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Oecologia

, Volume 65, Issue 4, pp 492–497 | Cite as

Prey selection by the copepod Diacyclops thomasi

  • Richard S. Stemberger
Original Papers

Summary

  1. 1.

    Adult females of the predaceous copepod, Diacyclops thomasi, consistently selected for the soft-bodied rotifers Synchaeta pectinata, Polyarthra major and P. remata when presented various combinations of 8 rotifer species and 2 crustacean species as prey. Diacyclops did not select for other small, soft-bodied rotifers such as P. vulgaris and Ascomorpha ecaudis and, for loricate species such as Keratella cochlearis, K. crassa and for large soft-bodied adult Asplanchna priodonta. The small cladocerans, Bosmina longirostris and Chydorus sphaericus also were resistant to predation by this copepod.

     
  2. 2.

    Increased hunger in Diacyclops increased the clearance rates on both vulnerable and Diacyclops-resistant prey but did not greatly increase mortality of resistant prey relative to vulnerable prey. Sated Diacyclops preferred small, vulnerable prey like P. major over larger-bodied Synchaeta. This effect may be attributed to limited gut space when food is abundant.

     
  3. 3.

    When Diacyclops was presented different relative proportions of Keratella and Synchaeta at a constant total prey density (500 prey/L), it selected Synchaeta over Keratella in all trial proportions. However, Diacyclops selected more strongly for Keratella (but at a much lower clearance rate than for Synchaeta) when the relative abundance of this predator-resistant species was greatest. These results support optimal foraging in this predator.

     
  4. 4.

    Predator-prey interactions of the kind reported in this study can help identify important food web pathways and can be used to interpret predator-mediated changes in zooplankton communities in mature.

     

Keywords

Clearance Rate Prey Density Prey Selection Rotifer Species Total Prey 
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.

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Copyright information

© Springer-Verlag 1985

Authors and Affiliations

  • Richard S. Stemberger
    • 1
  1. 1.Great Lakes Research DivisionThe University of MichiganAnn ArborUSA

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