AustralieFrV1, PascalFrancis, Curation, bibRecord, 003E06

Assessing parameter variability in a photosynthesis model within and between plant functional types using global Fluxnet eddy covariance data

Identifieur interne : 003E06 ( PascalFrancis/Curation ); précédent : 003E05; suivant : 003E07

Assessing parameter variability in a photosynthesis model within and between plant functional types using global Fluxnet eddy covariance data

Auteurs : M. Groenendijk [Pays-Bas] ; A. J. Dolman [Pays-Bas] ; M. K. Van Der Molen [Pays-Bas] ; R. Leuning [Australie] ; A. Arneth [Suède] ; N. Delpierre [France] ; J. H. C. Gash [Pays-Bas, Royaume-Uni] ; A. Lindroth [Suède] ; A. D. Richardson [États-Unis] ; H. Verbeeck [Belgique] ; G. Wohlfahrt [Autriche]

Source :

Agricultural and forest meteorology : (Print) [ 0168-1923 ] ; 2011.

RBID : Pascal:11-0032158

Descripteurs français

Pascal (Inist)
- Paramètre, Variabilité, Photosynthèse, Modélisation, Utilisation, Méthode covariance turbulence, Donnée, Transpiration, Biométéorologie, Modèle, Mathématiques appliquées, <<>>.

English descriptors

KwdEn :
- Applied mathematics, Biometeorology, Data, Eddy covariance method, Modeling, Models, Parameter, Photosynthesis, Transpiration, Use, Variability.

Abstract

The vegetation component in climate models has advanced since the late 1960s from a uniform prescription of surface parameters to plant functional types (PFTs). PFTs are used in global land-surface models to provide parameter values for every model grid cell. With a simple photosynthesis model we derive parameters for all site years within the Fluxnet eddy covariance data set. We compare the model parameters within and between PFTs and statistically group the sites. Fluxnet data is used to validate the photosynthesis model parameter variation within a PFT classification. Our major result is that model parameters appear more variable than assumed in PFTs. Simulated fluxes are of higher quality when model parameters of individual sites or site years are used. A simplification with less variation in model parameters results in poorer simulations. This indicates that a PFT classification introduces uncertainty in the variation of the photosynthesis and transpiration fluxes. Statistically derived groups of sites with comparable model parameters do not share common vegetation types or climates. A simple PFT classification does not reflect the real photosynthesis and transpiration variation. Although site year parameters give the best predictions, the parameters are generally too specific to be used in a global study. The site year parameters can be further used to explore the possibilities of alternative classification schemes.

