Can we predict future climate and compound-stressors for intertidal habitats?

Overview

This study aims to improve understanding of one of the most stressed and vulnerable habitats on Earth – the intertidal zone. Intertidal species are threatened by compounding stressors of warming seas, rising sea levels, and changing storm patterns. We rely on models to predict future climate, on land and in the ocean. However, these models struggle to represent complex processes that are fundamental to intertidal habitats.

Lead Supervisor: Jennifer Graham
Stakeholder Supervisor: Barbara (Bee) Berx (Scottish Government Marine Directorate)
Co-Supervisor 1: Michael Burrows
Co-Supervisor 2: Tim Szewczyk 

Supported by this multidisciplinary supervisory team, with expertise in physical and ecological processes, using both models and observations, this project will improve future projections, enabling improved management of intertidal habitats under climate change.

In addition to academic supervisors based at SAMS-UHI, this project will benefit from supervision from Dr Oliver Andrews, University of York, and Prof Peter Robins, Bangor University. Opportunities to collaborate with both Scottish Government and UK Met Office will also provide a direct route for research outputs into advice and policy across the UK.

What expertise and skills will the student develop? 

This project provides an exciting opportunity to develop a unique technical skill set that includes both observational sampling (field work) as well as coding for big data analysis and coastal climate modelling. The student will develop interdisciplinary expertise, including but not limited to:

- Coastal ocean dynamics

- Land-ocean-atmosphere interactions.

- Interacting climate extremes

- Ecology of coastal habitats

- Science communication and outreach

There will opportunities to plan and conduct field work, considering sampling locations exposed to different stressors. The student will also develop modelling skills, including numerical and statistical model analysis as well as machine learning approaches.

Based at SAMS-UHI, the student will join a cohort of ~30 postgraduate research students. They will be provided with various training opportunities including bitesize sessions regarding effective communication, teaching to teach etc., and will have access to taught courses hosted as part of the SAMS-UHI undergraduate programme if required.

Why is the project novel? 

This project provides a novel approach to climate projections that are targeted for sustainable management of intertidal habitats. Multidisciplinary methods will combine observational data sampling and analysis as well as both physical and ecological models (including machine learning techniques). The project is timely in that it will coincide with publication of the UK’s Fourth Climate Change Risk Assessment (CCRA4), as well as the next generation of regional ocean climate projections. Working closely with stakeholder partners, the student will then be able to engage with this community, as well as international networks, to help inform future climate policy advice.

What real-life challenge does it address?

Climate change poses many threats to intertidal habitats, combining impacts from the atmosphere, ocean and land surface. To support sustainable management of these environments, including effective restoration of degraded habitats, we rely on climate model projections to inform future survival of intertidal species, for example based on known temperature limits and projected future trends. This project will improve predictions of future changes and climate extremes, through targeted observations and modelling in this complex environment. Working with stakeholders, the results will be communicated to relevant partners and policy makers, to help sustainable management of these valuable coastal habitats.