A simulation-based framework to detect marine animal-vessel interactions using tracking data

Understanding how animals respond to vessels is a fundamental question in conservation, since interactions between marine animals and vessels can expose wildlife to threats such as fisheries bycatch and vessel collisions. Although animal-borne tags and vessel-tracking systems now allow both components to be monitored at fine spatiotemporal scales, distinguishing behavioural interactions from incidental co-occurrence remains challenging, particularly in areas of dense marine traffic. Here, we developed a simulation-based framework to determine whether an animal is attracted to or follows a vessel, or instead moves independently. We applied the framework to concurrent GPS data from 2,705 foraging trips by Scopolis shearwaters (Calonectris diomedea) and Automatic Identification System (AIS) trajectories from fishing and nonfishing vessels in the northwestern Mediterranean. Candidate association events (n = 1,567) were first identified using spatiotemporal proximity and subsequently tested against simulated seabird trajectories representing movement in the absence of a vessel response. The framework classified apparent associations arising when vessels approached stationary birds or when independently moving trajectories crossed by chance as independent movement. Overall, 53.5% of association events showed evidence of vessel attraction, following, or both, whereas the remainder were consistent with independent movement. Although only approximately 3% of the vessels recorded by AIS were fishing vessels, they accounted for 69% of attraction events and 74% of following events, whereas most associations with nonfishing vessels were consistent with incidental proximity. Attraction and following became less likely as birds spent more time stationary and were more likely during daytime, while following was less likely for nonfishing than fishing vessels. These ecologically coherent patterns support the biological relevance of the interactions identified by the simulation-based approach. Sensitivity analyses showed that the number of associations detected by conventional threshold methods increased markedly with broader proximity criteria, whereas inference of attraction and, particularly, following remained comparatively stable. Implemented in the R package intersimR, the framework provides an accessible, reproducible, and scalable approach for separating behavioural responses from incidental co-occurrence at the event level and identifying the animal-vessel interactions most relevant to conservation and management.