ecosystem in the northern ECS. Under expected warming ocean scenarios, the potential change in dominant phytoplankton groups from diatoms to cyanobacteria could cause substantial differences in quantity and qualitative aspects of primary marine food sources in the northern ECS. Comprehensive monitoring for qualitative and quantitative characteristics of different phytoplankton communities is warrant for a better understanding their potential consequences on the entire marine ecosystem in the ECS.

**Author Contributions:** Conceptualization, Y.K., S.-H.Y., H.J.O., and S.H.L.; methodology, Y.K. and J.J.K.; validation, Y.K., S.-H.Y., and S.H.L.; formal analysis, Y.K.; investigation, J.J.K., J.H.L., D.L., K.K., H.K.J., and J.L.; data curation, Y.K.; writing—original draft preparation, Y.K.; writing—review and editing, Y.K., J.J.K., and S.H.L.; and visualization, Y.K. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was supported by the "Development of marine ecological forecasting system for Korean waters (R2018067)" funded by the National Institute of Fisheries Science (NIFS), Korea. This research also partly supported by a part of the project entitled "Construction of Ocean Research Station and their application" funded by the Ministry of Oceans and Fisheries, Korea.

**Acknowledgments:** We thank the anonymous reviewers who greatly improved an earlier version of manuscript. **Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

### *Article* **Phytoplankton Community in the Western South China Sea in Winter and Summer**

**Changling Ding 1,2, Jun Sun 2,3,\*, Dhiraj Dhondiram Narale <sup>2</sup> and Haijiao Liu <sup>2</sup>**


**Abstract:** Phytoplankton are known as important harbingers of climate change in aquatic ecosystems. Here, the influence of the oceanographic settings on the phytoplankton community structure in the western South China Sea (SCS) was investigated during two seasons, i.e., the winter (December 2006) and summer (August–September, 2007). The phytoplankton community was mainly composed of diatoms (192 taxa), dinoflagellates (109 taxa), and cyanobacteria (4 taxa). The chain-forming diatoms and cyanobacteria *Trichodesmium* were the dominants throughout the study period. The phytoplankton community structure displayed distinct variation between two seasons, shifting from a diatom-dominated regime in winter to a cyanobacteria-dominated system in summer. The increased abundance of overall phytoplankton and cyanobacteria in the water column during the summer signifies the impact of nutrient advection due to upwelling and enriched eddy activity. That the symbiotic cyanobacteria–diatom (*Rhizosolenia–Richelia*) association was abundant during the winter signifies the influence of cool temperature. On the contrary, *Trichodesmium* dominance during the summer implies its tolerance to increased temperature. Overall, the two seasonal variations within the local phytoplankton community in the western SCS could simulate their community shift over the forthcoming climatic conditions.

**Keywords:** South China Sea; upwelling; eddy; diatom; *Trichodesmium*; *Rhizosolenia–Richelia*

#### **1. Introduction**

The South China Sea (SCS), a typically oligotrophic area, is the largest marginal sea in the tropical Pacific Ocean. The upper SCS is characterized by the monsoon-induced circulation and mesoscale eddies which predominantly impact biogeochemical progress; concurrently, the riverine input from the Pearl and Mekong Rivers dramatically affects nutrient exchange in the SCS [1–4]. Despite receiving large amounts of terrestrial nutrient input through the riverine discharge, the SCS only utilizes a small portion to support productivity [5,6]. Nutrient concentrations in the SCS are often below the detectable limits [7]. The ratios of nitrogen to soluble reactive phosphorus (N/P) were much lower than 16 (the Redfield N/P Ratio), suggesting nitrogen limitations in the SCS [8]. Nutrient deficiency causes relatively low chlorophyll concentrations [9–11], and low phytoplankton stock compared with other adjacent marginal seas [12–14]. The western SCS is located towards the east of the Vietnam coast, where the deep basin is extended by steep slopes, with a maximum depth reaching 4000 m. Vietnamese upwelling is one of the typical features in the western SCS, and the Vietnam offshore flowing to the north in summer causes a local enhancement of Vietnamese upwelling intensity [6]. In the western SCS, cyclonic eddies form frequently with a raised thermocline in winter, and anticyclonic eddies form with a depressed thermocline in summer [15]. Besides, summer circulation often has a dipole structure associated with an eastward jet, appearing off central Vietnam [16].

**Citation:** Ding, C.; Sun, J.; Narale, D.D.; Liu, H. Phytoplankton Community in the Western South China Sea in Winter and Summer. *Water* **2021**, *13*, 1209. https://doi.org/ 10.3390/w13091209

Academic Editor: Bo Kyung Kim

Received: 9 February 2021 Accepted: 9 April 2021 Published: 27 April 2021

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**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

These physical processes control nutrient flux from the deep water into the euphotic zone and subsequently affect the ocean's ecological status [17].

Marine phytoplankton, as the most important primary producer at the base of the marine food chain, are responsible for generating roughly half of the global net primary production, and play a key role in the elements cycle and energy flow in a marine ecosystem as the primary producers [18]. Physical processes such as upwelling and eddies are particularly relevant to phytoplankton productivity [19]. The instabilities of these processes help to create and maintain localized environments that favor the growth of phytoplankton [17]. The coupling between these physical and biological processes influences phytoplankton biomass and seasonal succession [20]. In the western SCS, a series of physical processes, controlling nutrient flux into the euphotic zone, play a profound role in supporting the phytoplankton growth and their spatio-temporal distribution [21–26]. High chlorophyll *a* concentration often occurs in the western SCS, where phytoplankton blooms even appear in summer when southwest monsoons are parallel to the Vietnamese coast [21,22]. Wang and Tang (2014) observed that the patchiness in spatial and vertical phytoplankton distribution was controlled by the vertical flux of nutrients caused by curl-driven upwelling in the western SCS [23]. Liang et al. (2018) found that the high chlorophyll *a* belt was determined by the advection of coastal upwelling water by the northeastward jet and the resultant cyclonic/anticyclonic eddies, which were defined as a 'jet-eddy system' [27]. Wang et al. (2016) calculated that the contribution of phytoplankton groups to the total chlorophyll *a* biomass changed along with cyclonic eddy dimensional structure [25].

