Data from: Direction matching for sparse movement data sets: determining interaction rules in social groups

It is generally assumed that high-resolution movement data are needed to
extract meaningful decision-making patterns of animals on the move. Here
we propose a modified version of force matching (referred to here as
direction matching), whereby sparse movement data (i.e., collected over
minutes instead of seconds) can be used to test hypothesized forces acting
on a focal animal based on their ability to explain observed movement. We
first test the direction matching approach using simulated data from an
agent-based model, and then go on to apply it to a sparse movement data
set collected on a troop of baboons in the DeHoop Nature Reserve, South
Africa. We use the baboon data set to test the hypothesis that an
individual’s motion is influenced by the group as a whole or,
alternatively, whether it is influenced by the location of specific
individuals within the group. Our data provide support for both
hypotheses, with stronger support for the latter. The focal animal showed
consistent patterns of movement toward particular individuals when
distance from these individuals increased beyond 5.6 m. Although the focal
animal was also sensitive to the group movement on those occasions when
the group as a whole was highly clustered, these conditions of isolation
occurred infrequently. We suggest that specific social interactions may
thus drive overall group cohesion. The results of the direction matching
approach suggest that relatively sparse data, with low technical and
economic costs, can be used to test between hypotheses on the factors
driving movement decisions.