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20.5. Prentice

Keynote Presentations at the GREENCYCLESII Summer School, Peyresq 15 - 24 May 2011


Speaker: Colin Prentice

colin.prentice -at-
c.prentice -at-

Macquarie University, Department of Biological Sciences, Faculty of Science, North Ryde NSW 2109, Australia and
Imperial College London, Silwood Park Campus, Ascot SL5 7PY, UK
Personal webpage


Title of the talk: Plant functional ecology for next-generation Earth System modelling (pdf: 11MB)



Plant functional ecology for next-generation Earth System modelling

Dynamic global vegetation models (DGVMs) were developed in the 1990s by fusion of elements from different modelling strands: terrestrial biogeochemical models like CENTURY, TEM and BIOME-BGC, biogeography models like BIOME, regional vegetation dynamics models (‘gap models’) like JABOWA and FORET, and biophsyical land-surface models like SIB and BATS. DGVMs came to prominence through model intercomparisons highlighted in the IPCC Third and Fourth Assessment Reports. In this context, their main application has been to the global carbon cycle and, in particular, assessment of the causes and future evolution of the land carbon sink. Most work on the evaluation of DGVMs has similarly focused on the models’ ability to reproduce large-scale observed features of the carbon cycle, including seasonal cycles, interannual variability and trends in atmospheric CO2 concentration as measured at remote sampling stations, and land-atmosphere CO2 fluxes as measured at flux towers. Valuable tests of models also can be based on the models’ predictions of other observed quantitaties such as “greenness” (fraction of absorbed photosynthetically active radiation, fAPAR) and runoff. Such data-model comparisons should be essential benchmarks for modelling.

I will argue that the current state of the art in dynamic global vegetation modelling is unsatisfactory on two counts. First, much of the “uncertainty” (i.e. differences among the predictions of different models) in the terrestrial carbon cycle is probably illusory because many models have not been adequately benchmarked. The quality and diversity of Earth System observations now available suggests the possibility of using these observations far more systematically to narrow this uncertainty. Second, the design of DGVMs reflects the state of knowledge in plant functional ecology circa 1990. Enormous advances have been made since then, both in fundamental ecophysiological process understanding and in the volume of information describing quantitative plant functional traits across species and functional types. As an illustration of the latter, the TRY plant trait data base (which is still growing rapidly) already contains well over 2 million entries, referring to almost 70,000 species—about a fifth of the entire world’s flora. Quantitative trait information has been used to establish empirical relationships, such as the leaf economics spectrum, which provide additional robust information for large-scale vegetation modelling. Much of the data collection effort has been justified to funding agencies by the need to provide improved comparative ecological information for DGVMs; but DGVMs have not actually used the data!

The time has arrived for a new generation of DGVMs, to be based on a more solid theoretical and empirical foundation. Next-generation models should be able to tackle some questions originally envisaged to be addressed with such models, e.g. transient biome boundary shifts, which current models struggle to represent. I will illustrate this proposition with examples of particular processes, including stomatal behaviour, the key plant-mediated link between the carbon and water cycles; heat stress tolerance, a topic of great relevance to global change yet absent from current models; and fire, a near-ubiquitous natural phenomenon now subject to complex influences of human actions. In all these cases, new knowledge suggests formulations of processes that look very different from the conventional ones.


Recommended background literature on this presentation:

