A multiplex centrality metric for complex social networks: sex, social status, and family structure predict multiplex centrality in rhesus macaques
A multiplex centrality metric for complex social networks: sex, social status, and family structure predict multiplex centrality in rhesus macaques
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DOI：
10.7717/peerj.8712
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发表时间：
2020-03-16
期刊：
影响因子：
2.7
通讯作者：
McCowan, Brenda
中科院分区：
文献类型：
--
作者：
Beisner, Brianne;Braun, Nildas;McCowan, Brenda
社会成员通过各种各样的社会行为进行互动，从而产生了多方面和复杂的社会生活。对于动物行为的研究，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，其中每种交互类型代表社会网络的不同层，具有比单层方法更好地捕获这种复杂性的潜力。计算个体在多层社会网络中的中心性可以揭示关键个体，更全面地表征社会角色。然而，现有的多层中心性度量并没有考虑到跨交互层的动态和功能差异。在这里，我们验证了一种量化多重中心性的新方法，称为共识排名，将这种方法应用于一种研究得很好的非人类灵长类动物恒河猴的多个社会群体。共识排序可以适当地处理动物社会生活的复杂性，例如具有不同属性（稀疏与密集）和生物学意义（竞争与附属互动）的网络。我们研究了个体属性或社会人口因素（性别、年龄、优势等级和确定性、母系规模、养育历史）是否与多重中心性有关。社会网络为7个社会群体构建了5个交互层（即攻击、状态信号、冲突监管、梳理和聚集）。在这五个层次中计算共识排名，并根据个人属性和社会人口因素进行分析。广义线性混合模型表明，共识排序检测了恒河猴已知的社会模式，表明多重中心性在等级高的雄性恒河猴和来自最大家族的雌性恒河猴中更大。此外，共识排名还表明，来自非常小的家庭和母亲抚养的个体（与托儿所抚养的个体相比）的女性更中心，这表明对多个社会领域的考虑揭示了个体的社会中心性和重要性，否则可能会被忽略。
Members of a society interact using a variety of social behaviors, giving rise to a multifaceted 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 sociodemographic 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.