Elucidating the spatiotemporal movements of plains zebra (Equus quagga) navigating in the Makgadikgadi, Botswana

In this wide-ranging, highly interdisciplinary project we will use cutting-edge GPS and inertial technology to locate and track a number of individual mammals moving within groups. Machine learning algorithms will be used to determine spatiotemporal and individual movement patterns. Key questions on animal navigation, physiology and behaviour will be asked. Analysis will be carried out on existing datasets coupled with measurements collected in UK and Botswana-based field work.

Specific aims - approximating to chapters:
1. Validation of fused GPS/IMU measurement systems to determine accurate position (centimetres accuracy) over time, stride phase and proxies for metabolic cost (water and food intake) within a herd. This is an essential first step for the rest of the work.
2. Behavioural biology. Determining of position and distance travelled in relation to time of day, temperature, light levels, weather, water and food intake of zebra in migrating herds in Botswana. does migration pattern change in response to external stimuli? Are movements time specific?
3. Understand navigational strategies used to migrate hundreds of kilometres by overlaying GPS data on 3D rendered models of the habitat. Aerial surveys will be used to capture high resolution photogrammetry to be processed computationally. High accuracy GPS data is crucial to decipher small but significant changes in route taken to investigate where decisions are made to change course. This will determine the use of landmarks or other strategies for navigating in challenging conditions.
4. Development of a machine learning algorithm to detect subtle changes in mechanics to automatically decipher behaviour. For example, a training dataset of animal movement will be used to identify key movements of interest (drinking, grazing, rolling, running etc) and fit to a classification model for unseen datasets.
5. Test model on unseen datasets and measure robustness under perturbed conditions using visual (virtual reality/3D modelling) and mechanical perturbations.
6. Evaluate the likely effect and applicability of such approaches to novel migrating species with a goal of increasing endurance and reducing the cost of commuting.

The project will provide comprehensive training at the interface between biology, engineering and computer science in the Structure & Motion Laboratory.