Inferring follower-followee relations from presence data: manta ray case study.

Social interactions are ubiquitous in groups of animals, although for some species these interactions might be difficult to observe or quantify. These interactions might be of different nature, e.g., competitive, mutualistic, parasitic, commensalistic, kinship, etc; and their global structure is naturally studied with the tools of complex network theory. One typical interaction is that of leading/following. Here we propose a method to extract follower-followee networks from presence data at a certain location. The method is based on the Kolmogorov-Smirnov distance between the distribution of waiting times between the consecutive presence of an individual i followed by the presence of j in the vicinity of a particular location and its conjugate distribution, i.e., j’s presence followed by i’s. We test the measure using controlled synthetic data based on Hawkes processes. As a case study we apply the method to an acoustic data set of manta rays. We first investigate the temporal heterogeneities of the presence of manta rays from the data of events at which mantas are recorded at a certain acoustic receiver. Next we construct the follower-followee network of manta-rays and characterize mantas in terms of their position on this network, paying attention to sex and size.