Organisms adapt and adjust in time and space as the environment changes. The rate at which they can do this is critical given the dramatic changes in the environment and finding efficient ways to estimate this is a pressing challenge for evolutionary ecologists. If populations adapt or adjust too slow they will become extinct. This multidisciplinary project will use empirical data on the Common Frog, combined with mathematical and computational approaches, to measure how fast organisms can evolve to a changing environment. The project will integrate ecological citizen-science data (Nature’s Calendar) with genomic data and will provide the successful candidate with training in range of highly sought-after analytical and computational skills.
When the environment changes organisms can track these changes by evolving or responding plastically. The Common Frog experiences large changes in spring temperature across its UK range, and it responds to these changes by spawning at different times depending on location. Our previous work examined how spatial patterns in spawning times could be harnessed to estimate the relative contributions of plasticity and evolution. We found that geographic variation in spawning time is achieved through a mixture of plasticity and evolution (Phillimore et al 2010). In order to understand the consequences of this for future environmental change we now need to understand something about patterns of dispersal and how costly it is to spawn too early or too late.
Dispersal in most organisms is hard to measure due to a number of limitations with mark-recapture methods. In this project we will develop new techniques that employ genomic data to measure dispersal, that could be applied to many organisms. We will combine this information with recent theoretical developments (Hadfield 2016) that allow us to assess the impact of future environmental change on the mismatch of frogs to their environment.
Although we use frogs as a test case, we envisage this work and the tools that arise from it will inform research on many organisms. We also envisage that the successful candidate will develop the skills necessary for a successful for career in modern science.
If you wish to apply for this project, please go to this link.