Host dispersal, individual variation and spatial heterogeneity in avian malaria

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Understanding how individuals vary is particularly important in evolutionary ecology, as this allows us to understand how individuals might respond to their environment. Parasites make up the majority of species, so investigating the interactions between hosts and parasites is an important part of understanding wild populations. Despite this, few such studies have been undertaken at a large enough scale to improve our knowledge of host-parasite interactions in the wild. Host infection with parasites varies markedly in space, even at a local scale in the case of avian malaria in our tit population. Hosts take their parasites with them wherever they go, so the dispersal of hosts is an important factor in understanding the spatial heterogeneity of disease. The risk of parasite infection in wild populations varies in space, often due to variation in the abundance of infectious stages of the parasite. This can be due to variation in environmental conditions such as temperature and humidity, or inherent spatial processes such as disease clustering. Does a site have a high level of disease infection due to the local environment, or because infected individuals have moved there? The proposed project will study a long term population of great tits and blue tits at Wytham Woods, near Oxford. Avian malaria is transmitted by mosquitoes, and infects 30% of breeding blue tits at Wytham. Our large nestbox population means that most breeding birds are individually ringed as chicks so we can track their movements; we can sample around 500 adults of both blue tits and great tits over a useful geographical scale to examine the influence of local environment and host dispersal on the distribution of avian malaria infection. Recent statistical models to predict the distribution and spread of disease that take account of this spatial dimension provide an increasingly good fit to the patterns seen in real life epidemics, such as the 2001 foot and mouth epidemic. Interestingly, the avian malaria parasites in our study population fall into two species groups that each has a different spatial distribution. Developments in the use of DNA-based malaria diagnosis, the use of Geographical Information Sytems to accurately map spatial locations and environmental measurements of habitat variation using satellite imagery and microclimate using miniature data loggers mean that we can confidently approach what were, until recently, logistically daunting questions in ecology. We have three objectives: 1. To understand the causes of individual variation in infection with avian malaria. To what extent is infection determined by natal conditions, maternal status, age or inherited factors? We will use a combination of existing long-term data on avian malaria in tits complemented by data collected during this project, and a large scale field experiment to switch clutches of eggs between nests. 2. To determine the extent to which the observed spatial distribution of the two malaria species results from host-driven processes, particularly host dispersal. We will examine the spatial characteristics of avian malaria infection between classes of birds with different dispersal, both residents and immigrants to the population, and conduct an experiment to manipulate dispersal by moving birds between woodlands. 3. Finally, we will employ a mathematical modelling approach to examine the relative roles if host dispersal, maternal immunity and the risk of malaria infection in generating the spatial patterns of disease we see in our study population. These models will concentrate on the important effects identified by our preceding work, generating new testable hypotheses and leading to further empirical and modelling work. These three approaches are made possible by the large and well studied population of tits, and will address the fundamental ecology of avian malaria in a wild bird population, while increasing our wider understanding of disease.