Herding as an emergent behaviour in harem groups of feral Garrano ponies
David Demitri Africa1, Kazushi Ikeda2, Tamao Maeda3
1Natural Language and Information Processing Group, Computer Laboratory, University of Cambridge, Cambridge, UK.
Abstract:
Collective decision-making and movement coordination are essential behaviours observed in biological systems, from animal herds to human crowds. Horses are a highly social species with a multilevel society. Herding, where the harem is collected to move in a certain direction, is an often-cited example of agonistic behaviour in horses, yet poorly understood in a granular, quantitative sense. We use transfer entropy to measure herding in a harem group of feral Garrano ponies in Serra D'Arga, Portugal. First, we characterize the harem's leader-follower relationships by quantifying the time lag (average 1.44 s) and duration (average 1.72 s) of influence during herding, establishing variance across social characteristics. Second, we internally validate transfer entropy as a method to detect herding by comparing it with traditional clustering methods. To augment the paucity of existing data, synthetic data is generated from a mathematical model of feral horse harems, demonstrating superior accuracy (0.80) and F1-score (0.76) against traditional clustering and time-series synchrony methods. Third, we provide evidence for herding as an emergent behaviour: leadership influence often propagates indirectly among mares in short bursts of information flow before reaching the entire harem. These results enrich our understanding of horse behaviour and provide a foundation for using transfer entropy to study decision-making in other species.
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