SYMP 11-4 - Rapid clonal evolution and food web dynamics

Wednesday, August 5, 2009: 9:00 AM
Blrm B, Albuquerque Convention Center
Stephen P. Ellner1, Lutz Becks2, Michael Cortez3, Gregor F. Fussmann4, Nelson G. Hairston Jr.5, Giles Hooker6 and Laura E. Jones1, (1)Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, (2)Max Planck Institute for Evolutionary Biology, (3)School of Biology, Georgia Institute of Technology, Atlanta, GA, (4)Department of Biology, McGill University, Montreal, QC, Canada, (5)Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, (6)Biological Statistics and Computational Biology, Cornell University, Ithaca, NY
Background/Question/Methods We study rapid contemporary evolution in a bottle: aquatic microcosms where predator-prey cycles drive and are in turn driven by evolutionary changes in prey defense traits. The resulting population dynamics depend not only on the presence or absence of coupled evolutionary change, but also on the nature and magnitude of heritable variation for traits affecting ecological interactions. I will present theoretical results on rapid evolution in predator-prey interactions motivated by our empirical findings.

Results/Conclusions

Methods from the theory of slow-fast dynamical systems can be used to reduce model dimension back down to two (predator and prey abundance). This allows for some simple graphical analyses, based on tradeoff curves and transitions between periods of rapid evolutionary change and periods of evolutionary stasis, that let us catalog the different qualitative types of dynamics that can occur. Heritable variation in both predator and prey for traits affecting their interaction leads to coupled oscillator models where dynamics at the genotypic level may stabilize predator-prey cycles or lead to bursting-type behaviors at the population level. Methods from functional data analysis make it possible to infer properties of underlying trait dynamics from observations at the population level, raising the hope that observational data on food web dynamics could be used to draw conclusions about the role of unobserved trait dynamics.

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