Data from: A framework for the identification of long-term social avoidance in longitudinal datasets

Animal sociality is of significant interest to evolutionary and behavioural ecologists, with efforts focused on the patterns, causes and fitness outcomes of social preference. However, individual social patterns are the consequence of both attraction to (preference for) and avoidance of conspecifics. Despite this, social avoidance has received far less attention than social preference. Here, we detail the necessary steps to generate a spatially explicit, iterative null model which can be used to identify non-random social avoidance in longitudinal studies of social animals. We specifically identify and detail parameters which will influence the validity of the model. To test the usability of this model, we applied it to two longitudinal studies of social animals (Eastern water dragons (Intellegama leseurii) and bottlenose dolphins (Tursiops aduncus) to identify the presence of social avoidances. Using this model allowed us to identify the presence of social avoidances in both species. We hope that the framework presented here inspires interest in addressing this critical gap in our understanding of animal sociality, in turn allowing for a more holistic understanding of social interactions, relationships and structure.

动物社会性一直是进化生态学与行为生态学家的核心研究议题，相关研究多聚焦于社会偏好的模式、成因及其适合度效应。然而，个体的社会模式实则源于对同种个体的吸引（即社会偏好）与规避双重作用。尽管如此，相较于社会偏好，社会规避的相关研究却长期受到忽视。本研究详细阐述了构建空间显式迭代零模型的完整流程，该模型可用于在社会性动物的纵向研究中识别非随机的社会规避行为。本研究还专门明确并详述了影响该模型有效性的各项参数。为验证该模型的实用性，我们将其应用于两项社会性动物的纵向研究：东部水龙（Intellegama leseurii）与印太宽吻海豚（Tursiops aduncus），以检测社会规避行为的存在。通过该模型，我们成功在两个物种中均检测到了社会规避行为。我们期望本研究提出的研究框架能够唤起学界对填补这一动物社会性研究关键空白的兴趣，进而推动我们对社会互动、社会关系与社会结构的全面认知。