Home Journals Articles Updates About
CN
image
收藏切换
Carbon-to-chlorophyll ratio and carbon content of phytoplankton community at the surface in coastal waters adjacent to the Zhujiang River Estuary during summer
收藏切换
PDF
Xiaoyong Yu1, 2, Jie Xu1, 2, *, Aimin Long1, 2, Ruihuan Li1, Zhen Shi1, Qian P Li1, 2
Acta Oceanologica Sinica | 2020, 39(2) : 123 - 131
Less
收藏切换
Acta Oceanologica Sinica | 2020, 39(2): 123-131
• Marine Biology •
Carbon-to-chlorophyll ratio and carbon content of phytoplankton community at the surface in coastal waters adjacent to the Zhujiang River Estuary during summer
Full
Xiaoyong Yu1, 2, Jie Xu1, 2, *, Aimin Long1, 2, Ruihuan Li1, Zhen Shi1, Qian P Li1, 2
Affiliations
  • 1 State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanography, Chinese Academy of Sciences, Guangzhou 510301, China
  • 2 University of Chinese Academy of Sciences, Beijing 100049, China
Published: 2020-02-25 doi: 10.1007/s13131-020-1556-6
Outline
收藏切换

Chlorophyll a (Chl a), particulate organic carbon (POC) and biogenic silica (BSi) were determined in coastal waters adjacent to the Zhujiang (Pearl) River Estuary (ZRE) during summer, in order to examine the C:Chl a ratio of phytoplankton and phytoplankton carbon in the plume-impacted coastal waters during summer, as well as to assess the relative contribution of diatoms to the phytoplankton biomass, by the regression between Chl a, POC and BSi. Our results showed that the C:Chl a ratio (g/g) of phytoplankton was high (up to 142), likely due to high light intensity and nutrient limitation. The river plume input stimulated phytoplankton growth, especially diatoms, resulting in higher relative contribution of phytoplankton carbon (55%) and diatoms (34%) to POC in the plume-impacted region​​​​​​​​​​​​​​ than those (33% and 13%) in high salinity area, respectively. Phytoplankton carbon (up to 538 μg/L) in the plume-impacted region was much higher than that (<166 μg/L) in high salinity area. Our findings were helpful to improve the biogeochemical model in coastal waters adjacent to the ZRE.

chlorophyll a  /  particulate organic carbon  /  biogenic silica  /  phytoplankton carbon  /  diatoms
Xiaoyong Yu, Jie Xu, Aimin Long, Ruihuan Li, Zhen Shi, Qian P Li. Carbon-to-chlorophyll ratio and carbon content of phytoplankton community at the surface in coastal waters adjacent to the Zhujiang River Estuary during summer[J]. Acta Oceanologica Sinica, 2020 , 39 (2) : 123 -131 . DOI: 10.1007/s13131-020-1556-6
Full Text
Less
1 Introduction
Less
Chlorophyll a (Chl a) is extensively used as a proxy of phytoplankton biomass, since Chl a is unique to plants and easily measured. However, the concentrations of pigments in phytoplankton cells vary with light and nutrient supply (Chan, 1980; Neale et al., 1989). It is desirable to characterize phytoplankton biomass in form of organic carbon instead of Chl a, in order to compare phytoplankton biomass with the biomass of other plankton such as viruses, bacteria and zooplankton (Buck et al., 1996). Furthermore, carbon content is the only variable to express phytoplankton biomass in the biogeochemical or ecological model. However, particulate organic carbon (POC) cannot be used to characterize phytoplankton biomass because it is not specific to phytoplankton and furthermore phytoplankton may not dominate in POC in terms of carbon content in unproductive regions. However, it is difficult to estimate phytoplankton carbon (PC) in marine environments as there is not an approach to separate phytoplankton carbon and non-phytoplankton carbon. Phytoplankton carbon can be estimated by Chl a concentration and the C:Chl a ratio of phytoplankton since Chl a is routinely measured as a robust parameter of phytoplankton biomass in practice. The C:Chl a ratio can be obtained by the linear regression of POC vs. Chl a concentrations (Cho and Azam, 1990; Chang et al., 2003).
