Skip to main content
Log in

The influence of key environmental variables on phytoplankton community structure in the estuary of tidal rivers around Luoyuan Bay, China

  • Published:
Journal of Ocean University of China Aims and scope Submit manuscript

Abstract

A total of 348 species belonging to 8 phyla and 125 genera were observed in seasonally sampled phytoplankton of tidal rivers from 13 sampling sites around Luoyuan Bay, and all field samplings were carried out in productive period (March/June/August/ December) at ebb tide. Bacillariophyta species were the most abundant species, followed by Chlorophyta, Cyanophytes, Euglenophyta, Cryptophyta, Dinophyta, Xanthophyta and Chrysophytas. Seasonal distribution index (SDI) value ranged from 0.63 to 0.86, which meant that species found at those sites in 4 seasons tended to be largely different. Phytoplankton individuals ranged from 5.939×104 ind L−1 in winter to 75.31×104 ind L−1 in autumn. Phytoplankton biomass ranged from 0.620 mg L−1 in summer to 2.373 mg L−1 in autumn. The grey correlation analysis (GCA) showed that the nutrient variables played an important role in the influence on phytoplankton community in every season. The canonical correspondence analysis (CCA) revealed impact of environmental variables on the different species, most of Bacillariophyta species were negative correlation with nutrients (TP and NH3-N) in the four seasons, Chlorophyta species and Cyanophyta species did not show obvious correlation with environment variables in every season. The combination of GRA analysis and CCA analysis provided a method to quantitatively reveal the correlation between phytoplankton community and environmental variables in water body of tidal rivers at this region.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Alpine, A. E., and Cloern, J. E., 1992. Trophic interactions and direct physical effects control phytoplankton biomass and production in an estuary. Limnology and Oceanography, 37: 946–955.

    Article  Google Scholar 

  • Aminot, A., and Chaussepied, M., 1983. Manuel des Analyses Chimiques en Milieu Marin. Brest, CNEXO, 395pp.

    Google Scholar 

  • Barinova, S., Keshri, J. P., Ghosh, S., and Sikdar, J., 2012. The influence of the monsoon climate on phytoplankton in the Shibpukur pool of Shiva temple in Burdwan, West Bengal, India. Limnological Review, 12.

    Google Scholar 

  • Bollmann, A., Bullerjahn, G. S., and McKay, R. M., 2014. Abundance and diversity of ammonia-oxidizing archaea and bacteria in sediments of trophic end members of the Laurentian Great Lakes, Erie and Superior. PLoS One, 9: e97068.

    Article  Google Scholar 

  • Chinese Environment Protection Bureau, 2002. Monitoring and Analyzing Methods for Water and Sewage. China Environment Science Press, Beijing, 836pp.

  • Collins, S. L., Micheli, F., and Hartt, L., 2000. A method to determine rates and patterns of variability in ecological communities. Oikos, 91: 285–293.

    Article  Google Scholar 

  • Davies, O. A., and Ugwumba, O. A., 2013. Tidal influence on nutrients status and phytoplankton population of okpoka creek, upper Bonny Estuary, Nigeria. Journal of Marine Biology, 7: 1–16.

    Article  Google Scholar 

  • Elith, J., Graham, C. H., Anderson, R. P., Dudík, M., Ferrier, S., Guisan, A., Hijmans, R. J., Huettmann, F., Leathwick, J. R., Lehmann, A., Li, J., Lohmann, L. G., Loiselle, B. A., Manion, G., Moritz, C., Nakamura, M., Nakazawa, Y., McC, J., Overton, M., Townsend Peterson, A., Phillips, S. J., Richardson, K., Scachetti-Pereira, R., Schapire, R. E., Soberón, J., Williams, S., Wisz, M., S., and Zimmermann, N. E., 2006. Novel methods improve prediction of species’ distributions from occurrence data. Ecography, 29: 129–151.

    Article  Google Scholar 

  • Foster, B. L., and Tilman, D., 2000. Dynamic and static views of succession: Testing the descriptive power of the chronosequence approach. Plant Ecology, 146: 1–10.

    Article  Google Scholar 

  • Fu, C. Y., Zheng, J. S., Zhao, J. M., and Xu, W. D., 2001. Application of grey relational analysis for corrosion failure of oil tubes. Corrosion Science, 43: 881–889.

