Optimal background matching camouflage

Constantine Michalis*, Nicholas E. Scott-Samuel, David P. Gibson, Innes C. Cuthill

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

24 Citations (Scopus)
353 Downloads (Pure)

Abstract

Background matching is the most familiar and widespread camouflage strategy: avoiding detection by having a similar colour and pattern to the background. Optimizing background matching is straightforward in a homogeneous environment, or when the habitat has very distinct sub-types and there is divergent selection leading to polymorphism. However, most backgrounds have continuous variation in colour and texture, so what is the best solution? Not all samples of the background are likely to be equally inconspicuous, and laboratory experiments on birds and humans support this view. Theory suggests that the most probable background sample (in the statistical sense), at the size of the prey, would, on average, be the most cryptic. We present an analysis, based on realistic assumptions about low-level vision, that estimates the distribution of background colours and visual textures, and predicts the best camouflage. We present data from a field experiment that tests and supports our predictions, using artificial moth-like targets under bird predation. Additionally, we present analogous data for humans, under tightly controlled viewing conditions, searching for targets on a computer screen. These data show that, in the absence of predator learning, the best single camouflage pattern for heterogeneous backgrounds is the most probable sample.

Original languageEnglish
Article number20170709
Number of pages6
JournalProceedings of the Royal Society B: Biological Sciences
Volume284
Issue number1858
DOIs
Publication statusPublished - 12 Jul 2017

Structured keywords

  • Cognitive Science
  • Visual Perception

Keywords

  • Animal coloration
  • Camouflage
  • Crypsis
  • Defensive coloration
  • Visual search

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