Area integrity index with random rearrangement (AIIRR): A new concept for quantifying disruptive colorations

  • Masahiko Tanahashi*
  • , Min Chen Lin
  • , Chung Ping Lin*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Disruptive coloration is one of the camouflaging strategies that use conspicuous coloration patterns to destroy the visual integrity of an object and interfere with the observer's visual perception. Such conspicuous coloration often divides the entire shape of the object into multiple areas, increasing the disruption effect. Here, we introduce a new concept of ‘segmental surface disruption’ and propose a computational framework to quantify the intensity of segmental surface disruption, namely, the area integrity index with random rearrangement (AIIRR). The AIIRR framework consists of two key parts: (1) statistically defined assessment of area integrity reduction (= increased separation) and (2) quantitative description of fuzzy and intermediate separation using the bootstrap method. In the second bootstrap process, coloration patterns are repeatedly arranged in a random manner and forced to generate different separation patterns. We develop the analytical programme for the basic AIIRR. The basic AIIRR only requires two external parameters: the number of Gaussian filters applied (n) and the shake amplitude (d), making it easy to use by general biologists. The basic AIIRR method successfully evaluated the difference in the strength of the area separation in Metapocyrtus and Pachyrhynchus weevils. The two-dimensional plot of the AIIRR and GabRat edge disruption intensities suggested the presence of different strategies of disruptive coloration in those weevils. AIIRR can be easily extended to handle colour images and possible extensions were also proposed in this study. The basic AIIRR programme and future updates are available via https://github.com/mtlucanid/AIIRR.

Original languageEnglish
Pages (from-to)1781-1795
Number of pages15
JournalMethods in Ecology and Evolution
Volume16
Issue number8
DOIs
Publication statusPublished - 2025 Aug

Keywords

  • Natsumushi software
  • PCA
  • bootstrap
  • image analysis
  • predator–prey interaction
  • shape analysis
  • visual signal

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Ecological Modelling

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