The Bigger Picture: Integrating Plankton Imaging Techniques to Explore Ecosystem Structure and Function

Project code: FILEMAN_PML_ARIES27

The Bigger Picture: Integrating Plankton Imaging Techniques to Explore Ecosystem Structure and Function

Project code: FILEMAN_PML_ARIES27

Project Description

Supervisors

Mrs Elaine Fileman, Plymouth Marine Laboratory – contact me

Dr Cecilia Liszka, British Antarctic Survey

Dr Eoin O’Gorman, University of Essex

Professor Pennie Lindeque, Plymouth Marine Laboratory

Geraint Tarling, British Antarctic Survey

 

Scientific Background

Marine plankton communities are sensitive indicators of environmental change and play a vital role in ocean food webs, fisheries productivity and carbon cycling. Understanding how these communities are structured, and the factors that influence their organisation, is essential for predicting future ecosystem change and the efficiency of the biological carbon pump. As imaging technologies become increasingly accessible alongside traditional net sampling, new opportunities are emerging to study plankton community structure using size-based approaches that provide insights into trophic dynamics, food web interactions and carbon export processes.

This project will use size-based imaging technologies of marine plankton communities to improve understanding of ecosystem function, inform ecosystem-based management, and support global efforts to monitor ocean health and climate change impacts.

 

Research Methodology

You will combine traditional net-derived plankton data with image-based observations from ship surveys and oceanic moorings to investigate seasonal and interannual changes in plankton community structure in the Scotia Sea (Southern Ocean) and Western English Channel.  You will explore how environmental drivers such as temperature, nutrient availability, sea ice, and mixed layer depth influence community size spectra, vertical particle flux and carbon export. This will be supported by sediment trap data and elemental analysis. A key aim is to assess how effectively imaging techniques complement traditional net sampling for characterising plankton communities.

 

Training

You will gain skills in plankton taxonomy, image processing, ecological statistics, safe laboratory practices, oceanographic data handling, and field ecology.  Laboratory work will include sample processing, microscopy, and benchtop imaging. Depending on your interests, the project could also explore linking plankton size patterns to krill dynamics, carbon export or nutritional quality, or developing tools for rapid ecosystem monitoring using machine-learning approaches. Participation in UK-based fieldwork will be available, offering training in quantitative plankton sampling and seagoing skills. Participation in Antarctic fieldwork may be a possibility but cannot be guaranteed.

 

Person Specification

We seek an inquisitive and motivated candidate with a background in marine science, biological oceanography, environmental science, data science, computer science or related discipline. Strong analytical, numerical and practical skills are essential. Experience in coding or applying quantitative methods in a biological or ecological discipline is desirable, but full training will be provided.

Acceptable first degree subject(s): Marine Science/ Environmental Science/ Natural Sciences or equivalent

References

  • Atkinson, A, Rossberg, AG, Gaedke, U, Sprules, G, Heneghan, RF, Batziakas, S, Grigoratou, M, Fileman, ES Schmidt, K, & Frangoulis, C. (2024) Steeper size spectra with decreasing phytoplankton biomass indicate strong trophic amplification and future fish declines. Nature Communications,15 (1) 381
  • Liszka, C.M. et al (2022) Plankton and nekton community structure in the vicinity of the South Sandwich Islands (Southern Ocean) and the influence of environmental factors https://doi.org/10.1016/j.dsr2.2022.105073
  • Kerr, T., Clark, J. R., Fileman, E., et al (2020) Collaborative deep learning models to handle class imbalance in flowcam plankton imagery doi: 10.1109/ACCESS.2020.3022242
  • O’Gorman, E. et al (2017) Unexpected changes in community size structure in a natural warming experiment. https://doi.org/10.1038/nclimate3368
  • Tarling, G.A., et al (2012) Seasonal trophic structure of the Scotia Sea pelagic ecosystem considered through biomass spectra and stable isotope analysis doi:10.1016/j.dsr2.2011.07.002

Key Information

  • This studentship has been shortlisted for funding under the UKRI NERC DLA funding scheme and will commence on 1 October 2027. The closing date for applications is 23:59 on 16 December 2026.
  • Successful candidates who meet UKRI’s eligibility criteria will be awarded a fully-funded studentship, which covers fees, maintenance stipend (£21,805 p.a. for 2026/27) and a research training and support grant (RTSG). A limited number of studentships are available for international applicants, with the difference between 'home' and 'international' fees being waived by the registering university. Please note, however, that ARIES funding does not cover additional costs associated with relocation to, and living in, the UK, such as visa costs or the health surcharge.
  • ARIES postgraduate researchers (PGRs) benefit from bespoke training and ARIES provides £2,500 to every student for access to external training, travel and conferences, on top of all Research Costs associated with the project. Excellent applicants from quantitative disciplines with limited experience in environmental sciences may be considered for an additional 3-month stipend to take advanced-level courses. Excellent applicants from quantitative disciplines with limited experience in environmental sciences may be considered for an additional 3-month stipend to take advanced-level courses.
  • ARIES is committed to equality, diversity, widening participation and inclusion in all areas of its operation. We encourage enquiries and applications from all sections of the community regardless of gender, ethnicity, disability, age, sexual orientation and transgender status. Academic qualifications are considered alongside non-academic experience, and our recruitment process considers potential with the same weighting as past experience.
  • All ARIES studentships may be undertaken on a part-time or full-time basis. International applicants should check whether there are any conditions of visa or immigration permission that preclude part-time study. All advertised project proposals have been developed with consideration of a safe, inclusive and appropriate research and fieldwork environment with respect to protected characteristics. If you have any concerns, please contact us.
  • For further information, please contact the supervisor. To apply for this Studentship, follow the instructions at the bottom of the page or click the 'apply now' link.
  • ARIES is required by our funders to collect Equality and Diversity Information from all of our applicants. The information you provide will be used solely for monitoring and statistical purposes; it will remain confidential and will be stored on the UEA SharePoint server. Data will not be shared with those involved in making decisions on the award of Studentships and will have no influence on the success of your application. It will only be shared outside of this group in an anonymised and aggregated form. You will be asked to complete the form by the University to which you apply.
  • ARIES studentships are subject to UKRI terms and conditions. Postgraduate Researchers are expected to live within reasonable distance of their host organisation for the duration of their studentship. Please see https://www.ukri.org/publications/terms-and-conditions-for-training-funding/ for more information.

Apply Now

Please send a CV and Cover Letter to ariesapp@essex.ac.uk, including the title and project code of the studentship you wish to apply for.