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Andrew D. Friend BSc PhD

Professor of Earth Systems Science


I am interested in the functioning of plants within the Earth system, in particular the physiology of carbon relations, controls on growth processes, and the competitive interactions between individuals within ecosystems. I use mathematical models to explore theories of how biological systems function and use these models to predict their future behaviour under changing climate and atmospheric CO2. We are growing hybrid poplar trees under a range of experimental conditions to investigate controls on wood formation and whole-tree growth, with the results being used to improve global vegetation models.


    • 2007-present: Department of Geography, University of Cambridge
    • 2007-2023: Fellow and Director of Studies, Clare College, Cambridge
    • 2003-2007 (then en detachĂ©ment): CNRS (CR1), Laboratoire des Sciences du Climat et de l’Environnement, Gif-sur-Yvette, France
  • 1999-2002: Associate Research Professor/Scientist (Rutgers/Columbia University), NASA Goddard Institute for Space Studies, New York City, USA
  • 1991-1999: HSO/SSO, Institute of Terrestrial Ecology, Edinburgh, Scotland
  • 1989-1991: Associate Research Scientist, Department of Environmental Sciences, University of Virginia, USA
  • 1989: YSSP, International Institute for Applied Systems Analysis, Vienna, Austria


  • PhD in Plant Physiological Ecology, Botany School and Downing College, University of Cambridge
  • BSc in Botany, University College London

PhD supervision

I welcome the opportunity to supervise PhD students who wish to work on modelling and observations in the areas of plant physiology, ecosystem dynamics, global biogeochemical cycles (especially the global carbon cycle), and/or climate systems, especially where one or more of these elements are coupled.

An example of a possible topic is shown at the end of this page, but many other topics are of equal interest – please feel free to suggest what you would like to work on within the general research areas described here.


[Publications will appear automatically from the University’s research database…]


  • Part IB (second year) biogeography: global plant ecology, carbon and water relations of plants, physiological diversity and global change.
  • Part IB (second year) research methods: modelling; structuring your dissertation
  • Part II (third year undergraduate) biogeography (course coordinator): determinants of terrestrial ecosystem productivity, modelling growth, land use, global modelling of ecosystem dynamics.
  • Undergraduate and postgraduate student research project supervision.
  • Postgraduate: MPhil in Holocene Climates: carbon-temperature feedback over the Holocene; modelling Holocene carbon and surface temperature dynamics.

External activities

  • European Geosciences Union (member)

Possible topic: The role of ecosystem physiological processes in the historical global carbon cycle on land

Terrestrial ecosystems plays a key role in the global carbon cycle, as well as providing humans and other ecosystem trophic levels with essential services. However, we only have a very poor understanding of the global behaviour of their interaction with the atmosphere, including the surface carbon balance. This is despite numerous observational systems collecting data on ecosystem state and behaviour. These observations include in situ fluxes, tree rings, and structural parameters such as height, as well as remote sensing estimates of surface light absorption, leaf area, and atmospheric CO2 dynamics (which can be used to estimate surface fluxes). It is essential that we improve our understanding of past fluxes and their controls in order to inform future projections of both impacts and feedbacks with the atmosphere. Examples of controls on temporal and spatial variability include seasonal drought, temperatures extremes, and storm damage (e.g. across the Amazon rainforest in 2005).

This PhD project will address this problem using a dynamic global vegetation model (see References below). The model will be further developed, tested, and used to better understand the role of climate and atmospheric CO2 on the historical global terrestrial carbon balance. The model exists in different forms that allow the analysis of controls on ecosystem state as a result of climate variability in space and time. The model will be extended to incorporate historical land use change, and simulations will be made of the global distribution of carbon sources and sinks. Comparisons will be made with satellite data (e.g. MODIS), in situ data such as from flux towers, and the dynamics of atmospheric CO2. In addition, collaborations with other research groups will be exploited to compare different model and remote-sensing based estimates of historical carbon fluxes. This will enable the quantification and attribution of uncertainty, and establish methodologies for further improving our understanding of controls on terrestrial ecosystem states and behaviour, particularly their roles in the global carbon cycle.


  • Friend AD et al. 2019. On the need to consider wood formation processes in global vegetation models and a suggested approach. Annals of Forest Science, doi:10.1007/s13595-019-0819-x
  • Friend AD et al. 2014. Carbon residence time dominates uncertainty in terrestrial vegetation responses to future climate and atmospheric CO2. Proceedings of the National Academy of Sciences 111, 3280-3285, doi:10.1073/pnas.1222477110Carbon residence time dominates uncertainty in terrestrial vegetation responses to future climate and atmospheric CO2. Proceedings of the National Academy of Sciences 111, 3280-3285, doi:10.1073/pnas.1222477110
  • Friend AD. 2010. Terrestrial plant production and climate change. Journal of Experimental Botany, 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 18, 2883-2902, doi:10.1175/JCLI3425.1.
  • Friend, A.D. and White, A. 2000. Evaluation and analysis of a dynamic terrestrial ecosystem model under preindustrial conditions at the global scale. Global Biogeochemical Cycles 14(4), 1173-1190.