Home Journals Articles Updates About
CN
image
收藏切换
Phytoplankton growth and microzooplankton grazing in the central and northern South China Sea in the spring intermonsoon season of 2017
收藏切换
PDF
Dawei Chen1, 2, 3, Congcong Guo1, 2, Linhui Yu3, Yuanzhen Lu3, Jun Sun1, 2, *
Acta Oceanologica Sinica | 2020, 39(6) : 84 - 95
Less
收藏切换
Acta Oceanologica Sinica | 2020, 39(6): 84-95
• Marine Biology •
Phytoplankton growth and microzooplankton grazing in the central and northern South China Sea in the spring intermonsoon season of 2017
Full
Dawei Chen1, 2, 3, Congcong Guo1, 2, Linhui Yu3, Yuanzhen Lu3, Jun Sun1, 2, *
Affiliations
  • 1 Tianjin Key Laboratory of Marine Resources and Chemistry, Tianjin University of Science and Technology, Tianjin 300457, China
  • 2 Research Centre for Indian Ocean Ecosystem, Tianjin University of Science and Technology, Tianjin 300457, China
  • 3 State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China
Published: 2020-06-25 doi: 10.1007/s13131-020-1593-1
Outline
收藏切换

Phytoplankton growth rates and mortality rates were experimentally examined at 21 stations during the 2017 spring intermonsoon (April to early May) in the northern and central South China Sea (SCS) using the dilution technique, with emphasis on a comparison between the northern and central SCS areas which had different environmental factors. There had been higher temperature but lower nutrients and chlorophyll a concentrations in the central SCS than those in the northern SCS. The mean rates of phytoplankton growth (μ0) and microzooplankton grazing (m) were (0.88±0.33) d–1 and (0.55±0.22) d–1 in the central SCS, and both higher than those in the northern SCS with the values of μ0 ((0.81±0.16) d–1) and m ((0.30±0.09) d–1), respectively. Phytoplankton growth and microzooplankton grazing rates were significantly coupled in both areas. The microzooplankton grazing impact (m/μ0) on phytoplankton was also higher in the central SCS (0.63±0.12) than that in the northern SCS (0.37±0.06). The microzooplankton abundance was significantly correlated with temperature in the surface. Temperature might more effectively promote the microzooplankton grazing rate than phytoplankton growth rate, which might contribute to higher m and m/μ0 in the central SCS. Compared with temperature, nutrients mainly affected the growth rate of phytoplankton. In the nutrient enrichment treatment, the phytoplankton growth rate (μn) was higher than μ0 in the central SCS, suggesting phytoplankton growth in the central SCS was nutrient limited. The ratio of μ0/μn was significantly correlated with nutrients concentrations in the both areas, indicating the limitation of nutrients was related to the concentrations of background nutrients in the study stations.

dilution technique  /  phytoplankton growth  /  microzooplankton grazing  /  South China Sea  /  spring intermonsoon season
Dawei Chen, Congcong Guo, Linhui Yu, Yuanzhen Lu, Jun Sun. Phytoplankton growth and microzooplankton grazing in the central and northern South China Sea in the spring intermonsoon season of 2017[J]. Acta Oceanologica Sinica, 2020 , 39 (6) : 84 -95 . DOI: 10.1007/s13131-020-1593-1
Full Text
Less
1 Introduction
Less
Marine phytoplankton is the main primary producer and plays a crucial role in marine ecosystems and the photosynthesis of phytoplankton is the key to the conversion of inorganic carbon to organic carbon in the pelagic food web (Sun, 2013). Microzooplankton are the zooplankton with body lengths of less than 200 µm including flagellates, ciliates, heterotrophic dinoflagellates and small metazoan larvae (Jyothibabu et al., 2008). Microzooplankton are the major grazers of phytoplankton, and control the growth of phytoplankton by grazing which is called “top-down” control (Landry and Calbet, 2004; Lehman, 1991). Notably, they can consume 60%–80% of primary production in the sea and regulate phytoplankton community composition via selective grazing, and affect the ultimate fate of carbon flow from microbial loop to the traditional food web (Banse, 2007; Landry and Calbet, 2004; Schmoker et al., 2013; Strom and Welschmeyer, 1991).
The main way to obtain the knowledge about the importance of microzooplankton in the marine food web is the dilution experiments (Landry and Hassett, 1982). The dilution technique has been extensively used to estimate phytoplankton growth rates and simultaneously estimates mortality rates due to microzooplankton grazing (Schmoker et al., 2013). Since it was proposed, the dilution technique has been widely conducted in different ecosystems and these studies have provided great insight into understanding microzooplankton grazing and phytoplankton growth in marine ecosystems (Landry and Calbet, 2004; Schmoker et al., 2013).
The South China Sea (SCS) is a semi-closed, secondary large marginal sea around the world located in the western Pacific. The SCS is heavily influenced by the southwest summer monsoon during the top of May to September, while is under the influence of the northeast winter monsoon during November to the next April (Su, 2004). Within this monsoon system, the central South China Sea (CSCS) is characterized with annual high temperature in surface water (26–29°C), while the salinity sometimes less than 34 influenced by rainfall and various water masses (Li and Su, 2000). The upper water column is often stratified and remains oligotrophic, therefore, the level of primary productivity is low due to depletion of inorganic nutrients (Wong et al., 2007). The ecological environment in the northern South China Sea (NSCS) is more complicated including estuaries, bays, shelves, slopes and open seas, and is susceptible to various physical processes such as typhoon, coastal upwelling, mesoscale eddy, river plume, etc. (Gong et al., 1992). The more complex physical processes may lead to phytoplankton blooms and the increase in primary production in the NSCS (Ning et al., 2004; Zheng and Tang, 2007; Hu et al., 2014).
There are already some studies on microzooplankton grazing and phytoplankton growth in the SCS, but most of them are concentrated in the region of the NSCS in summer or winter (e.g., Su et al., 2007; Zhou et al., 2011; Chen et al., 2013). So far, there are only few studies (Chen et al., 2009) investigating the basin area of the CSCS and none focus on comparison between the northern and central SCS with different environmental conditions, especially during the spring intermonsoon period.
2 Materials and methods
Less
2.1 Study area
A total of 21 experiments were conducted in the northern and central SCS during the Open Cruise Project in central South China Sea of National Nature Science Foundation of China, aboard the R/V Shiyan 1 from 30 March to 6 May, 2017 (Fig. 1).
For identifying spatial patterns, we classified the stations into two groups according to geography. Stations C34, C31, C26, C22 and Stations C2, L5, C9, C13 were located along 18°N transect and perpendicular to the shoreline in the NSCS, respectively. The remaining stations were located in the central region of the SCS (Fig. 1). Moreover, according to bathymetry: Station C2 was only station located in the shelf (bottom depth≤100 m); Stations L5, C9, C34 were located in the slope (100 m<bottom depth≤2 000 m); Stations C64, C66, C70 were distributed in waters around the Nansha Islands with bottom depth of about 2 000 m; the bottom depth of remaining stations were more than 3 000 m besides Station C31 (Fig. 1).
