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Microbial Ecology

, Volume 51, Issue 2, pp 137–146 | Cite as

Effect of Nutrient Loading on Bacterioplankton Community Composition in Lake Mesocosms

  • Kaisa Haukka
  • Eija Kolmonen
  • Rafiqul Hyder
  • Jaana Hietala
  • Kirsi Vakkilainen
  • Timo Kairesalo
  • Heikki Haario
  • Kaarina Sivonen
Article

Abstract

Changes in bacterioplankton community composition were followed in mesocosms set up in the littoral of Lake Vesijärvi, southern Finland, over two summers. Increasing nitrogen and phosphorus concentrations in the mesocosms represented different trophic states, from mesotrophic to hypertrophic. In 1998, the mesocosms were in a turbid state with a high biomass of phytoplankton, whereas in 1999, macrophytes proliferated and a clear-water state prevailed. The bacterial communities in the mesocosms also developed differently, as shown by denaturing gradient gel electrophoresis profiling of partial 16S rRNA gene fragments and by nonmetric multidimensional scaling analysis. In 1998, nutrient treatments affected the diversity and clustering of bacterial communities strongly, but in 1999, the bacterial communities were less diversified and not clearly affected by treatments. Canonical correspondence analysis indicated that bacterioplankton communities in the mesocosms were influenced by environmental physicochemical variables linked to the increasing level of eutrophication. Nitrogen concentration correlated directly with the bacterioplankton composition. In addition, the high nutrient levels had indirect effects through changes in the biomass and composition of phyto- and zooplankton. Sequencing analysis showed that the dominant bacterial divisions remained the same, but the dominant phylotypes changed during the 2-year period. The occurrence of Verrucomicrobia correlated with more eutrophic conditions, whereas the occurrence of Actinobacteria correlated with less eutrophic conditions.

Keywords

Phytoplankton Bacterial Community Total Suspended Solid Actinobacteria Canonical Correspondence Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

We thank Totte Niittylä and Jaana Vaitomaa for technical assistance. Financial support for the study was received from the Academy of Finland (grants 395901 and 201576 to K.S. and grant 48827 to K.H.) and from the Maj and Tor Nessling Foundation to K.H. The mesocosm experiment was funded by the European Commission (grant ENV4-CT97-0420 to T.K.).

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Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  • Kaisa Haukka
    • 1
    • 4
  • Eija Kolmonen
    • 1
  • Rafiqul Hyder
    • 1
  • Jaana Hietala
    • 2
  • Kirsi Vakkilainen
    • 2
  • Timo Kairesalo
    • 2
  • Heikki Haario
    • 3
  • Kaarina Sivonen
    • 1
  1. 1.Department of Applied Chemistry and MicrobiologyUniversity of HelsinkiHelsinkiFinland
  2. 2.Department of Ecological and Environmental SciencesUniversity of HelsinkiLahtiFinland
  3. 3.Department of MathematicsUniversity of HelsinkiHelsinkiFinland
  4. 4.National Public Health InstituteHelsinkiFinland

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