Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-20T08:27:05.788Z Has data issue: false hasContentIssue false

Temporal changes of phytoplankton community at different depths of a shallow hypertrophic reservoir in relation to environmental variables

Published online by Cambridge University Press:  20 June 2009

YongSu Kwon
Affiliation:
Department of Biology and The Korea Institute of Ornithology, Kyung Hee University, Seoul 130701, Korea
SoonJin Hwang*
Affiliation:
Department of Environmental Science, Konkuk University, Seoul 143701, Korea
KuSung Park
Affiliation:
Department of Environmental Science, Konkuk University, Seoul 143701, Korea
HoSeob Kim
Affiliation:
Watershed Management Research Divisions, National Institute of Environmental Research, Incheon 404170, Korea
BaikHo Kim
Affiliation:
Department of Environmental Science, Konkuk University, Seoul 143701, Korea
KyungHoon Shin
Affiliation:
Department of Environmental Marine Science, Hanyang University, Ansan 425791, South Korea
KwangGuk An
Affiliation:
School of Bioscience and Biotechnology, Chungnam National University, Daejeon 305764, South Korea
YoungHee Song
Affiliation:
Rural Research Institute, Ansan 426908, South Korea
YoungSeuk Park
Affiliation:
Department of Biology and The Korea Institute of Ornithology, Kyung Hee University, Seoul 130701, Korea
Get access

Abstract

We characterized phytoplankton community succession at different depths of a shallow hypertrophic reservoir in relation to physical and chemical environmental variables. The phytoplankton community was sampled biweekly at three different water depths (surface, middle and bottom) in the reservoir from November 2002 to February 2004. A range of 18 environmental variables including temperature, electrical conductivity (EC), total phosphorus (TP) and total nitrogen (TN) were measured to assess their influence on phytoplankton community succession. As well, combined multivariate analyses with a cluster analysis and a nonmetric multidimensional scale (NMDS) were conducted. Microcystis aeruginosa was the dominant species in all seasons except spring. Thus, Cyanophyceae was a dominant taxonomic group. In spring, Bacillariophyceae dominated, followed by Cryptophyceae and Chlorophyceae. The succession was relatively delayed at the middle and bottom layers compared with at the surface layer. Abundance and species richness of phytoplankton were also higher in the surface layer than in the bottom layer. Cluster analysis classified the phytoplankton community into four clusters at each depth, and the changes were also well reflected in the NMDS ordination. Each cluster showed seasonal patterns characterized by indicator species, as well as environmental variables such as temperature, conductivity, and nutrients including N and P. Seasonal dynamics of the phytoplankton community was the strongest at the surface layer and weakest at the bottom layer. These depth-variable environmental variables are likely to be the key factors driving changes in the phytoplankton community composition.