The C:Chl a ratio varies in a wide range across marine environments because of different environmental conditions (Geider, 1993; Buck et al., 1996; Chang et al., 2003; Vázquez-Domínguez et al., 2013). Hence, it is necessary to study the C:Chl a ratio across marine environments, in order to estimate the carbon content of the phytoplankton community. In coastal waters, diatoms are often the dominant species of the phytoplankton community, which contribute up to 75% of primary production (Nelson et al., 1995; Tréguer and De La Rocha, 2013). It was ecologically important to quantify the contribution of diatoms to phytoplankton biomass in coastal waters, to better understand the role of diatoms in carbon export in biological pump.
The coastal waters in the northern South China Sea are subjected to the influence of the Zhujiang River discharge during summer (Xu et al., 2008). The Zhujiang River is the second largest river in China in terms of freshwater discharge, with an annual average freshwater discharge of 1.05×104 m3/s (Yin et al., 2000). Around 80% of the river discharge occurs in the wet season (April–September). The river plume improved phytoplankton biomass dramatically in coastal waters (Xu et al., 2008). In the plume-impacted coastal waters, phytoplankton carbon and the C:Chl a ratio of phytoplankton has never been quantified, which was of significance to improve a biogeochemical model for the northern South China Sea. In this study, the objectives were to compare the C:Chl a ratios of phytoplankton and phytoplankton carbon between the plume-impacted coastal waters and the waters with no influence of the plume during summer, as well as the relative contribution of diatoms to the phytoplankton biomass.
2 Materials and methods
Less
2.1 Study sites
A cruise was conducted in June 14 to 29, 2016 in the Zhujiang River Estuary and its adjacent coastal waters aboard the R/V Haike 68. A total of 58 stations were visited and vertical profiles of temperature, salinity and fluorescence were measured with a CTD (Sea-bird) at each station. At twenty stations of which, nutrients, chlorophyll a (Chl a), particulate organic carbon/nitrogen (POC/N) and biogenic silica (BSi) were collected at the surface (Fig. 1).
2.2 Nutrients, Chl a, POC/N and BSi
Water samples for nutrients were filtered through the glass fiber filters (GF/F) and immediately frozen (–20°C) until analyzed. Inorganic nutrient concentrations were measured colorimetrically with a Seal AA3 auto analyzer (Bran-Luebbe, GmbH). The low concentrations of NO2+NO3 and soluble PO4 (orthophosphate) within the euphotic zone were measured by the long-cell method (Li et al., 2008; Li and Hansell, 2008) by incorporating a 50 cm liquid waveguide cell to AA3 with detection limits of 0.02 and 0.01 μmol/L, respectively.
For Chl a samples, 250 mL to 1 L seawater was filtered on the glass fiber filters (GF/F) and stored at –20°C immediately until analyzed. Chl a samples were sonicated for 20 min and extracted in 90% acetone at 4°C in the dark for 24 h. The samples were determined using a Turner Designs Model 10 Fluorometer after being centrifuged at 4 000 r/min for 10 min (Parsons et al., 1984).
The 250 mL to 1 L seawater for POC and PON samples were filtered onto precombusted (4 h at 460°C) 25 mm Whatman GF/F filters. Filters were dried at 60°C in an oven overnight and POC/N was determined with a CHN analyzer (Elementar, Vario El Cube).