    Article  Google Scholar 

  • Gameiro, C., Cartaxana, P., Cabrita, M. T., and Brotas, V., 2004. Variability in chlorophyll and phytoplankton composition in an estuarine system. Hydrobiologia, 525: 113–124.

    Article  Google Scholar 

  • Gächter, R., and Máreš, A., 1979. MELIMEX, an experimental heavy metal pollution study: Effects of increased heavy metal loads on phytoplankton communities. Schweizerische Zeitschrift für Hydrologie, 41: 228–246.

    Google Scholar 

  • Han, M. S., and Shu, Y. F., 1995. Atlas of Fresh-Water Biota in China. Ocean Press, Beijing, 375pp.

    Google Scholar 

  • Ho, C. Y., and Lin, Z. C., 2003. Analysis and application of grey relation and ANOVA in chemical-mechanical polishing process parameters. The International Journal of Advanced Manufacturing Technology, 21: 10–14.

    Article  Google Scholar 

  • Huhta, V., 1979. Evaluation of different similarity indexes as measures of succession in arthropod communities of the forest floor after clear-cutting. Oecologia, 41: 11–23.

    Article  Google Scholar 

  • Hu, H. J., Li, R. Y., Wei, Y. X., Zhu, H. Z., Chen, J. Y., and Shi, Z. X., 1980. Freshwater Algae in China. Shanghai Science and Technology Press, Shanghai, 525pp.

    Google Scholar 

  • Jasprica, N., Caric, M., Krsinic, F., Kapetanovic, T., Batistic, M., and Njire, J., 2012. Planktonic diatoms and their environment in the lower Neretva River estuary (Eastern Adriatic Sea, NE Mediterranean). Nova Hedwigia, 405–429.

    Google Scholar 

  • Lewis, W. M., 1978. Analysis of succession in a tropical phytoplankton community and a new measure of succession rate. American Naturalist, 112: 401–414.

    Article  Google Scholar 

  • Lewitus, A. J., 2002. Eutrophication processes in coastal systems: Origin and succession of plankton blooms and effects on secondary production in gulf coast estuaries. Copeia, 248–249.

    Google Scholar 

  • Li, J. Y., and Qi, Y. Z., 2010. Flora Algarum Sinicarum Aquae Dulcis (Tomus 14)-Bacillariophyta Naviculaceae. Science Press, Beijing, 177pp.

    Google Scholar 

  • Lin, S. J., Lu, I. J., and Lewis, C., 2007. Grey relation performance correlations among economics, energy use and carbon dioxide emission in Taiwan. Energy Policy, 35: 1948–1955.

    Article  Google Scholar 

  • Lin, Y., and Liu, S. F., 2004. A historical introduction to grey systems theory. Systems, Man and Cybernetics, 2004 IEEE International Conference, 3: 2403–2408.

    Article  Google Scholar 

  • Liu, L. H., Zuo, T., Chen, R. S., and Wang, J., 2007. Community structure and diversity of phytoplankton in the estuary of Yangtse River in autumn. Marine Fisheries Research, 28: 112–119.

    Google Scholar 

  • Lo, S. P., 2002. The application of an anfis and grey system method in turning tool-failure detection. The International Journal of Advanced Manufacturing Technology, 19: 564–572.

    Article  Google Scholar 

  • Lu, F., 1997. Research on the identification coefficient of relational grade for grey system. Systems Engineering Theory and Practice, 49–54.

    Google Scholar 

  • Ma, C., Shen, C. C., and Liu, Y., 2012. The composition and biodiversity of nekton species in Luoyuan Bay in summer. Journal of Fujian Fisheries, 34: 449–454.

    Google Scholar 

  • Moita, M. T., and Vilarinho, M. G., 1998. Checklist of phytoplankton species off Portugal: 70 years (1929-1998) of studies. Portugaliae Acta Biologica, 18 (1/4): 5–50.

    Google Scholar 

  • Patrick, R., and Reimer, C. W., 1966. The Diatoms of the United States, Vol.1. The Livingston Publishing Company, Pennsylvania, 688pp.

    Google Scholar 

  • Patrick, R., and Reimer, C. W., 1975. The Diatoms of the United States (volume 2, part 1). Sutter House, Pennsylvania, 213pp.

