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Dryad

Data from: Biased generalization of salient traits drives the evolution of warning signals

Cite this dataset

Gamberale-Stille, Gabriella; Kazemi, Baharan; Balogh, Alexandra; Leimar, Olof (2018). Data from: Biased generalization of salient traits drives the evolution of warning signals [Dataset]. Dryad. https://doi.org/10.5061/dryad.b5151

Abstract

The importance of receiver biases in shaping the evolution of many signalling systems is widely acknowledged. Here we show that receiver bias can explain which traits evolve to become warning signals. For warning colouration, a generalization bias for a signalling trait can result from predators learning to discriminate unprofitable from profitable prey. However, since the colour patterns of prey are complex traits with multiple components, it is crucial to understand which of the many aspects of prey appearance evolve into signals. We provide experimental evidence that the more salient differences in prey traits give rise to greater generalization bias, corresponding to stronger selection towards trait exaggeration. Our results are based on experiments with domestic chickens as predators in a Skinner-box-like setting, and imply that the difference in appearance between profitable and unprofitable prey that is most rapidly learnt produces the greatest generalization bias. As a consequence, certain salient traits of unprofitable prey are selected towards exaggeration to even higher salience, driving the evolution of warning colouration. This general idea may also help to explain the evolution of many other striking signalling traits found in nature.

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