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Seasonal variation of photosynthetic model parameters and leaf area index from global Fluxnet eddy covariance data

Groenendijk M., Dolman A. Johannes, Ammann Christof, Arneth Almur, Cescatti Alessandro, Dragoni D., Gash J.H.C., Gianelle Damiano, Gioli Beniamino, Kiely Gérard, Knohl Alexander, Law Beverly, Lund Magnus, Marcolla Barbara, Van der Molen Michiel K., Montagnani Leonardo, Moors Eddy J., Richardson Andrew D., Roupsard Olivier, Verbeeck Hans, Wohlfahrt Georg. 2011. Seasonal variation of photosynthetic model parameters and leaf area index from global Fluxnet eddy covariance data. Journal of Geophysical Research. Biogeosciences, 116 (G4), 18 p.

Journal article ; Article de recherche ; Article de revue à facteur d'impact
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Quartile : Q1, Sujet : GEOSCIENCES, MULTIDISCIPLINARY

Abstract : Global vegetation models require the photosynthetic parameters, maximum carboxylation capacity (Vcm), and quantum yield (a) to parameterize their plant functional types (PFTs). The purpose of this work is to determine how much the scaling of the parameters from leaf to ecosystem level through a seasonally varying leaf area index (LAI) explains the parameter variation within and between PFTs. Using Fluxnet data, we simulate a seasonally variable LAIF for a large range of sites, comparable to the LAIM derived from MODIS. There are discrepancies when LAIF reach zero levels and LAIM still provides a small positive value. We find that temperature is the most common constraint for LAIF in 55% of the simulations, while global radiation and vapor pressure deficit are the key constraints for 18% and 27% of the simulations, respectively, while large differences in this forcing still exist when looking at specific PFTs. Despite these differences, the annual photosynthesis simulations are comparable when using LAIF or LAIM (r2 = 0.89). We investigated further the seasonal variation of ecosystem‐scale parameters derived with LAIF. Vcm has the largest seasonal variation. This holds for all vegetation types and climates. The parameter a is less variable. By including ecosystem‐scale parameter seasonality we can explain a considerable part of the ecosystem‐scale parameter variation between PFTs. The remaining unexplained leaf‐scale PFT variation still needs further work, including elucidating the precise role of leaf and soil level nitrogen.

Classification Agris : F40 - Plant ecology
F62 - Plant physiology - Growth and development
P40 - Meteorology and climatology
U10 - Mathematical and statistical methods

Champ stratégique Cirad : Axe 6 (2005-2013) - Agriculture, environnement, nature et sociétés

Auteurs et affiliations

  • Groenendijk M., Université d'Amsterdam (NLD)
  • Dolman A. Johannes, Vrije Universiteit (NLD)
  • Ammann Christof, ACW (CHE)
  • Arneth Almur, Lund University (SWE)
  • Cescatti Alessandro, IES (ITA)
  • Dragoni D., Indiana University (USA)
  • Gash J.H.C., Université d'Amsterdam (NLD)
  • Gianelle Damiano, IASMA (ITA)
  • Gioli Beniamino, CNR (ITA)
  • Kiely Gérard, UCC (IRL)
  • Knohl Alexander, University of Göttingen (DEU)
  • Law Beverly, Oregon State University (USA)
  • Lund Magnus, Aarhus University (DNK)
  • Marcolla Barbara, IASMA (ITA)
  • Van der Molen Michiel K., Vrije Universiteit (NLD)
  • Montagnani Leonardo, University of Lund (SWE)
  • Moors Eddy J., Wageningen University (NLD)
  • Richardson Andrew D., Harvard University (USA)
  • Roupsard Olivier, CIRAD-PERSYST-UMR Eco&Sols (CRI)
  • Verbeeck Hans, University of Ghent (BEL)
  • Wohlfahrt Georg, Institute of Ecology (AUT)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/579977/)

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