How cognitive biases select for imperfect mimicry: a study of asymmetry in learning with bumblebees

Abstract

Imperfect mimicry presents a paradox of incomplete adaptation – intuitively, closer resemblance should improve performance. Receiver psychology can often explain why mimetic signals do not always evolve to match those of their models. Here, we explored the influence of a pervasive and powerful cognitive bias where associative learning depends upon an asymmetric interaction between the cue (stimulus) and consequence (reinforcer), such as in rats, which will associate light and tone with shock, and taste with nausea, but not the converse. Can such biases alter selection for mimicry? We designed an artificial mimicry system where bees foraged on artificial flowers, so that colours could be switched between rewarding or aversive. We found that when the colour blue was paired with a sucrose reward, other cues were ignored, but not when blue was paired with aversive compounds. We also tested the hypothesis that costs of errors affect how receivers sample imperfect mimics. However, costs of errors did not affect bee visits to imperfect mimics in our study. We propose a novel hypothesis for imperfect mimicry, in which the pairing between specific cues and reinforcers allows an imperfect mimic to resemble multiple models simultaneously. Generally, our results emphasize the importance of receiver psychology for the evolution of signal complexity and specificity.

Biased predation could promote convergence yet maintain diversity within Müllerian mimicry rings of Oreina leaf beetles

“…An alternative hypothesis to explain asymmetric generalization is that predators learn different traits when they are conditioned to different prey types. This could occur through a “stimulus salience” effect, where exceptionally salient stimuli tend to outcompete others during the associative learning process (Kazemi, Gamberale‐Stille, & Leimar, 2015; Kazemi, Gamberale‐Stille, Tullberg, & Leimar, 2014; Kikuchi & Dornhaus, 2018; Kikuchi, Mappes, Sherratt, & Valkonen, 2016; Mackintosh, 1976; Sherratt, Whissell, Webster, & Kikuchi, 2015). For example, if green is exceptionally salient, it may be the only trait that a predator learns to associate with unpalatability during training, so if the predator subsequently encounters a blue beetle, the blue beetle will be attacked.…”

A Novel Probabilistic Diffusion Model Based on the Weak Selection Mimicry Theory for the Generation of Hypnotic Songs

“…After undergoing long-term evolution, organisms eventually evolve to achieve the highest similarity to their target. In previous studies [64,65], natural selection was shown to regulate the direction of genetic evolution to facilitate adaptive coevolution of mimicry samples with the perceptual signals of their environment. Mimicry samples can adjust their phenotype to be similar to their target under various conditions, thereby aiming to achieve optimal similarity with the target.…”

Field evidence for colour mimicry overshadowing morphological mimicry

“…Among all the hypotheses suggested to explain the evolution of imperfect mimicry (reviewed in Kikuchi & Pfennig, 2013), the relaxed selection hypothesis has accumulated the most empirical support: selection against imperfect mimicry is weak (Penney et al., 2012; Sherratt, 2002; Sherratt & Peet‐Paré, 2017). One of the underlying reasons is related to predator cognition processes (Chittka & Osorio, 2007; Gamberale‐Stille et al., 2012; Kazemi et al., 2015; Kikuchi & Dornhaus, 2018; Sherratt & Peet‐Paré, 2017). When predators learn to discriminate between multiple components of the aposematic signal (e.g.…”