2.2 Dilution experiment
Seawater for dilution experiment was collected from 0.5 m depth using a clean plastic bucket, then was pre-screened through a 200 µm mesh and gently pooled into polycarbonate carboys, called the initial seawater (ISW). The particle-free water (PFW) was prepared by filtering the same seawater through a capsule filter with a pore size of 0.22 µm. For the dilution experiments, the ISW was diluted by PFW with a dilution series of 20%, 40%, 60%, 80% and 100% (ISW: (ISW plus PFW)) into 1.5 L transparent polycarbonate bottles in triplicate. In order to comply with the assumption of dilution technique (Landry and Hassett, 1982), all the bottles were enriched with additional nutrients (final concentrations of 0.5 µmol/L NH4Cl, 0.03 µmol/L KH2PO4, 0.5 µmol/L Na2SiO3 and 1.0 nmol/L FeSO4) to promote constant phytoplankton growth rates. Three same bottles were filled with ISW without nutrient addition as control treatment. To simulate in situ conditions, all of the incubation bottles were placed in a deck incubator for 24 h with temperature controlling by running surface seawater and covered with neutral-density screens for light regime control. All the filtration apparatus, mesh, carboy containers and incubation polycarbonate bottles were soaked in 10% HCl and thoroughly rinsed with MiliQ-water and filtered seawater prior to each experiment.
Triplicate seawater samples from the ISW were collected at the beginning of each incubation experiment to determine the initial Chlorophyll a (Chl a) concentrations. The ISW samples of 500 to 1 000 mL were filtered through 25 mm Whatman GF/F glass fiber filters under low vacuum. After filtration, the filters were stored in the dark at –20°C immediately until analysis. For each incubation bottle, the same procedures were used to determine Chl a concentrations to calculate phytoplankton growth rates and microzooplankton grazing rates after incubation.
Seawater of 100 mL from ISW was filtered with a 0.45 µm acetate fiber membrane and stored in –20°C for nutrient analysis.
Water samples from ISW for phytoplankton (1 L) and microzooplankton (2 L) taxonomy analyses were fixed with buffered formalin (final concentration 2%) and 1% Lugol’s solution, separately. These samples were stored cool in the dark until they were counted using the Utermöhl method (Utermöhl, 1958).
2.3 Sample analyses
The filters of Chl a samples were extracted with 5 mL 90% acetone and stored in darkness for 24 h at –20°C. Then, the Chl a concentrations were measured with a Turner-Designs Trilogy fluorometer (Welschmeyer, 1994). Nutrients (nitrate plus nitrite, phosphate, silicate, ammonium) were measured by a continuous flow AutoAnalyzer (Bran+Luebbe) on the basis of standard procedures (Hansen and Koroleff, 2007).
The data of water temperature and salinity were obtained using a CTD (Sea Bird 911 Plus).
For phytoplankton qualitative and quantitative analyses, the sample of 1 L was concentrated to 10 mL after sedimentation for 24 h. The supernatant was siphoned, then sub-sample were identified and counted to species level using an inverted microscope at magnifications of 200× or 400× according to the method of Utermöhl (1958). The phytoplankton taxonomy identification was carried out as described by Jin et al. (1965) and Yamaji (1966).
For enumeration of the microzooplankton, the samples were concentrated to 100 mL using a silicone tube after 24 h sedimentation. Then sub-samples were chosen and placed in Utermöhl chamber to determine species composition and abundance after settling for several hours with the same way as phytoplankton. The microzooplankton was classified into three main categories: ciliates, copepod nauplii, and heterotrophic dinoflagellates. Ciliates were classified into aloricate ciliates and loricate tintinnids according to their cilia and shapes (Zhang et al., 2012, 2015). Heterotrophic dinoflagellates were identified and counted in this study from the phytoplankton microscopy (Sun and Guo, 2011). The copepod nauplii were discriminated as one group and one single species.
2.4 Date analyses
Followed the standard data analysis procedures for the dilution method presented by Landry and Hassett (1982), the prey apparent growth rate (AGR, d–1) after incubation in each incubation bottle was assumed as the following equation independently:
${\rm {AGR}} = {\rm{ }}\frac{{\ln ({P_t}/{P_{\rm o}})}}{t},$
where t is the duration of the incubation in days and P0 and Pt represent the initial and final concentrations of Chl a, respectively. During the nutrient-added treatment, the phytoplankton growth rate (µn, d–1) and microzooplankton grazing rate (m, d–1) were calculated by least-square regression between AGR with nutrient addition and dilution factors (ISW:ISW plus PFW). The m and µn values were calculated as the absolute value of the slope and the intercept of the linear regression equation, respectively. In situ phytoplankton instantaneous growth rates (µ0, d–1) were calculated as the sum of m and the AGR without nutrient addition in the control group (Landry, 1993).
The grazing impact on phytoplankton by microzooplankton was often expressed by the ratio of microzooplankton grazing rate to phytoplankton growth rate (m/µ0) and other indices as follows. The percentage of phytoplankton standing stock (Pi, %/d) and potential primary production (Pp, %/d) ingested by the microzooplankton per day were calculated using the following equations (Verity et al., 1993):
$ {P_{{i}}} = (1 - {{\rm e}^{mt}}) \times 100\%,$
$ {P_p}{\rm{ = }}({{\rm{e}}^{{\mu _0}t}} - {{\rm{e}}^{({\mu _0} - m){{t}}}}){\rm{/}}({{\rm{e}}^{{\mu _0}t}} - {\rm{1}}) \times {\rm{100}}\%,$
where t is the time (d); m is microzooplankton grazing rate (d–1); µ0 is phytoplankton instantaneous growth rate (d–1).
A Tukey test was performed to compare the differences of various environmental and biological parameters between the NSCS and CSCS in present study. Pearson test was operated to test the correlation between variables in present study. p<0.05 or 0.01 was used as the significance level. All tests were performed using SPSS 14.0.
3 Result
Less
3.1 Environmental variables and Chl a
The sampling information and geographical, physical, and chemical parameters at the twenty-one stations are presented in Table 1. Surface water temperature was quite high and was always above 25°C. The temperature was lowest at Station L5 with the value of 25.29°C and highest at Station C47 (29.60°C). The average water temperature was (28.17±1.32)°C. Surface salinity ranged from 33.02 to 34.32 with an average value of 33.68±0.31. Temperature increased gradually from north to south in our study area, while salinity was the opposite. The nutrients concentrations of surface water varied among stations (Table 1). The maximum concentration of nitrate plus nitrite was 0.76 µmol/L at Station C22 (besides Station C26). Silicate concentration ranged from 0.65 to 2.12 µmol/L and was highest at Station C54 in the central basin (besides Station C26). The phosphate concentration was very low (the maximum was only 0.07 µmol/L) and was below the detection limit (0.008 µmol/L) at seven of twenty-one stations. The ammonium concentration ranged from 0.01 to 0.60 µmol/L, except Stations C26 and C9 with the values of 2.99 and 1.25 µmol/L, respectively. The Chl a concentrations of the originally sampled seawater ranged from 0.06 to 0.21 µg/L with an average value of (0.11±0.04) µg/L, and the high values were shown in the NSCS (Stations C22 and C26).
