Quantitative description and discrimination of butterfly wing patterns using moment invariant analysis.

Abstract

Studies examining and using pattern variation in insects for identification and characterization of individuals and populations have been limited by the methods available for quantifying wing patterns objectively. In this paper, differences in wing pattern are demonstrated statistically using moment invariant data sets generated automatically from digitized images of the speckled wood butterfly, Pararge aegeria (Linnaeus). Studies with other biological subjects have already shown moment invariants to work well with outline shapes and silhouettes. A pilot study with replicated monochrome photographs of a single butterfly showed the method could detect pattern differences between wing surfaces, even in the presence of simulated wing fading and damage. In a further study of the wings of 228 specimens, multivariate analyses of variance using the moment data reliably detected differences between groups of butterflies according to sex, geographical origin and culture history. Potential applications and future improvements of the moment methodology are considered.