Many studies have investigated phytoplankton biomass and the coupling of biological– physical processes in the western SCS. These existing related studies were focused mainly on pigments and remote sensing observations. However, yet, quantitative measures of phytoplankton diversity, a comprehensive interpretation of phytoplankton successions, and knowledge of interactions with diverse hydrodynamic settings are still meager. Knowledge of phytoplankton species and their response within the marine environment is essential to understand the responses of ocean biota to a dynamic ecosystem and changing global climate [28]. Here, we carried out a series of biogeochemical investigations during two seasons (winter and summer) in the western SCS. In this study, the cold-core cyclonic eddies and warm-core anticyclonic eddy were observed during the summer investigation [29]. The main objectives of this study were to evaluate the spatial and temporal difference of the phytoplankton community structure in different seasons, aiming to supply a cue of how physicochemical influence on the phytoplankton community shifts, to provide insights into the acclimation and adaptation of the phytoplankton community to a changing marine environment.

#### **2. Materials and Methods**

#### *2.1. Study Area*

The sampling was carried out from the western SCS extending eastwards from the Vietnamese shelf region towards the eastern deep basin (10–15◦ N, 110–112.5◦ E) (Figure 1). In this region, the seasonal reversal of monsoon winds mainly controls the upper-ocean circulations (Shaw and Chao, 1994). During the northeast (or winter) monsoon (November to March) a stronger cyclonic gyre exists in the western portion of the southern SCS [30]. A strong coastal jet occurs in the western boundary of the SCS, southward along the continental shelf from the Chinese coast to southern Vietnam [31], causing the basin-scale circulation. On the contrary, during the southwest (or summer) monsoon (April to August), the weaker anticyclonic gyre dominates upper layer circulations in the southwestern SCS. The northward jet separates from the Vietnamese coast at about 12◦ N in summer [32] and eddy pairs associate with the jet forms [33]. The upwelling takes place off the Vietnamese coast, which flows northeastward and carries the cold continental water into the open basin [31]. Two cruises were conducted on the R.V. 'Dongfanghong 2 during the southwest monsoon (December 2006) and northeast monsoon (August–September, 2007) periods to assess the phytoplankton community structure in the western SCS. Two cyclonic mesoscale

cold eddies were monitored in August and September, which were named as cold eddy 1 (CE1) and cold eddy 2 (CE2), respectively, during the cruise using in situ current, hydrographic measurements as well as concurrent satellite altimeter observations [29,34]. With a relatively steady intensity and radius, the CE2 endured for two weeks after its swift formation in late August and prior to its quick dissipation in mid-September. The anticyclonic warm eddies, marked WE, were also observed in the survey area [29]. During this study, a total of 15 and 36 stations were investigated in winter and summer, respectively. The sampling stations marked with dotted circles were located within the eddy area (Figure 1).

**Figure 1.** Map indicating the sampling stations along the southwestern region of the South China Sea (SCS) (Vietnamese upwelling region) (**A**). The arrows indicate the general surface current patterns in the SCS during the winter (black dotted arrows) and summer (black solid arrows) [35]. Map indicating the sampling locations during the winter (**B**) and summer seasons. The red dotted circle shows the eddy area, i.e., CE1: cold eddy 1, CE2: cold eddy 2, and WE: warm eddy [29,35]. The blue dotted lines show sampling sections defined as Section A, Section B, Section C, and Section D.

#### *2.2. Sample Collection and Analysis*

Seawater samples were collected from seven depths (0, 25, 50, 75, 100, 150, and 200 m) at 51 sampling stations using the Niskin bottles attached to a Rosette water sampler fitted with a Seabird 917 Plus site CTD system. A total of 40 and 230 samples for phytoplankton analysis were collected in winter and summer respectively. Temperature and salinity data were derived from the Seabird CTD. For enumeration of the phytoplankton community, a 3 L seawater sample was concentrated to 1 L by using 10 μm mesh and taken into polyethylene (PE) bottles, then fixed with 2% buffered formaldehyde solution and stored in darkness until completing the voyage.

After returning to the laboratory, the Utermöhl method was applied for phytoplankton water sample analysis [36]. A 1 L subsample was stood for 48 h, then 800 mL supernatant was removed carefully by siphoning through a catheter; it was important to note that the position of the catheter avoided touching the bottom of the bottle. After that, the remaining 200 mL liquid was well mixed gently, half of which was further concentrated with a 100 mL sedimentation column (Utermöhl method) for 48 h sedimentation [37]. Then, the phytoplankton species were identified and enumerated under an inverted microscope (AE2000, Motic, Xiamen, China) at 400× (or 200×) magnification, and five enumerations were performed under the non-overlapping field (529 field in total). The size limit of resolution for this analysis was ~5 μm. The phytoplankton species were identified using published standard literature [38] and the World Register of Marine species (http://www. marinespecies.org, Updated: 12 April 2021). The species identification was as close as possible to the species level.

