  Group dynamic movement is a fundamental aspect of many species' movements.
The need to adequately model individuals' interactions with other group members
has been recognised, particularly in order to differentiate the role of social
forces in individual movement from environmental factors. However, to date,
practical statistical methods which can include group dynamics in animal
movement models have been lacking. We consider a flexible modelling framework
that distinguishes a group-level model, describing the movement of the group's
centre, and an individual-level model, such that each individual makes its
movement decisions relative to the group centroid. The basic idea is framed
within the flexible class of hidden Markov models, extending previous work on
modelling animal movement by means of multi-state random walks. While in
simulation experiments parameter estimators exhibit some bias in non-ideal
scenarios, we show that generally the estimation of models of this type is both
feasible and ecologically informative. We illustrate the approach using real
movement data from 11 reindeer (Rangifer tarandus). Results indicate a
directional bias towards a group centroid for reindeer in an encamped state.
Though the attraction to the group centroid is relatively weak, our model
successfully captures group-influenced movement dynamics. Specifically, as
compared to a regular mixture of correlated random walks, the group dynamic
model more accurately predicts the non-diffusive behaviour of a cohesive mobile
group.
