Beisner Brianne, Braun Niklas, Pósfai Márton, Vandeleest Jessica, D'Souza Raissa, McCowan Brenda
Department of Population Health & Reproduction, School of Veterinary Medicine, University of California, Davis, Davis, CA, United States of America.
Neuroscience and Behavior Unit, California National Primate Research Center, Davis, CA, United States of America.
PeerJ. 2020 Mar 16;8:e8712. doi: 10.7717/peerj.8712. eCollection 2020.
Members of a society interact using a variety of social behaviors, giving rise to a multi-faceted and complex social life. For the study of animal behavior, quantifying this complexity is critical for understanding the impact of social life on animals' health and fitness. Multilayer network approaches, where each interaction type represents a different layer of the social network, have the potential to better capture this complexity than single layer approaches. Calculating individuals' centrality within a multilayer social network can reveal keystone individuals and more fully characterize social roles. However, existing measures of multilayer centrality do not account for differences in the dynamics and functionality across interaction layers. Here we validate a new method for quantifying multiplex centrality called consensus ranking by applying this method to multiple social groups of a well-studied nonhuman primate, the rhesus macaque. Consensus ranking can suitably handle the complexities of animal social life, such as networks with different properties (sparse vs. dense) and biological meanings (competitive vs. affiliative interactions). We examined whether individuals' attributes or socio-demographic factors (sex, age, dominance rank and certainty, matriline size, rearing history) were associated with multiplex centrality. Social networks were constructed for five interaction layers (i.e., aggression, status signaling, conflict policing, grooming and huddling) for seven social groups. Consensus ranks were calculated across these five layers and analyzed with respect to individual attributes and socio-demographic factors. Generalized linear mixed models showed that consensus ranking detected known social patterns in rhesus macaques, showing that multiplex centrality was greater in high-ranking males with high certainty of rank and females from the largest families. In addition, consensus ranks also showed that females from very small families and mother-reared (compared to nursery-reared) individuals were more central, showing that consideration of multiple social domains revealed individuals whose social centrality and importance might otherwise have been missed.
一个社会群体的成员通过各种社会行为进行互动，从而产生多层面且复杂的社会生活。对于动物行为的研究而言，量化这种复杂性对于理解社会生活对动物健康和适应性的影响至关重要。多层网络方法中，每种互动类型代表社交网络的不同层面，相较于单层方法，它更有潜力更好地捕捉这种复杂性。计算个体在多层社交网络中的中心性可以揭示关键个体，并更全面地刻画社会角色。然而，现有的多层中心性度量方法并未考虑互动层面之间动态和功能上的差异。在此，我们通过将一种名为共识排名的量化多重中心性的新方法应用于对恒河猴这一研究充分的非人灵长类动物的多个社会群体，来验证该方法。共识排名能够妥善处理动物社会生活的复杂性，比如具有不同属性（稀疏与密集）和生物学意义（竞争性与亲和性互动）的网络。我们研究了个体属性或社会人口统计学因素（性别、年龄、优势等级及确定性、母系群体规模、饲养历史）是否与多重中心性相关。针对七个社会群体构建了五个互动层面（即攻击、地位信号、冲突调节、梳理毛发和挤在一起）的社交网络。计算这五个层面的共识排名，并针对个体属性和社会人口统计学因素进行分析。广义线性混合模型表明，共识排名检测到了恒河猴中已知的社会模式，显示出在等级确定性高的高等级雄性以及来自最大家族的雌性中，多重中心性更高。此外，共识排名还表明，来自非常小的家族的雌性以及由母亲抚养（与在保育室抚养相比）的个体更处于中心位置，这表明考虑多个社会领域揭示了那些其社会中心性和重要性可能会被忽略的个体。
