Understanding Causal Effects of Perturbations on Social Systems to Allow Prediction of Natural Populations’ Responses to Change

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About the Project

Natural populations are often experience a variety of perturbations, ranging from extreme seasonal changes, weather events, disease outbreaks, or anthropogenic pressures. While much research has considered how these perturbations may influence the size and shape of a population (i.e. the demography), our understanding of the direct consequences of perturbations for the fine-scale structure of social connections between individuals (i.e. the social network) remains largely untested. Understanding – for instance – how individuals socially respond to the loss of their associates, the influx of new individuals, or changes in opportunities to interact with specific types of conspecifics, is challenging to examine. Further, the complexity of real-world social networks means that animal societies may react to perturbations in diverse ways, making it currently very challenging to predict outcomes.

This PhD project aims to establish a conceptual framework for predicting how perturbations might impact natural animal societies by using fine-scale, individual-level tracking data detailing social networks of wild populations experiencing rapid external changes. The research will adopt a two-pronged approach. Firstly, the project will use a wild bird population, great tits (Parus major), in Wytham Woods, Oxford, as a model experimental system for investigating the causal effects of perturbations. This population has been the subject of extensive research, with multiple experimental perturbations already conducted alongside continuous social network monitoring. By examining the outcome of these perturbations under a single framework, this research will aim to uncover how different perturbations causally affect social dynamics in natural settings, providing insights into the mechanisms that underpin social resilience and adaptability. Secondly, the project will draw upon a broader range of animal populations for which longitudinal social network tracking data are available during periods of population change. This will allow assessment of how natural, non-experimental perturbations -such as turnover of individuals – relates to changes in various social systems at a fundamental level. By comparing responses across diverse species and contexts, this project will examine whether any general rules govern how perturbations impact social networks in varied settings.

The aim of this project is to construct a framework and approach for elucidating the causal pathways linking perturbations to social network dynamics, and provide a foundation for allowing predictive realistic modeling of animal population responses under rapid externally-driven societal changes. By shedding new light on these relationships, the findings may contribute not only to behavioural ecology but also to interdisciplinary fields such as network science and sociology, highlighting the relevance of social dynamics in broader biological and ecological contexts. This project will primarily rely on previously collected datasets and experiments to address the above aims, through quantitative analysis and various computational approaches (for which training will be provided). Additionally, there is potential for further fieldwork to supplement existing datasets and explore new avenues of research if desired, both in experimental and observational studies. 

Eligibility

The minimum entry requirements for PhD study is a 2.1 honours degree, or equivalent, in a subject relating to your proposed area of research, or a good performance in a Masters level course in a relevant subject. A first class honours degree (or equivalent) is usually required to be competitive for scholarship funding and a Masters degree is also a valuable asset.

If English is not your first language, you’ll need to provide evidence of a language qualification. The minimum English language entry requirement for postgraduate research study in the Faculty of Biological Sciences is an IELTS of 6.0 overall with at least 5.5 in each component (reading, writing, listening and speaking) or equivalent. The test must be dated within two years of the start date of the course in order to be valid.

How to Apply

1) Complete the University of Leeds online application form

Select ‘NERC YES DTN Yorkshire Environmental Sciences’ as the Planned Course of Study.

The supporting documents needed to process your application are:

  • certificates and transcripts of any academic qualifications
  • English language qualification certificates
  • visa and immigration documents

All documents should be in English or be accompanied by a certified translation into English. 

They can be sent via the online research degree application or can be emailed to after you have submitted your application. Your email should include your student ID number (emailed to you on submission of your application), full name and your intended course of study. Please do not send original documents at the application stage and only provide documents via email.

2) Complete the YES.DTN application form. This is available on the YES•DTN website

To help us track our recruitment effort, please indicate in your email – cover/motivation letter where (hiringnearme.org) you saw this job posting.

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