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Global comparison of light use efficiency models for simulating terrestrial vegetation gross primary production based on the LaThuile database

Yuan Wenping, Cai Wenwen, Xia Jiangzhou, Chen Jiquan, Liu Shuguang, Dong Wenjie, Merbold Lutz, Law Beverly, Arain M.H., Beringer Jason, Bernhofer Christian, Black Andy, Blanken Peter D., Cescatti Alessandro, Chen Yang, François Louis, Gianelle Damiano, Janssens Ivan A., Jung Martin, Kato Tomomichi, Kiely Gérard, Liu Dan, Marcolla Barbara, Montagnani Leonardo, Raschi Antonio, Roupsard Olivier, Varlagin Andrej, Wohlfahrt Georg. 2014. Global comparison of light use efficiency models for simulating terrestrial vegetation gross primary production based on the LaThuile database. Agricultural and Forest Meteorology, 192-193 : pp. 108-120.

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Quartile : Q1, Sujet : FORESTRY / Quartile : Q1, Sujet : AGRONOMY / Quartile : Q1, Sujet : METEOROLOGY & ATMOSPHERIC SCIENCES

Abstract : Simulating gross primary productivity (GPP) of terrestrial ecosystems has been a major challenge inquantifying the global carbon cycle. Many different light use efficiency (LUE) models have been developedrecently, but our understanding of the relative merits of different models remains limited. Using CO2fluxmeasurements from multiple eddy covariance sites, we here compared and assessed major algorithmsand performance of seven LUE models (CASA, CFix, CFlux, EC-LUE, MODIS, VPM and VPRM). Comparisonbetween simulated GPP and estimated GPP from flux measurements showed that model performancediffered substantially among ecosystem types. In general, most models performed better in capturingthe temporal changes and magnitude of GPP in deciduous broadleaf forests and mixed forests than in evergreen broadleaf forests and shrublands. Six of the seven LUE models significantly underestimatedGPP during cloudy days because the impacts of diffuse radiation on light use efficiency were ignoredin the models. CFlux and EC-LUE exhibited the lowest root mean square error among all models at 80%and 75% of the sites, respectively. Moreover, these two models showed better performance than othersin simulating interannual variability of GPP. Two pairwise comparisons revealed that the seven modelsdiffered substantially in algorithms describing the environmental regulations, particularly water stress,on GPP. This analysis highlights the need to improve representation of the impacts of diffuse radiationand water stress in the LUE models. (Résumé d'auteur)

Mots-clés Agrovoc : Lumière, Efficacité, Utilisation, Modèle mathématique, Télédétection, Température, Végétation, Stress thermique, Stress dû à la sécheresse, Plante, Forêt, forêt mélangée, forêt feuillue, forêt résineuse, forêt tropicale, Arbuste, Prairie

Mots-clés géographiques Agrovoc : Chine

Classification Agris : F62 - Plant physiology - Growth and development
U10 - Mathematical and statistical methods
U40 - Surveying methods

Champ stratégique Cirad : Axe 6 (2014-2018) - Sociétés, natures et territoires

Auteurs et affiliations

  • Yuan Wenping, Beijing Normal University (CHN)
  • Cai Wenwen, Beijing Normal University (CHN)
  • Xia Jiangzhou, Beijing Normal University (CHN)
  • Chen Jiquan, Nanjing University of Information Science and Technology (CHN)
  • Liu Shuguang, Central South University of Forestry and Technology (CHN)
  • Dong Wenjie, Beijing Normal University (CHN)
  • Merbold Lutz, ETH (CHE)
  • Law Beverly, Oregon State University (USA)
  • Arain M.H., McMaster University (CAN)
  • Beringer Jason, Monash University (AUS)
  • Bernhofer Christian, Technische Universität Dresden (DEU)
  • Black Andy, University of British Columbia (CAN)
  • Blanken Peter D., University of Colorado (USA)
  • Cescatti Alessandro, IES (ITA)
  • Chen Yang, Beijing Normal University (CHN)
  • François Louis, Université de Liège (BEL)
  • Gianelle Damiano, IASMA (ITA)
  • Janssens Ivan A., Universiteit van Antwerpen (BEL)
  • Jung Martin, Max Planck Institut für Biogeochemie (DEU)
  • Kato Tomomichi, IPSL (FRA)
  • Kiely Gérard, UCC (IRL)
  • Liu Dan, Beijing Normal University (CHN)
  • Marcolla Barbara, IASMA (ITA)
  • Montagnani Leonardo, Forest Services and Agency for the Environment (ITA)
  • Raschi Antonio, CNR (ITA)
  • Roupsard Olivier, CIRAD-PERSYST-UMR Eco&Sols (CRI)
  • Varlagin Andrej, Russian Academy of Sciences (RUS)
  • Wohlfahrt Georg, Institute of Ecology (AUT)

Source : Cirad - Agritrop (https://agritrop.cirad.fr/573164/)

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