Biogenic silica in suspended matter was determined using alkaline extraction method (Ragueneau et al., 2005). Biogenic silica samples were collected on GE polycarbonate membranes (47-mm in diameter, 1 μm in pore size) in situ by filtering 250 mL to 1 L seawater. The filters were kept at –20°C immediately until analyzed. The filter was extracted using 0.2 mol/L NaOH (4.0 mL, pH 13.3) in polypropane centrifuge tube (Corning, polypropane, 15 mL) at 100°C for 40 min. After being cooled down to room temperature, 1.0 mL 1.0 mol/L HCl was added to neutralize the pH. Dissolved silicate [Si]1 and aluminum [Al]1 concentrations were determined after the supernatant was centrifuged for 10 min at 2 500 r/min. Subsequently, the filter was rinsed with deionized water for three times and dried at 60°C. The filter was digested again following the above digestion procedure. [Si]2 and [Al]2 were determined. (Si:Al)2 ratio was calculated from [Si]2/[Al]2 in the second step.
Dissolved silicate concentrations in the supernatant were determined according to the method described by Grasshoff et al. (1999). The dissolved aluminum concentrations were determined with a fluorescence spectrophotometer following the approach described by Ren et al. (2001). The corrected concentration of biogenic silica [BSi] was obtained using the following equation:
$\left[ {{\rm{BSi}}} \right] = {\left[ {{\rm{Si}}} \right]_1} - {\rm{ }}{\left[ {{\rm{Al}}} \right]_1} \times \frac{{{{\left[ {{\rm{Si}}} \right]}_2}}}{{{{\left[ {{\rm{Al}}} \right]}_2}}}.$
2.3 Estimate of the C:Chl a ratio, phytoplankton carbon, the relative contribution of phytoplankton to POC, the relative contribution of diatoms to phytoplankton biomass and POC
The average C:Chl a ratio of phytoplankton was derived from the slope in the regression of POC vs. Chl a. Phytoplankton carbon was calculated by multiplying Chl a concentration by the average C:Chl a ratio of phytoplankton for each sample. The relative contribution of phytoplankton to POC was obtained by dividing PC by POC.
The average Chl a:BSi ratio for diatoms was estimated by the slope in the regression of Chl a and BSi. The Chl a derived from diatoms was obtained by multiplying BSi concentration by the average Chl a:BSi ratio for each sample. The relative contribution of diatoms to phytoplankton was obtained by dividing Chl a derived from diatoms by Chl a. Similarly, the average C:BSi ratio for diatoms was estimated by the slope in the regression of POC and BSi. The POC derived from diatoms was obtained by multiplying BSi concentration by the average C:BSi ratio for each sample. The relative contribution of diatoms to POC was obtained by dividing POC derived from diatoms by POC.
2.4 Statistical analysis
Statistical analysis was performed using the Origin 8.5 software. A Pearson’s test was conducted to determine the significant correlation between variables (salinity, Chl a, POC, BSi, PC:POC) (p<0.05).
3 Results
Less
Salinity and temperature exhibited clear spatial variations (Fig. 2). Surface salinity varied in a wide range from 23.5 to 34. High salinity (>33) and low temperature (<29°C) were observed in upwelling region near the shore. The plume-impacted region was defined as the area with surface salinity of <32 (Mao et al., 1963). In twenty stations chosen (Table 1), six stations (Stas 13, 16, 30, 46, 49 and 51) with high surface salinity (>32) were considered to be not influenced by the river plume (Fig. 2).
Nutrients, Chl a, POC and BSi varied spatially, showing the pattern opposite to salinity. The highest nutrient concentration (NO3: 14.8 μmol/L, PO4: 0.12 μmol/L and SiO4: 4.95 μmol/L) occurred at Sta. 1 with the lowest salinity (23.5) (Table 1). At high salinity (>32) stations, nutrients remained low (NO3: <0.7 μmol/L, PO4: <0.12 μmol/L, Table 1). Similarly, the concentrations of Chl a, POC, PON and BSi were generally high (Chl a: 0.92–3.79 μg/L, POC: 21.5–67.9 μmol/L, PON: 2.81–13.1 μmol/L and BSi: up to 15.0 μmol/L) at low salinity stations and low (Chl a: <1.30 μg/L, POC: <33.0 μmol/L, PON: <8.89 μmol/L and BSi: mostly <1.70 μmol/L) at high salinity stations (Table 1, Fig. 3). C:N ratios (mol/mol) varied from 2.84 to 7.65 at all stations and did not considerably differ between the plume-impacted region and the high salinity area (Table 1). In addition, there was a significant negative correlation between salinity and these variables (Chl a, POC and BSi) (Fig. 4).