For nutrient estimation, 100 mL of seawater was collected in the clean plastic bottles and stored at −20 ◦C till further analysis. Nutrition data were supplied by Dr. Min Han Dai's lab, Xiamen University. In detail, dissolved inorganic nitrogen NOx (NO3 − + NO2 −) was analyzed by reducing NO3 − to NO NO2 − with a Cd column and then determining NO− <sup>2</sup> using the standard pink azo dye method, and a flow injection analyzer [39]. The dissolved inorganic phosphorus (PO4 <sup>3</sup>−) concentrations were measured using two independent methods. For PO4 <sup>3</sup><sup>−</sup> concentrations > 500 nM, the concentration was measured by the standard molybdenum blue procedure [40], and for PO4 <sup>3</sup><sup>−</sup> concentrations < 500 nM, measurements were taken with a home-made ship-board C18 enrichment-flow injection analysis system [24,41]. Silicate concentrations were estimated using the standard silica aluminum blue spectrophotometry method [39].

#### *2.3. Data Analysis*

Horizontal and depth-integrated distribution of phytoplankton and physiochemical parameters were projected using Ocean Data View 4.7.6 (https://odv.awi.de/en/software/, released on 2 March 2018). The histogram, scatter diagram, and box-whisker plots were plotted with Origin (Version 8.5) [42]. The Spearman's correlation analysis and canonical correspondence analysis (CCA) between assemblages and physicochemical parameters were performed using Past3 software (http://www.canadiancontent.net/tech/download/ PAST.html, released on June 2013).

The phytoplankton community diversity was evaluated mainly using the Shannon– Wiener diversity index (*H* ), Pielou evenness index (*J*), and dominance index (*Y*) [43]. The dominant species of phytoplankton was determined by dominance index (*Y*).

The Shannon–Wiener (S–W) diversity index (*H* ) was calculated by the equation below:

$$H\nu = -\sum\_{i=1}^{S} P\_i \log\_2 P\_i \to H\_{\text{max}} = \log\_2 S \tag{1}$$

where *Pi* is the relative cell abundance of a species, *i* is the numbers of the *i*-th species, and *S* is the numbers of total species in a sample. The evenness index (*J*) was calculated from *H'* using the following formula:

$$J = \frac{H'}{\log\_2 S} \tag{2}$$

where *H'* is the S–W diversity index, and *S* is the number of the total species in a sample. The phytoplankton dominance index (*Y*) was calculated as follows:

$$Y = \frac{n\_i}{N} \cdot f\_i \tag{3}$$

where *ni* is the number of the individual species, *N* is the total number of all species, and *fi* is the occurrence frequency of the species in a sample.

Community alpha diversity indices (Shannon–Weiner index *H'*, and Pielou evenness index *J*, Species Richness, Simpson, Chaol) were calculated and performed using the 'vegan' package by R version 3.6.1. (https://www.r-project.org/, released on 5 July 2019) [44]. The Kruskal–Wallis test was used to compare the abundance differences of phytoplankton groups and diversity indices among defined groups. The two-tailed *t*-test was used to compare the abundance of phytoplankton groups between different defined groups.

#### **3. Results**

#### *3.1. Seasonality in the Environmental Variables*

The surface temperature and salinity in the winter ranged from 27.06 to 28.69 ◦C and from 33.15 to 33.72, respectively. In summer the surface temperature varied from 26.53 to 29.78 ◦C, whereas surface salinity ranged from 28.86 to 34.14. During this period, two cyclonic eddies were accurately captured throughout the cruise using in situ current and hydrographic measurements as well as the concurrent satellite altimeter observations [29,35]. One cold eddy, CE1, lay in the north region (112◦ E, 14◦ N), which lasted from 15 to 31 August. The other cold eddy, CE2, located in the south region (111◦ E, 12◦ N), endured for one week (1–8 September). Meanwhile, a warm eddy (WE) was observed near the CE2 (112◦ E, 10◦ N) (6–8 September) (Figure 1). During both seasons, the entire study region was divided into the following eddy stages (as adopted by [35]): no eddy stage (NE, in winter (December 2006)), CE1 stage (15–24 August 2007), CE1 relaxation stage (CE1-r, 25 to 31 August 2007), CE2 (1–8 September 2007), and WE (6–8 September 2007). The sampling stations marked with dotted circles were located within the eddy area (Figure 1). The data of various environmental factors during both seasons are given in Table A1. During all stages, the temperature decreased with water depth. The temperature at 50–100 m was relatively high in the WE stage compared with other stages (Table A1). The salinity increased with water depth. The nutrition concentrations also increased with water depth, and they were relatively high in the winter compared with that in the summer (the eddy stages). Among the different cyclonic stages in the summer, the average concentration of inorganic nitrogen (nitrate and nitrite) was almost below 0.2 μmol/L (except in the CE1 stage) in the upper water (0–50 m). However, in the middle water column (50–100 m), the average concentration of inorganic nitrogen, phosphate, and silicate were relatively higher during the CE1 and CE2 stages than during the CE1-r and WE stages.

#### *3.2. Phytoplankton Species Composition in the Study Region*

During the winter, a total of 112 phytoplankton taxa belonging to six phyla (Bacillariophyta, Dinophyta, Cyanophyta, Chlorophyta, Haptophyta, and Chrysophyta) and 39 genera were identified in the study region. The phytoplankton community was mainly composed of diatoms with 99 taxa belonging to 29 genera. Among diatoms, *Chaetoceros* and *Rhizosolenia* emerged frequently. Species in the genera *Bacteriastrum* and *Coscinodiscus* declined evidently. Nine dinoflagellate taxa belonging to six genera were reported during the present study. The frequency of most dinoflagellate species, especially the species belonging to the genera *Protoperidinium*, *Ceratium*, *Oxytoxum*, *Amphisolenia*, *Ornithocercus*, *Podolampas,* and *Dinophysis,* was decreased in the winter compared to summer. During the winter season, the cyanobacteria group was mainly comprised of *Trichodesmium thiebautii*, *Trichodesmium erythraeum,* and the symbiotic cyanobacteria *Richelia intracellularis*. Among them, *T. thiebautii* was the most abundant (0.01), although with an extremely low occurrence frequency (0.50) (Table 1). Besides *T. thiebautii*, the diatom species *Thalassionema nitzschioides*, *Nitzschia* spp., *Thalassiosira rotula*, *Navicula* spp., and *Chaetoceros* spp. dominated the species assemblage (Table 1). Species such as *Dictyocha fibula* and *Scenedesmus quadricauda* were also observed during the winter (Table 1). The symbiont cyanobacteria *R*. *intracellularis* was mainly associated with diatom species such as *Guinardia cylindrus*, *Rhizosolenia styliformis,* and *Rhizosolenia hebetata*. Notably, its association with *R. hebetata* was more dominant during the winter.

