MULTILAYER NETWORK CENTRALITY IN RHESUS MACAQUE (MACACA MULATTA) NETWORKS IS INFLUENCED BY SEX, SOCIAL STATUS, AND FAMILY STRUCTURE |
B. A. Beisner1, M. Posfai2, N. Braun2, J. Vandeleest3, R. D'Souza2 and B. McCowan1,3 1University of California Davis, 1089 Veterinary Medicine Dr., Dept. of Population Health & Reproduction, Davis, CA 95616, USA, 2Dept. of Computer Science, University of California Davis, 3California National Primate Research Center, University of California Davis |
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Social life is complex, and multilayer social network techniques have great potential to advance our understanding of this complexity by integrating information across multiple social domains. We validated a recently-developed approach for measuring centrality in a multilayer social network, called Consensus Ranking, by applying it to the social networks of a well-characterized nonhuman primate: rhesus macaques. Social networks were constructed for five interaction layers (i.e., aggression, status signaling, conflict policing, grooming and huddling) for seven social groups (N=620 subjects) for which 4-6 weeks of behavioral data were available. Multilayer consensus ranks were calculated across these five layers and analyzed with respect to individual attributes and socio-demographic factors (i.e., age, sex, social status, matriline size, and rearing history). GLMMS showed that multilayer centrality was greater in high-ranking males with high dominance certainty (rank × certainty × sex: p=0.03), females from the smallest and largest families (small vs. medium: p=0.004; small vs. large: p=0.91), and mother-reared individuals (mother vs. nursery-reared: p=0.03). Furthermore, examination of who occupied the top consensus ranks for each group revealed several unexpectedly important individuals (e.g. middle-ranking) and some unimportant alphas. Thus, variation in multilayer centrality reflected known patterns in rhesus macaques, such as the importance of high-ranking adult males across multiple social domains, and also revealed individuals whose social centrality and importance might otherwise have been missed in any single interaction network. |
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