A regression between Chl a, BSi and POC in the plume-impacted region and high salinity area was observed, respectively (Table 2, Fig. 5). The average ratio of BSi to Chl a for diatoms was 0.19 and 0.14 in the plume-impacted region and high salinity area, respectively (Table 2). The relative contribution of diatoms to Chl a was on average 51% (14.1%–75.1%) in the plume-impacted region and 29% (11.2%–66.2%) in the high salinity area (Fig. 6, Table 2). The average ratio of BSi to POC was 2.80 and 1.91 in the plume-impacted region and the high salinity area, respectively (Table 2). The relative contribution of diatoms to POC was on average 34% (8.9%–61.8%) in the plume-impacted region and 13% (3.1%–33.6%) in the high salinity area (Fig. 6, Table 2). The average C:Chl a ratio (g/g) of phytoplankton was 142 in the plume-impacted region and 135 in the high salinity area, respectively (Table 2). The relative contribution of phytoplankton to POC was 55% (35.0%–72.9%) in the plume-impacted region and 33% (21.5%–48.5%) in the high salinity area (Fig. 6, Table 2). Phytoplankton carbon (PC) varied spatially, with high (up to 538 μg/L) in the plume-impacted region and low (<166 μg/L) in the high salinity area (Fig. 7).
4 Discussion
Less
In summer, a large area of the coastal waters in the northern South China Sea is subjected to the effect of the Zhujiang River Estuary, which delivers huge amount of nutrients. As a result, there was a clear environmental gradient along the inshore-offshore transect, as indicated by spatial variations in salinity. The Zhujiang River discharge input not only increased nutrient concentrations but also altered nutrient structure, leading to potential phosphorus limitation (Xu et al., 2008). Chl a, BSi and POC exhibited the same spatial pattern. Furthermore, salinity was significantly correlated with Chl a, BSi and POC (Fig. 4). These results suggested that riverine nutrient input triggered algal growth. Nutrient enrichment favored diatom blooms, resulting in the dominance of diatoms in the phytoplankton community. In nutrient-rich waters, the predominance of diatoms has been reported (Tréguer and De La Rocha, 2013). In addition, a significant correlation between Chl a and BSi concentrations in the plume-impacted region (Table 2, Fig. 5) was observed, confirming that the riverine nutrient input preferentially stimulated diatom growth. BSi and Chl a are the robust proxy of diatoms and phytoplankton biomass, respectively. According to the relationship between Chl a and BSi, it was estimated that diatoms contributed to on average 51% of Chl a-based phytoplankton biomass in the plume-impacted region, which was higher than that (29%) in the high salinity region. Correspondingly, it was estimated that diatoms made up 34% and 13% of POC in the plume-impacted region and high salinity area, respectively. Furthermore, the relative contribution of diatoms to POC and Chl a-based phytoplankton biomass was enhanced in the plume-impacted region, corroborating that diatoms outcompeted other phytoplankton groups as nutrients increased. Hence, the riverine nutrient input shifted the phytoplankton community composition and enhanced the contribution of diatoms to primary production.
POC:PON ratio (mol/mol) was on average 5.27 in this study. Meyer et al. (1994) suggested that the C:N ratio was 4–10 for phytoplankton, 6–8 for freshwater algae, approximately 5 for marine algae and more than 20 for terrestrial plants. Hence, POC primarily originated from marine organisms in the study area. In estuarine and coastal waters, POC origins were complicated and resulted from both phytoplankton-derived carbon and non-phytoplankton-derived carbon (Wienke and Cloern, 1987). It was very difficult to separate phytoplankton-derived carbon from non-phytoplankton-derived carbon. However, it was ecologically important to quantify the phytoplankton-derived carbon in aquatic environments. The regression of POC and Chl a is often used to estimate the phytoplankton-derived carbon by the C:Chl a ratio (Chang et al., 2003; Jakobsen and Markager, 2016). In our study, the C:Chl a ratio of phytoplankton at the surface was on average 142 in the plume-impacted region and 135 in high salinity area with no effect of the river plume, respectively.
