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Social networks in changing environments

机译:不断变化的环境中的社交网络

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Social network analysis (SNA) has become a widespread tool for the study of animal social organisation. However despite this broad applicability, SNA is currently limited by both an overly strong focus on pattern analysis as well as a lack of dynamic interaction models. Here, we use a dynamic modelling approach that can capture the responses of social networks to changing environments. Using the guppy, Poecilia reticulata, we identified the general properties of the social dynamics underlying fish social networks and found that they are highly robust to differences in population density and habitat changes. Movement simulations showed that this robustness could buffer changes in transmission processes over a surprisingly large density range. These simulation results suggest that the ability of social systems to self-stabilise could have important implications for the spread of infectious diseases and information. In contrast to habitat manipulations, social manipulations (e.g. change of sex ratios) produced strong, but short-lived, changes in network dynamics. Lastly, we discuss how the evolution of the observed social dynamics might be linked to predator attack strategies. We argue that guppy social networks are an emergent property of social dynamics resulting from predator-prey co-evolution. Our study highlights the need to develop dynamic models of social networks in connection with an evolutionary framework.
机译:社交网络分析(SNA)已成为研究动物社会组织的一种广泛工具。但是,尽管具有广泛的适用性,但SNA当前由于过于注重模式分析以及缺乏动态交互模型而受到限制。在这里,我们使用一种动态建模方法,可以捕获社交网络对不断变化的环境的响应。我们使用孔雀鱼(Poecilia reticulata)识别了鱼类社交网络背后的社会动力学的一般特性,并发现它们对人口密度和栖息地变化的差异具有高度的鲁棒性。运动仿真表明,这种鲁棒性可以缓冲传输过程中令人惊讶的大密度范围内的变化。这些模拟结果表明,社会系统的自我稳定能力可能对传染病和信息的传播具有重要意义。与栖息地操纵相反,社交操纵(例如性别比例的变化)在网络动力学方面产生了强烈但短暂的变化。最后,我们讨论了观察到的社会动态的演变如何与捕食者的攻击策略相关联。我们认为,孔雀鱼的社交网络是掠食者与猎物共同进化产生的社会动力的新兴属性。我们的研究强调了与进化框架相关的发展社交网络动态模型的必要性。

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