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Cambridge NERC Doctoral Training Partnerships

Graduate Research Opportunities

Lead supervisor: Andrew D. Friend, Geography

Brief summary: 
Terrestrial ecology is a poorly understood component of the global carbon cycle - this project will investigate the mechanisms responsible for the observed spatial and temporal variability in global land-atmosphere CO2 exchange using a new terrestrial ecosystem and land use model.
Importance of the area of research concerned: 
Natural terrestrial ecosystems are an important and highly dynamic component of the global carbon cycle, sequestering ca. 30% of the combined industrial and land use C emissions over 2011-2020, greatly reducing the atmospheric CO2 accumulation rate and hence climate change (Friedlingstein et al., 2022). However, global models have poor agreement regarding the contributions of different mechanisms and regions to this uptake, and struggle to reproduce the observed interannual and spatial variability of net C-fluxes (Canadell et al., 2021). Current understanding, as formulated in these models, therefore limits our ability to quantify future atmospheric CO2 and hence climate, even if we knew anthropogenic emissions. New approaches are therefore required, and this project will explore ideas concerning how plants and whole ecosystems work and consequences for the global carbon cycle.
Project summary : 
We are constructing a new global model of terrestrial ecosystem dynamics based on novel concepts that promise to resolve many of the limitations of existing approaches. Our model is formulated from the biological perspective of the plant, with mechanistic details regarding physiological processes and explicit competition between individuals for light, water, and nutrients. There are many possible avenues to explore with the model, and therefore the specific project can be developed around the particular interests of the student. Options include (i) further development of a model component (e.g. plant types, competition, fire, permafrost, soil respiration, land use); (ii) a focus on validation (e.g. using remote sensing); and/or (iii) a regional focus (e.g. Miombo savanna woodland or the subarctic). The model will contribute to annual assessments of the global carbon cycle.
What will the student do?: 
The specifics of what the student will do will depend on the focus of their project, but will primarily involve model development and hypothesis testing. Our global model is currently set up using a gap-model approach and a certain amount of physiological realism, with individual-tree competition. Model development will be based on assessments of process-representation derived from the literature, coding of this representation in off-line codes to test its behaviour, and integration of these codes into the global model with further testing against key datasets, such as iLAMB, FLUXNET, and various remote sensing resources. The student will be expected to present results at international conferences, visit other teams to discuss ideas, and write up the work in the peer-reviewed literature. The model is written in Fortran and runs on the Cambridge parallel computing cluster. Inputs and some outputs use netCDF and there are many tools and datasets available for analysing and running the model. Our current focus is on the prediction of the distribution of different plant types, their productivity, and how they might respond to changing climate and atmospheric CO2.
References - references should provide further reading about the project: 
Friedlingstein, P. et al. 2022. Global Carbon Budget 2021. Earth Syst. Sci. Data, vol. 14, pp.1917-2005. DOI:10.5194/essd-14-1917-2022.
Canadell, J.G. et al. 2021: Global Carbon and other Biogeochemical Cycles and Feedbacks. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V. et al. (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 673–816, doi:10.1017/9781009157896.007.
Friend, A.D. et al. 2014. Carbon residence time dominates uncertainty in terrestrial vegetation responses to future climate and atmospheric CO2. Proc. Natl. Acad. Sci. U S A, vol. 111, pp.3280-3285. DOI:10.1073/pnas.1222477110
You can find out about applying for this project on the Department of Geography page.