Variability and Uncertainty in the Reproductive Games of Cooperative Breeders - Psychology - NERC GW4+ DTP PhD studentship Ref: 2785

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: Dr Andrew Higginson, NERC Fellow, Psychology, Exeter
Co-Supervisor: Prof. Andy Radford, Biological Sciences, Bristol

Location: Streatham Campus, Exeter

Project description:

Our aim is to understand the reproductive behavior of animals of species in which offspring stay and help their parents raise siblings. Many species of mammals and birds do this, along with many insects, especially bees, ants and wasps. There is much variation in behaviour between and within species that is currently poorly understood. Life-history theory predicts how individual variation and environmental differences affect reproductive decisions such as age at maturity, fecundity and longevity. However, this theory does not apply to cooperative breeders because it ignores conflict over reproduction within groups. This gap is highly problematic because cooperative breeders and eusocial species often play critical roles in ecosystems (e.g. pollination, seed dispersal, crop herbivory, pest predation). This is impeding our ability to predict how organisms respond to changing environments, and their interactions with other species. This knowledge is imperative for securing the future of our natural resources.


Image 1: Meerkats are a classic example of mammalian cooperative breeders. Image 2: Social groups face competition from other groups, which will influence their reproduction, such as whether reproductives (purple circles) try to found other groups alone, in pairs, or with workers (yellow circles).

Project Aims and Methods

We will combine computational models with comparative analyses using existing data on many species. We will focus on three types of variation that have been neglected: differences between individuals in relatedness, size, etc.; variation over time and space of food and nest site availability; varying competition among groups.

In three theoretical studies, we will assess the influence of variation on within-group conflict to (1) consider how the possibility of becoming the dominant affects what subordinates might do; (2) ask why a reproductive would join with another or attempt to take-over a nest when the availability of nest sites varies over space or time; (3) predict what happens when dominant individuals can allow other individuals to reproduce in exchange for help, under competition from other groups.

We will test our predictions across species using meta-analysis that control for evolutionary history. We will exploit the vast amount of data on reproductive strategies and the characteristics of societies and ecology in cooperative breeders, from ants to meerkats.

We will predict how cooperatively breeding species might be affected by environmental changes, including nest-site availability and alterations to climate. By simulating different species, we can identify which species are most likely to need conserving.


The most suitable candidate would be a maths/physics/computer science graduate wanting to work in biology. This fits RCUK’s push to increase quantitative skills in the life sciences. The necessary skills could be learnt by a numerate biological graduate, with guidance from the supervisors.


- Concepts for understanding behaviour, especially game theory, which is the foundation of our understanding of social interactions but also used in economics and politics.
- Mathematical and computational approaches to understanding behaviour, using calculus and programming in Matlab, R, or C++, which are all widely used within and without academia.
- Dynamic programming approaches to understanding state-dependent behaviour, which was pioneered at Bristol by collaborators of both supervisors. 
- Advanced statistical techniques for comparative analysis: phylogenetically controlled analyses with R statistical packages. Higginson has published comparative analyses, and Radford is doing them as part of his ERC Consolidator grant.


Daly D, Higginson AD, Dong C, Ruxton GD, Speed MP (2012) Density-dependent investment in costly antipredator defences: An explanation for the weak survival benefit of group living. Ecol Lett 15: 576–583.

Feró O, Stephens PA, Barta Z, McNamara JM, Houston AI (2008). Optimal annual routines: New tools for conservation biology? Ecol Appl 18: 1563–1577.

Hawn, AT, Radford AN, Du Plessis MA (2007) Delayed breeding affects lifetime reproductive success differently in male and female green woodhoopoes. Curr Biol 17: 844–849.

Higginson AD, de Wert L, Rowland HM, Ruxton GD, Speed MP (2012) Masquerade is associated with polyphagy and larval overwintering in the Lepidoptera. Biol J Linn Soc 106: 90–103.

Higginson AD (2017) Conflict over previously abundant resources may explain between-species differences in declines: The anthropogenic competition hypothesis. Behav Ecol Sociobiol 71: 99.

Ito K, McNamara, JM, Yamauchi A, Higginson AD (2017) The evolution of cooperation by negotiation in noisy world. J Evol Biol 30: 603–615

Leadbeater E, Carruthers JM, Green JP, Rosser NS, Field J (2011). Nest inheritance is the missing source of direct fitness in a primitively eusocial insect. Science 333: 874–876.

McNamara JM (2013). Towards a richer evolutionary game theory. J R Soc Inter 10 20130544.

Radford AN, Majolo B, Aureli F (2016) Within-group behavioural consequences of between-group conflict: a prospective review. Proc R Soc Lond B 283: 20161567.

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.