Personal Statement
I am a theoretical ecologist (though I began my research career in theoretical physics), and I use mathematical models to understand how organisms interact with each other and with their environment. Biology has been described as a science of differences, and these differences manifest themselves at many levels: species use different strategies to survive, individuals of the same species can display a wide diversity of traits and life histories, and populations change over space and time. I am particularly interested in the ways that these different kinds of heterogeneity affect how species coexist, invade, and evolve. My research interests span conservation biology, evolutionary ecology, and epidemiology.

I teach ecology, statistics, and mathematical modelling. I welcome BSc, MSc, MRes, PhD students and postdoctoral fellows to my group to develop fundamental ecological theory, or to use models to address research questions in population biology from an individual-based perspective. Do email me if you are interested in developing a project.

I am the postgraduate research lead for the Department of Evolution, Ecology, and Behaviour. I am also the University of Liverpool's Academic Lead for the NERC Doctoral Training Partnership "Adapting to the challenges of a changing environment" (ACCE), which funds PhD studentships in the biological components of the natural environment.

Keywords: mathematical models, stochasticity, individual based models, spatial models, evolutionary ecology, epidemiology

Research Overview
Biology has been described as a science of differences, and these differences manifest themselves at many levels: species use different strategies to survive, individuals of the same species can display a wide diversity of traits and life histories, and populations change over space and time. I am particularly interested in the ways that these different kinds of heterogeneity affect how species coexist, invade, and evolve.

My principle research focus is on mathematical approaches that can take account of this heterogeneity without ending up with models that are hopelessly complicated. For example, to describe a population exactly one would have to know the characteristics of every individual in the system, but in many cases good approximations can be derived by describing the distribution of their attributes using a random process. For some years now I have been developing methods for quantifying the impact of spatial structure, stochasticity (noise), and other sorts of heterogeneity, which can be applied to the dynamics of a very wide range of systems of interacting populations.