TY - JOUR
T1 - Animal coloration patterns
T2 - Linking spatial vision to quantitative analysis
AU - Stoddard, Mary Caswell
AU - Osorio, Daniel
N1 - Funding Information:
We thank the editor, the associate editor, and two anonymous reviewers for their constructive comments; members of the Stoddard Lab for helpful feedback and discussion; and Audrey Miller for help with final formatting. We also thank Dan Rubenstein for sharing zebra images. Funding to M.C.S. was provided by Princeton University and a Sloan Research Fellowship.
Publisher Copyright:
© 2019 by The University of Chicago.
PY - 2019/2/1
Y1 - 2019/2/1
N2 - Animal coloration patterns, from zebra stripes to bird egg speckles, are remarkably varied. With research on the perception, function, and evolution of animal patterns growing rapidly, we require a convenient framework for quantifying their diversity, particularly in the contexts of camouflage, mimicry, mate choice, and individual recognition. Ideally, patterns should be defined by their locations in a low-dimensional pattern space that represents their appearance to their natural receivers, much as color is represented by color spaces. This synthesis explores the extent to which animal patterns, like colors, can be described by a few perceptual dimensions in a pattern space. We begin by reviewing biological spatial vision, focusing on early stages during which neurons act as spatial filters or detect simple features such as edges. We show how two methods from computational vision—spatial filtering and feature detection—offer qualitatively distinct measures of animal coloration patterns. Spatial filters provide a measure of the image statistics, captured by the spatial frequency power spectrum. Image statistics give a robust but incomplete representation of the appearance of patterns, whereas feature detectors are essential for sensing and recognizing physical objects, such as distinctive markings and animal bodies. Finally, we discuss how pattern space analyses can lead to new insights into signal design and macroevolution of animal phenotypes. Overall, pattern spaces open up new possibilities for exploring how receiver vision may shape the evolution of animal pattern signals.
AB - Animal coloration patterns, from zebra stripes to bird egg speckles, are remarkably varied. With research on the perception, function, and evolution of animal patterns growing rapidly, we require a convenient framework for quantifying their diversity, particularly in the contexts of camouflage, mimicry, mate choice, and individual recognition. Ideally, patterns should be defined by their locations in a low-dimensional pattern space that represents their appearance to their natural receivers, much as color is represented by color spaces. This synthesis explores the extent to which animal patterns, like colors, can be described by a few perceptual dimensions in a pattern space. We begin by reviewing biological spatial vision, focusing on early stages during which neurons act as spatial filters or detect simple features such as edges. We show how two methods from computational vision—spatial filtering and feature detection—offer qualitatively distinct measures of animal coloration patterns. Spatial filters provide a measure of the image statistics, captured by the spatial frequency power spectrum. Image statistics give a robust but incomplete representation of the appearance of patterns, whereas feature detectors are essential for sensing and recognizing physical objects, such as distinctive markings and animal bodies. Finally, we discuss how pattern space analyses can lead to new insights into signal design and macroevolution of animal phenotypes. Overall, pattern spaces open up new possibilities for exploring how receiver vision may shape the evolution of animal pattern signals.
KW - Animal coloration patterns
KW - Animal spatial vision
KW - Camouflage
KW - Communication
KW - Fourier transform
KW - Sensory ecology
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U2 - 10.1086/701300
DO - 10.1086/701300
M3 - Article
C2 - 30720360
AN - SCOPUS:85060196656
SN - 0003-0147
VL - 193
SP - 164
EP - 186
JO - American Naturalist
JF - American Naturalist
IS - 2
ER -