The C:Chl a ratios of phytoplankton in aquatic environments are generally regulated by numerous factors, such as temperature, light, nutrient concentrations (Zeitzschel, 1970). Laws and Bannister (1980) found that algae were able to adjust cellular carbon and chlorophyll quota according to the light levels. Nutrient limitation is regarded as an important factor for high C:Chl a ratio, which induces an increase in the C:Chl a ratios of phytoplankton (Hunter and Laws, 1981; Taylor et al., 1997). Generally, C:Chl a ratio was low in the light-limited conditions and high in high light levels and low nutrient conditions (Hunter and Laws, 1981; Taylor et al., 1997). The high salinity area was characterized by the pristine seawater with low nutrient concentrations (NO3<1 μmol/L, PO4<0.15 μmol/L; Table 1). In the plume-impacted region, despite of high nutrient input, phosphorus limitation occurred, while nitrogen limitation occurred in regions with no influence of the river plume in the South China Sea (Xu et al., 2008). Phosphorus limitation improved the C:Chl a ratio of phytoplankton. Redalje and Laws (1981) found that the C:Chl a ratios of phytoplankton increased to 200-300 for diatoms under nutrient-limited conditions. Furthermore, light levels in summer were high at the surface in tropical coastal waters we studied. Hence, high C:Chl a ratios of phytoplankton at the surface were attributed to high light intensity and nutrient limitation.
The C:Chl a ratios of phytoplankton reported were variable in a wide range across environments, such as 18.0–94.4 in the East China Sea (Chang et al., 2003), (>100) in the Columbia Estuary (Small and Prahl, 2004), (>100) in the surface zone in the North Atlantic Ocean (Buck et al., 1996) and 250 in the Jiaozhou Bay (Lü et al., 2009). Compared to the C:Chl a ratio (94) of phytoplankton in oligotrophic offshore waters of the East China Sea (Chang et al., 2003), the C:Chl a ratios of phytoplankton were higher in coastal waters adjacent to the Zhujiang River Estuary. The study area was located in a tropical region, where light intensity should be higher than that in the East China Sea, which was partly responsible for higher C:Chl a ratio of phytoplankton in pristine high salinity area than offshore waters in the East China Sea.
Based on the C:Chl a ratios of phytoplankton, phytoplankton carbon (up to 538 μg/L) in the plume-impacted region was higher than that (<166 μg/L) in high salinity area. In addition, the fraction of PC to POC was significantly negatively correlated with salinity (Fig. 8). These results suggested that the riverine nutrients stimulated phytoplankton growth and improved the relative contribution of phytoplankton carbon to POC.
5 Conclusions
Less
In summary, the C:Chl a ratio of phytoplankton was high in coastal waters adjacent to the ZRE, likely because of high light intensity and nutrient limitation. The Zhujiang River discharge input triggered algal blooms, especially diatom blooms, improved phytoplankton carbon content and its relative contribution to POC. To our knowledge, this was the first time to report the C:Chl a ratio of phytoplankton, phytoplankton carbon, the relative contribution of phytoplankton and diatoms to POC in coastal waters influenced by the Zhujiang River discharge. Our findings would be useful to improve the biogeochemical model in the northern South China Sea.
Acknowledgements
Less
We thank Dongxiao Wang for providing the CTD data and Kedong Yin for providing POC/N data.
Funding
Less
  • The National Natural Science Foundation of China under contract No. 41476137; the project of Qingdao National Laboratory for Marine Science and Technology under contract No. QNLM2016ORP0305.
