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Modelling forest management within a global vegetation model—Part 2: Model validation from a tree to a continental scale

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  • Bellassen, V.
  • le Maire, G.
  • Guin, O.
  • Dhôte, J.F.
  • Ciais, P.
  • Viovy, N.

Abstract

The construction of a new forest management module (FMM) within the ORCHIDEE global vegetation model (GVM) allows a realistic simulation of biomass changes during the life cycle of a forest, which makes many biomass datasets suitable as validation data for the coupled ORCHIDEE-FM GVM. This study uses three datasets to validate ORCHIDEE-FM at different temporal and spatial scales: permanent monitoring plots, yield tables, and the French national inventory data. The last dataset has sufficient geospatial coverage to allow a novel type of validation: inventory plots can be used to produce continuous maps that can be compared to continuous simulations for regional trends in standing volumes and volume increments. ORCHIDEE-FM performs better than simple statistical models for stand-level variables, which include tree density, basal area, standing volume, average circumference and height, when management intensity and initial conditions are known: model efficiency is improved by an average of 0.11, and its average bias does not exceed 25%. The performance of the model is less satisfying for tree-level variables, including extreme circumferences, tree circumference distribution and competition indices, or when management and initial conditions are unknown. At the regional level, when climate forcing is accurate for precipitation, ORCHIDEE-FM is able to reproduce most productivity patterns in France, such as the local lows of needleleaves in the Parisian basin and of broadleaves in south-central France. The simulation of water stress effects on biomass in the Mediterranean region, however, remains problematic, as does the simulation of the wood increment for coniferous trees. These pitfalls pertain to the general ORCHIDEE model rather than to the FMM. Overall, with an average bias seldom exceeding 40%, the performance of ORCHIDEE-FM is deemed reliable to use it as a new modelling tool in the study of the effects of interactions between forest management and climate on biomass stocks of forests across a range of scales from plot to country.

Suggested Citation

  • Bellassen, V. & le Maire, G. & Guin, O. & Dhôte, J.F. & Ciais, P. & Viovy, N., 2011. "Modelling forest management within a global vegetation model—Part 2: Model validation from a tree to a continental scale," Ecological Modelling, Elsevier, vol. 222(1), pages 57-75.
    • Handle: RePEc:eee:ecomod:v:222:y:2011:i:1:p:57-75
    DOI: 10.1016/j.ecolmodel.2010.08.038
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    References listed on IDEAS

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    1. Bellassen, V. & Le Maire, G. & Dhôte, J.F. & Ciais, P. & Viovy, N., 2010. "Modelling forest management within a global vegetation model—Part 1: Model structure and general behaviour," Ecological Modelling, Elsevier, vol. 221(20), pages 2458-2474.
    2. Sato, Hisashi & Itoh, Akihiko & Kohyama, Takashi, 2007. "SEIB–DGVM: A new Dynamic Global Vegetation Model using a spatially explicit individual-based approach," Ecological Modelling, Elsevier, vol. 200(3), pages 279-307.
    3. Böttcher, Hannes & Freibauer, Annette & Obersteiner, Michael & Schulze, Ernst-Detlef, 2008. "Uncertainty analysis of climate change mitigation options in the forestry sector using a generic carbon budget model," Ecological Modelling, Elsevier, vol. 213(1), pages 45-62.
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    Cited by:

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    2. Joetzjer, Emilie & Maignan, Fabienne & Chave, Jérôme & Goll, Daniel & Poulter, Ben & Barichivich, Jonathan & Maréchaux, Isabelle & Luyssaert, Sebastiaan & Guimberteau, Matthieu & Naudts, Kim & Bonal, , 2022. "Effect of tree demography and flexible root water uptake for modeling the carbon and water cycles of Amazonia," Ecological Modelling, Elsevier, vol. 469(C).
    3. Sainte-Marie, J. & Saint-André, L. & Nouvellon, Y. & Laclau, J.-P. & Roupsard, O. & le Maire, G. & Delpierre, N. & Henrot, A. & Barrandon, M., 2014. "A new probabilistic canopy dynamics model (SLCD) that is suitable for evergreen and deciduous forest ecosystems," Ecological Modelling, Elsevier, vol. 290(C), pages 121-133.

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