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Evaluating plant level eco-evolutionary optimality approaches in the context of land-surface modelling


   School of Geography and Environmental Science

   Wednesday, August 31, 2022  Funded PhD Project (Students Worldwide)

About the Project

The terrestrial biosphere plays a critical role in regulating water, energy and carbon exchanges between the land surface and the atmosphere, and vegetation is therefore a crucial component of the land-surface scheme in climate models. Although vegetation and land-surface models have become increasingly complex as they incorporate new processes, systematic errors and persistently large differences among carbon and water cycle projections by different models highlight the limitations of their current process formulations. Eco-evolutionary optimality theory provides a basis for developing hypotheses about the controls of key processes at leaf and plant level and thus is providing simple but robust formulations of these processes. Initial tests of these formulations suggests that they provide a parsimonious way of simulating vegetation in a land-surface modelling framework. The goal of this project is to implement eco-evolutionary optimality formulations of photosynthesis and primary production, dark respiration and stomatal behaviour within the JULES land-surface scheme of the UK Earth System Model, including explicitly differentiating the timescales of acclimation to environmental factors. The project will include comparing the performance of these new formulations against the existing version of JULES using field and experimental data, flux tower measurements and remote-sensing products.

Specific training opportunities

An understanding of theoretical developments in plant physiology and ecology.

An understanding of land-surface modelling and the role of the land surface in climate and carbon cycling.

Modelling skills through implementing new components in the JULES land-surface scheme.

Statistical, analytical and programming skills through the manipulation and analysis of field and remotely-sensed data sets for model evaluation.

Science communication skills including communication across disciplines and to policy-oriented stakeholders.

The project is designed as a thesis-by-papers. The student will be based in Reading but will be funded by the "Land Ecosystem Models based On New Theory, observations, and Experiments" (LEMONTREE) project and will have the opportunity to work closely with the international members of that project, including staff at UKMO. The student will be expected to take part in LEMONTREE science meetings and working groups, as well as presenting their work at appropriate international conferences.

Applicants should hold a 1st or upper 2nd class degree (or equivalent) in quantitative biology, environmental science or meteorology.

Good quantitative & analytical skills required.

Experience in programming (R, Fortran, Python) essential .

Where a candidate is successful in being awarded funding, this will be confirmed via a formal studentship award letter which is provided separately from any Offer of Admission and which is subject to standard checks for eligibility and other criteria.


Funding Notes

The PhD project is part of and funded by the "Land Ecosystem Models based On New Theory, observations, and Experiments" (LEMONTREE) project.
Tuition fees plus stipend for 3.5 years. Starts no later than October 2022.
Where a candidate is successful in being awarded funding, this will be confirmed via a formal studentship award letter which is provided separately from any Offer of Admission and which is subject to standard checks for eligibility and other criteria.

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