During the summer season, 320 taxa belonging to 148 genera and six phyla (Bacillariophyta, Dinophyta, Cyanophyta, Chlorophyta, Haptophyta, and Chrysophyta) were identified in the southwestern SCS. Among them, diatoms represented 187 taxa belonging to 54 genera and they were more dominant than the dinoflagellates (109 taxa from 22 genera). The phytoplankton community was more diverse in the summer than in the winter. The number of taxa and genera almost increased by a factor of two and three, respectively. *Trichodesmium* and *Chaetoceros* were the fpredominant genera in the phytoplankton community. The chain-forming species, including *T. thiebautii*, *T. nitzschioides*, *T. erythraeum*, *Chaetoceros dichaeta*, *Chaetoceros affinis*, *Chaetoceros lorenzianus*, *Thalassionema frauenfeldii*, *Pseudo-nitzschia delicatissima*, *Pseudo-nitzschia pungens*, *Leptocylindrus danicus*, *Hemiaulus hauckii,* and *Bacteriastrum comosum,* dominated the phytoplankton assemblage during the summer season (Table 1). In addition, the small-sized diatoms *Nitzschia* spp. and *Navicula* spp. were widely distributed in the study area. The cyanobacteria species *T. thiebautii*, *T. erythraeum,* and symbiotic cyanobacteria *R*. *intracellularis* and *Calothrix rhizosoleniae* were also reported during the summer. *R*. *intracellularis* was mainly associated with the diatom hosts such as *R. styliformis*, *G. cylindrus*, *R. hebetata,* and *Hemiaulus membranaceus* in the intercellular location. However, *C. rhizosoleniae* was attached externally to species like *Chaetoceros subsecumdus*, *C. affinis*, *Chaetoceros compressus*, *Chaetoceros glandazii,* and *Chaetoceros tortissimus*.

**Table 1.** List of the dominant phytoplankton species (with their occurrence frequency *f* and dominance index *Y*) observed during the winter and summer seasons in the southwestern South China Sea.


#### *3.3. Seasonal Distribution of Phytoplankton Community*

The phytoplankton abundance during the winter ranged from 0.08 × 103 to 9.52 × <sup>10</sup><sup>3</sup> cells L<sup>−</sup>1, with an average of 2.74 × 103 cells L−1. Diatom abundance ranged from 0.08 × 103 to 3.36 × 103 cells L−<sup>1</sup> (average 0.67 × 103 cells L−1) and comprised ~63% of the total phytoplankton abundance (Table A2). *Chaetoceros* was a common genus in the diatom group with an average abundance of 0.61 × 103 cells L−1. Diatoms dominated the phytoplankton assemblage at most stations, except St. Y22, where *Trichodesmium* contributed 92% (total 8.8 × 103 cells L−1) to total phytoplankton abundance in the surface water (Figure 2a). Cyanobacteria were observed only in three stations, with the abundance

of 0.56 × <sup>10</sup><sup>3</sup> cells L−<sup>1</sup> at St. Y23, 2.16 × <sup>10</sup><sup>3</sup> cells L−<sup>1</sup> at St. Y34, and 8.80 × <sup>10</sup><sup>3</sup> cells L−<sup>1</sup> at St. Y22 (continental region) (Figure A1). Moreover, the total abundance of *T. thiebautii* was 10.16 × 103 cells L<sup>−</sup>1, which accounted for a 24% proportion of the whole community. The symbiotic cyanobacteria only consisted of *Richelia intracellularis*, with a total abundance of 1.36 × <sup>10</sup><sup>3</sup> cells L<sup>−</sup>1, contributing ~27% to total community abundance. Dinoflagellate abundance ranged from 0.08 × 103 to 0.16 × 103 cells L−<sup>1</sup> (average 0.10 × 103 cells L<sup>−</sup>1) and contributed approximately 1% to total phytoplankton abundance. The highest dinoflagellate abundance was observed at open water station M07 (Figure 2a).

On the contrary, the overall phytoplankton abundance ranged from 0.02 × 103 to 128.82 × 103 cells L−1, with an average of 1.05 × 103 cells L−1. Compared to the winter season, the overall proportion of diatoms in the phytoplankton community decreased by 33.78% in summer, although the ratio of diatom/dinoflagellate was comparable. Conversely, the proportion of cyanobacteria increased by 12.11%, where *Trichodesmium* contributed up to 44.84% (Figure 2b). The diatom–diazotrophic associations decreased by 2.70%. Cyanobacteria was the most abundant group, as the abundance ranged from 0.02 × 103 to 123.15 × 103 cells L−<sup>1</sup> (average 1.89 × 103 cells L−1) and contributed to 69% of the total phytoplankton abundance. The abundance of *T. thiebautii* reached up to 121.55 × 103 cells L−1. The total abundance of symbiotic cyanobacteria in the region was 3.36 × 103 cells L<sup>−</sup>1, with a *Richelia intracellularis* and *Calothrix rhizosoleniae* abundance of 2.20 × 103 and 1.16 × <sup>10</sup><sup>3</sup> cells L−1, respectively. The cyanobacterial population was even distributed in deeper waters in the summer than that in the winter. The average abundance (0.83 × 103 cells L<sup>−</sup>1) and the proportion of diatoms were about half that of cyanobacteria (Table A2). Among the diatoms, *Chaetoceros* was the most dominant species and contributed ~42% to diatom abundance. Dinoflagellates, together with other groups, contributed a small proportion (below 10%) of the phytoplankton community (Table A2). Compared with historical data of phytoplankton composition and abundance in similar regions and seasons, we detected a relatively higher species number in the summer, and the average abundance of phytoplankton was in accordance with previous data (Table 2).

