PhD Students - as lead supervisor
  1. Yi-Shan Wang (co-supervised by Paul Blackwell, in the School of Maths and Stats at Sheffield)
  2. I am interested in understanding the spatio-temporal scale on which animals make their decisions to move and how that affects their spatial distribution. Currently, I am comparing different mathematical formalisms for upscaling movement decisions to spatial patterns, to understand which work best under a variety of conditions. I also plan to work on building a movement modelling framework that seeks to uncover the scales at which movement decisions are made, even when the temporal resolution of the data is quite different.
  3. Rhys Munden (co-supervised by Luca Börger and Rory Wilson, both at Biosciences in Swansea University)
  4. My project aims to build predictive models of animal movement, using sub-second data on their positions, accelerations, and energy expenditure gathered by Swansea University's SLAM group. Coupled with environmental information on topography and resource availability, these data allow us to understand, in quite some detail, the energetic costs and benefits of movement decisions. My research attempts to understand how movement paths arise from such energetic trade-offs.
  5. Natasha Ellison (co-supervised by Ben Hatchwell, in Animal and Plant Sciences at Sheffield)
  6. I am interested in investigating how patterns of home range space use emerge from the individual behavioural decisions of animals, driven by their life history needs. I intend to construct a mathematical framework which will be formulated and tested alongside data on long-tailed tits, which has been collected by the University of Sheffield over the past 20 years. I will explore deriving models to describe movement on the macroscale from underlying individual stochastic movement models, using elements of statistical mechanics. Unlike statistical models, theoretical models give us the ability to predict future patterns. It is of fundamental importance in conservation ecology to understand how and why organisms use their environment.
  7. Charlotte Martindale (co-supervised by Edward Codling, at Essex University)
  8. My project aims to analyse detailed data which was collected on a commercial dairy farm in the UK. I am looking at whether we can make inferences about the health status of housed dairy cows by modelling their movement patterns. Initially I will be comparing the movements of cows known to be either lame or non-lame at the start of the study with the objective of identifying any measurable differences between the two groups.
PhD Students - as co-supervisor
  1. Simon Rolph (lead supervised by Dylan Childs, and also co-supervised by Rob Salguero-Gómez and Rob Freckleton)
  2. My project is taking a data-driven approach to answering fundamental questions about what determines optimal life history strategies in a variable world across the taxonomic spectrum of life. I will primarily be using the COMPADRE and COMADRE matrix population model databases which describes the demography of over 1000 species from around the world. Through determining the major a/biotic demographic drivers this project will also help build a more comprehensive picture of the impacts of climate change on these species.