Stabilizing selection on individual pattern elements of aposematic signals
Author(s) -
Anne E. Winters,
Naomi F. Green,
Nerida G. Wilson,
Martin J. How,
Mary J. Garson,
N. Justin Marshall,
Karen L. Cheney
Publication year - 2017
Publication title -
proceedings of the royal society b biological sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.342
H-Index - 253
eISSN - 1471-2954
pISSN - 0962-8452
DOI - 10.1098/rspb.2017.0926
Subject(s) - aposematism , predation , biology , nudibranch , evolutionary biology , selection (genetic algorithm) , crypsis , camouflage , directional selection , natural selection , mimicry , zoology , ecology , predator , mollusca , artificial intelligence , computer science
Warning signal variation is ubiquitous but paradoxical: low variability should aid recognition and learning by predators. However, spatial variability in the direction and strength of selection for individual elements of the warning signal may allow phenotypic variation for some components, but not others. Variation in selection may occur if predators only learn particular colour pattern components rather than the entire signal. Here, we used a nudibranch mollusc, Goniobranchus splendidus , which exhibits a conspicuous red spot/white body/yellow rim colour pattern, to test this hypothesis. We first demonstrated that secondary metabolites stored within the nudibranch were unpalatable to a marine organism. Using pattern analysis, we demonstrated that the yellow rim remained invariable within and between populations; however, red spots varied significantly in both colour and pattern. In behavioural experiments, a potential fish predator, Rhinecanthus aculeatus , used the presence of the yellow rims to recognize and avoid warning signals. Yellow rims remained stable in the presence of high genetic divergence among populations. We therefore suggest that how predators learn warning signals may cause stabilizing selection on individual colour pattern elements, and will thus have important implications on the evolution of warning signals.
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