Special emphasis should be placed at Station C26. There were unusually high nutrient concentrations which were far more than other stations and lower temperature than ambient sites due to cold eddy (Tian et al., 2016). The total dissolved nitrogen (nitrate, nitrite and ammonium) concentration was highest at Station C26, with a value of 7.48 µmol/L, about ten times of the average value of remaining twenty stations (0.74 µmol/L). The silicate concentration was also highest at Station C26 (2.28 µmol/L), about 2 fold of the average value of other stations (1.28 µmol/L). However, the highest Chl a concentration was not found at Station C26 but Station C22 with the value of 0.21 µg/L. There was a sub maximum of Chl a concentration at Station C26 (0.18 µg/L).
The Pearson correlation analyze results between different environmental variables were showed in Table 2. The temperature was extremely negative correlated with surface salinity and Chl a concentrations (p<0.01 or 0.05) (Table 2). The concentration of nitrate plus nitrite showed extremely positive correlated with ammonium concentration and silicate concentration (p<0.05 or 0.01). The Chl a concentration was negative correlated with surface temperature (p<0.05), while positive correlated with surface salinity, silicate, ammonium and phosphate concentrations (p<0.05 or 0.01), respectively (Table 2).
There were obvious differences in different environmental variables between the NSCS and CSCS (Table 3). Surface water temperature in the CSCS ((28.99±0.49)°C) was higher than that in the NSCS ((26.83±1.12)°C) (t-test, p<0.05), but there was no statistically significant difference in surface salinity (t-test, p=0.865). The dissolved nitrogen (nitrate plus nitrite, ammonium) concentrations were lower in the CSCS than those in the NSCS (t-test, p<0.05). Similarly, the Chl a concentration in the CSCS ((0.09±0.02) µg/L) was also lower than that in the NSCS ((0.14±0.04) µg/L) (t-test, p<0.05).
3.2 Phytoplankton composition
A total of 92 species in 46 genera of phytoplankton belonging to Bacillariophyta, Dinophyta, Cyanophyta and Chrysophyta were identified in the initially sampled waters of twenty-one stations in the surface (Table 4). Bacillariophyta was the most diversified group in which 46 species belonging to 25 genera were recorded. Dinophyta contributed for species composition with 41 species belonging to 12 genera. Although species in Cyanophyta and Chrysophyta were also observed, they were very few and recorded more sporadically.
The phytoplankton abundances ranged from the minimum of 1 546 cells/L to the maximum of 14 016 cells/L, with an average value of 4 843 cells/L. Further, the mean cell abundance of cyanobacteria (Trichodesmium thiebautii mainly) was 3 303 cells/L which accounted for 68% of total phytoplankton abundance. Trichodesmium thiebautii was the pre-dominanted specie and the cell abundance was 15 cells/L (Station C52) to 11 864 cells/L (Station C22) with an average value of 3 277 cells/L. Abundances of diatom and dinoflagellate at different stations were showed in Fig. 2. The mean cell abundances of diatom and dinoflagellate were 1 247 cells/L and 289 cells/L, separately. Thalassionema nitzschioides, Thalassionema frauenfeldii, Synedra spp., and Thalassiothrix longissima were the most dominant diatoms in most experimental stations. Dinoflagellates such as Prorocentrum lenticulatum, Prorocentrum minimm and Protoperidinium sp., etc., also appeared much more in some sites.
There was significant higher phytoplankton abundance in the NSCS than that in the CSCS, due to the higher abundances of dinoflagellate and cyanobacteria (t-test, p<0.05 or p<0.01), but there was no significant differences in diatom abundance between the NSCS and CSCS.
3.3 Microzooplankton community structure
In the initially sampled waters, there were sixty-two ciliate species identified belonging to 26 genera (Table 4). Ciliates were categorized into loricate tintinnids with 50 species and aloricate ciliates with 12 species. Loricate tintinnids mainly consisted of species in the genera of Tintinnopsis (13 species), Eutintinnus (8 species) and Rhabdonella (13 species). Aloricate ciliates mainly consisted of species in the genera of Strombidium including S. sulcatum, S. tintinnodes, S. paracalkinsi and S. conicum, and Apostrombidium, Rimostrombidium. The abundances of ciliates ranged from 34 ind./L to 183 ind./L, and were mainly contributed by Strombidium with high abundance. Due to high species diversity of Tintinnopsis, the abundances of Tintinnopsis was also high in some stations.
The copepod nauplii were identified in 18 experimental stations, and the maximum abundance was 51 ind./L, which accounted for 30% of microzooplankton abundance at Station C13.
Heterotrophic dinoflagellates in genera of Protoperidinium, Gymnodinium and Gyrodinium mainly were identified in all experimental stations. The abundance of heterotrophic dinoflagellates was higher (108 ind./L on average) than that of ciliates (77 ind./L on average) at sixteen experimental stations (Fig. 3).
There were no significant differences in abundances of ciliates (t-test, p=0.566) and heterotrophic dinoflagellates (t-test, p=0.114) between the NSCS and CSCS. But in the whole sites, the abundances of ciliates and heterotrophic dinoflagellates were positively correlated with temperature, respectively (p<0.05 or p<0.01) (Fig. 4).
3.4 Phytoplankton growth and microzooplankton grazing rates
Phytoplankton growth and microzooplankton grazing rates from the dilution experiments are shown in Table 5. Phytoplankton growth rates (µ0) at different experimental stations ranged from 0.45 to 1.52 ((0.85±0.28) d–1) and microzooplankton grazing rates (m) ranged from 0.20 to 0.87 ((0.45±0.22) d–1). The microzooplankton grazing pressure on the phytoplankton community expressed by the percentages of phytoplankton standing stock (Pi, %/d) and potential primary production (Pp, %/d) that were ingested by microzooplankton, is also shown in Table 5. The microzooplankton consumed 18%–58% ((35.15±12.78)%/d) of standing stocks and 37%–91% ((62.90±16.64)%/d) of potential primary productivity for total phytoplankton among experimental stations. Moreover, the specific value of m/µ0, ranged from 0.29 to 0.89 with the average value of 0.53±0.17.
The phytoplankton growth and microzooplankton grazing rates were (0.81±0.16) d–1 and (0.30±0.09) d–1 in the NSCS, and were lower than those in the CSCS with the values of (0.88±0.16) d–1 and (0.55±0.22) d–1, separately (t-test, p<0.05 or p<0.01) (Table 6, Fig. 5). The microzooplankton grazing pressure on phytoplankton (m/µ0, Pi, Pp) in the CSCS were (0.63±0.12), (40.91±12.33), and (73.09±11.57) d–1, respectively, which were also higher than those in the NSCS with the values of (0.37±0.06), (25.80±6.67), and (46.35±7.46) d–1, respectively (t-test, p<0.05) (Table 6, Fig. 5).
