Modelling and Inference for Movement by Interacting Individuals
Lead supervisor: Prof. Paul Blackwell, School of Mathematics and Statistics, University of Sheffield;
Co-supervisors: Dr Jon Pitchford; Dept of Biology & Dept of Mathematics, University of York; Dr Mark Lambert; National Wildlife Management Centre, Animal, and Plant Health Agency
Improvements in tracking technology mean that it is now often possible to monitor the movements of several individual animals in a wild population simultaneously, using GPS tags or collars, or similar devices. This creates exciting opportunities to learn about the way in which animals interact, and so improve our understanding of social structure, reproductive behaviour, potential transmission of disease, etc. At the moment, however, these opportunities are largely unexploited, as typically the analysis of movement data is carried out separately for each animal. Existing models of collective movement are largely theoretical and are generally not directly fitted to real data.
The aim of this project is to develop realistic models of the ways in which animals influence each others’ movement, and statistical methods to fit these models to data. The initial emphasis will be on how members of the same species interact in the wild, making use of datasets on badgers and wild boar collected by the National Wildlife Management Centre (NWMC), part of the UK government’s Animal and Plant Health Agency. As well as the general scientific interest, badgers are of interest because of concern about their role in the spread of bovine TB, and understanding wild boar behaviour is important because of the need to monitor and control their population.
The models and methods developed will build on recent work by the academic supervisors which apply ideas from Markov chains, diffusion processes and Bayesian statistics to movement modelling for a wide range of species. The student will spend one or more periods based at NWMC in Sand Hutton, near York, working closely with the applied supervisor and other scientists there.
This project would suit a student with a strong mathematical background, with skills in statistics, probability or computing, and an interest in – or willingness to learn about – wildlife ecology.
Details of some recent papers relevant to this project are given below.
Blackwell PG, Niu M, Lambert MS, LaPoint SD (2016) Exact Bayesian inference for animal movement in continuous time. Methods Ecol Evol 7:184-195.
Croft S, Budgey R, Pitchford JW, Wood AJ (2015) Obstacle avoidance in social groups: new insights from asynchronous models. J Roy Soc Interface 12:20150178.
Langrock, R, Hopcraft, JGC, Blackwell, PG, Goodall, V, King, R, Niu., M, Patterson, TA, Pedersen, MW, Skarin, A, Schick, RS (2014) Modelling group dynamic animal movement. Methods in Ecology and Evolution 5:190-199.
Niu M, Blackwell PG & Skarin A (2016) Modelling interdependent animal movement in continuous time. Biometrics 72:315-324.
Quy RJ, Massei G, Lambert MS, Coats J, Miller LA & Cowan DP (2014) Effects of a GnRH vaccine on the movement and activity of free-living wild boar (Sus scrofa). Wildlife Research 41:185-193
How to apply
To apply for this project please complete an on-line application formApply
Please select ‘Standard PhD’
Department: School of Mathematics and Statistics
Project title: Modelling and Inference for Movement by Interacting Individuals
Supervisor(s): Prof. Paul Blackwell, Dr Jon Pitchford, Dr Mark Lambert
You can apply for more than one project to increase your chances to be nominated for an interview, but you can be interviewed for only one.