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Olivier Penacchio, Julie Harris; Warning signals: speeding up ultra-rapid animal detection. Journal of Vision 2018;18(10):2. doi: https://doi.org/10.1167/18.10.2.
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Many species in the animal kingdom use camouflage to avoid predation. By contrast, aposematic species are thought to use a strategy that makes them easier for would-be predators to spot: they adopt distinctive signals, called warning signals, to inform predators that they are unprofitable. Conspicuousness has been identified as a potential pivotal attribute of the design of warning signals, but very few studies have evaluated this proposition directly. We explored the effect of warning signals on human observers in a fast animal detection experiment. In a forced-choice design, pairs of commercially available photographs of natural scenes, only one of which pictured an animal, were presented for 20 ms on either side of a central fixation point. Target images pictured terrestrial animals, ranging from mammals to amphibians and insects in their natural environment, distractor images showed natural landscapes similarly made. Participants reported, via button press, on which side the animal appeared. The set of target images contained as many aposematic as control species. Participants were not informed of the two distinct categories before the experiment was finished. Contrast was normalised across the whole set of target and distractor images and target size was balanced between the two classes of target images. In line with previous reports (Thorpe, Fize, & Marlot, 1996; Kirchner & Thorpe, 2006), we found observers could do this task with very fast speed (median 443 ms) and accuracy (93%). Our novel finding here was that reaction times were significantly shorter (30 ms, 428 ms versus 457 ms) and detection more accurate (95.5% versus 90%) for aposematic animals, than for non-aposematic animals. Our findings demonstrate that there is something special about aposematic patterns, and that they are 'more conspicuous' in terms of their speed of detection. We do not yet know what specific image characteristics of the pattern are responsible.
Meeting abstract presented at VSS 2018
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