Spatially- and Directionally-varying Reflectance of Milli-scale Feather Morphology


Meeting Abstract

P1.95  Friday, Jan. 4  Spatially- and Directionally-varying Reflectance of Milli-scale Feather Morphology HARVEY, TA*; BOSTWICK, KS; MARSCHNER, S; Yale University; Cornell University; Cornell University todd.harvey@yale.edu

Birds have evolved diverse plumage through complex morphological modifications. Plumage is fundamental to how birds interact with their world; the signaling function of plumage plays a role in an organism’s social interaction and is a determining factor in an organism’s overall visual identity. Previous case studies have established the vast morphological modifications of individual, specialized feathers, and the millimeter-scale topography generated by the shape and orientation of feather sub-structures. We present investigations into a previously understudied aspect of avian visual signaling: directional reflectance and its relationship to milli-scale structure, namely its barbs and barbules. We hypothesized that structural modifications produce anisotropic reflectance, the direction of which may be predicted by the orientation of the milli-scale structure of the vane. We developed non-destructive tools and methods to investigate the signaling potential of the feather. We correlated measurements of directional light scattering to the milli-scale morphology of select samples of structurally-colored bird plumage. The results of these analyses lead to a more thorough understanding of the relationships between directional reflectance and the structure of the feather itself. Having found the reflectance to be anisotropic, we demonstrated that the change in the direction of the reflectance over the surface of the vane could in fact be predicted from the orientation of the different branches of the barb. The improved understanding of the variation in directional reflectance over the surface of the feather should allow for better comprehension of avian behavior, evolution of morphological adaptations, and the synthesis of more accurate predictive models.

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