skip to primary navigationskip to content

Tanentzap Group: Evolution on the wild side: the predictability of adaptation to global change


Supervisor: Andrew Tanentzap (Plant Sciences
Co-Supervisor: Luisa Orsini, University of Birmingham and Shelley Arnott, Queen's University

Importance of the area of research concerned:

Given the rapid rate at which humans are changing the environment, there is a pressing need to predict how the traits of wild populations are responding. Two major questions are whether adaptation is repeatable, and how its pace and magnitude vary in time and space. Yet these questions have rarely been addressed in nature because the temporal scale of natural selection was traditionally thought to operate over geological timescales. Emerging evidence is now challenging this idea (Geerts et al. 2015).

Project summary:

This project uses the natural archives of lakes as a "time machine" to track the repeatability and pace of evolution in time and space (Orsini et al. 2013). We will test for genetic adaptation in keystone Daphnia grazers in response to major environmental stressors, such as climate warming, "aquatic osteoporosis", and predator introductions. Many of these stressors have occurred repeatedly across replicate but disconnected lakes, offering a natural experiment with which to study the contemporary evolution of wild populations. The first part of this project will characterise the genetic structure of Daphnia before and after stressors in otherwise similar lakes. The second part will test how the pace and magnitude of evolution varies along environmental gradients. Genomic scans will identify regions under selection and overlap among loci will determine the repeatability of adaptation.

What will the student do?

The student will identify the study species and stressors. Using existing data on the environmental characteristics of the study lakes, they will choose the study sites and travel to Canada to collect sediment cores. The student will then dissect cores in the lab and extract resting eggs for sequencing alongside any relevant contemporary archived samples. In the first instance, the student will use established microsatellites to differentiate clones and then undertake new techniques in whole genome amplification and sequencing. The student will also be responsible for performing all the required bioinformatics and population genetic analyses.


  • Geerts A.N. et al. 2015. Rapid evolution of thermal tolerance in the water flea Daphnia. Nature Climate Change, vol. 5, pp.665–668. DOI 10.1038/nclimate2628
  • Orsini L. et al. 2013. The evolutionary time machine: using dormant propagules to forecast how populations can adapt to changing environments. Trends in Ecology & Evolution, vol. 28, pp.274–282. DOI 10.1016/j.tree.2013.01.009
  • Bosse M. et al. 2017. Recent natural selection causes adaptive evolution of an avian polygenic trait. Science, vol. 358, pp.365–368. DOI 10.1126/science.aal3298

Applying: To the NERC DTP programme:


The University has moved into its "red" phase in response to the coronavirus (COVID-19) outbreak. All University staff, except those needed for business-critical activity, are now working remotely. Please contact us by email until further notice.