    Google Scholar 

  • Qi, Y. Z., 1995. Flora Algarum Sinicarum Aquae Dulcis. Tomus IV, Bacillariophyta, Centricae. Science Press, Beijing, 104pp.

    Google Scholar 

  • Qi, Y. Z., and Li, J. Y., 2004. Flora Algarum Sinicarum Aquae Dulcis (Tomus X )-Bacillariophyta-Pennatae. Science Press, Beijing, 161pp.

    Google Scholar 

  • Romanov, R. E., and Kirillov, V. V., 2012. Analysis of the seasonal dynamics of river phytoplankton based on succession rate indices for key event identification. Hydrobiologia, 695: 293–304.

    Article  Google Scholar 

  • Sallehuddin, R., Shamsuddin, S. M. H., and Hashim., S. Z. M., 2008. Application of grey relational analysis for multivariate time series. In: Eighth International Conference on Intelligent Systems Design and Applications, IEEE, Kaohsiung, 432–437.

    Google Scholar 

  • Shi, Z. X., 2004. Flora Algarum Sinicarum Aquae Dulcis (Tomus XII)-Bacillariophyta-Gomphonemaceae. Science Press, Beijing, 147pp.

    Google Scholar 

  • Shu, Y. F., and Han, M. S., 1993. Atlas of Marine Plankton in China. Ocean Press, Beijing, 224pp.

    Google Scholar 

  • Ter Braak, C. J. F., 1987. The analysis of vegetation-environment relationships by canonical correspondence analysis. Theory and Models in Vegetation Science, 8: 69–77.

    Article  Google Scholar 

  • Ter Braak, C. J. F., 1990. Interpreting canonical correlation analysis through biplots of structure correlations and weights. Psychometrika, 55: 519–531.

    Article  Google Scholar 

  • Ter Braak, C. J. F., and Verdonschot, P. F. M., 1995. Canonical correspondence analysis and related multivariate methods in aquatic ecology. Aquatic Sciences, 57: 255–289.

    Article  Google Scholar 

  • Tosun, N., 2005. Determination of optimum parameters for multi-performance characteristics in drilling by using grey relational analysis. The International Journal of Advanced Manufacturing Technology, 28: 450–455.

    Article  Google Scholar 

  • Yan, Q., 2011. Study on the community structure of phytoplankton and environmental impact assessment in Harbin section of Songhua River. Master Thesis, Northeast Forestry University, China, 11–45.

    Google Scholar 

  • Yang, S. M., Dong, S. G., and Tang, Z. H., 2010. Phytoplankton community of the Luoyuan Bay in summer 2005. Transactios of Oceanology and Limnology, 101–108.

    Google Scholar 

  • Zhang L. N. 2010. Eological monitoring of Phytoplankton on community structure and water quality assessment of trophic status: River of the Hailang, Mudanjiang, China. Master Thesis, Northeast Forestry University, China, 5–41.

    Google Scholar 

  • Zhang, Z. S., and Huang, X. F., 1991. Research Methods for Freshwater Plankton. Science Press, Beijing, 426pp.

    Google Scholar 

  • Zhu, H. Y., and Chen, J. Y., 2000. Bacillariophyta of the Xizang Plateau. Science Press, Beijing, 353pp.

    Google Scholar 

  • Zhu, H. R., 1991. Flora Algarum Sinicarum Aquae Dulcis (Tomus II, Chroococcophyceae). Science Press, Beijing, 161pp.

    Google Scholar 

  • Zhu, H. R., 2007. Flora Algarum Sinicarum Aquae Dulcis (Tomus IX)-Cyanophyta (Hormogonophyceae). Science Press, Beijing, 312pp.

    Google Scholar 

Download references

Acknowledgements

This work was financially supported by China Shenhua Energy Company Limited. We are grateful to Mr. Yongde LI, Miss Xiaolu CHEN, Yinlin LIN and Wentin ZHANG for helping in sampling.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Wenbin Pan.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pan, W., Zheng, P., Liang, Y. et al. The influence of key environmental variables on phytoplankton community structure in the estuary of tidal rivers around Luoyuan Bay, China. J. Ocean Univ. China 16, 803–813 (2017). https://doi.org/10.1007/s11802-017-3217-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11802-017-3217-8

Key words

Navigation