The importance of pests and diseases associated with forests has never been greater, with highly damaging outbreaks, evidence of greater spread and impact, new organisms being introduced, and established threats exacerbated by changes in climate and host availability. Dothistroma needle blight, a fungal disease of pine trees, is of particular economic importance in UK forestry. Alongside fieldwork and experiments, theoretical models can provide key insights into how infectious diseases, such as Dothistroma, spread, but the spatially-structured nature of forest ecosystems presents key modelling challenges.

In this project you will develop mathematical and computational models to understand the dynamics of infectious disease within forest ecosystems, focussed on Dothistroma needle blight. The challenge of the PhD project will be to include vital real-world details into your models, for example:

seasonality in both the disease and tree life-history traits, 
periodic disturbances such as wildfires, and different disease control strategies,
community structure.

You will work closely with your co-supervisor at Forest Research to embed key details of the disease and tree biology and potentially identify data to fit your models to. This is therefore an exciting opportunity for genuine interdisciplinary research.

Your primary research will involve developing systems of differential equations and stochastic simulation models of disease spread in spatially-structured populations. The project would therefore suit an applicant with a background in mathematics and/or computing; biologists with strong quantitative skills are also encouraged to apply. You will mostly be based in the School of Mathematics & Statistics at the University of Sheffield under the supervision of Dr Alex Best. During the project you will also undertake a 3-6 month placement at Forest Research with Dr Kath Tubby, providing you with an excellent career development opportunity, as well as the chance to develop your research under the supervision of the knowledgeable team at Forest Research.