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 climate models. Most vegetation models characterise the complexity of the terrestrial biosphere through plant functional types, which are defined in terms of life form, leaf form, phenology, climate tolerance, and photosynthetic pathway for non-woody plants. However, this means that critical parameters for individual processes must be defined for each plant functional type - and in many cases there is insufficient data to do this in a realistic way. The LEMONTREE project is using eco-evolutionary optimality theory to provide a basis for developing hypotheses about the controls of key processes at leaf and whole plant level and thus is providing simple but robust formulations of these processes. The goal of this project is to extend the eco-evolutionary optimality theory framework to predicting characteristics of plant functional types and to develop a parsimonious scheme for predicting ecosystem level traits that are critical for the simulation of terrestrial carbon and water exchanges. The PhD project is part of and funded by the "Land Ecosystem Models based on New Theory, observations, and Experiments" (LEMONTREE) project: (https://research.reading.ac.uk/lemontree/).
Specific training opportunities
• An understanding of theoretical developments in plant physiology and ecology
• Modelling skills through implementing new components in the P modelling scheme
• Statistical, analytical and programming skills through the manipulation and analysis of field and remotely-sensed data sets for model development and 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 be co-supervised by external PIs on the project. The student will also have the opportunity to work closely with the international members of the LEMONTREE project. 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 or environmental science.
• 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.