**Figure 2.** Composition and abundance (cell L<sup>−</sup>1) of phytoplankton community in the surface water in the winter (**A**) and summer (**B**), and vertical distribution (station average) patterns of phytoplankton group relative abundance (%) in the winter (**C**) and summer (**D**).


**Table 2.** Comparison of historical data of phytoplankton with average cell abundance in the South China Sea.

#### *3.4. Vertical Distribution of Phytoplankton Community at Different Eddy Stages*

The phytoplankton composition and abundance during the summer and winter seasons were not only different in the surface layer but also the water column (Figure 2). In the winter, the abundances and proportions of cyanobacteria were comparable to that of diatoms, whereas in the summer, the cyanobacterial population was close to double that of diatoms. During the winter, the relative abundance of diatoms was greater below 50 m (peak abundance 2.56 × 103 cells L−<sup>1</sup> at Stn 23), whereas the dinoflagellates (25 m) and cyanobacteria (0 and 25 m) abundance increased above 50 m (Figures 2c and A1). The highest abundance of cyanobacteria (8.8 × 103 cells L<sup>−</sup>1) was observed in the surface water at Stn 22. Dinoflagellates contributed more to total phytoplankton at M07. Other phytoplankton species, mainly *Dictyocha fibula,* were relatively abundant and contributed 7.95% to total phytoplankton abundance in the surface water. During the summer, phytoplankton were mainly distributed towards the south of 13◦ N. Among them, the cyanobacteria mainly flourished in the area with eddy existence (especially around the sites of 14.5◦ N, 112◦ E and 12◦ N, 114◦ E), while diatoms were distributed in the southern area and the open basin (Figure 2b, Figure A2). The abundances of diatoms and dinoflagellates in the eddy mature stage (CE2) rose to 10 times that in the eddy relaxation stage (Figure 2b). Dinoflagellates accounted for a relatively high proportion of total phytoplankton at Y00 and stations along 14◦ N (Figure 2a). The abundance of *Dictyocha fibula* was very low, with the proportion of 0.06% of total phytoplankton abundance. Overall, depth-wise the cyanobacterial population was relatively abundant (>50%) until 100 m, whereas diatoms and (to some extent) dinoflagellates dominated deeper layers (Table A3). Moreover, the vertical distribution of cyanobacteria revealed their dominance on the edge of cold eddies and the open basin (Figure 3b, Section A, and Section B), as well as in the area influenced by the warm eddy (Figure 3b, Section C, and Section D). Differently, other phytoplankton (excluding cyanobacteria) mainly emerged in the center of cold eddies (Figure 3a, Section A, and Section B), followed by the continental area impacted by coastal upwelling (Figure 3a, Section D).

**Figure 3.** Vertical distribution of phytoplankton abundance during the summer. (**a**) Phytoplankton (Phyto) excluding cyanobacteria; (**b**) cyanobacteria (Cyano). CE1: cold eddy 1, CE2: cold eddy 2, and WE: warm eddy.

The proportions of the main phytoplankton groups changed remarkably with different stages (Figure 4a). The abundance of *Trichodesmium* in the phytoplankton community increased in the summer. The ratio of diatom to dinoflagellate (dia/din) was comparable during the winter and summer, whereas it was lower in CE2 (34.10) than in WE (Table A4). The diatom to cyanobacteria ratio (dia/cya) in the winter was five times more than in the summer. Furthermore, the dia/cya ratio was lower in the eddy periods than the no eddy and eddy relaxation stages. The relative contribution of algae groups including diatoms, dinoflagellates, and symbionts decreased dramatically during cold eddy mature stages but increased significantly during the later stages (Figure 4a). The dominant genus *Trichodesmium* presented a discrepant occurrence; however, its relative contribution to the phytoplankton community was much higher than that in non-eddy stages. The proportion of *Trichodesmium* (80.92%) and the dia/cya ratio (0.23) in the cold eddy mature period (CE2) were comparable to that in the warm eddy period (WE) (80.06%, 0.24, respectively) (Figure 4a). The phytoplankton abundance varied significantly above 50 m in the water column, while no significant difference was observed below the 50 m layer (Figure 4b). The phytoplankton community significantly varied seasonally (two-tailed *t*-test, *p* < 0.05)

(Table A5). Similarly, the variation of diatoms and dinoflagellates other than cyanobacteria showed a significant difference between eddy stages (*p* < 0.01). Moreover, the abundance of different phytoplankton groups, excluding cyanobacteria, had statistical differences among different periods (Kruskal–Wallis test, *p* < 0.01) (Figure A3). Thus, the overall results indicate that the phytoplankton community composition and structure changed with season and eddy development.

**Figure 4.** The relative abundance (%) contribution of different groups to the phytoplankton community (**a**), and the vertical variation of phytoplankton abundance (cell L−1) at different eddy stages (**b**). (NE: winter, CE1: cold eddy 1, CE1-r: cold eddy 1 relaxation, CE2: cold eddy 2, and WE: warm eddy).

