4.5 Article

The social network structure of a wild meerkat population: 1. Inter-group interactions

期刊

BEHAVIORAL ECOLOGY AND SOCIOBIOLOGY
卷 63, 期 9, 页码 1295-1306

出版社

SPRINGER
DOI: 10.1007/s00265-009-0782-x

关键词

Social networks; Meerkats; Inter-group encounters; Roving males; Spatial factors

资金

  1. Department for Environment, Food and Rural Affairs
  2. Higher Education Funding Council for England
  3. Cambridge Infectious Diseases Consortium
  4. BBSRC

向作者/读者索取更多资源

Groups of individuals frequently interact with each other, but typically analysis of such interactions is restricted to isolated dyads. Social network analysis (SNA) provides a method of analysing polyadic interactions and is used to analyse interactions between individuals. We use a population of 12 groups (ca. 250 animals) of wild meerkats (Suricata suricatta) to test whether SNA can also be used to describe and elucidate patterns of inter-group interactions. Using data collected over 24 months, we constructed two sets of networks, based on direct encounters between groups and instances of roving males visiting other groups. We analysed replicated networks of each type of interaction to investigate similarities between networks of different social interactions as well as testing their stability over time. The two network types were similar to each other when derived from long-term data, but showed significant differences in structure over shorter timescales where they varied according to seasonal and ecological conditions. Networks for both types of inter-group interaction constructed from data collected over 3 months reliably described long-term (12- and 24-month) patterns of interactions between groups, indicating a stable social structure despite variation in group sizes and sex ratios over time. The centrality of each meerkat group in roving interactions networks was unaffected by the sex ratio of its members, indicating that male meerkats preferentially visit geographically close groups rather than those containing most females. Indeed, the strongest predictors of network structure were spatial factors, suggesting that, in contrast to analyses of intra-group interactions, analyses of inter-group interactions using SNA must take spatial factors into account.

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