Covariations between plant functional traits emerge from constraining parameterization of a terrestrial biosphere model

Research output: Contribution to journalArticle


Aim: The mechanisms of plant trait adaptation and acclimation are still poorly understood and, consequently, lack a consistent representation in terrestrial biosphere models (TBMs). Despite the increasing availability of geo-referenced trait observations, current databases are still insufficient to cover all vegetation types and environmental conditions. In parallel, the growing number of continuous eddy-covariance observations of energy and CO2 fluxes has enabled modellers to optimize TBMs with these data. Past attempts to optimize TBM parameters mostly focused on model performance, overlooking the ecological properties of ecosystems. The aim of this study was to assess the ecological consistency of optimized trait-related parameters while improving the model performances for gross primary productivity (GPP) at sites. Location: Worldwide. Time period: 1992–2012. Major taxa studied: Trees and C3 grasses. Methods: We optimized parameters of the ORCHIDEE model against 371 site-years of GPP estimates from the FLUXNET network, and we looked at global covariation among parameters and with climate. Results: The optimized parameter values were shown to be consistent with leaf-scale traits, in particular, with well-known trade-offs observed at the leaf level, echoing the leaf economic spectrum theory. Results showed a marked sensitivity of trait-related parameters to local bioclimatic variables and reproduced the observed relationships between traits and climate. Main conclusions: Our approach validates some biological processes implemented in the model and enables us to study ecological properties of vegetation at the canopy level, in addition to some traits that are difficult to observe experimentally. This study stresses the need for: (a) implementing explicit trade-offs and acclimation processes in TBMs; (b) improving the representation of processes to avoid model-specific parameterization; and (c) performing systematic measurements of traits at FLUXNET sites in order to gather information on plant ecophysiology and plant diversity, together with micro-meteorological conditions.


  • Marc Peaucelle
  • Cédric Bacour
  • Philippe Ciais
  • Nicolas Vuichard
  • Sylvain Kuppel
  • Josep Peñuelas
  • Luca Belelli Marchesini
  • Peter D. Blanken
  • Nina Buchmann
  • Jiquan Chen
  • Nicolas Delpierre
  • Ankur R. Desai
  • Eric Dufrene
  • Damiano Gianelle
  • Cristina Gimeno-Colera
  • Carsten Gruening
  • Carole Helfter
  • Lukas Hörtnagl
  • Andreas Ibrom
  • Richard Joffre
  • Tomomichi Kato
  • Thomas E. Kolb
  • Beverly Law
  • Ivan Mammarella
  • Lutz Merbold
  • Stefano Minerbi
  • Leonardo Montagnani
  • Ladislav Šigut
  • Mark Sutton
  • Andrej Varlagin
  • Timo Vesala
  • Georg Wohlfahrt
  • Sebastian Wolf
  • Dan Yakir
  • Nicolas Viovy
External organisations
  • Centre for Ecological Research and Forestry (CERAF)
  • University of Aberdeen
  • Edmund Mach Foundation
  • RUDN University
  • University of Colorado
  • ETH Zürich
  • Michigan State University
  • University of Paris-Sud
  • University of Wisconsin-Madison
  • Fundacion Centro de Estudios Ambientales del Mediterraneo (CEAM)
  • Centre for Ecology & Hydrology, Wallingford
  • Technical University of Denmark
  • Hokkaido University
  • Northern Arizona University
  • Oregon State University
  • University of Helsinki
  • International Livestock Research Institute Nairobi
  • Forest Services, Autonomous Province of Bolzano
  • Free University of Bozen-Bolzano
  • A.N. Severtsov Institute of Ecology and Evolution, RAS
  • University of Innsbruck
  • Weizmann Institute of Science Israel
  • Laboratoire des Sciences du Climat et de l'Environnement
  • University of Paris-Saclay
  • European Commission Joint Research Centre, Ispra
  • University of Montpellier
  • Paul Valéry University of Montpellier
  • Global Change Research Centre of the Czech Academy of Sciences
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Ecology


  • data assimilation, optimization, ORCHIDEE, plant acclimation, plant functional traits, terrestrial model
Original languageEnglish
Pages (from-to)1351-1365
JournalGlobal Ecology and Biogeography
Issue number9
Early online date2019 Jun 30
Publication statusPublished - 2019
Publication categoryResearch