Aquatic Ecology

, Volume 42, Issue 2, pp 227–236

Quantitative responses of lake phytoplankton to eutrophication in Northern Europe

  • R. Ptacnik
  • L. Lepistö
  • E. Willén
  • P. Brettum
  • T. Andersen
  • S. Rekolainen
  • A. Lyche Solheim
  • Laurence Carvalho


Based on the currently largest available dataset of phytoplankton in lakes in northern Europe, we quantified the responses of three major phytoplankton classes to eutrophication. Responses were quantified by modelling the proportional biovolumes of a given group along the eutrophication gradient, using generalized additive models. Chlorophyll-a (Chl-a) was chosen as a proxy for eutrophication because all classes showed more consistent responses to Chl-a than to total phosphorus. Chrysophytes often dominate in (ultra-) oligotrophic lakes, and showed a clear decrease along the eutrophication gradient. Pennate diatoms were found to be most abundant at moderate eutrophication level (spring-samples). Cyanobacteria often dominate under eutrophic conditions, especially in clearwater lakes at Chl-a levels >10 μg l−1 (late summer samples). We compare the relationships among types of lakes, based on the lake typology of the northern geographic intercalibration group, and among countries sharing common lake types. Significant differences were found especially between humic and clearwater lakes, and between low- and moderately alkaline lakes, but we could not identify significant differences between shallow and deep lakes. Country-specific differences in response curves were especially pronounced between lakes in Norway and Finland, while Swedish lakes showed an intermediate pattern, indicating that country-specific differences reflect large-scale geographic and climatic differences in the study area.