Correlation analysis showed that the microzooplankton grazing rates were positively correlated to phytoplankton growth rates in both the NSCS (n=13, p<0.01) and CSCS (n=8, p<0.01) (Fig. 6).
Nutrient limitation indices (µ0/µn) were scattered over a wide area, from 0.55 to 1.37 with the average value of 0.87±0.20, suggesting that nutrients had different effects among stations in this study area. In the NSCS with the higher nutrient concentrations, the ratio was 1.03 on average, indicating phytoplankton growth rates estimates in the nutrient addition treatments (µn) were almost the same as the estimates in control group (µ0) and no nutrient limitation in the NSCS. But in the CSCS, the µ0/µn ratio was just 0.77 on average and the ratios were below 1 at all the thirteen sites, suggesting that nutrients became the limiting factors for phytoplankton growth in the CSCS. The difference of µ0/µn between the NSCS and CSCS was not statistically significant (t-test, p=0.219), but as a whole it was obviously related to nutrient concentrations (Table 7).
The grazing rate (m) in surface waters was positively correlated with temperature and ciliate and microzooplankton abundances, separately (p<0.01). The temperature was positively correlated with µn, (p<0.05), but was not correlated significantly with μ0 (p=0.203) (Table 7).
4 Discussion
Less
4.1 Effects of environmental factors on microzooplankton distribution
Few studies on detailed microzooplankton species composition and abundance in the region of the SCS have been carried out previously. Microzooplankton are important consumers of phytoplankton production in the open ocean (Stelfox-Widdicombe et al., 2000) and play a critical role in the microbial loop (Schmoker et al., 2013). Microzooplankton abundance and metabolism are affected by many factors, such as temperature, oxygen and nutrients (Caron and Hutchins, 2013). Generally, it is believed that temperature and feed concentration are the main factors affecting ciliates (Nielsen and Kicrboe, 1994; Strom et al., 2007; Zhang et al., 2011). Archer et al. (1996) found that the growth rate of dinoflagellates was lower in the low temperature environment, and the temperature restriction of the growth rate was also applicable to ciliates (Rose and Caron, 2007). In addition, Setälä and Kivi (2003) showed the abundance of ciliates was significant correlation with the Chl a concentrations, and Gómez (2007) pointed out that the numbers of loricate tintinnids were mainly limited by diet, so they were distributed in the aquifer with the highest Chl a concentration. In the SCS, Zhou et al. (2015a) also pointed the significantly positive correlation between ciliates abundance and Chl a concentration.
In our experiments, the same results are also found, which the abundances of heterotrophic dinoflagellates and the ciliates are positively correlated with temperature, respectively (Fig. 4). However, there is no significant correlation between microzooplankton abundance and Chl a concentration. This may be due to the complex distribution pattern of microzooplankton, and other factors can also influence the distribution of microzooplankton (Nielsen and Kicrboe, 1994; Quevedo et al., 2003). High productivity waters often correspond to high biomass of microzooplankton (First et al., 2007). However, a different species composition, abundance and prey quality of microzooplankton will lead to different food preference and the changes of phytoplankton communities in the species and size composition (Teixeira and Figueiras, 2009). Most ciliates were resistant to diatom, while some larger heterotrophic dinoflagellates (e.g., Gyrodinium) preferentially feed on diatom (Archer et al., 1996; Leising et al., 2005). The Tintinnopsis sp. belonging to loricate tintinnids could only incept pico- or nano-phytoplankton because of their small oral diameter (median 38.5 µm), while aloricate ciliates could graze particles as large as themselves (Burkill et al., 1987; Paranjape, 1987; Gifford, 1988). The food preference in species and particle size of phytoplankton may result in no significant correlation between microzooplankton abundance and total Chl a concentration. In nature, the growth of microzooplankton is dependent on the suitable prey, but the abundances and species composition of microzooplankton are controlled by the higher consumers (meso- and macrozooplankton) directly (Porter et al., 1985; Gifford et al., 1995; Lonsdale et al., 2000). In addition, environmental factors may influence the abundance of microzooplankton. Increased irradiance and exposure to ultraviolet radiation may have significant direct effects on the growth and behavior of some heterotrophic protists (Macaluso et al., 2009), which may affect the structure of marine food webs as a result of species-specific differences in ultraviolet sensitivity (Belzile et al., 2006). Oxygen is also necessary for the respiration of microzooplankton (Verity et al., 2002). There is no enough data to determine the specific causes of decoupling between microzooplankton abundance and Chl a concentration in the present study and further study is necessary.
4.2 Comparisons of rate estimates with previous studies
It is cautious to compare our data with other studies in the same area or similar environment before discussing environmental effects on microzooplankton grazing rates and phytoplankton growth rates. All the µ and m are within the reviewed ranges based on global data collection (Calbet and Landry, 2004; Schmoker et al., 2013). There are few studies on microzooplankton grazing in the CSCS and NSCS, especially during spring intermonsoon season. Previous studies in the waters adjacent to our study area are happened in winter and summer. For example, Chen et al. (2009) reported an average µ of (0.75±0.62) d−1 and an average m of (0.65±0.51) d−1 in the western SCS near our study area in summer, which was similar to our results observed in the CSCS. Zhou et al. (2015b) estimated an average µ of (0.92±0.32) d−1 and an average m of (0.46±0.20) d−1 in the southern SCS during summertime, while in winter, the rates were lower with the values of (0.54±0.22) d−1 and (0.27±0.13) d−1 for µ and m, respectively. Chen et al. (2013) reported that the average values of m were (0.49±0.47) d−1 and (0.35±0.21) d−1, and the µ were (0.89±0.45) d−1 and (0.61±0.32) d−1 for summer and winter in the NSCS, respectively. These rates are similar to our results (Tables 5 and 6).
Globally, there are relatively few studies at similar latitudes in the open ocean. Yang et al. (2004) reported µ and m in summer were 0.35–0.75 d−1 and 0.51–0.67 d−1, respectively, in the western Pacific with latitudes similar to those stations of the CSCS in the present study. The µ0 and m estimated by Landry et al. (1998) showed similar results in the subtropical and tropical Arabian Sea with the mean growth rates of 0.85 and 0.62 d−1 in summer and winter, while the mean grazing rates were 0.68 and 0.65 d−1, respectively. Caron and Dennett (1999) showed the µ0 of (0.84±0.29) d−1 and the m of (0.35±0.18) d−1 during the northeast monsoon season, while the µ0 of (0.44±0.19) d−1 and the m of (0.30±0.17) d−1 during spring intermonsoon season in the Arabian Sea, respectively. Also in the Arabian Sea, Edwards et al. (1999) compared the results of dilution method experiments between during and after the southwest monsoon, which indicated the µ0 were (0.81±0.47) and (0.68±0.15) d−1 during and after the southwest monsoon, meanwhile the m were (0.33±0.19) d−1 and (0.41±0.19) d−1, respectively. Although the results of these studies are slightly different, they are all within reasonable range.
