Behavioral Ecology
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some human-perceived illusions not apply to other species but also
some even work in the opposite direction (e.g., Watanabe et al. 2013).
Such findings demonstrate that the rules of image perception vary
greatly across different animals, which implies that the potential “illusionary toolkit” should be correspondingly large. Rather than expecting common iterations of a limited range of illusions, we might
therefore expect many, often species-specific, examples. Intriguingly,
it follows that the true opportunity for illusion in the natural world
will greatly transcend our perception of it; that is, there are likely
countless potential routes to illusion that humans cannot even begin
to imagine. This deepens the empirical challenge because we neither
know where to look nor what to look for in the first place.
By the same token, the presence of interspecific variation in the
nature of perceptual illusions also implies great potential for signal
adaptation. Intraspecific signaling systems may evolve in ways that
elicit illusions in conspecific but not heterospecific viewers, or vice
versa. Otherwise highly conspicuous sexual ornaments may, for
example, be tuned to distort the perception of dominant predators.
Kelley and Kelley (2014) also explore how ornaments may also be
displayed in ways that selectively activate illusions, such as the displays of fiddler crabs (Callander et al. 2013) and guppies (Gasparini
et al. 2013). These examples, however, lead us back to the broader
issue of empirical estimation. Although each could signify the operation of an Ebbinghaus illusion (whereby a focal object appears
deceptively larger in comparison with smaller adjacent objects), they
are also consistent with explanations based around comparative decision making and social signaling. Heuristically, this underscores the
need to convincingly demonstrate that perceptual illusion is actually
at play. This may be accomplished through detailed knowledge of
visual and spatial processing or through linking vision and behavior in highly specific contexts. Putative motion-related illusions, for
example, such as the role of snake bands in reversing their apparent
direction of travel (Jackson et al. 1976), may be informed by knowledge of refresh rates in the eyes of relevant viewers. If we knew how
fast such a snake need ideally travel to distort the perception of its
predator(s), then this might offer a basis for testing against actual
snake movement in ecologically relevant situations. Compelling evidence may also reside in signals that match predictions for perceptual
distortion based on generalizable features, such as perspective (as in
the well-described bower bird example; e.g. Endler et al. 2010).
Overall, Kelley and Kelley (2014) present an impressive insight
into the varied potential for perceptual illusion in visual signal evolution. The crucial next step forward demands a guiding empirical framework for testing such phenomena. Given the indelible
stamp of our own perception of what constitutes a visual illusion,
the need for objectivity in such work will perhaps prove paramount
among all the endeavors of behavioral ecology.
Address correspondence to D.J. Kemp. E-mail: [email protected].
Received 9 December 2013; revised 10 January 2014;
accepted 13 January 2014; Advance Access publication 22 March 2014.
doi:10.1093/beheco/aru012
Forum editor: Sue Healy
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Perceptual biases and animal illusions:
a response to comments on Kelley
and Kelley
Laura A. Kelleya and Jennifer L. Kelleyb
of Psychology, University of Cambridge, Downing
Street, Cambridge CB2 3EB, UK and bCentre for Evolutionary
Biology/Neuroecology Group, School of Animal Biology, The
University of Western Australia, Stirling Highway, Crawley, Western
Australia 6009, Australia
aDepartment
Can animals create illusions? What are they used for? What can
they tell us about the evolution of signaling traits and receiver
perception? These are just some of the questions that we have
attempted to address in our recent review of animal illusions
and other forms of sensory deception (Kelley and Kelley 2014).
Although it is always potentially risky to suggest an umbrella term
such as “animal illusion” to describe signals/traits with a diverse
range of functions and perceptual mechanisms, we hope that our
review stimulates behavioral ecologists to reconsider the important
role of perception in both natural and sexual selection.
