Badger social networks and their implications for disease transmission

Abstract

Diseases that infect wildlife populations pose a significant threat to public health, agriculture, and conservation efforts. The spread of these diseases can be influenced by the social structure of the population, and therefore often need to be accounted for in disease models. In this thesis I use high-resolution contact data to explore the social structure of a high-density population of European badgers (Meles meles). I explore how this structure might influence the spread of bovine tuberculosis (bTB), a debilitating disease of cattle for which badgers are a wildlife reservoir. Denning and home range data collected using radio tracking is also used to determine how this social structure is related to badger space use. I use social network analysis to identify the community structure of the badger population, revealing that badgers interact in fewer, more distinct groups than previously assumed. This is likely to inhibit the spread of disease through the population, given that the probability of infection entering a new social group will be reduced. However, among-group contact is still found to occur even between the most isolated groups. I show that this among-group contact is more likely to occur between less related individuals, possibly suggesting that breeding behaviour may drive among-group contact as a mechanism for inbreeding avoidance. To gain additional insight into this among-group contact, I determine how badger spatial behaviours are related. I show that the use of dens (setts) away from the social group’s main sett (outlier setts) in the spring is associated with extra-territorial ranging. I also show that this extra-territorial ranging is associated with more central network positions. The seasonality of this behaviour further suggests that this may be related to breeding activity. These findings suggest that behaviours associated with extra-group ranging may increase the risk of acquiring and transmitting infection. Therefore, use of outlier setts in the spring could act as a spatial proxy to identify high-risk individuals for disease spread, offering potential targets for disease control. Finally, I discuss the implications of these findings in regard to what they reveal about badger behaviour, disease transmission, and the design of effective disease control strategies. The importance of understanding population social structure for the study of wildlife disease in general is also discussed.