Modelling evolution of host defence in seasonal environments.

Infectious disease is rife throughout the world, with species at risk of infection at every level, from bacteria to humans. These diseases can have devastating effects on populations, which has led to a rich biological and mathematical literature on this topic. There are many factors that can affect the spread and impact of an infectious disease, including environmental heterogeneity and host-parasite evolution. The combination of infection dynamics, heterogeneous environments and evolution could provide powerful insights into real-world systems; however, this has yet to be explored in much detail with regards to temporally heterogeneous environments. In this thesis I use mathematical models and experimental techniques to investigate the effect of temporally fluctuating environments on host-parasite evolution. Throughout the mathematical analysis, I use the adaptive dynamics framework to study evolution, and implement temporal heterogeneity through a periodic host birth rate. First, I consider host-only evolution through avoidance, and consider how increasingly variable environments affects the end-point of evolution. Second, I investigate the potential for host diversity through three different defence mechanisms in a seasonal environment, with a particular focus on evolution through mortality tolerance. I then conduct an experimental evolution study using the bacteria P. fluorescens SBW25 and its parasitic bacteriophage SBW25Φ2, where environmental heterogeneity is implemented through oscillating nutrient concentrations. The results from the experiment are reinforced by a coevolutionary model, which incorporates seasonality through evidence-based assumptions on the bacterial growth. The work in this thesis is part of a growing field of research investigating temporal environments and evolution in host-parasite systems. It contributes some important results to the field, and demonstrates the power of developing experimental and theoretical work together, which can result in a more cohesive understanding of host-parasite evolution.