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Evolutionary Dead End in the Galápagos: Divergence of Sexual Signals in the Rarest of Darwin's Finches

Overview of attention for article published in PLOS ONE, June 2010
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Title
Evolutionary Dead End in the Galápagos: Divergence of Sexual Signals in the Rarest of Darwin's Finches
Published in
PLOS ONE, June 2010
DOI 10.1371/journal.pone.0011191
Pubmed ID
Authors

Henrik Brumm, Heather Farrington, Kenneth Petren, Birgit Fessl

Abstract

Understanding the mechanisms underlying speciation remains a challenge in evolutionary biology. The adaptive radiation of Darwin's finches is a prime example of species formation, and their study has revealed many important insights into evolutionary processes. Here, we report striking differences in mating signals (songs), morphology and genetics between the two remnant populations of Darwin's mangrove finch Camarhynchus heliobates, one of the rarest species in the world. We also show that territorial males exhibited strong discrimination of sexual signals by locality: in response to foreign songs, males responded weaker than to songs from their own population. Female responses were infrequent and weak but gave approximately similar results. Our findings not only suggest speciation in the mangrove finch, thereby providing strong support for the central role of sexual signals during speciation, but they have also implications for the conservation of this iconic bird. If speciation is complete, the eastern species will face imminent extinction, because it has a population size of only 5-10 individuals.

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Geographical breakdown

Country Count As %
United States 5 6%
France 1 1%
Ecuador 1 1%
Portugal 1 1%
United Kingdom 1 1%
Brazil 1 1%
Romania 1 1%
Argentina 1 1%
Unknown 75 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 22 25%
Student > Ph. D. Student 18 21%
Student > Bachelor 9 10%
Professor 6 7%
Other 5 6%
Other 17 20%
Unknown 10 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 56 64%
Environmental Science 7 8%
Psychology 2 2%
Engineering 2 2%
Biochemistry, Genetics and Molecular Biology 1 1%
Other 4 5%
Unknown 15 17%