Skip to main content
Log in

Environmental influence on coastal phytoplankton and zooplankton diversity: a multivariate statistical model analysis

  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

In a marine ecosystem, the diversity of phytoplankton can influence the diversity of zooplankton, or vice versa, and both can be affected by the environmental factors. In this study, we used principal component analysis (PCA) to identify the major sources of influence on the coastal water near an industrial park, following by construction of structural equation model (SEM) to determine the direct and indirect effect of the factors on phytoplankton and zooplankton diversity. PCA results indicated that the coastal area was mainly affected by riverine discharge (represented by high PC factor loadings of transparency and turbidity) and seasonal change (represented by temperature). SEM further suggested that both riverine discharge and seasonal influences can directly affect phytoplankton diversity, but indirectly affected zooplankton diversity via changes in phytoplankton. Using PCA to determine the sources of influence followed by construction of SEM allowed us to understand the relative importance of the environmental factors, direct or indirect, on phytoplankton and zooplankton diversity. When environmental changes occur, a new SEM could be constructed using the same category of physical and biological data and then compared to the current model to verify whether the environmental changes were the cause of alterations in planktonic communities in the area.

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.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Arhonditsis, G. B., Paerl, H. W., Valdes-Weaver, L. M., Stow, C. A., Steinberg, L. J., & Reckhow, K. H. (2007). Application of Bayesian structural equation modeling for examining phytoplankton dynamics in the Neuse River Estuary (North Carolina, USA). Estuarine, Coastal and Shelf Science, 72, 63–80.

    Article  Google Scholar 

  • Arhonditsis, G. B., Stow, C. A., Steinberg, L. J., Kenney, M. A., Lathrop, R. C., McBride, S. J., et al. (2006). Exploring ecological patterns with structural equation modeling and Bayesian analysis. Ecological Modelling, 192, 385–409.

    Article  Google Scholar 

  • Aruga, R., Negro, G., & Ostacoli, G. (1993). Multivariate data analysis applied to the investigation of river pollution. Fresenius' Journal of Analytical Chemistry, 346, 968–975.

    Article  CAS  Google Scholar 

  • Bigler, C., & Hall, R. I. (2003). Diatoms as quantitative indicators of July temperature: A validation attempt at century-scale with meteorological data from northern Sweden. Palaeogeography, Palaeoclimatology, Palaeoecology, 189, 147–160.

    Article  Google Scholar 

  • Cloern, J. E. (1999). The relative importance of light and nutrient limitation of phytoplankton growth: A simple index of coastal ecosystem sensitivity to nutrient enrichment. Aquatic Ecology, 33, 3–16.

    Article  Google Scholar 

  • Colebrook, J. M. (1982). Continuous plankton records: Seasonal variations in the distribution and abundance of plankton in the North Atlantic Ocean and the North Sea. Journal of Plankton Research, 4, 435–462.

    Article  Google Scholar 

  • Eloranta, P. (1993). Diversity and succession of the phytoplankton in a small lake over a two-year period. Hydrobiologia, 249, 25–32.

    Article  Google Scholar 

  • Falkowski, P. G., & Owens, T. G. (1980). Light-shade adaptation: Two strategies in marine phytoplankton. Plant Physiology, 66, 632–635.

    Article  Google Scholar 

  • Finlay, K., Beisner, B. E., Patoine, A., & Pinel-Alloul, B. (2007). Regional ecosystem variability drives the relative importance of bottom-up and top-down factors for zooplankton size spectra. Canadian Journal of Fisheries and Aquatic Sciences, 64, 516–529.

    Article  CAS  Google Scholar 

  • Flöder, S., Urabe, J., & Kawabata, Z. (2002). The influence of fluctuating light intensities on species composition and diversity of natural phytoplankton communities. Oecologia, 133, 395–401.

    Article  Google Scholar 

  • Geddes, M. C. (1984). Seasonal studies on the zooplankton communtiy of Lake Alexandrina, River Murray, South Australia, and the role of turbidity in determining zooplankton community structure. Marine and Freshwater Research, 35, 417–426.

    Article  Google Scholar 

  • Gurung, T. B., Kagami, M., Yoshida, T., & Urabe, J. (2000). Relative importance of biotic and abiotic factors affecting bacterial abundance in Lake Biwa: An empirical analysis. Limnology, 2, 19–28.

    Article  Google Scholar 

  • Han, C. C., Tew, K. S., & Fang, L. S. (2007). Spatial and temporal variations of two cyprinids in a subtropical mountain reserve—A result of habitat disturbance. Ecology of Freshwater Fish, 16, 395–403.

    Article  Google Scholar 

  • Hart, R. C. (1988). Zooplankton feeding rates in relation to suspended sediment content: Potential influences on community structure in a turbid reservoir. Freshwater Biology, 19, 123–139.

