Predator mimicry, not conspicuousness, explains the efficacy of butterfly eyespots

Abstract

Large conspicuous eyespots on butterfly wings have been shown to deter predators. This has been traditionally explained by mimicry of vertebrate eyes, but recently the classic eye-mimicry hypothesis has been challenged. It is proposed that the conspicuousness of the eyespot, not mimicry, is what causes aversion due to sensory biases, neophobia or sensory overloads. We conducted an experiment to directly test whether the eye-mimicry or the conspicuousness hypothesis better explain eyespot efficacy. We used great tits (Parus major) as model predator, and tested their reaction towards animated images on a computer display. Birds were tested against images of butterflies without eyespots, with natural-looking eyespots, and manipulated spots with the same contrast but reduced resemblance to an eye, as well as images of predators (owls) with and without eyes. We found that mimetic eyespots were as effective as true eyes of owls and more efficient in eliciting an aversive response than modified, less mimetic but equally contrasting eyespots. We conclude that the eye-mimicry hypothesis explains our results better than the conspicuousness hypothesis and is thus likely to be an important mechanism behind the evolution of butterfly eyespots.

Keywords: IRTree GLMMS; animal coloration; deception; eyespots; mimicry; predator–prey interactions.

Figure 1.

Treatments, sample sizes and the planned comparisons tested. OE, owl with eyes; OW, owl without eyes; BR, butterfly with real eyespots; BM, butterfly with modified eyespots; BW, butterfly without eyespots.

Figure 2.

Structure of the binomial tree leading to the four behavioural response categories recorded. Circles represent binomial nodes with the two alternative outcomes coded as 1 (black arrows) or 0 (grey arrows). Table represents the binomial node values necessary to code each categorical outcome.

Figure 3.

Observed proportions (grey bars) and fitted values (dashed lines) for the response tree GLMMs at all four tree nodes. Bar errors correspond to standard errors of the proportion.