Inducible, anti-predator traits are a classic example of phenotypic plasticity. Their evolutionary dynamics depend on their genetic basis, the historical pattern of predation risk that populations have experienced and current selection gradients. When populations experience predators with contrasting hunting strategies and size preferences, theory suggests contrasting micro-evolutionary responses to selection. Daphnia pulex is an ideal species to explore the micro-evolutionary response of anti-predator traits because they face heterogeneous predation regimes, sometimes experiencing only invertebrate midge predators and other times experiencing vertebrate fish and invertebrate midge predators. We explored plausible patterns of adaptive evolution of a predator-induced morphological reaction norm. We combined estimates of selection gradients that characterize the various habitats that D. pulex experiences with detail on the quantitative genetic architecture of inducible morphological defences. Our data reveal a fine scale description of daphnid defensive reaction norms, and a strong covariance between the sensitivity to cues and the maximum response to cues. By analysing the response of the reaction norm to plausible, predator-specific selection gradients, we show how in the context of this covariance, micro-evolution may be more uniform than predicted from size-selective predation theory. Our results show how covariance between the sensitivity to cues and the maximum response to cues for morphological defence can shape the evolutionary trajectory of predator-induced defences in D. pulex.
Evolution of a predator-induced, nonlinear reaction norm
M. Carter,M. Lind,Stuart R. Dennis,William T. Hentley,A. Beckerman
Published 2017 in Proceedings of the Royal Society B: Biological Sciences
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- Publication year
2017
- Venue
Proceedings of the Royal Society B: Biological Sciences
- Publication date
2017-08-04
- Fields of study
Biology, Medicine, Mathematics, Environmental Science
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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