Abstract
Cuttlefish and other cephalopods achieve dynamic background matching with two general classes of body patterns: uniform (or uniformly stippled) patterns and mottle patterns. Both pattern types have been described chiefly by the size scale and contrast of their skin components. Mottle body patterns in cephalopods have been characterized previously as small-to-moderate-scale light and dark skin patches (i.e. mottles) distributed somewhat evenly across the body surface. Here we move beyond this commonly accepted qualitative description by quantitatively measuring the scale and contrast of mottled skin components and relating these statistics to specific visual background stimuli (psychophysics approach) that evoke this type of background-matching pattern. Cuttlefish were tested on artificial and natural substrates to experimentally determine some primary visual background cues that evoke mottle patterns. Randomly distributed small-scale light and dark objects (or with some repetition of small-scale shapes/sizes) on a lighter substrate with moderate contrast are essential visual cues to elicit mottle camouflage patterns in cuttlefish. Lowering the mean luminance of the substrate without changing its spatial properties can modulate the mottle pattern toward disruptive patterns, which are of larger scale, different shape and higher contrast. Backgrounds throughout nature consist of a continuous range of spatial scales; backgrounds with medium-sized light/dark patches of moderate contrast are those in which cuttlefish Mottle patterns appear to be the most frequently observed.
Highlights
Cephalopod adaptive coloration is among the most sophisticated in the animal kingdom because the neurally controlled chromatophore system permits a diverse repertoire of body patterning (Messenger, 2001) for a broad range of communication and camouflage (Hanlon and Messenger, 1996)
In the present study, which is about visual perception, we focus on which specific statistical properties of reduced and defined backgrounds influence the production of the light and dark components of cuttlefish body patterns
To quantify the degree of ‘mottledness’ or ‘granularity’ of the light and dark skin patches expressed by a cuttlefish, we developed an automated method (Barbosa et al, 2008b) to statistically characterize mottle patterns by analyzing the image of the animal in different spatial frequency bands accomplished with a fast Fourier transform of the image
Summary
Cephalopod adaptive coloration is among the most sophisticated in the animal kingdom because the neurally controlled chromatophore system permits a diverse repertoire of body patterning (Messenger, 2001) for a broad range of communication and camouflage (Hanlon and Messenger, 1996). And counterintuitively, our morphological analyses of body patterns uncovered only three basic patterning templates among thousands of cuttlefish images: Uniform, Mottle and Disruptive; many other cephalopods (squid, octopus, etc.) show these three types of camouflage patterns as well [summarized in Hanlon and Messenger (Hanlon and Messenger, 1996)] This comparative morphological trend enabled us to develop a working hypothesis to account for the remarkable speed of visual assessment and subsequent body pattern change. Our overall hypothesis, based upon the concept of parsimony, is that there is a relatively simple ‘visual sampling rule’ for each of the basic camouflage pattern types of uniform, mottle and disruptive [summarized in Hanlon (Hanlon, 2007; Hanlon et al, 2009)] Such a rule set would represent the simplest, fastest neural pathway that begins with visual input at the retina, progresses to central nervous system (CNS) processing and proceeds to motor output via direct neuro-muscular control of the skin chromatophores to produce the camouflage pattern (Messenger, 2001). In the present study we are only addressing the visual cues that elicit mottle patterns, the other body patterns (e.g. uniform and stipple and perhaps more fine-tuned patterns) that are on this continuum of background matching patterns will be addressed in the future
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