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A dynamic optical signal in a nocturnal moth

Kelley, J.L., Tatarnic, N.J., Schröder-Turk, G.E., Endler, J.A. and Wilts, B.D. (2019) A dynamic optical signal in a nocturnal moth. Current Biology, 29 (17). 2919-2925.e2.

Link to Published Version: https://doi.org/10.1016/j.cub.2019.07.005
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Abstract

The wings of butterflies and moths generate some of the most spectacular visual displays observed in nature [1, 2, 3]. Particularly striking effects are seen when light interferes with nanostructure materials in the wing scales, generating bright, directional colors that often serve as dynamic visual signals [4]. Structural coloration is not known in night-flying Lepidoptera, yet here we show a highly unusual form of wing coloration in a nocturnal, sexually dimorphic moth, Eudocima materna (Noctuidae). Males feature three dark wing patches on the dorsal forewings, and the apparent size of these patches strongly varies depending on the angle of the wing to the viewer. These optical special effects are generated using specialized wing scales that are tilted on the wing and behave like mirrors. At near-normal incidence of light, these “mirror scales” act as thin-film reflectors to produce a sparkly effect, but when light is incident at ∼20°–30° from normal, the reflectance spectrum is dominated by the diffuse scattering of the underlying, black melanin-containing scales, causing a shape-shifting effect. The strong sexual dimorphism in the arrangement and architecture of the scale nanostructures suggests that these patterns might function for sexual signaling. Flickering of the male’s wings would yield a flashing, supernormal visual stimulus [5] to a viewer located 20°–30° away from the vertical, while being invisible to a viewer directly above the animal. Our findings reveal a novel use of structural coloration in nature that yields a dynamic, time-dependent achromatic optical signal that may be optimized for visual signaling in dim light.

Item Type: Journal Article
Murdoch Affiliation(s): Information Technology, Mathematics and Statistics
Publisher: Elsevier
Copyright: © 2019 Published by Elsevier Ltd.
URI: http://researchrepository.murdoch.edu.au/id/eprint/51220
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