PhD Studentship: Genomics-informed Conservation

Primary Supervisor – Prof. Cock van Oosterhout

Many species are at immediate risk of extinction due to habitat decline, environmental change, pollution, invasive species, and overexploitation. These direct threats are recorded on the IUCN Red List, which categorises species in terms of their risk of extinction over short time frames (10 years or three generations). These direct threats also undermine the health of genomes and gene pools. This “genomic erosion” endangers species survival over much longer time frames. Genomic data are currently being generated for ~2 million species, and these data can be used to assess the longer-term extinction risk. We will capitalise on this by developing computer models in the software SLiM and AI models to predict the 10-generation / 100-year extinction risk and recovery potential of sequenced bird species.  

The PhD student will develop computer simulations to integrate the genomic, ecological, and environmental factors, providing a holistic approach to predicting species’ extinction. In particular, you will model 363 bird species which have genomic data, detailed Red List data, as well as relevant biological data (e.g., life history data, environmental data). In addition, you will analyse the population viability of zoo populations (for which we have genomic data) to assess how they can best contribute to the restoration of genetic diversity and viability of wild populations. This includes a Conservation Management Plan for the release of the pink pigeon in Mauritius. Finally, you will use computer models to assess the potential risks and benefits of genome engineering, i.e., technologies currently being developed in de-extinction projects. In particular, you will simulate how the restoration of genetic diversity using DNA variation from museum samples might affect the gene pool of the wild population. You will thus build very realistic models to assess the extinction risk and recovery potential of threatened species using state-of-the-art and future technologies. 

Funding Details

Additional Funding Information

This PhD project is in a competition for a Faculty of Science funded studentship. Funding is available to UK applicants and comprises ‘home’ tuition fees and an annual stipend of £19,237 (for a maximum 3 years)

Closing Date: 27 November 2024 (at 11.59 pm) 

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