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The green-beard effect is a thought experiment used in evolutionary biology to explain selective altruism among individuals of a species. The idea of a green-beard gene was proposed by William D. Hamilton in his articles of 1964, and got the name from the example used by Richard Dawkins ("I have a green beard and I will be altruistic to anyone else with green beard") in The Selfish Gene (1976). A green-beard effect occurs when an allele, or a set of linked alleles, produce three expressed (or phenotypic) effects: a perceptible trait—the hypothetical "green beard" recognition of this trait by others; and preferential treatment of individuals with the trait by others with the trait The carrier of the gene (or a specific allele) is essentially recognizing copies of the same gene (or a specific allele) in other individuals. Whereas kin selection involves altruism to related individuals who share genes in a non-specific way, green-beard alleles promote altruism toward individuals who share a gene that is expressed by a specific phenotypic trait. Some authors also note that the green-beard effects can include "spite" for individuals lacking the "green-beard" gene. This can have the effect of delineating a subset of organisms within a population that is characterized by members who show greater cooperation toward each other, this forming a "clique" that can be advantageous to its members who are not necessarily kin. Green-beard effect could increase altruism on green-beard phenotypes and therefore its presence in a population even if genes assist in the increase of genes that are not exact copies; all that is required is that they express the three required characteristics. Green-beard alleles are vulnerable to mutations that produce the perceptible trait without the helping behaviour. Altruistic behaviour is paradoxical when viewed in the light of old ideas of evolutionary theory that emphasised the role of competition.
Sandor Kasas, Livan Bladimir Alonso Sarduy, Jens Nielsen
Dario Floreano, Laurent Keller, Markus Waibel