Supervisor(s): 

Professor Robert Beynon and Professor Jane Hurst

I have a masters in Animal Behaviour and welfare from Queen’s University Belfast and an honours degree in Biology from the University of Dundee. My main area of interest is animal welfare particularly with finding new non-invasive methods for researching animals. This interest began with my undergraduate project which aimed to identify the sex of wild wood mice using hair samples but I did not think this was the optimal method to use. It was more stressful to the animals and required more effort and money than determining sex by observation. It was this project that inspired me to do a masters in animal behaviour and welfare. For my masters project the aim was to determine if lions had individualised vocalisation signatures. This would allow lions to be identified and tracked based on acoustic cues rather than relying on sightings. I very much enjoyed my masters and it confirmed my desire to pursue research as a career. I therefore chose to do a PhD that involves investigating an alternative method to population monitoring using mass spectrometry. Before starting the PhD I spent six months volunteering in South Africa on various research projects.

A new approach to non-invasive monitoring of cryptic mammals 

Rapid Evaporative Ionisation Mass Spectrometry (REIMS) is a new way of analysing biological material by a very simple treatment. A diathermy electrode is used to burn biological material and generates an aerosol that is highly information rich. REIMS is fast, non-invasive and requires no sample preparation. For my project I will investigate the potential of REIMS to be used as a non-invasive method for monitoring mammals, using faeces as the biological source. I have already used REIMS to discriminate between sex, age and genotype of laboratory strains of house mice. A spectra was produced for each pellet burned, the spectra were analysed by Random Forests using Rstudio within R. The accuracies of assigning faecal pellets to the correct sex and age class were 80%, suggesting that REIMS has the potential to identify sex and age from faecal material. REIMS could also be used to discriminate other parameters such as stress (presence of cortisol) or pregnancy. I will also investigate what is responsible for the variation between spectra. I will determine what ions are present and if the microbiome has an effect. This is a case project with Waters as my industrial partner.