References
Less
Buck K R, Chavez F P, Campbell L. 1996. Basin-wide distributions of living carbon components and the inverted trophic pyramid of the central gyre of the North Atlantic Ocean, Summer 1993. Aquatic Microbial Ecology, 10(3): 283–298, doi: 10.3354/ame010283
Chan A T. 1980. Comparative physiological study of marine diatoms and dinoflagellates in relation to irradiance and cell-size. II. Relationship between photosynthesis, growth, and carbon/chlorophyll a ratio. Journal of Phycology, 16(3): 428–432, doi: 10.1111/j.1529-8817.1980.tb03056.x
Chang J, Shiah F K, Gong G C, et al. 2003. Cross-shelf variation in carbon-to-chlorophyll a ratios in the East China Sea, Summer 1998. Deep Sea Research Part II: Topical Studies in Oceanography, 50(6–7): 1237–1247, doi: 10.1016/S0967-0645(03)00020-1
Cho B C, Azam F. 1990. Biogeochemical significance of bacterial biomass in the ocean’s euphotic zone. Marine Ecology Progress Series, 63: 253–259, doi: 10.3354/meps063253
Geider R J. 1993. Quantitative phytoplankton physiology: implications for primary production and phytoplankton growth. In: Proceedings of ICES Marine Science Symposium. Vol 197. Oxford: Oxford University Press, 52–62
Grasshoff K, Kremling K, Ehrhardt M. 1999. Methods of Seawater Analysis. 3rd ed. Weinheim: Wiley-VCH, 159–228
Hunter B L, Laws E A. 1981. ATP and chlorophyll a as estimators of phytoplankton carbon biomass. Limnology and Oceanography, 26(5): 944–956, doi: 10.4319/lo.1981.26.5.0944
Jakobsen H H, Markager S. 2016. Carbon-to-chlorophyll ratio for phytoplankton in temperate coastal waters: seasonal patterns and relationship to nutrients. Limnology and Oceanography, 61(5): 1853–1868, doi: 10.1002/lno.10338
Laws E A, Bannister T T. 1980. Nutrient- and light-limited growth of thalassiosira fluviatilis in continuous culture, with implications for phytoplankton growth in the ocean. Limnology and Oceanography, 25(3): 457–473, doi: 10.4319/lo.1980.25.3.0457
Li Q P, Hansell D A. 2008. Nutrient distributions in baroclinic eddies of the oligotrophic North Atlantic and inferred impacts on biology. Deep Sea Research Part II: Topical Studies in Oceanography, 55(10–13): 1291–1299, doi: 10.1016/j.dsr2.2008.01.009
Li Q P, Hansell D A, Zhang Jiazhong. 2008. Underway monitoring of nanomolar nitrate plus nitrite and phosphate in oligotrophic seawater. Limnology and Oceanography: Methods, 6(7): 319–326, doi: 10.4319/lom.2008.6.319
Lü Shuguo, Wang Xuchen, Han Boping. 2009. A field study on the conversion ratio of phytoplankton biomass carbon to chlorophyll-a in Jiaozhou Bay, China. Chinese Journal of Oceanology and Limnology, 27(4): 793–805, doi: 10.1007/s00343-009-9221-0
Mao H L, Kan T C, Lan S F. 1963. A preliminary study of the Yangtze diluted water and its mixing processes. Oceanologia et Limnologia Sinica (in Chinese), 5(3): 183–206
Meyers P A. 1994. Preservation of elemental and isotopic source identification of sedimentary organic matter. Chemical Geology, 114(3–4): 289–302, doi: 10.1016/0009-2541(94)90059-0
Neale P J, Cullen J J, Yentsch C M. 1989. Bio-optical inferences from chlorophyll a fluorescence: What kind of fluorescence is measured in flow cytometry?. Limnology and Oceanography, 34(8): 1739–1748, doi: 10.4319/lo.1989.34.8.1739
Nelson D M, Tréguer P, Brzezinski M A, et al. 1995. Production and dissolution of biogenic silica in the ocean: revised global estimates, comparison with regional data and relationship to biogenic sedimentation. Global Biogeochemical Cycles, 9(3): 359–372, doi: 10.1029/95GB01070
