Characterizing the movement patterns of animals is crucial to improve our understanding of their behavior and thus develop adequate conservation strategies. Such investigations, which could not have been implemented in practice only a few years ago, have been facilitated through the recent advances in tracking methods that enable researchers to study animal movement at an unprecedented spatio-temporal resolution. However, the identification and extraction of patterns from spatio-temporal trajectories is still a general problem that has relevance for many applications. Here, we rely on the concept of resting event networks to identify the presence of daily mobility patterns in animal spatio-temporal trajectories. We illustrate our approach by analyzing spatio-temporal trajectories of several fish species in a large hydropeaking river.

表征动物的运动方式对于增进我们对动物行为的了解并从而制定适当的保护策略至关重要。跟踪方法的最新进展为这种研究提供了便利，这些研究以前仅在几年前才在实践中进行，这使研究人员能够以空前的时空分辨率研究动物运动。然而，从时空轨迹识别和提取模式仍然是一个普遍的问题，与许多应用相关。在这里，我们依靠休息事件网络的概念来识别动物时空轨迹中日常活动模式的存在。我们通过分析一条大水峰河中几种鱼类的时空轨迹来说明我们的方法。