Coevolution of slow-fast populations: Evolutionary sliding, evolutionary pseudo-equilibria and complex Red Queen dynamics

F. Dercole, R. Ferrière, A. Gragnani, S. Rinaldi

Research output: Contribution to journalArticlepeer-review

68 Scopus citations


We study the interplay of ecological and evolutionary dynamics in communities composed of populations with contrasting time-scales. In such communities, genetic variation of individual traits can cause population transitions between stationary and cyclic ecological regimes, hence abrupt variations in fitness. Such abrupt variations raise ridges in the adaptive landscape, where the populations are poised between equilibrium and cyclic coexistence and along which evolutionary trajectories can remain sliding for long times or halt at special points called evolutionary pseudo-equilibria. These novel phenomena should be generic to all systems in which ecological interactions cause fitness to vary discontinuously. They are demonstrated by the analysis of a predator-prey community, with one adaptive trait for each population. The eco-evolutionary dynamics of the system show a number of other distinctive features, including evolutionary extinction and two forms of Red Queen dynamics. One of them is characterized by intermittent bouts of cyclic oscillations of the two populations.

Original languageEnglish (US)
Pages (from-to)983-990
Number of pages8
JournalProceedings of the Royal Society B: Biological Sciences
Issue number1589
StatePublished - Apr 22 2006


  • Adaptive ridge
  • Eco-evolutionary dynamics
  • Evolutionary sliding and pseudo-equilibria
  • Predator-prey coevolution
  • Red Queen dynamics
  • Slow-fast population dynamics

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Environmental Science(all)
  • Agricultural and Biological Sciences(all)


Dive into the research topics of 'Coevolution of slow-fast populations: Evolutionary sliding, evolutionary pseudo-equilibria and complex Red Queen dynamics'. Together they form a unique fingerprint.

Cite this