Data from: Distinguishing social from nonsocial navigation in moving animal groups

Many animals, such as migrating shoals of fish, navigate in groups. Knowing the mechanisms involved in animal navigation is important when it comes to explaining navigation accuracy, dispersal patterns, population and evolutionary dynamics and consequently the design of conservation strategies. When navigating towards a common target, animals could interact socially by sharing available information directly or indirectly, or each individual could navigate by itself and aggregations may not disperse because all animals are moving towards the same target. Here, we present an analysis technique that uses individual movement trajectories to determine the extent to which individuals in navigating groups interact socially, given knowledge of their target. The basic idea of our approach is that the movement direction of individuals arises from a combination of responses to the environment and to other individuals. We estimate the relative importance of these responses, distinguishing between social and non-social interactions. We develop and test our method using simulated groups and demonstrate its applicability to empirical data in a case study on groups of guppies moving towards shelter in a tank. Our approach is generic and can be extended to different scenarios of animal group movement.

诸多动物（例如洄游鱼群）会以群体形式开展导航活动。明晰动物导航所涉及的内在机制，对于阐释导航精度、扩散模式、种群与演化动态，进而制定保护策略均具有重要意义。当群体朝着共同目标导航时，动物既可以通过直接或间接共享可用信息开展社会互动，也可各自独立导航——由于所有个体均朝向同一目标移动，群体聚合体不会发生分散。本研究提出一种分析技术，该方法可利用个体运动轨迹，在已知导航目标信息的前提下，判断群体导航过程中个体间社会互动的程度。本方法的核心逻辑在于，个体的运动方向源于对环境与其他个体的响应的综合作用。我们可通过该方法估算两类响应的相对重要性，并区分社会互动与非社会互动。本研究通过模拟群体对所提方法进行开发与验证，并以水箱中朝向遮蔽处移动的孔雀鱼群体为案例，验证了该方法对实证数据的适用性。本方法具有通用性，可推广至动物群体运动的各类场景中。