4.3 Environmental effects in the variations of phytoplankton growth and microzooplankton grazing rates
Calbet and Landry (2004) pointed that there was a significant positive correlation (p<0.001, R2=0.37) between phytoplankton growth and microzooplankton grazing rates based on the dataset collected on open oceans and offshore marine systems. The latest review confirmed this point (Schmoker et al., 2013). In fact, microzooplankton feed passively and always preferentially feed on fast-growing species to gain a stable food source and maintain its own growth. The high coupling of grazing rate and phytoplankton growth rate also promotes ecosystem stability (Sun et al., 2007; Strom, 2002). Similar result was observed in present study, the microzooplankton grazing rate was positively correlated with the phytoplankton growth rate in both study areas (p<0.01) (Fig. 6), similar to previous studies in the SCS (Chen et al., 2009; Zhou et al., 2015a).
Previous studies indicated that the phytoplankton mortality by microzooplankton grazing was higher in oligotrophic waters and open ocean, and lower in eutrophic and coastal environments (e. g., Landry et al., 1997; Calbet and Landry, 2004). Similar results have emerged in our experiments. There are obviously higher grazing pressure on phytoplankton (m/µ0, Pi and Pp) in the CSCS than those in the NSCS with higher nutritional level and biomass. In our study, the temperature in the NSCS was significantly lower than that in the CSCS, while microzooplankton grazing rate was more sensitive to temperature and it meant the growth rate of phytoplankton might increase more slowly with temperature than microzooplankton growth and grazing rates (e.g., López-Urrutia et al., 2006; Rose and Caron, 2007; López-Urrutia, 2008; Chen et al., 2012). The high grazing impact might have been caused by a larger increase of microzooplankton grazing than of phytoplankton growth rates in the CSCS.
Compared with temperature, nutrients played a more significant role in phytoplankton growth in the spring of the SCS (Hu et al., 2014). The open sea of the SCS has very low phytoplankton biomass and primary production due to lack of nutrients (Ning et al., 2004; Wong et al., 2007; Tan and Shi, 2009) and is generally considered to be nitrogen limited in the open waters (Chen, 2005; Wu et al., 2003). In the spring intermonsoon period, the increase of surface heat and the decay of turbulent mixing as a result of switching monsoon, leaded to the strongest stratification and minimum mixed layer depth in the euphotic layer (Shi et al., 2001), which restrain the vertical nutrient supply and phytoplankton photosynthesis in the upper layer (Hu et al., 2014). The results in the present study confirm that the nutrient limitation index (µ0/µn) is related to nutrients concentrations (nitrate plus nitrite, ammonium and silicate) (Table 7). Caron and Dennett (1999) pointed the ratio of μ0/μn was averaged 0.71 during the spring intermonsoon season in the Arabian Sea, corresponded to samples in which total dissolved inorganic nitrogen concentrations were low. In contrast to spring intermonsoon season, the ratio of μ0/μn was 0.94 on average during the winter northeast monsoon season with higher nutrient concentrations.
However, there was no significant correlation between phytoplankton growth rate and nutrients concentrations, even that the phytoplankton growth rate was higher in the CSCS with lower nutrients concentrations than those in the NSCS (Fig. 5). One possible explanation is that different phytoplankton may have differently responded to nutrients. Phytoplankton community in oligotrophic subtropical and tropical waters is usually dominated by small sized pico-cells (<3 µm), including Prochlorococcus, Synechoccus and pico-eukaryotic phytoplankton (Zubkov et al., 2000; Liu et al., 2007). Small phytoplankton are better adapted oligotrophic environment because of their larger surface-to-volume ratio, which gives them an advantage in acquiring nutrients and absorbing light energy competing with larger cells (Raven, 1998). Liu et al. (2009) reported that both the abundance and growth rate of Synechococcus increased with the water temperature increasing, similar to the results of previous studies (Tsai et al., 2005; Chang et al., 1996). Zhou et al. (2015a) also noted there were higher growth rates of pico-phytoplankton than micro-phytoplankton in the SCS. Furthermore, although the nutrient concentrations are low in the CSCS, phytoplankton may obtain nutrients support from cellular internal recycled nutrients and nutrients remineralization by grazers (Sun et al., 2013; Zhou et al., 2015a). Zhou et al. (2015a) speculated the coupling between microzooplankton grazing and phytoplankton growth rates could helpful sustain the high rate of phytoplankton growth by using the recycled nutrient supply through microzooplankton grazing in the SCS only when the phytoplankton standing stock was in a relatively low level like the CSCS in present study (p<0.01, R2=0.79) (Fig. 6a). With the increase of phytoplankton standing stock, there might be a looser coupling between phytoplankton and microzooplankton (Strom, 2002; Irigoien et al., 2005) like the NSCS in present study (p<0.01, R2=0.71) (Fig. 6a). High grazing impact on phytoplankton by microzooplankton could be the result of the close coupling between phytoplankton growth and microzooplankton grazing rates (Zhou et al., 2015a). As a result, the higher growth rate and grazing rate are emerged in the CSCS. Meanwhile, the higher grazing impacts in the CSCS than those in the NSCS contribute to maintain higher biomass and primary production in the NSCS.
5 Conclusions
Less
Generally, it is believed that temperature and feed concentration are the major factors affecting microzooplankton abundance. Temperature plays an obvious role in promoting the abundance and distribution of microzooplankton in the present study. Strangely, there is no correlation between microzooplankton abundance and Chl a concentration. Some other factors are also playing an unknown role, maybe the nanozooplankton or cascading trophic relationships. Composition and size of phytoplankton, ingestion by the higher consumers (meso- and macrozooplankton) and environmental factors may be the culprit and need further study to determine.
Significant spatial variations in phytoplankton growth rate and microzooplankton grazing rate as well as environmental variables between the NSCS and CSCS, are observed in the present study. There are obviously higher m, μ0 and grazing impact (m/μ0) though the nutrients and Chl a concentrations are lower in the CSCS than those in the NSCS, separately. Temperature can be one important factor affecting both rates, but more sensitive for grazing rate, which may contribute to higher m and m/μ0 in the CSCS. Due to the lack of nutrients in the surface layer during the spring intermonsoon season, the growth of phytoplankton is affected and the nutrient limitation index (µ0/µn) is obviously related to nutrient concentrations. Nevertheless, the dominant pico-phytoplankton can effectively utilize nutrients because of their larger surface-to-volume ratio even in oligotrophic waters. Meanwhile, phytoplankton could obtain nutrients support to maintain growth from cellular internal recycled nutrients and nutrients remineralized by grazers. The coupling between microzooplankton grazing and phytoplankton growth may promote nutrient recycling and maintain high grazing impact on phytoplankton.
