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Cambridge NERC Doctoral Training Partnerships

Graduate Research Opportunities

Supervisor: Andrew D. Friend (Geography)  

Importance of the area of research:

Atmospheric CO2 concentrations are increasing due to anthropogenic emissions caused by fossil fuel use and deforestation. However, the rate of CO2 increase has been strongly limited by land and marine carbon sinks. The land sinks are poorly understood, making it difficult to forecast future CO2 levels and hence compromising the usefulness of current scientific understanding for policy debate and decision. These sinks are presumably driven by increased plant growth and soil carbon. However, global models of plant growth and vegetation dynamics lack realism in many components, particularly with respect to controls on growth and ecosystem dynamics/demography, and diverge strongly under future scenarios.

Project summary:

A novel approach to modelling land surface ecosystem processes is being developed and will be used to assess the historical land carbon sink, and forecast its future behaviour. This model is built around an individual plant growth model that utilises improved biological realism over previous approaches, in particular with respect to the balance between controls from source (i.e. photosynthesis) and sink (i.e. meristem activity) processes. This individual model is nested in a competition framework which allows for the prediction of plant thinning and vegetation change over time. Individuals are parameterised as belonging to different plant types, and soil processes simulate the availability of water and nutrients for plant growth, as well as the dynamics of plant litter and soil carbon. This model framework will be developed to assess the behaviour of global terrestrial ecosystems

What the student will do:

The student will become familiar with the current knowledge concerning the role of terrestrial ecosystem in the global carbon cycle and the fundamental physiological and ecological processes that impinge on the dynamics of the land sink. They will learn how the global vegetation model to be used in this project works, and extend it to treat managed land, such as croplands and plantations, and fire. They will then extensively test the model using a variety of observational datasets, in particular those that constrain the historical terrestrial carbon balance. They will then use the model to forecast the future balance and status/distributions of terrestrial ecosystems under a variety of climate change scenarios as part of various international projects.

Please contact the lead supervisor directly for further information relating to what the successful applicant will be expected to do, training to be provided, and any specific educational background requirements.


Friend, A.D., Lucht, W., Rademacher, T.T., Keribin, R., Betts, R., Cadule, P., Ciais, P., Clark, D.B., Dankers, R., Falloon, P.D., Ito, A., Kahana, R., Kleidon, A., Lomas, M.R., Nishina, K., Ostberg, S., Pavlick, R., Peylin, P., Schaphoff, S., Vuichard, N., Warszawski, L., Wiltshire, A., Woodward, F.I. 2014. Carbon residence time dominates uncertainty in terrestrial vegetation responses to future climate and atmospheric CO2. Proceedings of the National Academy of Sciences, vol. 111, pp.3,280-3,285., doi:10.1073/pnas.1222477110

Friend, A.D. 2010. Terrestrial plant production and climate change. Journal of Experimental Botany, vol. 61, pp. 1293-1309, doi:10.1093/jxb/erq019

Friend, A.D. and Kiang, N.Y. 2005. Land-surface model development for the GISS GCM: Effects of improved canopy physiology on simulated climate. Journal of Climate vol. 18, pp. 2,883-2,902, doi:10.1175/JCLI3425.1.

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Other projects available from the Lead Supervisor can be viewed here.

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