Data from: Similar but different: dynamic social network analysis highlights fundamental differences between the fission-fusion societies of two equid species, the onager and Grevy's zebra

Understanding why animal societies take on the form that they do has benefited from insights gained by applying social network analysis to patterns of individual associations. Such analyses typically aggregate data over long time periods even though most selective forces that shape sociality have strong temporal elements. By explicitly incorporating the temporal signal in social interaction data we re-examine the network dynamics of the social systems of the evolutionarily closely-related Grevy’s zebras and wild asses that show broadly similar social organizations. By identifying dynamic communities, previously hidden differences emerge: Grevy’s zebras show more modularity than wild asses and in wild asses most communities consist of solitary individuals; and in Grevy’s zebras, lactating females show a greater propensity to switch communities than non-lactating females and males. Both patterns were missed by static network analyses and in general, adding a temporal dimension provides insights into differences associated with the size and persistence of communities as well as the frequency and synchrony of their formation. Dynamic network analysis provides insights into the functional significance of these social differences and highlights the way dynamic community analysis can be applied to other species.通过将社交网络分析（social network analysis）应用于个体关联模式，学界对动物社会形态成因的认知得以显著深化。尽管塑造社会性的多数选择压力均具备显著的时间维度特征，但此类分析通常会将数据在较长时段内进行聚合处理。我们通过在社交互动数据中显性纳入时间维度信号，重新审视了进化关系密切、社会组织大体相似的细纹斑马（Grevy’s zebras）与野驴（wild asses）的社交系统网络动态。通过识别动态社群（dynamic communities），此前被掩盖的差异得以显现：细纹斑马的网络模块化（modularity）程度高于野驴，且野驴的多数社群由独居个体构成；而在细纹斑马中，泌乳雌性相较于非泌乳雌性与雄性，更倾向于在社群间移动。静态网络分析未能捕捉到这两类模式；总体而言，加入时间维度后，我们得以洞悉社群规模、存续时长，以及社群形成的频率与同步性相关的差异。动态网络分析有助于阐释这类社交差异的功能意义，并彰显了动态社群分析可推广应用于其他物种的路径。