Most important:
  • Wright IJ, Reich PB, Westoby M, Ackerly DD, Baruch Z, Bongers F, Cavender-Bares J, Chapin T, Cornelissen JHC, Diemer M, Flexas J, Garnier E, Groom PK, Gulias J, Hikosaka K, Lamont BB, Lee T, Lee W, Lusk C, Midgley JJ, Navas ML, Niinemets U, Oleksyn J, Osada N, Poorter H, Poot P, Prior L, Pyankov VI, Roumet C, Thomas SC, Tjoelker MG, Veneklaas EJ, Villar R (2004) The worldwide leaf economics spectrum. Nature 428:821-827, doi:10.1038/nature02403
  • Denman KL, Brasseur G, Chidthaisong A, Ciais P, Cox PM, Dickinson RE, Hauglustaine D, Heinze C, Holland E, Jacob D, Lohmann U, Ramachandran S, Leite da Silva Dias P, Wofsy SC, Zhang X (2007) Couplings between changes in the climate system and biogeochemistry. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller (eds.)] Cambridge University Press, Cambridge.
  • Prentice IC, Bondeau A, Cramer W, Harrison SP, Hickler T, Lucht W, Sitch S, Smith B, Sykes MT (2007) Dynamic global vegetation modelling : quantifying terrestrial ecosystem responses to large-scale environmental change. In: J. Canadell, L. Pitelka and D. Pataki (eds) Terrestrial Ecosystems in a Changing World, Springer-Verlag, Berlin, pp. 175-192.
  • Prentice IC (2010) The burning issue. Science 330:1636-1637, doi:10.1126/science.1199809

If you have more time:
  • Cramer W, Bondeau A, Woodward FI, Prentice IC, Betts RA, Brovkin V, V. Cox PM, Fisher V, Foley J, Friend AD, Kucharik C, Lomas MR, Ramankutty N, Sitch S, Smith B, White A, Young-Molling C (2001) Global responses of terrestrial ecosystems to changes in CO2 and climate. Global Change Biology 7:357-373, doi:10.1046/j.1365-2486.2001.00383.x
  • Prentice IC, Farquhar GD, Fasham MJR, Goulden ML, Heimann M, Jaramillo VJ, Kheshgi HS, Le Quéré C, Scholes RJ, Wallace DWR (2001) The carbon cycle and atmospheric carbon dioxide. In Houghton JT, Ding Y, Griggs DJ, Noguer M, van der Linden PJ, Dai X, Maskell K, Johnson CA (eds) Climate Change 2001: The Scientific Basis. Cambridge University Press, Cambridge, pp. 183-237.
  • Sitch S, Smith B, Prentice IC, Arneth A, Bondeau A, Cramer W, Kaplan JO, Levis S, Lucht W, Sykes MT, Thonicke K, Venevsky S (2003) Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model. Global Change Biology 9:161-185, doi:10.1046/j.1365-2486.2003.00569.x
  • Friedlingstein P, Cox P, Betts R, Bopp L, Von Bloh W, Brovkin V, Cadule P, Doney S, Eby M, Fung I, Bala G, John J, Jones C, Joos F, Kato T, Kawamiya M, Knorr W, Lindsay K, Matthews HD, Raddatz T, Rayner P, Reick C, Roeckner E, Schnitzler KG, Schnur R, Strassmann K, Weaver AJ, Yoshikawa C, Zeng N, (2006) Climate-carbon cycle feedback analysis: Results from the (CMIP)-M-4 model intercomparison. J Clim 19:3337–3353
  • Marlon JR, Bartlein PJ, Carcaillet C, Gavin DG, Harrison SP, Higuera PE, Joos F, Power MJ, Prentice IC (2008) Climate and human influences on biomass burning over the past two millennia. Nature Geoscience 1:697-702, doi:10.1038/ngeo313
  • Sitch S, Huntingford C, Gedney N, Levy PE, Lomas M, Piao S, Betts R, Ciais P, Cox P, Friedlingstein P, Jones CD, Prentice IC, Woodward FI (2008) Evaluation of the terrestrial carbon cycle, future plant geography and climate-carbon cycle feedbacks using 5 Dynamic Global Vegetation Models (DGVMs). Global Change Biology 14:2015-2039, doi:10.1111/j.1365-2486.2008.01626.x
  • Medlyn BE, Duursma RA, Eamus D, Ellsworth DS, Prentice IC, Barton CVM, Crous KY, De Angelis P, Freeman M, Wingate L (2011) Reconciling the optimal and empirical approaches to modelling stomatal conductance. Global Change Biology doi:10.1111/j.1365-2486.2010.02375.x

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