    Article  Google Scholar 

  • Hoelter, J. W. (1983). The analysis of covariance structures: Goodness-of-fit indices. Sociological Methods Research, 11, 325–344.

    Article  Google Scholar 

  • Howell, R. D. (1996). LISREL 8 with PRELIS2 for Windows. Journal of Marketing Research, 33, 377–381.

    Article  Google Scholar 

  • Hsieh, W. C., Lee, H. J., Tew, K. K., Lin, C., Fan, K. S., & Meng, P. J. (2010). Estimating nutrient budgets in a coastal lagoon. Chinese Science Bulletin, 55, 484–492.

    Article  CAS  Google Scholar 

  • Laughlin, D. C., & Abella, S. R. (2007). Abiotic and biotic factors explain independent gradients of plant community composition in ponderosa pine forests. Ecological Modelling, 205, 231–240.

    Article  Google Scholar 

  • Liang, S. H., Shieh, B. S., & Fu, Y. S. (2002). A structural equation model for physiochemical variables of water, benthic invertebrates, and feeding activity of waterbirds in the Sitsao wetlands of southern Taiwan. Zoological Studies, 41, 441–451.

    Google Scholar 

  • Lin, H. J., Wang, T. C., Su, H. M., & Hung, J. J. (2005). Relative importance of phytoplankton and periphyton on oyster-culture pens in a eutrophic tropical lagoon. Aquaculture, 243, 279–290.

    Article  Google Scholar 

  • Malaeb, Z. A., Summers, J. K., & Pugesek, B. H. (2000). Using structural equation modeling to investigate relationships among ecological variables. Environmental and Ecological Statistics, 7, 93–111.

    Article  Google Scholar 

  • McCune, B., & Grace, J. B. (2002). Analysis of ecological communities. Oregon: MjM Software Design.

    Google Scholar 

  • McQuatters-Gollop, A., Raitsos, D. E., Edwards, M., Pradhan, Y., Mee, L. D., Lavender, S. J., et al. (2007). A long-term chlorophyll data set reveals regime shift in North Sea phytoplankton biomass unconnected to nutrient trends. Limnology and Oceanography, 52, 635–648.

    Article  CAS  Google Scholar 

  • Nasrollahzadeh, H. S., Bin Din, Z., Foong, S. Y., & Makhlough, A. (2008). Trophic status of the Iranian Caspian Sea based on water quality parameters and phytoplankton diversity. Continental Shelf Research, 28, 1153–1165.

    Article  Google Scholar 

  • Oviatt, C. A., Hyde, K. J. W., Keller, A. A., & Turner, J. T. (2007). Production patterns in Massachusetts Bay with outfall relocation. Estuaries and Coasts, 30, 35–46.

    CAS  Google Scholar 

  • Paffenhöfer, G. A. (1983). Vertical zooplankton distribution on the northeastern Florida shelf and its relation to temperature and food abundance. Journal of Plankton Research, 5, 15–33.

    Article  Google Scholar 

  • Parinet, B., Lhote, A., & Legube, B. (2004). Principal component analysis: An appropriate tool for water quality evaluation and management-application to a tropical lake system. Ecological Modelling, 178, 295–311.

    Article  CAS  Google Scholar 

  • Pugesek, B. H., Tomer, A., & von Eye, A. (2003). Structural equation modeling—Applications in ecological and evolutionary biology. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Ramdani, M., Elkhiati, N., Flower, R. J., Thompson, J. R., Chouba, L., Kraiem, M. M., et al. (2009). Environmental influences on the qualitative and quantitative composition of phytoplankton and zooplankton in North African coastal lagoons. Hydrobiologia, 622, 113–131.

    Article  CAS  Google Scholar 

  • Rhee, G. Y., & Gotham, I. J. (1981). The effect of environmental factors on phytoplankton growth: Temperature and the interactions of temperature with nutrient limitation. Limnology and Oceanography, 26, 635–648.

    Article  CAS  Google Scholar 

  • Schumacker, R. E., & Lomax, R. G. (2004). A beginner’s guide to structural equation modeling. Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Shannon, C. E., & Weaver, W. (1949). The mathematical theory of communication. Urbana, IL: The University of Illinois Press.

    Google Scholar 

  • Shrestha, S., & Kazama, F. (2007). Assessment of surface water quality multivariate statistical techniques: A case study of the Fuji river basin, Japan. Environmental Modelling and Software, 22, 464–475.

    Article  Google Scholar 

  • Smith, S., & Vidal, J. (1984). Spatial and temporal effects of salinity, temperature and chlorophyll on the communities of zooplankton in the southeastern Bering Sea. Journal of Marine Research, 42, 221–257.

