Project Description
Supervisors
Professor Vincent Moulton, University of East Anglia – Contact me
Professor Thomas Mock, University of East Anglia
Dr Richard Leggett, Earlham Institute
Dr Fanny Monteiro, School of Geographical Sciences, University of Bristol
Scientific background
Arctic ecosystems are among those that are most affected by climate change anywhere on Earth, with air temperatures rising four times faster than the global average. The Arctic Ocean supports a complex ecosystem including fish, marine mammals, and zooplankton, and microbes are at the base of this food web. However, due to inaccessibility of the Arctic, there is a fundamental lack of understanding into how microbial communities in the Central Arctic Ocean respond to seasonal changes. To fill this knowledge gap, the 2019-2020 Multidisciplinary Observatory for Study of the Arctic Climate (MOSAiC) expedition undertook the largest ever survey of the Arctic Ocean, including the first ever year-long time series of Arctic metagenomes.
Research methodology
The aim of this project is to analyse and model changes in microbial diversity and traits over the course of a year, using genomic data from the MOSAiC expedition whose analysis is being co-coordinated by experts in the supervisory team at UEA. The student will synthesise multiple data sources from MOSAiC, including biogeochemical measurements, oceanographic data, and the MOSAiC metagenome time-series. Gene abundance and expressions level will be used as indicators of physiological traits, such as ice-adaptation and nutrient metabolism. The student will become familiar with both traditional species distribution models and machine learning tools and will use them to build models describing seasonal changes in microbial communities. In latter stages of this project, these models will be combined with broader oceanographic and climate predictions to forecast how Arctic microbial communities and traits might change in response to climate change.
Training
The student will work with a world-leading team of experts in Arctic microbial genomics and ocean modelling based at UEA, The Earlham Institute and University of Bristol as well as other members of the MOSAiC consortium. They will gain new skills in areas including bioinformatics, data analysis, machine learning, ecosystem modelling, and marine microbiology.
Person specification
2:1 Bachelor degree in Computer Science, Data Science or equivalent. We are looking for an enthusiastic student who is excited about applying interdisciplinary techniques to understand the potential effects of global change on oceanic microbes.