Type
Research Article
Copyright
© EDP Sciences, 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abdul-Hussein, M.M. and Mason, C.F., 1988. The phytoplankton community of a eutrophic reservoir. Hydrobiologia , 169, 265277. CrossRef
APHA, 1995. Standard Methods for the Examination of Water and Wastewater, 19th edition, APHAAWWAWEF, Washington, DC.
Bettinetti, R., Morabito, G. and Provini, A., 2000. Phytoplankton assemblage structure and dynamics as indicator of the recent trophic and biological evolution of the western basin of Lake Como (N. Italy). Hydrobiologia , 435, 177190. CrossRef
Brook, A.S. and Torke, B.G., 1977. Vertical and seasonal chlorophyll a in Lake Michigan. J. Fish. Res. Board Can. , 34, 22802287. CrossRef
Calijuri, M.C., Dos Santos, A.C.A. and Jati, S., 2002. Temporal changes in the phytoplankton community structure in a tropical and eutrophic reservoir (Barra Bonita, S.P. Brazil). J. Plankton Res. , 24, 617634. CrossRef
Chen, Y., Qin, B., Teubner, K. and Dokulil, M.T., 2003. Long-term dynamics of phytoplankton assemblages: Microcystis-domination in Lake Taihu, a large shallow lake in China. J. Plankt. Res. , 25, 445453. CrossRef
Dufrêne, M. and Legendre, P., 1997. Species assemblages and indicator species: the need for a flexible asymmetrical approach. Ecol. Monogr. , 67, 345366.
Gervais F., Siedel U., Heilmann B., Weithoff G., Heisig-Gunkel G. and Nicklisch A., 2003. Smallscale vertical distribution of phytoplankton, nutrients and sulphide below the oxycline of a mesotrophic lake. J. Plankton Res., 25, 273–278.
Grime, J.P., 1977. Evidence for the existence of three primary strategies in plants and its relevance to ecological and evolutionary theory. Am. Nat. , 111, 11691194. CrossRef
Grime J.P., 1979. Plant Strategies and Vegetation Processes, John Wiley, New York.
Harris G.P., 1986. Phytoplankton Ecology: Structure, Function and Fluctuation, Chapman and Hall, New York.
Higashi, Y. and Seki, H., 2000. Ecological adaptation and acclimatization of natural freshwater phytoplankton with a nutrient gradient. Environ. Pollut. , 109, 311320. CrossRef
Hirose H. and Yamagishi T., 1977. Illustrations of the Japanese Freshwater Algae, Uchidarokakuho, Tokyo, 933 p. (in Japanese).
Horne A.J. and Goldman C.R., 1994. Limnology, McGrow-Hill Inc., New York.
Huisman, J., Jonker, R.R., Zonneveld, C. and Weissing, F.J., 1999. Competition for light between phytoplankton species: experimental tests of mechanistic theory. Ecology , 80, 211222. CrossRef
Huovinen P.S., Brett M.T. and Goldman C.R., 1999. Temporal and vertical dynamics of phytoplankton net growth in Castle Lake, California. J. Plankton Res., 21, 373–385.
Jiang, J.G., Wu, S.G. and Shen, Y.F., 2007. Effects of seasonal succession and water pollution on the protozoan community structure in an eutrophic lake. Chemosphere , 66, 523532. CrossRef
John D.M., Whitton B.A. and Brook A.J., 2003. The Freshwater Algal Flora of the British Isles, An Identification Guide to Freshwater and Terrestrial Algae, Cambridge University Press, New York, USA.
Kalff J., 2002. Limnology: Inland water ecosystems, Prentice-Hall, New Jersey.
Karacaoglu, D., Dalkiran, N. and Dere, S., 2006. Factors affecting the phytoplankton diversity and richness in a shallow eutrophic lake in Turkey. J. Freshwat. Ecol. , 21, 575581.
KARICO, 2001. Report of Water Monitoring in Agricultural Reservoirs, S. Korea, Korea Agriculture and Rural Infrastructure Cooperation, Ansan (in Korean).
Keister, J.E. and Peterson, W.T., 2003. Zonal and seasonal variations in zooplankton community structure off the central Oregon coast, 1998–2000. Prog. Oceanogr. , 57, 341361. CrossRef
Kenkel, N.C. and Orloci, L., 1986. Applying metric and non-metric multidimensional scaling to ecological studies: some new results. Ecology , 67, 919928. CrossRef
Kim H.S., 2004. Study on the growth dynamics and ecotechnological control of algae in reservoirs, Ph.D. Dissertation Thesis, Kunkuk University, Seoul, Korea (in Korean with English abstract).
Kim, H.S., Hwang, S.J., Shin, J.K., An, K.G. and Yoon, C.G., 2007. Effects of limiting nutrients and N:P ratios on the phytoplankton growth in a shallow hypertrophic reservoir. Hydrobiologia , 581, 255267. CrossRef
Kim H.S., Hwang S.J. and Konf D.S., 2008. Growth kinetics of phytoplankton in shallow eutrophic reservoir. J. Korean Society on Water Quality, 24, 550–555 (in Korean with English abstract).
