Modelling forest disturbance and biomass changes in tropical forests, Geography, Mathematics


   College of Engineering, Mathematics and Physical Sciences

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  Prof S Sitch, Prof P Friedlingstein  No more applications being accepted  Funded PhD Project (UK Students Only)

About the Project

Location:

 

Geography, Streatham Campus, Exeter

The University of Exeter’s Department of Geography is inviting applications for a PhD studentship to fully-funded through a gift from the Virtual Earth System Research Institute (VESRI), an initiative of Schmidt Futures, to commence on 01 February 2024 or as soon as possible thereafter.  For eligible students the studentship will cover Home tuition fees plus an annual tax-free stipend of at least £18,622 for 3.5 years full-time, or pro rata for part-time study.  The student would be based in the Faculty of Environment, Science and Economy at the Streatham Campus in Exeter.

Project Description:

Around one quarter of anthropogenic carbon dioxide emissions are taken up by land ecosystems, mitigating climate change (Friedlingstein et al., ESSD 2023). The largest land sink is located in tropical forests with their high productivity and biomass (Ahlstrom et al., 2015). Yet these ecosystems are also heavily impacted by deforestation and degradation. Earth System Model (ESMs) results suggest a diminishing land sink with climate change, with tropical forests particularly vulnerable to future warming and changing precipitation patterns (Cox et al., Nature 2000, Friedlingstein et al., Journal of Climate 2006). However, biological carbon loss and mortality processes are major gaps in our current knowledge of the carbon cycle, which have been oversimplified in ESMs.

A deluge of new empirical datasets illuminates critical processes which could previously only be observed at a handful of locations: satellite constellations delivering daily spectral images of the whole Earth at meter resolution; compilations of thousands of measurements of functional traits for plants. Second, with new machine learning (ML) methods these high dimensionality observations can now guide the development of ESMs through the identification of spatio-temporal patterns and drivers-related relationships for C loss variables.

As part of the Schmidt Future’s Carbon Loss In Plants, Soils and Oceans (Calipso) project this PhD will focus on modelling tropical forest disturbance (eg forest fires) and associated biomass change utilising remote-sensing data and machine-learning, and further to inform ESMs.

The PhD would entail learning data assimilation approaches, use of Earth Observations and modelling. The student will also benefit from access to further empirical and remote-sensing data from complementary projects funded through the European Space Agency and UK’s Natural Environment Research Council.        

This award provides annual funding to cover Home tuition fees and a tax-free stipend.  For students who pay Home tuition fees the award will cover the tuition fees in full, plus at least £18,622 per year tax-free stipend. 

The studentship will be awarded on the basis of merit for 3.5 years of full-time study to commence on 1 February 2024.

This has been approved by Schmidt Futures. 

For further information and to apply please follow this link - Award details | Funding and scholarships for students | University of Exeter


Biological Sciences (4) Environmental Sciences (13) Geography (17) Geology (18) Mathematics (25)

Funding Notes

The University of Exeter’s Department of Geography is inviting applications for a PhD studentship to fully-funded through a gift from the Virtual Earth System Research Institute (VESRI), an initiative of Schmidt Futures, to commence on 01 February 2024 or as soon as possible thereafter. For eligible students the studentship will cover Home tuition fees plus an annual tax-free stipend of at least £18,622 for 3.5 years full-time, or pro rata for part-time study. The student would be based in the Faculty of Environment, Science and Economy at the Streatham Campus in Exeter.

Where will I study?