Stabilizing selection on individual pattern elements of aposematic signals

Anne Winters, Naomi Green, Nerida G Wilson, Martin How, Mary Garson, N. Justin Marshall, Karen L Cheney

Research output: Contribution to journalArticle (Academic Journal)peer-review

38 Citations (Scopus)
290 Downloads (Pure)

Abstract

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 recognise 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.
Original languageEnglish
Article number20170926
Number of pages9
JournalProceedings of the Royal Society B: Biological Sciences
Volume284
Issue number1861
Early online date23 Aug 2017
DOIs
Publication statusPublished - 30 Aug 2017

Keywords

  • Colour pattern
  • warning signals
  • genetic differentiation
  • marine molluscs

Fingerprint

Dive into the research topics of 'Stabilizing selection on individual pattern elements of aposematic signals'. Together they form a unique fingerprint.

Cite this