Professor Thomas Mock (University of East Anglia, School of Environmental Sciences)
Professor Kevin Flynn (Plymouth Marine Laboratory)
Mrs Claire Widdicombe (Plymouth Marine Laboratory)
Diatoms are microscopic plankton, characterised by their spectacular cell walls which they construct from biogenic silica (‘glass’). Found throughout the global ocean, they are often abundant in coastal and high latitude environments where they form blooms visible from space. They play a fundamental role in marine ecosystems, drawing carbon dioxide down from the atmosphere and exporting the associated carbon to deeper waters. They also fuel marine food webs and help to support global fisheries.
Several factors underpin the success of diatoms, including a tremendous diversity of forms, physiological flexibility, and high levels of protection against predation and viral attack. However, much uncertainty surrounds what combination of characteristics enable different diatom species to thrive and when. This uncertainty undermines our ability to predict the response of diatoms to environmental change and to fully understand the vital ecological role they play.
The student will investigate combinations of ecological processes and genetic/physiological adaptations that enable diatoms to succeed. They will use metabolomics and metatranscriptomics to study how diatoms sense and respond to their environment; and with this insight, develop innovative simulation models of diatoms and their role in marine ecosystems. The models will be used to test hypotheses that explain observed patterns and trends in diatom diversity and population dynamics. The work will focus on the Western English Channel (WEC), exploiting a rich 30-year data series on diatoms and associated environmental variables, and laboratory and field data collected during the project.
The project will provide the student with an exciting opportunity to work with a supervisory team that includes world leaders in the study of microalgae physiology and evolution; marine plankton ecology; plankton simulation modelling; and marine ecosystem modelling. The student will learn advanced data analysis and modelling techniques; gain laboratory and field work experience; and acquire generic time management and team working skills. The student will present their findings at national and international conferences.
The project will suit an outstanding student with a degree in a numerate discipline (e.g. biochemistry, physics, oceanography) and a keen interest in marine science. Experience in Python programming is desirable.