    Article  Google Scholar 

  • Steiger, J. H. (1989). EZPATH: A supplementary module for SYSTAT and SYGRAPH. Evanston, IL: SYSTAT.

    Google Scholar 

  • Stow, C. A., & Borsuk, M. E. (2003). Enhancing causal assessment of estuarine fishkills using graphical models. Ecosystem, 6, 11–19.

    Article  Google Scholar 

  • Su, H. M., Lin, H. J., & Hung, J. J. (2004). Effects of tidal flushing on phytoplankton in a eutrophic tropical lagoon in Taiwan. Estuarine, Coastal and Shelf Science, 61, 739–750.

    Article  CAS  Google Scholar 

  • Tew, K. S., & Lo, W. T. (2005). Distribution of Thaliacea in SW Taiwan coastal water in 1997, with special reference to Doliolum denticulatum, Thalia democratica and T. orientalis. Marine Ecology Progress Series, 292, 181–193.

    Article  Google Scholar 

  • Tew, K. S., Chou, W. R., & Fang, L. S. (2006). Phytoplankton diversity and community structure in the coastal area of Chang-Hua during 2005. Platax, 3, 31–38.

    Google Scholar 

  • Tomer, A. (2003). A short history of structural equation models. In B. H. Pugesek, A. Tomer, & A. von Eye (Eds.), Structural equation modeling—Applications in ecological and evolutionary biology (pp. 85–124). Cambridge: Cambridge University Press.

    Chapter  Google Scholar 

  • Tomer, A., & Pugesek, B. H. (2003). Guidelines for the implementation and publication of structural equation models. In B. H. Pugesek, A. Tomer, & A. von Eye (Eds.), Structural equation modeling—Applications in ecological and evolutionary biology (pp. 125–140). Cambridge: Cambridge University Press.

    Chapter  Google Scholar 

  • van Spaendonk, J. C. M., Kromkamp, J. C., & de Visscher, P. R. M. (1993). Primary production of phytoplankton in a turbid coastal plain estuary, the Westerschelde (The Netherlands). Netherlands Journal of Sea Research, 31, 267–279.

    Article  Google Scholar 

  • Vega, M., Pardo, R., Barrado, E., & Deban, L. (1998). Assessment of seasonal and polluting effects on the quality of river water by exploratory data analysis. Water Research, 32, 3581–3592.

    Article  CAS  Google Scholar 

  • Vidal, J. (1980). Physioecology of zooplankton. I. Effects of phytoplankton concentration, temperature, and body size on the growth rate of Calanus pacificus and Pseudocalanus sp. Marine Biology, 56, 111–134.

    Article  Google Scholar 

  • Wang, J., Cota, G. F., & Comiso, J. C. (2005). Phytoplankton in the Beaufort and Chukchi Seas: Distribution, dynamics, and environmental forcing. Deep-Sea Research Part II-Topical Studies in Oceanography, 52, 3355–3368.

    Article  Google Scholar 

  • Wenning, R. J., & Erickson, G. A. (1994). Interpretation and analysis of complex environmental data using chemometric method. Trends in Analytical Chemistry, 13, 446–457.

    Article  CAS  Google Scholar 

  • Wetsteyn, L. P. M. J., & Kromkamp, J. C. (1994). Turbidity, nutrients and phytoplankton primary production in the Oosterschelde (the Netherlands) before, during and after a large-scale coastal engineering project (1980–1990): Structure and functioning of the pelagic system. Hydrobiologia, 282(83), 61–78.

    Article  Google Scholar 

  • Williamson, J., & Harrison, S. (2002). Biotic and abiotic limits to the spread of exotic revegetation species. Ecological Applications, 12, 40–51.

    Article  Google Scholar 

  • Wu, C. R., Chao, S. Y., & Hsu, C. (2007). Transient, seasonal and interannual variability of the Taiwan Strait current. Journal of Oceanography, 63, 821–833.

    Article  Google Scholar 

  • Yang, K. L. (2002). Spatial and seasonal variation of PM10 mass concentrations in Taiwan. Atmospheric Environment, 36, 3403–3411.

    Article  CAS  Google Scholar 

Download references

Acknowledgments

Thanks are due to Ministry of Economic Affairs, ROC for the financial support of the research, National Sun Yat-Sen University, National Dong Hwa University, and National Museum of Marine Biology and Aquarium for the use of various facilities, and Dr. Dave Glover and Ms. Cathy Doyle for helpful comments and suggestions on the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kwee Siong Tew.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chou, WR., Fang, LS., Wang, WH. et al. Environmental influence on coastal phytoplankton and zooplankton diversity: a multivariate statistical model analysis. Environ Monit Assess 184, 5679–5688 (2012). https://doi.org/10.1007/s10661-011-2373-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10661-011-2373-3

Keywords

Navigation