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Cunniffe Group: Tainted Love? Modelling the epidemiology, ecology and evolutionary consequences of pollinator-transmitted plant disease


Supervisor: Nik Cunniffe (Plant Sciences)


A number of plant diseases can be transmitted by pollinators. However pollinator service is typically also required for plants to reproduce: attractiveness to pollinators promotes reproduction, but also brings plants into contact with disease. The implications of this epidemiological-ecological dynamic are not well understood. How flower attractiveness might respond to these contrasting pressures when there is pollinator-transmitted disease is not understood. Doing so requires techniques and insights from plant epidemiology, pollinator behavioural ecology, plant population dynamics and population genetics. In this project we will link these diverse areas via a mathematical modelling approach.

The student will develop a mathematical models of the interaction between plant and pollinator populations over a single season, coupling transmission of disease to pollinator service. This model will be scaled-up to run over many seasons, and to represent population genetics, including plant genes that make flowers more or less attractive to pollinators in the model. Mathematical analysis and numerical simulation will be performed. Models will be rendered stochastic, to allow for natural variability, and by scaling-up to a metapopulation, will allow for spatial spread of disease, pollinators and plant genotypes. Where appropriate empirical data from existing studies will be used to parameterise and test the models. The framework of adaptive dynamics offers the possibility of understanding whether the plant population-or indeed the pollinator or pathogen populations-will branch into different species, allowing long-term population trajectories over evolutionary time to be predicted.


The student would learn i) mapping a complex biological system to a parsimonious mathematical model; ii) modern methods for simulating epidemiological models; iii) evolutionary analysis; iv) experience of applying mathematics to a biological system.
The project would best suit a student with from a background in mathematics, engineering, physics or ecology, ideally with some knowledge of computer programming. However, students with a wet-lab background have enjoyed and been successful in my laboratory in the past.


  • Groen, S.C., Jiang, S., Murphy, A.M., Cunniffe, N.J., Westwood, J.H., Davey, M.P., Bruce, T.J.A., Caulfield, J.C., Furzer, O.J., Reed, A., Robinson, S.I., Miller, E., Davis, C.N., Pickett, J.A., Whitney, H.M., Glover, B.J. and Carr, J.P. Virus infection of plants alters pollinator preference: a payback mechanism for susceptible hosts? PLoS Pathogens. 12:e1005906.
  • Antonovics, J. 2005. Plant venereal diseases: insights from a messy metaphor. New Phytologist. Vol. 165, pp 71-80.

Apply to: The NERC DTP programme


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