Selection for territory acquisition is modulated by social network structure in a wild songbird. (6th February 2015)

• Record Type: Journal Article
• Authors: Farine, D. R.; Sheldon, B. C.
• Is Part Of: Journal of evolutionary biology. Volume 28:Number 3(2015:Mar.)
• Page Start: 547
• Page End: 556
• Publication Date: 2015-02-06
• Subjects: Evolution (Biology) -- Periodicals; Biology -- Periodicals; 576.8
• DOI: 10.1111/jeb.12587
• Languages: English
• ISSNs: 1010-061X

Abstract

<abstract abstract-type="main" id="jeb12587-abs-0001"> <title>Abstract</title> <p>The social environment may be a key mediator of selection that operates on animals. In many cases, individuals may experience selection not only as a function of their phenotype, but also as a function of the interaction between their phenotype and the phenotypes of the conspecifics they associate with. For example, when animals settle after dispersal, individuals may benefit from arriving early, but, in many cases, these benefits will be affected by the arrival times of other individuals in their local environment. We integrated a recently described method for calculating assortativity on weighted networks, which is the correlation between an individual's phenotype and that of its associates, into an existing framework for measuring the magnitude of social selection operating on phenotypes. We applied this approach to large‐scale data on social network structure and the timing of arrival into the breeding area over three years. We found that late‐arriving individuals had a reduced probability of breeding. However, the probability of breeding was also influenced by individuals' social networks. Associating with late‐arriving conspecifics increased the probability of successfully acquiring a breeding territory. Hence, social selection could offset the effects of nonsocial selection. Given parallel theoretical developments of the importance of local network structure on population processes, and increasing data being collected on social networks in free‐living populations, the integration of these concepts could yield significant insights into social evolution.</p> </abstract>