Water framework directive Indicators Chrysophytes Cyanobacteria Diatoms 





  1. Andersen T (1997) Pelagic nutrient cycles: herbivores as sources and sinks. Ecological Studies, vol 129. Springer, BerlinGoogle Scholar
  2. Britton G (1983) The biochemistry of natural pigments. Cambridge University PressGoogle Scholar
  3. Brettum P (1989) Alger som indikator på vannkvalitet i norske innsjøer. Planteplankton. Niva-Rapport 0-86116:1–111 (in Norwegian)Google Scholar
  4. Downing JA, Watson SB, McCauley E (2001) Predicting Cyanobacteria dominance in lakes. Can J Fish Aquat Sci 58:1905–1908CrossRefGoogle Scholar
  5. European Commission (2000) Directive of the European Parliament and of the Council 2000/60/EC establishing a framework for Community action in the field of water policy. Official Journal 2000 L 327/1, European Commission, BrusselsGoogle Scholar
  6. Hörnström E (1981) Trophic characterization of lakes by means of qualitative phytoplankton analysis. Limnologica 13:246–261Google Scholar
  7. Intercalibration Guidance (2005) Common implementation strategy for the water framework directive (2000/60/EC). Guidance on the intercalibration process 2004–2006. Guidance document no.14. European Communities 2005. ISBN 92-894-9471-9Google Scholar
  8. Kohl JG, Nicklisch A (1988) Ökophysiologie der Algen. Akademischer Verlag, Berlin (in German)Google Scholar
  9. Komárek J, Anagnostidis K (1999) Cyanoprocaryota 1. Teil: Chroococcales. Gustav Fischer, Jena, GermanyGoogle Scholar
  10. Lepistö L, Räike A, Pietiläinen O-P (1999) Long-term changes of phytoplankton in a eutrophicated boreal lake during the past one hundred years (1893–1998). Algol Stud 94:223–244Google Scholar
  11. Lyche A. (1990) Cluster analysis of plankton community structure in 21 lakes along a gradient of trophy. Verh Int Verein Limnol 24:586–591Google Scholar
  12. Moe J, Dudley B, Ptacnik R (2008) REBECCA databases: experiences from compilation and analyses of monitoring data from 5000 lakes in 20 European countries. Aquatic Ecol. doi:10.1007/s10452-008-9190-y
  13. Naumann E (1919) Några synpunkter angående limnoplanktons ökologi, med särskild hänsyn till fytoplankton. Svensk Botanisk Tidskrift 13:51–58 (in Swedish)Google Scholar
  14. Nygaard G (1949) Hydrobiological studies on some Danish ponds and lakes. II: the quotient hypothesis and some little known or new phytoplankton organisms. Kunglige Danske Vidensk Selskab 7:1–242Google Scholar
  15. Olrik K, Blomqvist P, Brettum P et al (1998) Methods for quantitative assessment of phytoplankton in freshwaters, part I. Naturvårdsverket, Stockholm, 86 ppGoogle Scholar
  16. Phillips G, Pietiläinen OP, Carvalho L, Solimini A, Lyche Solheim A, Cardoso AC (2008) Chlorophyll—nutrient relationships of different lake types using a large European dataset. Aquatic Ecol. doi:10.1007/s10452-008-9180-0
  17. Ptacnik R, Diehl S, Berger S (2003) Performance of sinking and non-sinking phytoplankton taxa in a gradient of mixing depths. Limnol Oceanogr 48:1903–1912Google Scholar
  18. Ptacnik R, Solimini AG, Andersen A, Tamminen T, Brettum P, Lepistö L, Willén E, Rekolainen S (2008) Diversity predicts stability and resource use efficiency in natural phytoplankton communities. Proc Natl Acad Sci USA 105:5134–5138PubMedCrossRefGoogle Scholar
  19. Raven JA (1995) Comparative aspects of chrysophyte nutrition with emphasis on carbon, phosphorus and nitrogen. In: Sandgren CD et al (eds) Chrysophyte algae: ecology, phylogeny and development. Cambride University Press, New YorkGoogle Scholar
  20. R Development Core Team (2007) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, AustriaGoogle Scholar
  21. Reynolds CS (1980) Phytoplankton assemblages and their periodicity in stratifying lake systems. Holarctic Ecol 3:141–159Google Scholar
  22. Reynolds CS (1984) The ecology of freshwater phytoplankton. Cambridge University Press, New YorkGoogle Scholar
  23. Sakamoto Y, Ishiguro M, Kitagawa G (1986) Akaike information criterion statistics. D. Reidel Publishing Company, Dordrecht, The NetherlandsGoogle Scholar
  24. Sandgren C. D. (1988) The ecology of chrysophyte flagellates: their growth and perennation strategies as freshwater phytoplankton. In: Sandgren CD (ed) Growth and reproductive strategies of freshwater phytoplankton. Cambridge University Press, Cambridge, pp 9–104Google Scholar
  25. Skjelkvåle BL, Henriksen A, Jónsson GS, Mannio J, Wilander A, Jensen JP, Fjeld E, Lien L (2001) Chemistry of lakes in the Nordic region—Denmark, Finland with Åland, Iceland, Norway with Svalbard and Bear Island, and Sweden. SNO 4391-2001. NIVA, Oslo, 39 ppGoogle Scholar
  26. Sommer U (1991) Phytoplankton: directional succession and forced cycles. In: Remmert H (ed) The mosaic-cycle concept of ecosystems, ecological studies 85. Springer, Heidelberg, GermanyGoogle Scholar
  27. Teiling E (1955) Some mesotrophic phytoplankton indicators. Int Assoc Theor Appl Limn XII:212–215Google Scholar
  28. Teubner K, Tolotti M, Greisberger S et al (2003) Steady state phytoplankton in a deep pre-alpine lake: species and pigments of epilimnetic versus metalimetic assemblages. Hydrobiologia 502:49–64CrossRefGoogle Scholar
  29. Vollenweider RA (1989) Eutrophication. In: Meybeck M, ChapmanD, Helmer R (eds) Global freshwater quality—a first assessment. World Health Organization and the United Nations Environmental ProgrammeGoogle Scholar
  30. Vuorio K, Lepistö L, Holopainen AL (2007) Intercalibrations of freshwater phytoplankton analysis. Boreal Environ Res 12:561–569Google Scholar
  31. Watson SB, McCauley E, Downing J (1997) Patterns in phytoplankton taxonomic composition across temperate lakes of differing nutrient status. Limnol Oceanogr 42:486–495CrossRefGoogle Scholar
  32. Willén E (2000) Phytoplankton in water quality assessment—an indicator concept. In: Heinonen P, Ziglio G, Van Der Beken A (eds) Hydrological and limonological aspects of lake monitoring. Wiley, New YorkGoogle Scholar
  33. Wood SN (2006) Generalized additive models: an introduction with R. Chapman & Hall/CRC, Boca Raton, FloridaGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  • R. Ptacnik
    • 1
  • L. Lepistö
    • 2
  • E. Willén
    • 3
  • P. Brettum
    • 1
  • T. Andersen
    • 1
    • 4
  • S. Rekolainen
    • 2
  • A. Lyche Solheim
    • 1
  • Laurence Carvalho
    • 5
  1. 1.Norwegian Institute for Water Research (NIVA)OsloNorway
  2. 2.Finnish Environment Institute (SYKE)HelsinkiFinland
  3. 3.Swedish University of Agricultural Sciences (SLU)UppsalaSweden
  4. 4.Department of BiologyUniversity of OsloOsloNorway
  5. 5.Centre for Ecology and Hydrology (CEH)PenicuikScotlandUK

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