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The monitoring of animal movement patterns provides insights into animalsdecision-making behaviour. It is generally assumed that high-resolution dataare needed to extract meaningful behavioural patterns, which potentially limitsthe application of this approach. Obtaining high-resolution movement datacontinues to be an economic and technical challenge, particularly for animalsthat live in social groups. Here, we test whether accurate movement behaviourcan be extracted from data that possesses increasingly lower temporalresolution. To do so, we use a modified version of force matching, in whichsimulated forces acting on a focal animal are compared to observed movementdata. We show that useful information can be extracted from sparse data. Weapply this approach to a sparse movement dataset collected on the adult membersof a troop of baboons in the DeHoop Nature Reserve, South Africa. We use thesedata to test the hypothesis that individuals are sensitive to isolation fromthe group as a whole or, alternatively, whether they are sensitive to thelocation of specific individuals within the group. Using data from a focalanimal, our data provide support for both hypothesis, with stronger support forthe latter. Although the focal animal was found to be sensitive to the group,this occurred only on a small number of occasions when the group as a whole washighly clustered as a single entity away from the focal animal. We suggest thatspecific social interactions may thus drive overall group cohesion. Given thatsparse movement data is informative about individual movement behaviour, wesuggest that both high (~seconds) and relatively low (~minutes) resolutiondatasets are valuable for the study of how individuals react to and manipulatetheir local social and ecological environments.

Sparse movement data can reveal social influences on individual travel decisions