About the Project
PhD Project Summary:
This project will explore new ways of collecting and analyzing surveillance data within the context of marine animal biology. Marine animals have become stranded along UK coasts for centuries but the reasons for these events remain unclear. Discovery of a stranded animal often leads to questions regarding why such events happen, and what they indicate about the health of our oceans. Long-term accumulation of stranding data allows the investigation of trends in stranding numbers, indices of health and causes of mortality and can provide essential baseline information to detect emerging diseases, unusual mortality events, and anthropogenic impacts. However, extrapolating the strandings record to the at-sea population is challenging as reported cases are a complex function of biological, physical, and social processes. This study seeks to improve the statistical modelling techniques for strandings data to facilitate their use for monitoring and to reduce uncertainty in quantifying anthropogenic impacts on marine populations. It will interrogate the strandings databases available for the UK, and other countries bordering the North Sea, to model spatiotemporal patterns of strandings incorporating multiple data sources, and examine how these novel insights can help inform management decisions and develop more robust future monitoring strategies. This has application to wider opportunistic wildlife surveillance schemes and offers tangible benefit to the work of the monitoring and consenting bodies collaborating on this project.
The MVLS/EPSRC grant provides tuition fees and stipend of at least £15,285 (UKRI rate 2020/21).
Please view application information here: https://www.gla.ac.uk/colleges/mvls/graduateschool/mvlsepsrcstudentships/
Once you have all the required application documentation, please apply here: https://www.gla.ac.uk/study/applyonline/?CAREER=PGR&PLAN_CODES=ZY38-7316
Based on your current searches we recommend the following search filters.
Based on your current search criteria we thought you might be interested in these.