Résumé
Animal movements are widely studied in ecology, and the analysis of tracking data usually gains from splitting the time-series into different parts before interpreting movement strategies. The recent increase in data accuracy and resolution allows for the study of fine-scale movements where each behavioral change is recorded. We propose a simple method to identify the elementary units of movement in a trajectory, resulting in breaks in the track corresponding to the animals' decisions to change its movement. We quantify the movement between successive steps with a vector of speed and direction and represent a movement path in a trigonometric circle space in order to visualize behavioral changes instead of spatial changes. In this space, the distance between successive points informs about their similarity in both speed and direction. We quantify the temporal changes in these distances with a cumulative sum and use a line simplification algorithm to identify breaks in the slope that correspond to breaks in the consistency of successive distance values. We test the algorithm on simulated trajectories and show that the expected number of segments is accurately identified. Moreover, we relate the resulting segmentation from recorded trajectories to events observed using animal-borne video footage and show that the presence of stimuli in the surroundings of the animal is associated with a higher frequency of changes in movement. As an applied example, we propose a descriptive analysis of the segments and show that segments of particular characteristics are not distributed equally along the trajectory, highlighting larger-scale behavioral strategies.