Princeton University Library Catalog

Horsing Around: Quantifying the Resilience of the Social Networks of Equus caballus

Author/​Artist:
Zhao, Jennifer [Browse]
Format:
Senior thesis
Language:
English
Advisor(s):
Rubenstein, Daniel [Browse]
Department:
Princeton University. Department of Ecology and Evolutionary Biology [Browse]
Class year:
2016
Description:
71 pages
Summary note:
My thesis investigates the effects of perturbations, specifically the removal and reintroduction of individuals, on the resilience of the social networks of domestic horses. Resilience, the capacity to respond to new pressures, is important in understanding the mechanisms behind how animal societies respond to the challenge of changes in environment, interspecies contact, and human interaction. I conducted six perturbation experiments. In each experiment I collected baseline data for two days, removed an individual, collected removal data for three days, reintroduced the same individual, and collected reintroduction data for two days. I determined how domestic horses responded to the removal and reintroduction of individuals varying in prosocial and aggressive tendencies. In this study, I used social network analysis to visualize interaction patterns with proximity and aggression networks, and the consequent resilience of the social structure of horses. I apply a novel application of GPS trackers to facilitate data collection on proximity networks. I determined that when removing individuals of higher centrality, the association network patterns change significantly. Likewise, the removal of a highly ranked individual has a greater effect on the aggression network. Dominant horses show more of an increase in outward aggression than expected, perhaps to fight for their original rank upon reintroduction. These findings show that removal of low centrality and low ranking horses will impact the resilience of the network less. The implications of my research span many scales of interest. On the local scale, herd managers should avoid removing horses of high centrality or high rank. On a larger scale, a better understanding of the resilience of horse networks allows for extension to modeling disease spread in these networks. Finally, conservation researchers should carefully teach individuals bred in captivity the proper reactions to aggression before reintroducing them, to minimize the effect on the resilience of the wild population.