Forecasting the ecosystem and biogeochemical responses to sea ice change in the Southern Ocean

Background

Antarctica is undergoing rapid environmental change with the unprecedented decline in sea ice observed over recent years raising urgent questions about the resilience of ice-dependent species and the stability of ecological and biogeochemical processes. There is considerable uncertainty on how biodiversity and associated biogeochemical processes are responding to these shifts, creating new climate and ecosystem risks. In the Southern Ocean, poleward range shifts of the dominant zooplankton, Antarctic krill and salps have been recorded, while copepod distributions are more stable. These species differ in their environmental preferences, size, feeding behaviour and life history, which influence how they store and release carbon. Such ecosystem-level responses influence both carbon export and food web structure. Understanding these responses is vital to assess how Antarctic ecosystems contribute to global climate regulation and to reduce uncertainty in predicting long-term climate change.

PhD Opportunity

The project will address major uncertainties on how sea ice loss and climate driven environmental change will influence the movement, displacement and resilience of Southern Ocean zooplankton communities. The student will investigate how environmental variability, including changes in sea ice characteristics (e.g. concentration, extent and thickness), drives species distribution and abundance. Biological and physical data from multiple sources, including satellite observations and long term monitoring programmes will be integrated into a predictive multimodal framework such as IceNet, a probabilistic deep learning model originally developed to forecast sea ice concentration. By adapting and expanding this framework, the project will identify emerging changes in ice-dependent species and quantify their potential effects on ecosystem function and carbon export. Findings will inform fisheries management, as Antarctic krill supports the largest and fastest growing fishery in the Southern Ocean.

This PhD offers opportunities to develop expertise in data synthesis and analysis, machine learning, ecological modelling and forecasting. The student will develop species distribution models, which aim to predict species abundance and habitat suitability given relevant environmental conditions. These will be combined with mechanistic models to estimate carbon export under different species assemblages and environmental conditions. They will also use data driven approaches to detect early warning signals of change, improving our capacity to forecast ecological responses in a warming climate.

The student will gain experience across marine ecology, biogeochemistry and climate science, contributing to UNRISKS’s broader aim of improving decision-making under uncertainty in the face of rapidly changing climate. The project will be co-supervised by Dr Michel Tsamados (sea ice remote sensing), Dr Jennifer Freer (British Antarctic Survey: marine ecology and modelling) and Dr Louisa van Zeeland (Alan Turing Institute: AI methods).

Applicant Profile

This PhD will suit students with backgrounds in environmental science, oceanography, ecology, climate science, data science, maths, physics or computing who want to apply quantitative tools to real world climate and ecosystem questions. Students should have computational skills in R, Python or MATLAB. Experience in working with data, writing code and analysing large datasets is desirable. An interest in modelling biological and biogeochemical processes, applying machine learning and understanding ecological change in the context of climate risks and uncertainty is important. Curiosity and willingness to work across disciplines are essential.

Other Information

Bowler et al. (2025) AI sea ice forecast for Arctic conservation: A case study presenting the timing of caribou sea ice migration https://doi.org/10.1002/2688-8319.70034

Freer et al. (2025) A new dynamic distribution model for Antarctic krill reveals interactions with their environment, predators, and the commercial fishery in the south Scotia Sea region. Limnology and Oceanography https://doi.org/10.1002/lno.12809

Manno C, Fielding S, Stowasser G, et al. (2020) Continuous moulting by Antarctic krill drive pulses of carbon export in the north Scotia Sea, Southern Ocean. Nature Communications https://doi.org/10.1038/s41467-020-19956-7

Ratnarajah (2021) Regenerated iron: How important are different zooplankton groups to oceanic productivity. Current Biology https://doi.org/10.1016/j.cub.2021.05.016

Ratnarajah et al. (2023) Monitoring and modelling zooplankton in a changing climate. Nature Communications https://doi.org/10.1038/s41467-023-36241-5

Schmidt et al. (2016) Zooplankton gut mobilises lithogenic iron for ocean productivity. Current Biology 10.1016/j.cub.2016.07.058

Smith AJR, Wotherspoon S, Ratnarajah L, et al. (2025) Antarctic krill vertical migration modulate seasonal carbon export. Science DOI: https://doi.org/10.1126/science.adq556

Sulikova et al. (2025) Satellite derived volume budget of Antarctic sea ice https://doi.org/10.22541/essoar.175760566.66149370/v1

Sylvester et al. (2025) Untangling the complexities of larval Antarctic krill overwintering success under climate change. https://doi.org/10.1093/icesjms/fsaf049