Data from: Using network analysis to study behavioural phenotypes: an example using domestic dogs

Phenotypic integration describes the complex interrelationships between organismal traits, traditionally focusing on morphology. Recently, research has sought to represent behavioural phenotypes as composed of quasi-independent latent traits. Concurrently, psychologists have opposed latent variable interpretations of human behaviour, proposing instead a network perspective envisaging interrelationships between behaviours as emerging from causal dependencies. Network analysis could also be applied to understand integrated behavioural phenotypes in animals. Here, we assimilate this cross-disciplinary progression of ideas by demonstrating the use of network analysis on survey data collected on behavioural and motivational characteristics of police patrol and detection dogs (Canis lupus familiaris). Networks of conditional independence relationships illustrated a number of functional connections between descriptors, which varied between dog types. The most central descriptors denoted desirable characteristics in both patrol and detection dog networks, with ‘Playful’ being widely correlated and possessing mediating relationships between descriptors. Bootstrap analyses revealed the stability of network results. We discuss the results in relation to previous research on dog personality, and benefits of using network analysis to study behavioural phenotypes. We conclude that a network perspective offers widespread opportunities for advancing the understanding of phenotypic integration in animal behaviour.表型整合（Phenotypic integration）指生物体各性状间的复杂相互关联，传统研究多聚焦于形态学维度。近年来，相关研究尝试将行为表型视为由准独立潜在性状构成的集合。与此同时，心理学研究者对人类行为的潜在变量解释提出质疑，转而提出网络视角：该视角将行为间的相互关联视为由因果依赖关系催生的产物。网络分析（Network analysis）亦可用于探究动物的整合行为表型。本研究吸纳这一跨学科的思想演进，通过对警用巡逻犬与搜毒犬（Canis lupus familiaris）的行为及动机特征调查数据开展网络分析，展示了该方法的应用路径。基于条件独立关系构建的网络展现出特征变量间的多种功能关联，且这类关联在两类犬只中存在差异。在两类犬只的网络中，中心性最高的特征变量均指向优良性状；其中“爱玩（Playful）”这一特征的关联范围最广，且在各特征变量间发挥中介作用。自助法（Bootstrap）分析验证了网络分析结果的稳定性。本研究结合过往犬只性格相关研究，探讨了运用网络分析探究行为表型的优势。最终我们得出结论：网络视角为深化动物行为领域的表型整合研究提供了广阔的发展空间。