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A08	`01`	`1`	`ENG`	`@1 Assessing parameter variability in a photosynthesis model within and between plant functional types using global Fluxnet eddy covariance data`
A11	`01`	`1`		`@1 GROENENDIJK (M.)`
A11	`02`	`1`		`@1 DOLMAN (A. J.)`
A11	`03`	`1`		`@1 VAN DER MOLEN (M. K.)`
A11	`04`	`1`		`@1 LEUNING (R.)`
A11	`05`	`1`		`@1 ARNETH (A.)`
A11	`06`	`1`		`@1 DELPIERRE (N.)`
A11	`07`	`1`		`@1 GASH (J. H. C.)`
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A14	`01`			`@1 VU University Amsterdam, Hydrology and Geo-Environmental Sciences @3 NLD @Z 1 aut. @Z 2 aut. @Z 3 aut. @Z 7 aut.`
A14	`02`			`@1 CSIRO Marine and Atmospheric Research @2 Canberra @3 AUS @Z 4 aut.`
A14	`03`			`@1 Department of Earth and Ecosystem Sciences, Lund University @3 SWE @Z 5 aut. @Z 8 aut.`
A14	`04`			`@1 Universite Paris-Sud, Laboratoire Ecologie Systematique et Evolution, UMR8079 @2 Orsay 91405 @3 FRA @Z 6 aut.`
A14	`05`			`@1 Centre for Ecology and Hydrology @2 Wallingford @3 GBR @Z 7 aut.`
A14	`06`			`@1 Harvard University, Department of Organismic and Evolutionary Biology, HUH, 22 Divinity Avenue @2 Cambridge, MA 02138 @3 USA @Z 9 aut.`
A14	`07`			`@1 Laboratory of Plant Ecology, Ghent University, Coupure Links 653 @2 9000 Ghent @3 BEL @Z 10 aut.`
A14	`08`			`@1 Institut für Ökologie, Universität Innsbruck @3 AUT @Z 11 aut.`
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C01	`01`		`ENG`	@0 The vegetation component in climate models has advanced since the late 1960s from a uniform prescription of surface parameters to plant functional types (PFTs). PFTs are used in global land-surface models to provide parameter values for every model grid cell. With a simple photosynthesis model we derive parameters for all site years within the Fluxnet eddy covariance data set. We compare the model parameters within and between PFTs and statistically group the sites. Fluxnet data is used to validate the photosynthesis model parameter variation within a PFT classification. Our major result is that model parameters appear more variable than assumed in PFTs. Simulated fluxes are of higher quality when model parameters of individual sites or site years are used. A simplification with less variation in model parameters results in poorer simulations. This indicates that a PFT classification introduces uncertainty in the variation of the photosynthesis and transpiration fluxes. Statistically derived groups of sites with comparable model parameters do not share common vegetation types or climates. A simple PFT classification does not reflect the real photosynthesis and transpiration variation. Although site year parameters give the best predictions, the parameters are generally too specific to be used in a global study. The site year parameters can be further used to explore the possibilities of alternative classification schemes.
C02	`01`	`X`		`@0 002A32C03`
C03	`01`	`X`	`FRE`	`@0 Paramètre @5 01`
C03	`01`	`X`	`ENG`	`@0 Parameter @5 01`
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C03	`02`	`X`	`SPA`	`@0 Variabilidad @5 02`
C03	`03`	`X`	`FRE`	`@0 Photosynthèse @5 03`
C03	`03`	`X`	`ENG`	`@0 Photosynthesis @5 03`
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C03	`04`	`X`	`FRE`	`@0 Modélisation @5 04`
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C03	`07`	`X`	`FRE`	`@0 Donnée @5 07`
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C03	`07`	`X`	`SPA`	`@0 Dato @5 07`
C03	`08`	`X`	`FRE`	`@0 Transpiration @5 08`
C03	`08`	`X`	`ENG`	`@0 Transpiration @5 08`
C03	`08`	`X`	`SPA`	`@0 Transpiración @5 08`
C03	`09`	`X`	`FRE`	`@0 Biométéorologie @5 09`
C03	`09`	`X`	`ENG`	`@0 Biometeorology @5 09`
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C03	`11`	`X`	`FRE`	`@0 Mathématiques appliquées @5 29`
C03	`11`	`X`	`ENG`	`@0 Applied mathematics @5 29`
C03	`11`	`X`	`SPA`	`@0 Matemáticas aplicadas @5 29`
C03	`12`	`X`	`FRE`	`@0 <<>> @4 INC @5 68`
C07	`01`	`X`	`FRE`	`@0 Méthode statistique @5 33`
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C07	`01`	`X`	`SPA`	`@0 Método estadístico @5 33`
N21				`@1 024`
N44	`01`			`@1 OTO`
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Pascal:11-0032158

Le document en format XML

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<term>Models</term>
<term>Parameter</term>
<term>Photosynthesis</term>
<term>Transpiration</term>
<term>Use</term>
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<keywords scheme="Pascal" xml:lang="fr"><term>Paramètre</term>
<term>Variabilité</term>
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<term>Méthode covariance turbulence</term>
<term>Donnée</term>
<term>Transpiration</term>
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<front><div type="abstract" xml:lang="en">The vegetation component in climate models has advanced since the late 1960s from a uniform prescription of surface parameters to plant functional types (PFTs). PFTs are used in global land-surface models to provide parameter values for every model grid cell. With a simple photosynthesis model we derive parameters for all site years within the Fluxnet eddy covariance data set. We compare the model parameters within and between PFTs and statistically group the sites. Fluxnet data is used to validate the photosynthesis model parameter variation within a PFT classification. Our major result is that model parameters appear more variable than assumed in PFTs. Simulated fluxes are of higher quality when model parameters of individual sites or site years are used. A simplification with less variation in model parameters results in poorer simulations. This indicates that a PFT classification introduces uncertainty in the variation of the photosynthesis and transpiration fluxes. Statistically derived groups of sites with comparable model parameters do not share common vegetation types or climates. A simple PFT classification does not reflect the real photosynthesis and transpiration variation. Although site year parameters give the best predictions, the parameters are generally too specific to be used in a global study. The site year parameters can be further used to explore the possibilities of alternative classification schemes.</div>
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<fA08 i1="01" i2="1" l="ENG"><s1>Assessing parameter variability in a photosynthesis model within and between plant functional types using global Fluxnet eddy covariance data</s1>
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Assessing parameter variability in a photosynthesis model within and between plant functional types using global Fluxnet eddy covariance data

Assessing parameter variability in a photosynthesis model within and between plant functional types using global Fluxnet eddy covariance data

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