#### *3.5. Diversity of Phytoplankton Community*

The Shannon–Weiner index (*H'*) and Pielou evenness index (*J*) were used for analyzing phytoplankton community diversity in this study. Our results show that the Shannon– Weiner index had a similar distribution pattern to the Pielou evenness index in both seasons (Figure A1). During the winter, the Shannon–Weiner index and Pielou evenness index ranged from 0.50 to 3.35 (avg. 1.28) and 0.09 to 0.57 (avg. 0.22), respectively, in the surface water (Figure 5a). High phytoplankton community diversity was observed in the open ocean region (Figure 5b). In the summer, the Shannon–Weiner and Pielou evenness indexes ranged from 0.01 to 5.14 (avg. 2.70) and 0.01 to 0.62 (avg. 0.32), respectively, in the surface water. Diversity indices were significantly higher in the summer than winter (*p* < 0.001), whereas the Pielou evenness index was significantly lower (*p* < 0.05) during the summer (Figures A1 and A4). This emphasizes that the surface water phytoplankton community in the summer was significantly more diverse than in the winter. Moreover, the phytoplankton community diversity in the summer was high in the water column (from 25 to 75 m depth) and also in eddy-controlled areas. Then, phytoplankton diversity was also higher towards the southern part around 13◦ N (Figure 5). In the study region, the diatoms and cyanobacteria controlled the phytoplankton community structure, whereas dinoflagellates and other groups contributed significantly to the transformation of the phytoplankton community and diversity.

**Figure 5.** Shannon–Wiener diversity index (*H'*) (**a**) and cell abundance (**b**) of the phytoplankton community at different layers in summer.

#### *3.6. Effect of the Environmental Cues on the Phytoplankton Community*

The influence of the environmental factors on shaping the phytoplankton community structure in the western SCS was assessed using Spearman's correlation and CCA analysis (Figure 6). The phytoplankton community in the region was significantly influenced by the seasonality in the environmental characteristics. During the winter season, phytoplankton was positively correlated with temperature and Si/N ratio, and was mainly influenced by nitrogen (nitrate and nitrite) (Figure 6a,b). The various diatom groups had a different response to the aquatic environment. *Bacteriastrum* and *Chaetoceros*, which belong to the class of Centricae, exhibited significant relationships with environmental parameters, whereas diatoms that belonged to the class Pennatae had no significant relationship with any environmental parameter (Figure 6a,b). In detail, Centricae was positively influenced by temperature but negatively by water depth. However, Pennatae showed a discrepant relationship with the environment as compared to Centricae. These disparate responses evidence that the Centricae thrives in upper warm water, whereas Pennatae prefers the cool lower water. The Chrysophyte member *Dictyocha* was significantly associated with the various environmental parameters, which could eventually fuel its growth during the winter (Figure 6a). Cyanobacteria were significantly influenced by N/P and Si/N ratios, while dinoflagellates did not reveal an obvious correlation with environmental parameters.

The abundance of phytoplankton groups, excluding cyanobacteria, was significantly different during both the summer and winter seasons (Kruskal–Wallis test, *p* < 0.01) (Table A3). During the summer, the various phytoplankton groups (except Pennatae diatoms) were significantly influenced by the changing environmental factors (such as temperature, salinity, and nutrients at the respective depths) (Figure 6c,d)). However, the Pennatae diatom species did not show a significant relationship with environmental parameters, similar to that in winter (Figure 6c,d). Unexpectedly, *Dictyocha* also was not influenced by the changing water characteristics in the summer season. Cyanobacteria, including *Trichodesmium* and symbionts, were significantly influenced by the spatially and temporally changing environmental parameters. In summer, temperature, salinity, and nutrients were the important factors significantly controlling the phytoplankton growth (*p* < 0.05). This could evidence that the dynamic change in the environment (due to eddies and upwelling) results in temperature and nutrient variations, which in turn influence profoundly the phytoplankton community structure.

**Figure 6.** The influence of the environmental factors on the phytoplankton community shown with Spearman's correlation and CCA value, respectively. Notes: (**A**,**B**) represents Spearman's correlation and CCA for the winter samples, and (**C**,**D**) represents Spearman's correlation and CCA for the summer samples. Environmental parameters include temperature (T), salinity (S), depth (Dep), PO4 <sup>3</sup><sup>−</sup> (P), N: NOx (P), SiO3 <sup>2</sup><sup>−</sup> (Si), N/P ratio, and Si/N ratio. Phytoplankton are listed as the following groups: diatoms G1 to G3 represent *Bacteriastrum*, *Chaetoceros*, and *Rhizosolenia,* belonging to the class of Centricae, G4 to G6 represent Fragilariaceae, Naviculaceae, and Nitzschiaceae, belonging to the class of Pennatae, and G7 to G9 represent *Dictyocha*, *Trichodesmium,* and symbionts. Dia: diatom, Din: dinoflagellate, Cya: cyanobacteria, and Phy: phytoplankton.

#### **4. Discussion**

#### *4.1. Influence of Hydrological Processes on the Phytoplankton Community*

The East Asian monsoon system has a strong bearing on the oceanographic and resultant biological features of the SCS. During the winter monsoons, the circulation in the southern SCS forms a cyclonic gyre, and an anticyclonic gyre during the summer monsoon. The surface water in most areas of the SCS is impoverished of nutrients due to a strong pycnocline, leading to a paucity of phytoplankton stock and production [19]. In winter, towards the western boundary of the SCS, the Vietnam offshore flow (which exists between 11◦ and 16◦ N) drifts northwards (along the coast) in the summer and southwards during the winter [31]. This flow pattern forms an offshore jet between 12◦–13◦ N, resulting in a local enhancement of the upwelling intensity during the summer. The peculiarity of stretching deformation separates the Vietnamese upwelling from the offshore area and water masses [6,36]. Simultaneously, a strong coastal jet forms a dipole recirculation pattern and flows northeastward between a cyclonic cold eddy (CE2) and an anticyclonic warm eddy (WE) [29]. In this study, the phytoplankton community, especially diatoms, showed relatively high diversity in the continental margin influenced by the Vietnamese upwelling. Previously, the high Chlorophyll *a* concentrations were observed along the Vietnamese coast [21,27,51]. Loick-Wilde et al. (2017) estimated that the diatoms dominated the cellcarbon biomass in the Vietnamese upwelling area [11]. The nutrient advection during the coastal upwelling stimulates the phytoplankton growth in the upper layers [27].