Parsons T R, Maita Y, Lalli C M. 1984. A Manual of Chemical & Biological Methods for Seawater Analysis. Oxford: Pergamon Press, 101–104
Ragueneau O, Savoye N, Del Amo Y, et al. 2005. A new method for the measurement of biogenic silica in suspended matter of coastal waters: using Si: Al ratios to correct for the mineral interference. Continental Shelf Research, 25(5–6): 697–710, doi: 10.1016/j.csr.2004.09.017
Redalje D G, Laws E A. 1981. A new method for estimating phytoplankton growth rates and carbon biomass. Marine Biology, 62(1): 73–79, doi: 10.1007/BF00396953
Ren Jingling, Zhang Jing, Luo Jingqing, et al. 2001. Improved fluorimetric determination of dissolved aluminium by micelle-enhanced lumogallion complex in natural waters. Analyst, 126(5): 698–702, doi: 10.1039/b007593k
Small L F, Prahl F G. 2004. A particle conveyor belt process in the columbia river estuary: evidence from chlorophyll a and particulate organic carbon. Estuaries, 27(6): 999–1013, doi: 10.1007/BF02803426
Taylor A H, Geider R J, Gilbert F J H. 1997. Seasonal and latitudinal dependencies of phytoplankton carbon-to-chlorophyll a ratios: results of a modelling study. Marine Ecology Progress Series, 152: 51–66, doi: 10.3354/meps152051
Tréguer P J, De La Rocha C L. 2013. The world ocean silica cycle. Annual Review of Marine Science, 5: 477–501, doi: 10.1146/annurev-marine-121211-172346
Vázquez-Domínguez E, Morán X A G, López-Urrutia A. 2013. Photoacclimation of picophytoplankton in the central Cantabrian Sea. Marine Ecology Progress Series, 493: 43–56, doi: 10.3354/meps10549
Wienke S M, Cloern J E. 1987. The phytoplankton component of seston in San Francisco Bay. Netherlands Journal of Sea Research, 21(1): 25–33, doi: 10.1016/0077-7579(87)90020-2
Xu Jie, Ho A Y T, Yin Kedong, et al. 2008. Temporal and spatial variations in nutrient stoichiometry and regulation of phytoplankton biomass in Hong Kong waters: influence of the Pearl River outflow and sewage inputs. Marine Pollution Bulletin, 57(6–12): 335–348, doi: 10.1016/j.marpolbul.2008.01.020
Yin Kedong, Qian Peiyuan, Chen J C, et al. 2000. Dynamics of nutrients and phytoplankton biomass in the Pearl River Estuary and adjacent waters of Hong Kong during summer: preliminary evidence for phosphorus and silicon limitation. Marine Ecology Progress Series, 194: 295–305, doi: 10.3354/meps194295
Zeitzschel B. 1970. The quantity, composition and distribution of suspended particulate matter in the Gulf of California. Marine Biology, 7(4): 305–318, doi: 10.1007/BF00750823
Appendix
Less
Year 2020 volume 39 Issue 2
PDF
61
34
Cite this Article
BibTeX
Article Info
doi: 10.1007/s13131-020-1556-6
  • Receive Date：2018-04-11
  • Online Date：2026-03-31
  • Published：2020-02-25
Article Data
Affiliations
History
  • Received：2018-04-11
  • Accepted：2018-05-18
Funding
The National Natural Science Foundation of China under contract No. 41476137; the project of Qingdao National Laboratory for Marine Science and Technology under contract No. QNLM2016ORP0305.
Affiliations
    1 State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanography, Chinese Academy of Sciences, Guangzhou 510301, China
    2 University of Chinese Academy of Sciences, Beijing 100049, China

Corresponding:

References
Share
https://castjournals.cast.org.cn/joweb/aos/EN/10.1007/s13131-020-1556-6
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