Funding
Less
  • The National Key Research and Development Program of China under contract No. 2019YFC1407805; the National Natural Science Foundation of China under contract Nos 41876134 and 41676112; the University Innovation Team Training Program for Tianjin under contract No. TD12-5003; the Tianjin 131 Innovation Team Program under contract No. 20180314; the Changjiang Scholar Program of Chinese Ministry of Education to Jun Sun under contract No. T2014253.
References
Less
Archer S D, Leakey R J G, Burkill P H, et al. 1996. Microbial dynamics in coastal waters of East Antarctica: herbivory by heterotrophic dinoflagellates. Marine Ecology Progress Series, 139: 239–255, doi: 10.3354/meps139239
Banse K. 2007. Do we live in a largely top-down regulated world?. Journal of Biosciences, 32(4): 791–796, doi: 10.1007/s12038-007-0080-6
Belzile C, Demers S, Ferreyra G A, et al. 2006. UV effects on marine planktonic food webs: a synthesis of results from mesocosm studies. Photochemistry and Photobiology, 82(4): 850–856, doi: 10.1562/2005-09-27-RA-699
Burkill P H, Mantoura R F C, Llewellyn C A, et al. 1987. Microzooplankton grazing and selectivity of phytoplankton in coastal waters. Marine Biology, 93(4): 581–590, doi: 10.1007/BF00392796
Calbet A, Landry M R. 2004. Phytoplankton growth, microzooplankton grazing, and carbon cycling in marine systems. Limnology and Oceanography, 49(1): 51–57, doi: 10.4319/lo.2004.49.1.0051
Caron D A, Dennett M R. 1999. Phytoplankton growth and mortality during the 1995 Northeast Monsoon and Spring Intermonsoon in the Arabian Sea. Deep Sea Research Part II: Topical Studies in Oceanography, 46(8–9): 1665–1690, doi: 10.1016/S0967-0645(99)00039-9
Caron D A, Hutchins D A. 2013. The effects of changing climate on microzooplankton grazing and community structure: drivers, predictions and knowledge gaps. Journal of Plankton Research, 35(2): 235–252, doi: 10.1093/plankt/fbs091
Chang J, Chung C C, Gong G C. 1996. Influences of cyclones on chlorophyll a concentration and Synechococcus abundance in a subtropical western Pacific coastal ecosystem. Marine Ecology Progress Series, 140: 199–205, doi: 10.3354/meps140199
Chen Bingzhang, Zheng Liping, Huang Bangqin, et al. 2013. Seasonal and spatial comparisons of phytoplankton growth and mortality rates due to microzooplankton grazing in the northern South China Sea. Biogeosciences, 10(4): 2775–2785, doi: 10.5194/bg-10-2775-2013
Chen Bingzhang, Landry M R, Huang Bangqin, et al. 2012. Does warming enhance the effect of microzooplankton grazing on marine phytoplankton in the ocean?. Limnology and Oceanography, 57(2): 519–526, doi: 10.4319/lo.2012.57.2.0519
Chen Bingzhang, Liu Hongbin, Landry M R, et al. 2009. Close coupling between phytoplankton growth and microzooplankton grazing in the western South China Sea. Limnology and Oceanography, 54(4): 1084–1097, doi: 10.4319/lo.2009.54.4.1084
Chen Y F L. 2005. Spatial and seasonal variations of nitrate-based new production and primary production in the South China Sea. Deep Sea Research Part I: Oceanographic Research Papers, 52(2): 319–340, doi: 10.1016/j.dsr.2004.11.001
Edwards E S, Burkill P H, Stelfox C E. 1999. Zooplankton herbivory in the Arabian Sea during and after the SW monsoon, 1994. Deep Sea Research Part II: Topical Studies in Oceanography, 46(3–4): 843–863, doi: 10.1016/S0967-0645(98)00130-1
First M R, Lavrentyev P J, Jochem F J. 2007. Patterns of microzooplankton growth in dilution experiments across a trophic gradient: implications for herbivory studies. Marine Biology, 151(5): 1929–1940, doi: 10.1007/s00227-007-0629-9
Gifford D J. 1988. Impact of grazing by microzooplankton in the Northwest Arm of Halifax Harbour, Nova Scotia. Marine Ecology Progress Series, 47: 249–258, doi: 10.3354/meps047249
Gifford D J, Fessenden L M, Garrahan P R, et al. 1995. Grazing by microzooplankton and mesozooplankton in the high-latitude North Atlantic Ocean: spring versus summer dynamics. Journal of Geophysical Research, 100(C4): 6665–6675, doi: 10.1029/94JC00983
Gómez F. 2007. Trends on the distribution of ciliates in the open Pacific Ocean. Acta Oecologica, 32(2): 188–202, doi: 10.1016/j.actao.2007.04.002
Gong G C, Liu K K, Liu C T, et al. 1992. The chemical hydrography of the South China Sea west of Luzon and a comparison with the West Philippine Sea. Terrestrial, Atmospheric and Oceanic Sciences, 3(4): 587–602, doi: 10.3319/TAO.1992.3.4.587(O
Hansen H P, Koroleff F. 2007. Determination of nutrients. In: Grasshoff K, Kremling K, Ehrhardt M, eds. Methods of Seawater Analysis. 3rd ed. New York: Wiley
Hu Zifeng, Tan Yehui, Song Xingyu, et al. 2014. Influence of mesoscale eddies on primary production in the South China Sea during spring inter-monsoon period. Acta Oceanologica Sinica, 33(3): 118–128, doi: 10.1007/s13131-014-0431-8
Irigoien X, Flynn K J, Harris R P. 2005. Phytoplankton blooms: a ‘loophole’ in microzooplankton grazing impact?. Journal of Plankton Research, 27(4): 313–321, doi: 10.1093/plankt/fbi011
Jin Dexiang, Chen Jinhuan, Huang Kaige. 1965. China Marine Planktonic Diatoms (in Chinese). Shanghai: Shanghai Scientific and Technical Publishers, 1–219
Jyothibabu R, Devi C R A, Madhu N V, et al. 2008. The response of microzooplankton (20–200 μm) to coastal upwelling and summer stratification in the southeastern Arabian Sea. Continental Shelf Research, 28(4–5): 653–671, doi: 10.1016/j.csr.2007.12.001
Landry M R. 1993. Estimating rates of growth and grazing mortality of phytoplankton by the dilution method. In: Kemp P J, Cole J J, Sherr B F, et al., eds. Handbook of Methods in Aquatic Microbial Ecology. New York: CRC Press, 715–722
Landry M R, Brown S L, Campbell L, et al. 1998. Spatial patterns in phytoplankton growth and microzooplankton grazing in the Arabian Sea during monsoon forcing. Deep Sea Research Part II: Topical Studies in Oceanography, 45(10–11): 2353–2368, doi: 10.1016/S0967-0645(98)00074-5
Landry M R, Calbet A. 2004. Microzooplankton production in the oceans. ICES Journal of Marine Science, 61(4): 501–507, doi: 10.1016/j.icesjms.2004.03.011
