Nongenetic Effects, Adaptation and Extinction in a Changing World: Towards a Predictive Theory - Mathematics - NERC GW4+ DTP PhD studentship Ref: 2797

About the award

This project is one of a number that are in competition for funding from the NERC Great Western Four+ Doctoral Training Partnership (GW4+ DTP).  The GW4+ DTP consists of the Great Western Four alliance of the University of Bath, University of Bristol, Cardiff University and the University of Exeter plus six Research Organisation partners:  British Antarctic Survey, British Geological Survey, Centre for Ecology and Hydrology, the Met Office, the Natural History Museum and Plymouth Marine Laboratory.  The partnership aims to provide a broad training in earth and environmental sciences, designed to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see

The studentships will provide funding for a stipend which is currently £14,553 per annum for 2017-2018, research costs and UK/EU tuition fees at Research Council UK rates for 42 months (3.5 years) for full-time students, pro rata for part-time students.


Main Supervisor: Prof Stuart B Townley, Mathematics, Environment and Sustainability Institute, University of Exeter
Co-Supervisor: Dr Sinead English, School of Biological Sciences, University of Bristol
Co-Supervisor: Dr Bram Kuijper, Environment and Sustainability Institute, University of Exeter

Location: Penryn Campus, Cornwall

Project description:

There is growing interest in nongenetic effects (NGEs), where parents influence offspring phenotypes through the transmission of factors other than DNA, such as chromatin modifications, small RNAs or maternal hormones. While interest in NGEs has focused on their role in extended inheritance1,2, their consequences on population dynamics remain contested3,4. Some studies predict that NGEs facilitate rapid adaptation5, by allowing parents to inform young about environmental change6. In contrast, others argue that NGEs enhance extinction rates, as selection carries over to future generations7, resulting in dramatic fluctuations in population size8. To resolve this controversy, the current project aims to use an interdisciplinary approach. First, we will derive novel eco-evolutionary models that add the evolutionary dynamic of nongenetic effects9,10 to influential models of ecological competition and predator-prey interactions. Second, we will use ecological experiments in the tsetse fly model system (UBristol) to assess when and where nongenetic effects result in population extinction.

Project Aims and Methods

While NGEs affect suites of ecologically important traits5,11,12, we lack quantitative tools to  predict
when NGEs influence extinction risk. This project fills the gap by using an exciting mix of mathematical modeling and ecological experiments in the tsetse fly system, an important disease vector. We aim to (1) build much-needed ecological theory which includes evolving NGEs, (2) assess how NGEs affect transient responses to ecological perturbations, (3) measure population dynamics of experimental populations with different levels of NGEs and (4) asses how robust these populations are to sudden perturbations. In years 1-2, the student will use expertise at UExeter9,10,13,14 to derive eco-evolutionary models where evolving nongenetic effects influence key ecological processes like intraspecific competition15 and transient dynamics16. These models will be novel in allowing NGEs to evolve: the few population dynamic models including NGEs assume them to be constant8,17,18. In years 3-3.5, the student will work at UBristol19–23 to test predictions in tsetse fly populations, which exhibit strong maternal effects that vary with maternal condition22. Consequently, by manipulating maternal environment, the strength of NGEs can be varied, giving us a powerful tool to investigate consequences on population dynamics and their role in transient responses to sudden environmental shocks.


Due to the interdisciplinary nature of the project, it is suitable for candidates with a strong experimental background who are looking to grow their analytical skills (mathematics, programming). Additionally, also candidates with a more analytical background fit our profile, particularly if they have an interest in expanding their experimental skills.


During the first 2 years at UExeter, the student will tap into a wealth of postgraduate courses delivered at UExeter’s Penryn campus. The student will take part in a course on Mathematics in Biology and Ecology, which focuses on eco-evolutionary models and computer programming techniques in R and Matlab. In addition, the student will receive regular mentoring on dynamical systems theory, project and data management and analysis on high performance computers.
During the final 1.5 years at UBristol, the student will receive training on data analysis (GLMMs, Bayesian methods), lab techniques (animal husbandry, physiological assays), writing skills and dynamic programming.


1. Danchin É, Charmantier A, Champagne FA, Mesoudi A, Pujol B, Blanchet S. Beyond DNA: integrating inclusive inheritance into an extended theory of evolution. Nat Rev Genet. 2011;12(7):475-486. doi:10.1038/nrg3028.

2. Daxinger L, Whitelaw E. Understanding transgenerational epigenetic inheritance via the gametes in mammals. Nat Rev Genet. 2012;13(3):153-162. doi:10.1038/nrg3188.

3. Bossdorf O, Richards CL, Pigliucci M. Epigenetics for ecologists. Ecol Lett. 2008;11(2):106-115. doi:10.1111/j.1461- 0248.2007.01130.x.

4. Verhoeven KJF, vonHoldt BM, Sork VL. Epigenetics in ecology and evolution: what we know and what we need to know. Mol Ecol. 2016;25(8):1631-1638. doi:10.1111/mec.13617.

5. Salinas S, Munch SB. Thermal legacies: transgenerational effects of temperature on growth in a vertebrate: Thermal transgenerational plasticity. Ecol Lett. 2012;15(2):159-163. doi:10.1111/j.1461-0248.2011.01721.x.

