Aposematic color patterns are the dominant axis of phenotypic diversification in Nymphalid butterflies

Abstract

Butterfly wing patterns serve diverse roles in visual communication, from aposematic signaling and mimicry to mate attraction and camouflage. In brush-footed butterflies (Nymphalidae), this diversity can be traced to the wing pattern "ground plan" that generates phenotypes deterministic in origin yet highly multidimensional in form. Quantifying such complexity at scale has long been a challenge, limiting our understanding of how visual signals interact, constrain one another, and evolve. Here, we used computer vision to extract high-dimensional traits from standardized museum specimens and assembled the largest comparative dataset of wing color patterns to date, spanning over one third of all known Nymphalid species. We first tested whether chemically defended species occupy a distinct region in morphospace and then derived a quantitative score for aposematism from the principal color patterns associated with defense. Using this score, we examined whether aposematic signals are expressed consistently across wing surfaces and sexes, and whether their origins are linked to shifts in evolutionary rate. We found that the dominant axis of morphospace is defined by chromatic and achromatic contrast, along which defended and undefended species cluster. Validation with an expert-labeled moth dataset confirmed that this axis separates aposematic from non-aposematic phenotypes across Lepidoptera. Consistent with theory, strongly aposematic species showed greater visual similarity between dorsal and ventral surfaces, between sexes, and among individuals. Rate analyses further indicated that aposematic patterns evolved repeatedly and were associated with non-linear shifts in evolutionary tempo. Together, these results identify aposematism as the dominant organizing axis of wing color pattern evolution in Nymphalidae. Significance statementButterflies are renowned for their striking diversity of wing patterns, including the warning colors that signal chemical defense to predators. Yet whether such warning patterns share common features across lineages has remained unclear. Here, we applied a metric computer vision model to more than 16,000 museum specimens spanning one third of all Nymphalid species, encoding their wing patterns into a common morphospace. Within this space, high-contrast aposematic patterns emerged as the dominant axis of diversification, explaining up to 20% of phenotypic variance. These signals were expressed consistently across wing surfaces, sexes, and individuals, and evolved repeatedly across the family. Our approach demonstrates how computer vision enables meaningful comparative analyses of complex patterns, revealing general principles of butterfly diversification.