title: Pattern recognition algorithm reveals how birds evolve individual egg pattern signatures.
abstract: Pattern-based identity signatures are commonplace in the animal kingdom, but how they are recognized is poorly understood. Here we develop a computer vision tool for analysing visual patterns, NATUREPATTERNMATCH, which breaks new ground by mimicking visual and cognitive processes known to be involved in recognition tasks. We apply this tool to a long-standing question about the evolution of recognizable signatures. The common cuckoo (Cuculus canorus) is a notorious cheat that sneaks its mimetic eggs into nests of other species. Can host birds fight back against cuckoo forgery by evolving highly recognizable signatures? Using NATUREPATTERNMATCH, we show that hosts subjected to the best cuckoo mimicry have evolved the most recognizable egg pattern signatures. Theory predicts that effective pattern signatures should be simultaneously replicable, distinctive and complex. However, our results reveal that recognizable signatures need not incorporate all three of these features. Moreover, different hosts have evolved effective signatures in diverse ways.
authors.affiliation: 1] Department of Organismic and Evolutionary Biology and Museum of Comparative Zoology, Harvard University, Cambridge, Massachusetts 02138, USA [2] Harvard Society of Fellows, Harvard University, Cambridge, Massachusetts 02138, USA.
authors.forename: Mary Caswell
authors.initials: MC
authors.lastname: Stoddard
authors.affiliation: Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, UK.
authors.forename: Rebecca M
authors.initials: RM
authors.lastname: Kilner
authors.affiliation: Computer Laboratory, University of Cambridge, Cambridge CB3 0FD, UK.
authors.forename: Christopher
authors.initials: C
authors.lastname: Town
mesh_terms: D000465:Algorithms; D000818:Animals; D005075:Biological Evolution; D001717:Birds / Q000502:physiology*; D004528:Egg Shell / Q000502:physiology*; D008954:Models, Biological; D010363:Pattern Recognition, Automated / Q000379:methods*; D010858:Pigmentation / Q000502:physiology; D021641:Recognition, Psychology / Q000502:physiology*; D012044:Regression Analysis