During the summer season, eddies were persistent in the upper ocean layers in the SCS. The phytoplankton community structure changed with eddy developments. Statistical analysis revealed that the growth of various algae groups (except cyanobacteria) significantly varied with different eddy development phases, suggesting a significant influence of eddies on the phytoplankton community in the study region. The high phytoplankton abundance observed between the 25 and 100 m depth layers was mainly influenced by eddies. Earlier studies in the SCS pointed out that the maximum chlorophyll

*a* concentration often appeared from 50 to 100 m in the non-eddy region, and appeared at 75 m in the eddy [23,27]. The cold eddy occurrence resulted in a continuous increase in diatom abundance compared to the non-eddy period, as observed previously [20]. The nutrient advection due to variable vertical motion could support the difference in phytoplankton abundance variation in the subsurface water [27]. Mesoscale eddies were proved to supply 20–40% of the nutrient requirements of phytoplankton [52,53]. The enhanced productivity in eddies could be even comparable to the productivity supported by upwelled subsurface nitrate driven during the prevailing monsoon [9]. The increased chlorophyll *a* concentrations due to nutrient enrichment during cyclonic eddies were also observed elsewhere [54]. Nutrient supplements derived from eddy occurrence, resulting in phytoplankton development, reflected the inter-coupling between physical and biochemical processes in the SCS region.

Different phytoplankton functional groups have a varied response to seasonal and spatial fluctuations of environmental factors [55]. Diatoms are a major starter of food chains and food webs, and important contributors to marine primary production and the ocean carbon cycle [56,57]. Cyanobacteria could maintain the balance of the global ocean nitrogen budget by biological nitrogen fixation [58]. In this study, the diversity and abundance of phytoplankton were much higher in the summer than that in the winter. Diatoms contributed more to phytoplankton abundance in the winter, but cyanobacteria (*Trichodesmium* dominance) contributed more in the summer. This seasonal variation clearly explains the shifts within the phytoplankton community from diatoms (in winter) to cyanobacteria (in summer). Earlier, in the SCS, a higher proportion of diatoms in the phytoplankton assemblage was reported during the winter than in summer [19]. However, discrepantly, the dominance of *Trichodesmium* was not reported earlier [19]. Moreover, high phytoplankton abundance was reported at a deeper layer due to the deepened thermocline in the summer, compared with that in the winter. The variations of major phytoplankton groups were explained by different adaptive strategies to overcome the constraints imposed by temperature and nutrient concentration variations in the SCS [59]. Here, wind pumping also played a significant role in inducing high biological productivity during the summer monsoon. The upwelling and cold eddies both fueled the nutrient enrichment and eventually the phytoplankton diversity during the summer season. Overall, in the western SCS, the seasonality of the phytoplankton community and growth dynamics could be significantly influenced by the coupled physical processes mostly driven by the East Asian Monsoon. Changes in compositions of phytoplankton in this study provide clues in understanding the mechanisms that regulate their acclimation and adaptation to changing environments.

#### *4.2. Significance of Diazotrophic Cyanobacteria in the Western SCS*

Nitrogen acted as an essential but limiting factor for phytoplankton. Nitrogen concentration in the surface water was mostly below the detection limit in the western SCS. Although frequent eddies, driven by upwelling and monsoon, replenish nutrients from the deeper water, nitrogen lost through denitrification (leading to Redfield ratios below 16) in the water column becomes a major limiting factor for phytoplankton growth [60]. Therefore, diazotrophic cyanobacteria essentially alleviate nitrogen limitation and are involved in regulating marine productivity [1,61,62]. In this study, diazotrophic cyanobacteria containing *Trichodesmium* and the diatom-associated symbionts *Richelia* and *Calothrix* were the highest in abundance. *Trichodesmium* was the most dominant species in the phytoplankton community in the continental margin and the oligotrophic basin during both seasons. The dominance of *Trichodesmium* was also recorded in the SCS earlier [62]. The high abundance of *Trichodesmium* that appeared in the subsurface water could be controlled by upwelling and eddies. Together with eddy perturbations, the abundance of *Trichodesmium* was more than 12 times higher in the eddy mature period than that in the degenerating stage. Compared to the previous study [19], the *Trichodesmium* abundance was above one order of magnitude higher in our study. Here, temperature and nutrient concentration were signif-

icant influencing factors for the *Trichodesmium* population. Earlier studies in this region indicated that *Trichodesmium* regulated the higher N2 fixation and primary production rates in the oligotrophic offshore waters [11]. The nitrogen-fixing by *Trichodesmium* was quickly converted to plankton biomass and, in particular, the abundance of the diatoms (increased by 1.4–15 factor) in the Pacific Ocean [63]. Thus, here, it can be speculated that the thriving *Trichodesmium* population potentially contributes the bioavailable nitrogen into the oligotrophic waters in the western SCS. In addition, the symbionts *Calothrix* and *Richelia,* and their host diatoms, were relatively abundant in the summer, whereas *Rhizosolenia–Richelia* dominated in the winter. Symbionts often formed blooms in the low-nutrient water of the Pacific and the Atlantic Oceans [64–67]. Foster et al. (2011) estimated that the diatom partners influenced the growth and metabolism of their cyanobacterial symbionts *Richelia* and *Calothrix*, and the export of diazotroph-derived nitrogen supported the growth of the diatom partners [68]. Thus, diazotrophic symbioses and *Trichodesmium* would potentially play an important role in the nitrogen supplementation and phytoplankton growth of the oligotrophic ocean.