That selection might act on animal perception is not a novel suggestion, and significant advances have been made by considering
the role of the “psychological landscape” (Guilford and Dawkins
1991) in sensory bias (Ryan et al. 1990; Endler 1992), sensory traps
(Christy 1995), mimicry (Wickler 1968), and perceptual biases
(Schaefer and Ruxton 2009; Ryan and Cummings 2013). The key
question is how do animal visual illusions fit into these models of
signal evolution (Théry 2014)? This is a difficult question to answer
and is one of the reasons that we presented a continuum of examples of sensory manipulation, in addition to those that might be illusory. We hope that this general approach will kick-start the debate
as to what does and does not constitute an illusion. Nonetheless,
we suggest that animal illusions can be considered part of a broad
model that describes the importance of perceptual biases in shaping the evolution of animal traits (Ryan 2014). Illusions can exploit
perceptual biases, manipulate mechanisms of perceptual processing, and enforce errors of perception. Importantly, animal illusions
may not only enhance the efficacy of sexual signals (making illusions difficult to distinguish from comparative mate choice), but
they should also act to exploit perceptual processes in other contexts, such as natural selection.
Although there has been a recent resurgence in the field of
protective coloration and significant advances have been made
in modeling animal visual systems, the underlying processes of
Stevens • Confusion and illusion
pattern perception have scarcely been considered (Merilaita
2014). Stevens’ (2014) suggestion that disruptive coloration cannot
be considered an illusion because it primarily relies on preventing detection highlights the importance of considering the different levels of sensory processing that are involved in detecting and
recognizing prey (Troscianko et al. 2009). For example, differential blending is a form of disruptive coloration where some elements of the prey’s coloration are highly contrasting, while other
color patches blend into the background (Cott 1940; Stevens and
Merilaita 2009). This form of coloration might be considered illusory because it disrupts predators’ perceptual grouping mechanisms so that some patches of the prey’s body are more likely to
be grouped with the background rather than with the adjacent
color patches (Espinosa and Cuthill 2014). Object detection and
identification therefore requires several levels of sensory processing
involving both low-level edge detection neurons and higher level
stages that use perceptual grouping to resolve border ownership
(Troscianko et al. 2009).
Although we have suggested a broad working definition of
animal illusions, several of the invited commentaries (Kemp and
White 2014; Stevens 2014) rightly point out that the field can only
progress if a clear empirical framework is presented. In the human
literature, illusions are often classified according to their appearance or cause but have been liable to change as theoretical understanding progresses. Gregory (1997) suggested 4 types of illusion
based on analogous errors of language: fiction (e.g., Kanizsa triangle), paradox (e.g., Penrose stairs), ambiguity (e.g., Necker cube),
and distortion (e.g., Müller-Lyer lines). Two further categories
have since been added (Gregory 2009): blindness (e.g., attentional
deficiencies) and instability (e.g., op art). This approach is likely
to present significant challenges given the interspecific variability
observed in animals and the lack of knowledge concerning the
mechanisms involved. Perhaps a simpler categorization of different types of illusion may provide a way forward. In our review, we
classified illusions based on their putative perceptual effects (Coren
and Girgus 1978) although it may be difficult to elucidate perceptual outcomes in nonhuman animals and 1 illusion may induce
multiple perceptual outcomes (Kelley and Endler 2012). It is also
worth noting that traits themselves may not necessarily be illusory—rather the context in which they are presented acts to distort perception of the trait (e.g., assimilation illusion). This suggests
that it is important to consider how a trait is perceived in different
social and environmental contexts; furthermore, the previous perceptual experience (i.e., working knowledge of the world) of the
receiver may be important. In particular, future research requires
guidelines for quantifying animal perception in an ecologically
relevant setting using natural visual scenes. Moving forward, it is
crucial that behavioral ecologists collaborate closely with cognitive
469
neuroscientists to further understand the processes that create subjective perceptual worlds.
Address correspondence to L.A. Kelley. E-mail: [email protected].
Received 13 February 2014; revised 14 February 2014; accepted 17
February 2014; Advance Access publication 15 March 2014.
doi:10.1093/beheco/aru040
Forum editor: Sue Healy
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