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Strategies of phenotypic low-food adaptation in Daphnia: Filter screens, mesh sizes, and appendage beat rates

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons56790

Lampert,  Winfried
Department Ecophysiology, Max Planck Institute for Limnology, Max Planck Institute for Evolutionary Biology, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons56610

Brendelberger,  Heinz
Department Ecophysiology, Max Planck Institute for Limnology, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Zitation

Lampert, W., & Brendelberger, H. (1996). Strategies of phenotypic low-food adaptation in Daphnia: Filter screens, mesh sizes, and appendage beat rates. Limnology and Oceanography, 41(2), 216-223.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000F-E2CF-1
Zusammenfassung
Daphnia collects more food at low particle concentrations by increasing its maximum filtering rate either by enlarging the area of its filter screens or by increasing its appendage beat rate (ABR). Various species of Daphnia grown at low levels of food phenotypically enlarge their filter screens. Models of the flow across a filter predict that the energy required to obtain a certain increase in filtering rate is a linear function of the screen area but increases proportionally to the square of ABR. A daphniid should be able to increase its filtering rate without expending more energy if it enlarges the filter and simultaneously reduces ABR. To test the model predictions, we measured morphometric parameters (areas, open space, intersetular distances) of the filters and ABR for Daphnia adapted to high food and to low food. Daphniids adapted to low food not only have larger filter screens, they also have finer meshes. In Daphnia adapted to low food, mean ABR is slightly reduced and there is a negative relationship between filter-screen area and ABR in the low-food treatment. Gains in filtering rate are higher and reductions in ABR are lower than predicted by the equilibrium model, hence Daphnia optimizes input rather than minimizing energy expenditures for filtering