#### *4.3. Phytoplankton Thermal Adaptations Inferred from Seasonal Successions*

Global warming has increased steadily and increasingly involved deeper layers of the ocean since 1990 [69]. The warming ocean temperature would cause an alteration in the succession of the phytoplankton community [70–72]. Rising temperatures this century will cause poleward shifts in species' thermal niches [73]. Concomitantly, the ongoing global climate change is also linked to prolonged periods of anomalously high sea surface temperatures, which are defined as marine heatwaves [74]. From 1925 to 2016, the global average marine heatwave frequency and duration increased by 34 and 17%, respectively, resulting in a 54% increase in annual marine heatwave days globally [75]. Marine heatwaves have been accompanied by a large-scale change in surface chlorophyll levels, shifts in marine species location, and the reshaping of community structure [76,77]. Evidence from the field indicates temperature changes may lead to changes in diatom biogeography [59,78], and each species, even within the same genus, has its own characteristic temperature performance curve [79]. In this study, the seasonal succession of phytoplankton showed a predominance of diatoms in the phytoplankton community in the cool winter, which further shifted to cyanobacterial prevalence during the warm summer. Furthermore, in this study diatoms belonging to Centricae (represented by *Chaetoceros*, *Rhizosolenia,* and *Bacteriastrum*) were significantly related to temperature, as compared to Pennatae groups (such as Fragilariaceae, Naviculaceae, and Nitzschiaceae). The dominance of Centricae diatom species is often observed in the tropical ocean [14,80,81]. In the future, Centricae will become a potentially more sensitive group in the succession of the phytoplankton community as a consequence of the ocean temperature rise. On the other side, ocean stratification caused by rising temperature could result in nutrient deficiency [82]. Cyanobacteria prefer such a warm habitat with the low-nutrient oligotrophic condition. Here, in this study, the declining diatom predominance in the phytoplankton community during the warm condition could reveal their vulnerability to increasing temperature. On the contrary, flourishing cyanobacterial populations, mainly *Trichodesmium,* in warm conditions reflected their preference and adaptability in response to environmental change. The overall findings of our study could provide insight into phytoplankton community succession in future global temperature rise, and its further influence on biogeochemical cycles.

#### **5. Conclusions**

Here, we addressed the seasonal variability of the phytoplankton population in the western SCS, during the summer and winter monsoon periods. The seasonal changes of the phytoplankton community shifted from a diatom-dominated regime in winter to a cyanobacteria-dominated regime in the summer. This community change was controlled by eddies and upwelling activities during this season. Precisely, nutrient advection due to eddy activity triggered phytoplankton abundance, diversity, and *Trichodesmium*

proliferation in summer. However, elevated temperature adversely influenced the diatom– diazotrophic association during the summer. The phytoplankton community succession responses to local oceanographic forces provide insights into forecasting biotic community evolution in the future global climate change.

**Author Contributions:** Conceptualization, J.S. and C.D.; methodology, J.S.; software, C.D.; validation, J.S. and C.D.; formal analysis, C.D.; investigation, C.D.; resources, J.S.; data curation, J.S.; writing original draft preparation, C.D.; writing—review and editing, J.S., D.D.N., and H.L.; visualization, C.D.; supervision, J.S.; project administration, J.S.; funding acquisition, J.S. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the National Key Research and Development Project of China (2019YFC1407805), the National Natural Science Foundation of China (41876134, 41676112, 41276124, and 41406155), the Key Project of Key Laboratory of Integrated Marine Monitoring and Applied Technologies for Harmful Algal Blooms (MATHAB201805), the Tianjin 131 Innovation Team Program (20180314), and the Changjiang Scholar Program of Chinese Ministry of Education (T2014253) to Jun Sun.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data presented in this study are available in insert article.

**Acknowledgments:** We would like to thank Minhan Dai from Xiamen University for the nutrients data and CTD data supply. Special thanks to Qingshan Luan and Qing He for their hard work in sample collection.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **Appendix A**

**Table A1.** The average of environmental factors during different eddy developmental stages (-: missing data).



**Table A2.** The abundance of phytoplankton during the winter and summer seasons (cell L<sup>−</sup>1).

**Table A3.** The in-depth average abundances and proportions of phytoplankton groups during the winter and summer seasons.


**Table A4.** TThe abundance of phytoplankton groups at different eddy developmental stages.




Note: a: diatom, b: dino, c: cyan, d: others; *t*-test: 1: 0.01 < *p* < 0.05, 2: *p* < 0.01, 3: *p* > 0.05.

**Figure A1.** Vertical variation of phytoplankton abundance (**a**) and surface distribution diagram of community diversity (**b**) in winter.

**Figure A2.** Horizontal distributions of cyanobacteria (Cyano) and other phytoplankton (Phyto) abundances at the different water layers in summer.

**Figure A3.** The phytoplankton group difference among defined stages by Kruskal–Wallis test (\*\*: *p* < 0.01, A: winter, B: summer, C: warm eddy, D: Eddy II, E: Eddy I, F: Eddy I relaxation, a: phytoplankton, b: diatom, c: dinoflagellate, and d: others).

**Figure A4.** Alpha diversity indices were analyzed between the two seasons (\*: 0.01 < *p* < 0.05, \*\*\*: *p* < 0.001).

#### **References**


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