Fitting different visual models to behavioral patterns of parasitic egg rejection along a natural egg color gradient in a cavity-nesting host species

Autor: Mikus Abolins-Abols, Daniel Hanley, Marcel Honza, Mark E. Hauber, Jarkko Rutila, Peter Samaš, Thomas J. Manna, Miroslav Capek
Rok vydání: 2019
Předmět:
Zdroj: Vision research. 167
ISSN: 1878-5646
Popis: Avian brood parasites lay their eggs in other birds' nests, and hosts can mitigate the fitness cost of raising unrelated offspring by rejecting parasitic eggs. A visually-based cognitive mechanism often thought to be used by hosts to discriminate the foreign egg is to compare it against the hosts' own eggshell by size, shape, maculation, and/or ground coloration (i.e., absolute chromatic contrast). However, hosts may instead discriminate eggs based on their colors along a scale of natural avian eggshell coloration (i.e., directional chromatic contrast). In support of this latter visual process, recent research has found that directional chromatic contrasts can explain some host species' rejection behavior better than absolute chromatic or achromatic contrasts. Here, for the first time, we conducted an experiment in a cavity-nesting host species to test the predictions of these different visual mechanisms. We experimentally parasitized nests of the Common Redstart Phoenicurus phoenicurus, a regular host of a mimetic-egg laying Common Cuckoo Cuculus canorus host-race, using painted, immaculate 3D-printed model eggs in two geographically distant areas (Finland and Czech Republic). We found that directional chromatic contrasts better explained rejection behaviors in both parasitized (Finland) and non-parasitized (Czech Republic) host populations, as hosts rejected eggs that were noticeably browner, but not eggs that were noticeably bluer, than redstart eggs. These results support the paradigm of a single rejection threshold predicted by the directional chromatic contrast model and contribute to a growing generality of these patterns across diverse avian host-brood parasite systems.
Databáze: OpenAIRE