Wild cricket social networks show stability across generations

BMC Evolutionary Biology

Research Article

Rolando Rodríguez-Muñoz¹  Tom Tregenza¹  David N. Fisher² 

[1] Centre for Ecology and Conservation, Penryn Campus, University of Exeter, TR109FE, Penryn, Cornwall, UK;Centre for Ecology and Conservation, Penryn Campus, University of Exeter, TR109FE, Penryn, Cornwall, UK;Department for Integrative Biology, Summerlee Science Complex, University of Guelph, N1G 2W1, Guelph, ON, Canada;

关键词: Exponential random graph models;    Gryllus;    Network comparison;    Population structure;   

DOI  :  10.1186/s12862-016-0726-9

 received in 2016-07-18, accepted in 2016-07-19,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundA central part of an animal's environment is its interactions with conspecifics. There has been growing interest in the potential to capture these interactions in the form of a social network. Such networks can then be used to examine how relationships among individuals affect ecological and evolutionary processes. However, in the context of selection and evolution, the utility of this approach relies on social network structures persisting across generations. This is an assumption that has been difficult to test because networks spanning multiple generations have not been available. We constructed social networks for six annual generations over a period of eight years for a wild population of the cricket Gryllus campestris.ResultsThrough the use of exponential random graph models (ERGMs), we found that the networks in any given year were able to predict the structure of networks in other years for some network characteristics. The capacity of a network model of any given year to predict the networks of other years did not depend on how far apart those other years were in time. Instead, the capacity of a network model to predict the structure of a network in another year depended on the similarity in population size between those years.ConclusionsOur results indicate that cricket social network structure resists the turnover of individuals and is stable across generations. This would allow evolutionary processes that rely on network structure to take place. The influence of network size may indicate that scaling up findings on social behaviour from small populations to larger ones will be difficult. Our study also illustrates the utility of ERGMs for comparing networks, a task for which an effective approach has been elusive.

【 授权许可】

CC BY   
© The Author(s). 2016