Kokociński, M. and Soininen, J., 2008. Temporal variation in phytoplankton in two lakes with contrasting disturbance regimes. Fund. Appl. Limnol. , 171, 3948. CrossRef
Laughlin, D.C. and Abella, S.R., 2007. Abiotic and biotic factors explain independent gradients of plant community composition in ponderosa pine forests. Ecol. Model. , 205, 231240. CrossRef
McCune B. and Grace J.B., 2002. Analysis of Ecological Communities, MjM Software Design, Gleneden Beach, Oregon, USA.
McCune B. and Mefford M.J., 1999. PCORD. Multivariate Analysis of Ecological Data, Version 4.41, MjM Software, Gleneden Beach, Oregon, USA.
Mielke, E.W., Berry, K.J. and Johnson, E.S., 1976. Multiresponse permutation procedures for a priori classifications. Commun. Stat. Theory Methods , 5, 14091424. CrossRef
Oh, H.M., Ahn, C.Y., Lee, J.W., Chon, T.S., Choi, K.H. and Park, Y.S., 2007. Community patterning and identification of predominant factors in algal bloom in Daechung Reservoir (Korea) using artificial neural networks. Ecol. Model. , 203, 109118. CrossRef
Padisak, J., 1992. Seasonal succession of phytoplankton in a large shallow lake (Balaton, Hungary) a dynamic approach to ecological memory, its possible role and mechanisms. J. Ecol. , 80, 217230. CrossRef
Peterson, W.T. and Keister, J.E., 2003. Interannual variability in copepod community composition at a coastal station in the northern California Current: a multivariate approach. Deep Sea Res. , 50, 24992517. CrossRef
Pinilla, G.A., 2006. Vertical distribution of phytoplankton in a clear water lake of Colombian Amazon (Lake Boa, Middle Caquetá). Hydrobiologia , 568, 7990. CrossRef
Prescott G.W., 1962. Algae of the Western Great Lakes Area, Wm. C. Brown Co., Dubuque, Iowa.
Priscu, J.C. and Goldman, C.R., 1983. Seasonal dynamics of the deep-chlorophyll maximum in Castle lake, California. Can. J. Fish. Aquat. Sci. , 40, 208214. CrossRef
Ptacnik, R., Diehl, S. and Berger, S., 2003. Performance of sinking and non-sinking phytoplankton taxa in a gradient of mixing depths. Limnol. Oceanogr. , 48, 19031912. CrossRef
Reynolds, C.S., 1984. Phytoplankton periodicity: the interactions of form, function and environmental variability. Freshwat. Biol. , 14, 111142. CrossRef
Reynolds C.S., 1988. Functional morphology and adaptive strategies of freshwater phytoplankton. In: Sandgren C.D. (ed.), Growth and Survival Strategies of Freshwater Phytoplankton, Cambridge University Press, Cambridge, 388–433.
Reynolds C.S., 2006. The Ecology of Phytoplankton, Cambridge University Press, Cambridge.
Romo S. and Miracle R., 1994. Long-term phytoplankton changes in a shallow hypertrophic lake, Albufera of Valencia (Spain). Hydrobiologia, 275/276, 153–164.
Salmaso, N., 1996. Seasonal variation in the composition and rate of change of the phytoplankton community in a deep subalpine lake (Lake Garda, Northern Italy). An application of nonmetric multidimensional scaling and cluster analysis. Hydrobiologia , 337, 4968. CrossRef
Salmaso, N., 2002. Ecological patterns of phytoplankton assemblages in Lake Garda: seasonal, spatial and historical features. J. Limnol. , 61, 95115. CrossRef
Shannon, C.E., 1948. A mathematical theory of communication. The Bell System Technical Journal , 27, 379423. CrossRef
StatSoft Inc, 2004. STATISTICA (data analysis software system), Version 7, http://www.statsoft.com.
Tilzer, M.M., Paerl, H.W. and Goldman, C.R., 1977. Sustained viability of aphotic phytoplankton in Lake Taho (California Nevada). Limnol. Oceanogr. , 22, 8491. CrossRef
Valério, E., Faria, N., Paulino, S. and Pereira, P., 2008. Seasonal variation of phytoplankton and cyanobacteria composition and associated microcystins in six Portuguese freshwater reservoirs. Ann. Limnol. - Int. J. Lim. , 44, 189196. CrossRef
Wang, X.L., Lu, Y.L., He, G.Z., Han, J.Y. and Wang, T.Y., 2007. Exploration of relationships between phytoplankton biomass and related environmental variables using multivariate statistic analysis in a eutrophic shallow lake: A 5-year study. J. Environ. Sci. (China) , 19, 920927. CrossRef
Wetzel R.G., 2001. Limnology, Lake and River Ecosystems, Academic Press, San Diego, USA.
Winder, M. and Hunter, D.A., 2008. Temporal organizing of phytoplankton communities linked to physical forcing. Oecologia , 156, 179192. CrossRef