CR2025_39 Defining the cascading effects of global warming – from the microbial loop to marine food webs (MicroHeat)

Lead Supervisor: Eva Sonnenschein, Department of Biosciences, Swansea University

Email: e.c.sonnenschein@swansea.ac.uk

Co-supervisors: Tamsyn Uren Webster, Department of Biosciences, Swansea University; Shovonlal Roy, Department of Geography and Environmental Sciences, University of Reading

Marine ecosystems are highly sensitive to global warming, however, the detailed mechanisms by which temperature changes affect food web dynamics remain poorly understood. This PhD project aims to fill this gap by examining how rising ocean temperatures affect microbial communities and their metabolic processes, and how these changes subsequently influence the marine food chain.

Laboratory experiments will simulate future warming conditions to explore how temperature-driven shifts in microbial communities affect phyto- and zooplankton and fish physiology and population dynamics. Microbial diversity will be assessed using genomic analysis and functional changes will be defined by metatransciptomics. Statistical analysis and modelling will be performed to derive relationships between temperature changes and response of the microbial communities and their links to fish, with a view to better understand marine ecosystems response to environmental changes.

The student will:

1. Simulate future warming scenarios in laboratory experiments (year 1): Conduct controlled experiments to replicate potential future ocean temperatures and assess how these conditions influence the interactions between microbes, phytoplankton, zooplankton, and fish. Explore how temperature changes affect the physiology and population dynamics of phytoplankton, zooplankton, and fish, key players in the food chain using a range of physiological analyses, including transcriptomics.
2. Examine the effects of rising ocean temperatures on microbial communities associated with microalgae, zooplankton, and fish (year 2): Investigate how changes in temperature impact the structure and composition of microbial communities in marine ecosystems using amplicon sequence analysis. Study how temperature-induced shifts in microbial metabolism affect nutrient cycling and energy flow through the food web using (meta)transcriptomic analysis.
3. Apply statistical analysis and modelling techniques (year 3): Use statistical methods and modelling to analyze experimental data and predict how warming-driven changes in microbial communities and metabolic processes will affect marine food web dynamics.

By designing comprehensive laboratory experiments and deriving data-driven  interaction models, this project will enhance ecosystem models to predict how warming oceans will reshape marine food webs, from microbes to higher trophic levels. The research will provide crucial insights into the resilience of marine ecosystems to climate change, helping inform conservation strategies and sustainable management of marine resources.

Training opportunities: 

This PhD project offers a unique interdisciplinary experience combining hands-on research in marine biology, microbiology, molecular biology, bioinformatics, and statistical modeling. The student will conduct experiments in the advanced aquarium, microbiology and molecular labs at Swansea University, with data analysis and modeling at the University of Reading, integrating experimental and computational methods. An optional industrial placement would provide practical industry experience, enhancing employability and professional connections. Additionally, the student will be able to attend cutting-edge workshops and conferences, gaining highly sought-after skills and exposure to the latest methodologies and scientific break-throughs.

Student profile: 

This project would be suitable for students with a degree in Biosciences or a closely related discipline with knowledge of basic microbiology and animal physiology. Interest in learning molecular biology techniques, such as genomic or metatranscriptomic analysis, is desirable. Candidates may have quantitative skills for statistical analysis and ecological modelling. The ability to collaborate within multidisciplinary teams and a keen interest in climate change impacts on marine ecosystems will be essential.