Romano Valéria, Puga-Gonzalez Ivan, MacIntosh Andrew J J, Sueur Cédric
IMBE, Aix Marseille Univ., Avignon Univ., CNRS, IRD, Marseille, France.
Center for Modelling Social Systems (CMSS) at NORCE, Kristiansand, Norway.
R Soc Open Sci. 2024 Feb 28;11(2):231619. doi: 10.1098/rsos.231619. eCollection 2024 Feb.
How interactions between individuals contribute to the emergence of complex societies is a major question in behavioural ecology. Nonetheless, little remains known about the type of immediate social structure (i.e. social network) that emerges from relationships that maximize beneficial interactions (e.g. social attraction towards informed individuals) and minimize costly relationships (e.g. social avoidance of infected group mates). We developed an agent-based model where individuals vary in the degree to which individuals signal benefits versus costs to others and, on this basis, choose with whom to interact depending on simple rules of social attraction (e.g. access to the highest benefits) and social avoidance (e.g. avoiding the highest costs). Our main findings demonstrate that the accumulation of individual decisions to avoid interactions with highly costly individuals, but that are to some extent homogeneously beneficial, leads to more modular networks. On the contrary, individuals favouring interactions with highly beneficial individuals, but that are to some extent homogeneously costly, lead to less modular networks. Interestingly, statistical models also indicate that when individuals have multiple potentially beneficial partners to interact with, and no interaction cost exists, this also leads to more modular networks. Yet, the degree of modularity is contingent upon the variability in benefit levels held by individuals. We discuss the emergence of modularity in the systems and their consequences for understanding social trade-offs.
个体之间的相互作用如何促成复杂社会的出现，是行为生态学中的一个主要问题。尽管如此，对于从最大化有益互动（例如对有见识个体的社会吸引力）和最小化代价高昂的关系（例如对受感染群体成员的社会回避）的关系中产生的直接社会结构（即社会网络）类型，我们仍知之甚少。我们开发了一个基于主体的模型，其中个体在向他人传递利益与代价的程度上存在差异，并在此基础上，根据社会吸引力（例如获得最高利益）和社会回避（例如避免最高成本）的简单规则，选择与谁互动。我们的主要研究结果表明，个体做出避免与代价高昂但在某种程度上具有同质益处的个体互动的决策积累，会导致形成更多模块化网络。相反，倾向于与益处极大但在某种程度上具有同质代价的个体互动的个体，会导致形成模块化程度较低的网络。有趣的是，统计模型还表明，当个体有多个潜在的有益伙伴可供互动且不存在互动成本时，这也会导致形成更多模块化网络。然而，模块化程度取决于个体所拥有的利益水平的变异性。我们讨论了系统中模块化的出现及其对理解社会权衡的影响。
