Using continuous in-situ zooplankton imagery and AI-based classification to examine Southern Ocean zooplankton functional traits and implications for marine aerosol production REP 2026

Using continuous in-situ zooplankton imagery and AI-based classification to examine Southern Ocean zooplankton functional traits and implications for marine aerosol production REP 2026

Lead Supervisor:
Cecilia Liszka

Locations:
British Antarctic Survey

Duration:
8-10 weeks

Suitable undergraduate degrees:
Ecology, Environmental Science, Environmental Statistics, Marine Science, Related subject

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Project background

Scientific Background

Zooplankton play a central role in marine ecosystems, mediating energy transfer between primary producers and higher trophic levels and influencing biogeochemical cycles. They are also a key conduit of carbon to the deep ocean through the biological carbon pump (BCP).

Increasing evidence additionally points to a potential role for zooplankton in marine aerosol production, through processes such as the generation of organic-rich sea spray and the transformation of biologically derived material in the surface ocean. Both of these processes are particularly important in the Southern Ocean where data are often sparse and the environment increasingly influenced by a changing climate.

Robust, spatially resolved observations of zooplankton abundance, size structure and taxonomic composition are essential for advancing our understanding of ocean-atmosphere coupling, yet zooplankton sampling is usually based on net samples taken at specific locations. A recent project on board the RRS Sir David Attenborough trialled a continuous in-situ plankton imager to collect data along a Southern Ocean oceanographic transect. Alongside this, data were collected on environmental parameters and marine aerosols. The project will utilise this unique dataset alongside state-of-the-art AI-based image classification, to deliver novel insights into near-surface zooplankton community structure and their potential influence on marine aerosol generation.

 

Research Methodology

The core dataset consists of high-frequency image data that have been classified into taxonomic groups using an AI-based classifier. A primary objective is to derive estimates of zooplankton densities from image-based counts. This will involve developing and validating conversion methodologies that translate numbers of detected objects into volumetric densities, explicitly accounting for variations in sampling parameters and changes in image acquisition settings (including differing size thresholds applied during the sampling period). Using these density estimates, the project will quantify the relative contributions of major zooplankton taxa or functional groups (e.g. size) along the transect, examining how community structure varies in response to changing oceanographic conditions.

The outputs of this project will contribute to wider research investigating the potential contribution of zooplankton to marine aerosol production. The zooplankton data will be integrated with concurrent underway environmental measurements, including temperature, salinity and chlorophyll fluorescence, to explore relationships between biological and physical drivers. Statistical and multivariate analyses will be used to identify environmental correlates of zooplankton abundance, size structure and community composition, providing insight into the mechanisms shaping observed patterns and constraints for linking biological variability in the upper ocean to aerosol processes at the air-sea interface.

Eligibilty criteria

Students must meet all of the eligibility requirements listed below to apply for a REP:

  • Be undertaking their first undergraduate degree studies (or integrated Masters) – note that students in in their final year who have graduated and no longer have student status at the time the placement starts are not eligible;
  • Be eligible for subsequent NERC PhD funding (please see the relevant text in the ‘Terms and conditions for training funding’ and associated guidance for further information – https://www.ukri.org/publications/terms-and-conditions-for-training-funding/); and
  • Have the right to work in the UK.

 

Students from outside the UK who do not already have right to work in the UK should not apply.

How to apply

The deadline for applications will be midday (12 noon BST) on Wednesday 20 May 2026.  

In order to be considered for a placement, please apply to aries.dtp@uea.ac.uk providing the following:

  • A supporting statement explaining your motivation for applying for this project. Please include answers to the following questions:
    • which project are you applying for?
    • why have you applied for this project (e.g. what interested you about this project, what in particular made you want to undertake this research)?
    • what do you hope to achieve by undertaking this placement (e.g. is it for experience, to gain skills, to develop your interests)?
    • what skills do you have that make you an ideal candidate for this placement (e.g. what skills have you developed during your degree that might apply)?
    • what do you hope to do when you complete your degree (e.g. have you considered a working in scientific research in the future, or is this your first experience)?
  • A recent CV
  • A reference from your personal tutor (please ask your tutor to send this to us directly)
  • An interim transcript if available
  • Please also complete the online EDI form (this form is a mandatory part of the application process, but contains ‘prefer not to say’ options for all questions asked)
Selection process
  • Applications are screened for eligibility
  • Applications are forwarded to supervisors (the EDI form is not included)
  • Supervisors shortlist candidates and interview for the placement.

 

Candidates will be scored according to the following criteria:

  • Fit to project (e.g. your current skills, area of study, interests)
  • Enthusiasm for environmental research (e.g. what you hope to achieve through undertaking this placement, why you chose this project in particular)
  • Evidence of suitability to undertake a research placement (e.g. evidence from your tutor reference, transcript, and CV that you are an engaged student)

 

Successful candidates will be informed by Friday 12 June 2026.