Back to search results

PhD Studentship: Seascape Genomics of Antarctic Deep-sea Coral: Groundtruthing Larval Dispersal Models With Genetic Connectivity Data

University of Essex - School of Life Sciences

Qualification Type: PhD
Location: Colchester
Funding for: International Students
Funding amount: Not Specified
Hours: Full Time
Placed On: 10th October 2019
Closes: 7th January 2020
Reference: 11300

Supervisory Team:

Dr Michelle Taylor (University of Essex)

Dr Oliver Hogg (Cefas)

Dr Rebecca Ross (Institute of Marine Research, Norway)

Dr Gerrit Nanninga (University of Essex)

Dr Rui Vieira (Cefas)

Dr Emma Young (British Antarctic Survey)

Detailed understanding of dispersal and genetic connectivity is critical in determining processes underpinning population persistence and productivity, speciation, appropriate scales for management, and the potential for recovery from detrimental impacts e.g. climate change and/or fishing.

Larval dispersal models (LDMs) integrate mathematical hydrodynamic models with species’ biological data to predict population connectivity. They are economical, in time and effort, compared to genetic connectivity research (no sampling/expensive laboratory analyses). For this reason, LDMs are increasingly used in marine environments to investigate connectivity (Ross et al., 2016; 2019), especially in areas challenging to sample, e.g. deep sea. However, very few LDMs are validated with genetic connectivity data. This project creates LDMs and then compares outputs with ground-truthed genomic connectivity data - a combined approach called “seascape genomics” (Selkoe et al., 2016). By using environmental data alongside genomic data, the drivers of connectivity across this rapidly-changing region are investigated. The study focuses on deep-sea octocorals from sub-Antarctic UK overseas territories – some are MPAs giving this project an applied output with great potential for management impacts.

Collate oceanographic and environmental datasets and investigate the utility of various oceanographic models, combined with Lagrangian particle simulators, to predict larval dispersal in deep-sea octocorals. Compare dispersal model outputs with known genomic connectivity between study sites. Research will be undertaken at UoE using a high performance computing server. On regular visits to Cefas, model utility will be assessed and outputs integrated into practical protection measures.

Mathematical modelling – Oceanographic models and Lagrangian particle simulators.

Mapping/geographic data analyses skills using ArcGIS / QGIS / R.

Analysing genomic connectivity data – STACKS, BAYESCAN, STRUCTURE, and adegenet in R.

Communicating science to policy makers (minimum 3 months at Cefas).

This PhD suits a quantitatively-minded candidate. Suitable degrees could cover topics such as genetics, mathematics, physics and/or biologists with an interest in modelling. Essential - some experience in statistical or mathematical modelling. Desirable - working knowledge and experience in R/ Matlab, an interest in deep-sea ecology.

Please apply by sending a CV (including contact details of two academic referees) and a cover letter explaining your motivation and suitability for the PhD to Emma Revill If you have any questions please feel free to contact any member of the supervisory team.

This project has been shortlisted for funding by the ARIES NERC Doctoral Training Partnership, and will involve attendance at mandatory training events throughout the course of the PhD.

Shortlisted applicants will be interviewed on 18/19 February 2020.

Successful candidates who meet UKRI’s eligibility criteria will be awarded a NERC studentship - UK/EU nationals who have been resident in the UK for 3 years are eligible for a full award.

Excellent applicants from quantitative disciplines with limited experience in environmental sciences may be considered for additional 3-month stipend to take advanced-level courses in the subject area.

Further information, visit

We value your feedback on the quality of our adverts. If you have a comment to make about the overall quality of this advert, or its categorisation then please send us your feedback
Advert information

Type / Role:

Subject Area(s):


PhD tools
More PhDs from University of Essex

Show all PhDs for this organisation …

More PhDs like this
Join in and follow us

Browser Upgrade Recommended has been optimised for the latest browsers.

For the best user experience, we recommend viewing on one of the following:

Google Chrome Firefox Microsoft Edge