6. Bonduriansky R, Crean AJ, Day T. The implications of nongenetic inheritance for evolution in changing environments. Evol Appl. 2011;5:192-201. doi:10.1111/j.1752-4571.2011.00213.x.

7. Räsänen K, Kruuk LEB. Maternal effects and evolution at ecological time-scales. Funct Ecol. 2007;21(3):408-421. doi:10.1111/j.1365-2435.2007.01246.x.

8. Benton TG, Ranta E, Kaitala V, Beckerman AP. Maternal effects and the stability of population dynamics in noisy environments. J Anim Ecol. 2001;70(4):590-599. doi:10.1046/j.1365-2656.2001.00527.x.

9. Townley S, Ezard THG. A G matrix analogue to capture the cumulative effects of nongenetic inheritance. J Evol Biol. 2013;6:1234-1243. doi:10.1111/jeb.12089.

10. Kuijper B, Johnstone RA, Townley S. The evolution of multivariate maternal effects. PLoS Comput Biol. 2014;10(4):e1003550. doi:10.1371/journal.pcbi.1003550.

11. Donelson JM, Munday PL, McCormick MI, Pitcher CR. Rapid transgenerational acclimation of a tropical reef fish to climate change. Nat Clim Change. 2012;2(1):30-32.

12. Allan BJM, Miller GM, McCormick MI, Domenici P, Munday PL. Parental effects improve escape performance of juvenile reef fish in a high-CO2 world. Proc R Soc Lond B Biol Sci. 2014;281(1777). doi:10.1098/rspb.2013.2179.

13. Kuijper B, Hoyle RB. When to rely on maternal effects and when on phenotypic plasticity? Evolution. 2015;69:950-968. doi:10.1111/evo.12635.

14. Kuijper B, Johnstone RA. Parental effects and the evolution of phenotypic memory. J Evol Biol. 2016;29:265-276. doi:10.1111/jeb.12778.

15. Hart SP, Schreiber SJ, Levine JM. How variation between individuals affects species coexistence. Coulson T, ed. Ecol Lett. 2016;19(8):825-838. doi:10.1111/ele.12618.

16. Stott I, Townley S, Hodgson DJ. A framework for studying transient dynamics of population projection matrix models. Ecol Lett. 2011;14(9):959-970.

17. Inchausti P, Ginzburg LR. Maternal effects mechanism of population cycling: a formidable competitor to the traditional predator-prey view. Philos Trans R Soc Lond B Biol Sci. 2009;364(1520):1117-1124. doi:10.1098/rstb.2008.0292.

18. Garbutt JS, Little TJ, Hoyle A. Maternal effects on offspring consumption can stabilize fluctuating predator-prey systems.
Proc R Soc Lond B Biol Sci. 2015;282(1820):20152173. doi:10.1098/rspb.2015.2173.

19. English S, Pen I, Shea N, Uller T. The information value of non-genetic inheritance in plants and animals. PLoS ONE. 2015;10(1):e0116996. doi:10.1371/journal.pone.0116996.

20. English S, Cowen H, Garnett E, Hargrove JW. Maternal effects on offspring size in a natural population of the viviparous tsetse fly. Ecol Entomol. 2016;41(5):618-626. doi:10.1111/een.12333.

21. English S, Uller T. Does early-life diet affect longevity? A meta-analysis across experimental studies. Biol Lett. 2016;12(9):20160291. doi:10.1098/rsbl.2016.0291.

Entry requirements:         

Applicants should have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK.   Applicants with a Lower Second Class degree will be considered if they also have Master’s degree.  Applicants with a minimum of Upper Second Class degree and significant relevant non-academic experience are encouraged to apply. 

All applicants would need to meet our English language requirements by the start of the  project

Applicants who are classed as International for tuition fee purposes are not eligible for funding.


Application deadline:7th January 2018
Value:£14,553 per annum for 2017-18
Duration of award:per year
Contact: PGR Recruitment

How to apply

In the application process you will be asked to upload several documents.  Please note our preferred format is PDF, each file named with your surname and the name of the document, eg. “Smith – CV.pdf”, “Smith – Cover Letter.pdf”, “Smith – Transcript.pdf”.

•       CV
•       Letter of application outlining your academic interests, prior research experience and reasons for wishing to
        undertake the project.
•       Transcript(s) giving full details of subjects studied and grades/marks obtained.  This should be an interim transcript
        if you are still studying.
•       If you are not a national of a majority English-speaking country you will need to submit evidence of your current
        proficiency in English. 

You will be asked to name 2 referees as part of the application process however we will not contact these people until the shortlisting stage. Your referees should not be from the prospective supervisory team.

The closing date for applications is midnight on 7 January 2018.  Interviews will be held at the University of Exeter between 5 - 16 February 2018.

If you have any general enquiries about the application process please email  Project-specific queries should be directed to the supervisor.

During the application process, the University may need to make certain disclosures of your personal data to third parties to be able to administer your application, carry out interviews and select candidates.  These are not limited to, but may include disclosures to:

• the selection panel and/or management board or equivalent of the relevant programme, which is likely to include staff from one or more other HEIs;

• administrative staff at one or more other HEIs participating in the relevant programme.

Such disclosures will always be kept to the minimum amount of personal data required for the specific purpose. Your sensitive personal data (relating to disability and race/ethnicity) will not be disclosed without your explicit consent.