Landry M R, Hassett R P. 1982. Estimating the grazing impact of marine micro-zooplankton. Marine Biology, 67(3): 283–288, doi: 10.1007/BF00397668
Lehman J T. 1991. Interacting growth and loss rates: the balance of top-down and bottom-up controls in plankton communities. Limnology and Oceanography, 36(8): 1546–1554, doi: 10.4319/lo.1991.36.8.1546
Leising A W, Horner R, Pierson J J, et al. 2005. The balance between microzooplankton grazing and phytoplankton growth in a highly productive estuarine fjord. Progress in Oceanography, 67(3–4): 366–383, doi: 10.1016/j.pocean.2005.09.007
Li Fengqi, Su Yusong. 2000. Analyses of Water Masses in Oceans (in Chinese). Qingdao: Qingdao Ocean University Press, 377–378
Liu Hongbin, Chang J, Tseng C M, et al. 2007. Seasonal variability of picoplankton in the Northern South China Sea at the SEATS station. Deep Sea Research Part II: Topical Studies in Oceanography, 54(14–15): 1602–1616, doi: 10.1016/j.dsr2.2007.05.004
Liu Hongbin, Suzuki K, Nishioka J, et al. 2009. Phytoplankton growth and microzooplankton grazing in the Sea of Okhotsk during late summer of 2006. Deep Sea Research Part I: Oceanographic Research Papers, 56(4): 561–570, doi: 10.1016/j.dsr.2008.12.003
Lonsdale D J, Caron D A, Dennett M R, et al. 2000. Predation by Oithona spp. on protozooplankton in the Ross Sea, Antarctica. Deep Sea Research Part II: Topical Studies in Oceanography, 47(15–16): 3273–3283, doi: 10.1016/S0967-0645(00)00068-0
López-Urrutia Á, Martin E S, Harris R P, et al. 2006. Scaling the metabolic balance of the oceans. Proceedings of the National Academy of Sciences of the United States of America, 103(23): 8739–8744, doi: 10.1073/pnas.0601137103
López-Urrutia Á. 2008. The metabolic theory of ecology and algal bloom formation. Limnology and Oceanography, 53(5): 2046–2047, doi: 10.4319/lo.2008.53.5.2046
Landry M R, Barber R T, Bidigare R R, et al. 1997. Iron and grazing constraints on primary production in the central equatorial Pacific: an EqPac Synthesis. Limnology and Oceanography, 42(3): 405–418, doi: 10.4319/lo.1997.42.3.0405
Macaluso A L, Mitchell D L, Sanders R W. 2009. Direct effects of UV-B radiation on the freshwater heterotrophic nanoflagellate Paraphysomonas sp. Applied and Environmental Microbiology, 75(13): 4525–4530, doi: 10.1128/AEM.02803-08
Nielsen T G, Kicrboe T. 1994. Regulation of zooplankton biomass and production in a temperate, coastal ecosystem. 2. Ciliates. Limnology and Oceanography, 39(3): 508–519, doi: 10.4319/lo.1994.39.3.0508
Ning X, Chai F, Xue H, et al. 2004. Physical-biological oceanographic coupling influencing phytoplankton and primary production in the South China Sea. Journal of Geophysical Research, 109(C10): C10005, doi: 10.1029/2004JC002365
Paranjape M A. 1987. Grazing by microzooplankton in the eastern Canadian arctic in summer 1983. Marine Ecology Progress Series, 40: 239–246, doi: 10.3354/meps040239
Porter K G, Sherr E B, Sherr B F, et al. 1985. Protozoa in planktonic food webs. The Journal of Protozoology, 32(3): 409–415, doi: 10.1111/j.1550-7408.1985.tb04036.x
Quevedo M, Viesca L, Anadón R, et al. 2003. The protistan microzooplankton community in the oligotrophicnorth-eastern Atlantic: large- and mesoscale patterns. Journal of Plankton Research, 25(5): 551–563, doi: 10.1093/plankt/25.5.551
Raven J A. 1998. The twelfth Tansley Lecture. Small is beautiful: the picophytoplankton. Functional Ecology, 12(4): 503–513
Rose J M, Caron D A. 2007. Does low temperature constrain the growth rates of heterotrophic protists? Evidence and implications for algal blooms in cold waters. Limnology and Oceanography, 52(2): 886–895, doi: 10.4319/lo.2007.52.2.0886
Schmoker C, Hernández-León S, Calbet A. 2013. Microzooplankton grazing in the oceans: impacts, data variability, knowledge gaps and future directions. Journal of Plankton Research, 35(4): 691–706, doi: 10.1093/plankt/fbt023
Setälä O, Kivi K. 2003. Planktonic ciliates in the Baltic Sea in summer: distribution, species association and estimated grazing impact. Aquatic Microbial Ecology, 32(3): 287–297
Shi Ping, Du Yan, Wang Dongxiao, et al. 2001. Annual cycle of mixed layer in South China Sea. Journal of Tropical Oceanography (in Chinese), 20(1): 10–17
Stelfox-Widdicombe C E, Edwards E S, Burkill P H, et al. 2000. Microzooplankton grazing activity in the temperate and sub-tropical NE Atlantic: summer 1996. Marine Ecology Progress Series, 208: 1–12, doi: 10.3354/meps208001
Strom S. 2002. Novel interactions between phytoplankton and microzooplankton: their influence on the coupling between growth and grazing rates in the sea. Hydrobiologia, 480(1–3): 41–54
Strom S L, Macri E L, Olson M B. 2007. Microzooplankton grazing in the coastal gulf of Alaska: variations in top-down control of phytoplankton. Limnology and Oceanography, 52(4): 1480–1494, doi: 10.4319/lo.2007.52.4.1480
Strom S L, Welschmeyer N A. 1991. Pigment-specific rates of phytoplankton growth and microzooplankton grazing in the open subarctic Pacific Ocean. Limnology and Oceanography, 36(1): 50–63, doi: 10.4319/lo.1991.36.1.0050
Su Jilan. 2004. Overview of the South China Sea circulation and its influence on the coastal physical oceanography outside the Pearl River Estuary. Continental Shelf Research, 24(16): 1745–1760, doi: 10.1016/j.csr.2004.06.005
Su Qiang, Huang Liangmin, Tan Yehui, et al. 2007. Preliminary study of microzooplankton grazing and community composition in the north of South China Sea in autumn. Marine Science Bulletin, 9(2): 43–53
Sun Jun. 2013. Carbon calculation on marine phytoplankton and its related fishery carbon sink. Progress in Fishery Sciences (in Chinese), 34(1): 90–96
Sun Jun, Feng Yuanyuan, Wang Dan, et al. 2013. Bottom-up control of phytoplankton growth in spring blooms in Central Yellow Sea, China. Deep Sea Research Part II: Topical Studies in Oceanography, 97: 61–71, doi: 10.1016/j.dsr2.2013.05.006
