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Effects of UV-B irradiated algae on zooplankton grazing

MPG-Autoren
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Lürling,  Miquel
Department Ecophysiology, Max Planck Institute for Limnology, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Zitation

De Lange, H. J., & Lürling, M. (2003). Effects of UV-B irradiated algae on zooplankton grazing. Recent Developments in Fundamental and Applied Plankton Research, 133-144.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-000F-DC24-A
Zusammenfassung
We tested the effects of UV-B stressed algae on grazing rates of zooplankton. Four algal species ( Chlamydomonas reinhardtii, Cryptomonas sp., Scenedesmus obliquus and Microcystis aeruginosa) were used as food and fed to three zooplankton species ( Daphnia galeata, Bosmina longirostris and Brachionus calyciflorus), representing different taxonomic groups. The phytoplankton species were cultured under PAR conditions, and under PAR supplemented with UV-B radiation at two intensities (0.3 W m(-2) and 0.7 W m(-2), 6 hours per day). Ingestion and incorporation experiments were performed at two food levels (0.1 and 1.0 mg C l(-1)) using radiotracer techniques. The effect of food concentration on ingestion and incorporation rate was significant for all three zooplankton species, but the effect of UV-B radiation was more complex. The reactions of the zooplankton species to UV-B stressed algae were different. UV-B stressed algae did not affect Daphnia grazing rates. For Bosmina the rates increased when feeding on UV-B stressed Microcystis and decreased when feeding on UV-B stressed Chlamydomonas, compared with non-stressed algae. Brachionus grazing rates were increased when feeding on UV-B stressed Cryptomonas and UV-B stressed Scenedesmus, and decreased when feeding on UV-B stressed Microcystis, compared with non- stressed algae. These results suggest that on a short time scale UV-B radiation may result in increased grazing rates of zooplankton, but also in decreased grazing rates. Long term effects of UV-B radiation on phytoplankton and zooplankton communities are therefore difficult to predict.