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PhD in Earth Sciences:Modelling coral survival in a warming world

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  • Full or part time
    Dr B Swallow
    Dr N Kamenos
    Prof M Scott
    Dr H Burdett
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

The ecosystem services provided by coral reefs are worth over $100 billion annually and include coast line protection, tourism, food and medical derivatives. However, the health of the constituent corals can be significantly impacted by coral bleaching. Coral bleaching is the loss of symbiotic zooxanthellae (Symbiodiniaceae) from tropical corals and can be caused by stressors such as thermal perturbations, disease and freshwater runoff (Fig. 1.). Thermal perturbations are thought to be the most significant bleaching trigger, and have been well documented in conjunction with major global bleaching events in 1998, 2002 & 2016/2017. These mass bleaching events caused widespread coral death with catastrophic ecosystem and service provision impacts. However, sub-lethal bleaching can also occur where the coral bleaches but recovers, and this may act as a ‘safety valve’ allowing coral hosts to survive periods of thermal stress in warmer waters.
Despite the devastation caused by severe coral bleaching, it is still difficult to accurately assess if corals will survive in the warmer oceans projected for the end of the century. Specifically, we do not fully understand if, and how, corals will spatially disperse by the end of the century. This is important as there is evidence that certain areas may act as coral refugia, harbouring colonies resilient to climate change.
Aim: To better understand future coral dispersal and any roles of coral refugia this project will integrate biological timeseries with spatiotemporal modelling to determine future coral reef extent.

This project will include spatiotemporal analysis of coral distribution and resilience patterns from long-term ecological datasets, ensuring applicability to real-world conservation and resource management problems. Statistical inferential frameworks will be used to project future coral distributions under various climate change scenarios. There will also be the opportunity to explore how changing land-use might interact with climate change drivers on coral distributions.
Modelling: Spatiotemporal modelling of environmental data is often conducted using Bayesian hierarchical models, with the hierarchies representing the variation in temporal and spatial scales of the data or environmental process (Ledo et al (2016); Brown et al (2017); Jones-Todd et al (2018)). It also provides a natural probabilistic framework for predicting future coral distributions and their associated uncertainties. Estimation of relevant quantities of interest in spatiotemporal models can be conducted using a variety of statistical approaches, including Markov chain Monte Carlo (MCMC) and INLA. The project will determine the relevant choice of methods in the context of coral distribution modelling.

Field work: If desired, the scholar will have the opportunity to conduct model validation in relevant regions, such as the Caribbean, Red Sea and Mediterranean (Fig. 2; diving is optional), adopting state-of-the-art high-resolution 3D survey techniques.

For more details see:


How to Apply: Please contact Nick Kamenos for further details

Funding Notes

Funding is available to cover tuition fees UK applicants, as well as paying a stipend at the Research Council rate (estimated £15,009 for Session 2020-21).
UKRI regulations apply. These criteria require all students to be Home or EU domiciled, and only allows for EU students to receive a full maintenance grant if they have been resident in the UK for the last 3 years prior to the commencement of their studentship.

How good is research at University of Glasgow in Earth Systems and Environmental Sciences?

FTE Category A staff submitted: 34.80

Research output data provided by the Research Excellence Framework (REF)

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