Abstract

Understanding disease dynamics in animal hosts is fundamental to understanding the emergence of zoonotic infections and to developing pest management strategies based on the use of natural enemies. One research question I examined recently is whether natural selection plays a role in driving insect host–¬pathogen population dynamics. Another question was whether we can identify mechanisms of transmission and risks of disease spillover to humans through correlations between biotic and abiotic conditions and disease prevalence in animals such as the Australian fruit bat. For the first question, I conducted research on the gypsy moth, host to a baculovirus. Field experiments showed that reduced risk of infection in gypsy moth is heritable but costly, confirming two key assumptions of eco-evolutionary host–pathogen models.Furthermore, when using these estimated parameters, model predictions showed population cycles that closely resembled gypsy moth outbreaks in North America. The intense selection imposed by natural enemies on many defoliating insects, including the gypsy moth, suggests that eco-evolutionary theory more effectively explains gypsy moth population cycles than does traditional ecological theory. This work therefore contributed crucial evidence that eco-evolutionary dynamics occur in nature, with important implications for insect pest management. For the second question, I conducted research on the Australian fruit bat and Hendra virus. The virus is a pathogen endemic to bats, but can also spillover to horses and humans. I examined how the prevalence of the Hendra virus varies in space and time. I also assessed the effects of bat abundance, and temperature and precipitation on pulses of Hendra virus prevalence. Evidence suggested that pulses cluster around winter months, except in the central latitudes of eastern Australia where these pulses occur earlier and more strongly. Larger pulses were associated with increased bat abundance and reduced rainfall in previous seasons¬. The results suggested complex interactions between bat density, climatic factors, and Hendra virus prevalence. I will therefore discuss the modeling approaches taken to understand these dynamics