Sun Jun, Feng Yuanyuan, Zhang Yaohong, et al. 2007. Fast microzooplankton grazing on fast-growing, low-biomass phytoplankton: a case study in spring in Chesapeake Bay, Delaware Inland Bays and Delaware Bay. Hydrobiologia, 589(1): 127–139, doi: 10.1007/s10750-007-0730-6
Sun Jun, Guo Shujin. 2011. Dinoflagellate heterotrophy. Acta Ecologica Sinica (in Chinese), 31(20): 6270–6286
Tan Saichun, Shi Guangyu. 2009. Spatiotemporal variability of satellite-derived primary production in the South China Sea, 1998–2006. Journal of Geophysical Research, 114(G3): G03015
Teixeira I G, Figueiras F G. 2009. Feeding behaviour and non-linear responses in dilution experiments in a coastal upwelling system. Aquatic Microbial Ecology, 55(1): 53–63
Tian Yongqing, Huang Honghui, Gong Xiuyu, et al. 2016. The formation mechanism of the low temperature and high salinity water mass near the Zhongsha Islands in the South China Sea in March 2014. Journal of Tropical Oceanography (in Chinese), 35(2): 1–9
Tsai A Y, Chiang K P, Chang J, et al. 2005. Seasonal diel variations of picoplankton and nanoplankton in a subtropical western Pacific coastal ecosystem. Limnology and Oceanography, 50(4): 1221–1231, doi: 10.4319/lo.2005.50.4.1221
Utermöhl H. 1958. Zur vervollkommnung der quantitativen phytoplankton-methodik: mit 1 tabelle und 15 abbildungen im text und auf 1 tafel. SIL Communications, 9(1): 1–38
Verity P G, Stoecker D K, Sieracki M E, et al. 1993. Grazing, growth and mortality of microzooplankton during the 1989 North Atlantic spring bloom at 47°N, 18°W. Deep Sea Research Part I: Oceanographic Research Papers, 40(9): 1793–1814, doi: 10.1016/0967-0637(93)90033-Y
Verity P G, Wassmann P, Frischer M E, et al. 2002. Grazing of phytoplankton by microzooplankton in the Barents Sea during early summer. Journal of Marine Systems, 38(1–2): 109–123, doi: 10.1016/S0924-7963(02)00172-0
Welschmeyer N A. 1994. Fluorometric analysis of chlorophyll a in the presence of chlorophyll b and pheopigments. Limnology and Oceanography, 39(8): 1985–1992, doi: 10.4319/lo.1994.39.8.1985
Wong G T F, Ku T L, Mulholland M, et al. 2007. The Southeast Asian Time-series Study (SEATS) and the biogeochemistry of the South China Sea—an overview. Deep Sea Research Part II: Topical Studies in Oceanography, 54(14–15): 1434–1447, doi: 10.1016/j.dsr2.2007.05.012
Wu Jingfeng, Chung S W, Wen L S, et al. 2003. Dissolved inorganic phosphorus, dissolved iron, and Trichodesmium in the oligotrophic South China Sea. Global Biogeochemical Cycles, 17(1): 1008
Yamaji I. 1966. Illustrations of the Marine Plankton of Japan. Osaka: Hoikusha Publishing Co Ltd, 1–538
Yang E J, Choi J K, Hyun J H. 2004. Distribution and structure of heterotrophic protist communities in the northeast equatorial Pacific Ocean. Marine Biology, 146(1): 1–15, doi: 10.1007/s00227-004-1412-9
Zhang Wuchang, Feng Meiping, Yu Ying, et al. 2012. Illustrated Guide to Contemporary Tintinnids in the World (in Chinese). Beijing: Science Press
Zhang Jiangtao, Yin Kedong, Dong Lihua. 2011. Microzooplankton grazing rate of size-fractionated phytoplankton in spring in the Yellow Sea, China. Marine Sciences (in Chinese), 35(9): 1–7
Zhang Wuchang, Yu Ying, Xiao Tian. 2015. An Illustrated Guide to Marine Planktonic Aloricate Oligotrich Ciliates (in Chinese). Beijing: Science Press
Zheng Guangming, Tang Danling. 2007. Offshore and nearshore chlorophyll increases induced by typhoon winds and subsequent terrestrial rainwater runoff. Marine Ecology Progress Series, 333: 61–74
Zhou Linbin, Tan Yehui, Huang Liangmin, et al. 2011. Phytoplankton growth and microzooplankton grazing in the continental shelf area of northeastern South China Sea after Typhoon Fengshen. Continental Shelf Research, 31(16): 1663–1671, doi: 10.1016/j.csr.2011.06.017
Zhou Linbin, Tan Yehui, Huang Liangmin, et al. 2015a. Does microzooplankton grazing contribute to the pico-phytoplankton dominance in subtropical and tropical oligotrophic waters?. Acta Ecologica Sinica, 35(1): 29–38, doi: 10.1016/j.chnaes.2014.12.007
Zhou Linbin, Tan Yehui, Huang Lianmin, et al. 2015b. Seasonal and size-dependent variations in the phytoplankton growth and microzooplankton grazing in the southern South China Sea under the influence of the East Asian monsoon. Biogeosciences, 12(22): 6809–6822, doi: 10.5194/bg-12-6809-2015
Zubkov M V, Sleigh M A, Burkill P H. 2000. Assaying picoplankton distribution by flow cytometry of underway samples collected along a meridional transect across the Atlantic Ocean. Aquatic Microbial Ecology, 21(1): 13–20
Appendix
Less
Year 2020 volume 39 Issue 6
PDF
40
21
Cite this Article
BibTeX
Article Info
doi: 10.1007/s13131-020-1593-1
  • Receive Date：2019-05-15
  • Online Date：2026-03-31
  • Published：2020-06-25
Article Data
Affiliations
History
  • Received：2019-05-15
  • Accepted：2019-06-17
Funding
The National Key Research and Development Program of China under contract No. 2019YFC1407805; the National Natural Science Foundation of China under contract Nos 41876134 and 41676112; the University Innovation Team Training Program for Tianjin under contract No. TD12-5003; the Tianjin 131 Innovation Team Program under contract No. 20180314; the Changjiang Scholar Program of Chinese Ministry of Education to Jun Sun under contract No. T2014253.
Affiliations
    1 Tianjin Key Laboratory of Marine Resources and Chemistry, Tianjin University of Science and Technology, Tianjin 300457, China
    2 Research Centre for Indian Ocean Ecosystem, Tianjin University of Science and Technology, Tianjin 300457, China
    3 State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China

Corresponding:

References
Share
https://castjournals.cast.org.cn/joweb/aos/EN/10.1007/s13131-020-1593-1
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT
Links
Articles
Latest Articles
Most Read
Collections
Updates
Events
News
Multimedia
About
About Us
Contact
No. 86 Xueyuan South Road, Haidian District, Beijing
100081
010-62199257
qkjq@cast.org.cn

Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House