Reference : Can principal component analysis be used to predict the dynamics of a strongly non-li...
Scientific journals : Article
Life sciences : Environmental sciences & ecology
http://hdl.handle.net/2268/4304
Can principal component analysis be used to predict the dynamics of a strongly non-linear marine biogeochemical model?
English
Raick, Caroline [Université de Liège - ULg > Département des sciences et gestion de l'environnement > Océanologie >]
Beckers, Jean-Marie mailto [Université de Liège - ULg > Département d'astrophys.]
Soetaert, Karline [Netherlands Institute of Ecology > Center for Estuarine and Marine Ecology > > >]
Grégoire, Marilaure mailto [Université de Liège - ULg > Département des sciences et gestion de l'environnement > Océanologie >]
25-Jul-2006
Ecological Modelling
Elsevier Science Bv
196
3-4
345-364
Yes (verified by ORBi)
International
0304-3800
Amsterdam
[en] marine ecosystem models ; reduction of model complexity ; principal component analysis
[en] In the framework of model complexity reduction, we investigate the ability of the principal component analysis technique to represent in a compact form the dynamics of a coupled physical-ecosystem model. The biogeochemical model describes the evolution in time and depth of the partly decoupled nitrogen and carbon cycles of the pelagic food web in the Ligurian Sea (North Western Mediterranean Sea) through 19 biogeochemical state variables. The GHER hydrodynamic model (1D version) is used to represent the physical forcings. The coupled model presents a high variability in time and space that can be decomposed in modes by principal component analysis. To investigate the possibility of being represented in a compact form, the model is constrained to evolve in a reduced space spanned by its most dominant modes of variability that are the empirical orthogonal functions (EOFs). Different orthogonal bases (formed by 1D and OD EOFs) are used to investigate the performance and realism of the method. 1D vertical EOFs show a tendency to impose a spatial structure to model results according to the most dominant EOFs. In the case of OD EOFs, results of the reduced model can be very close to the original one, but it requires a large number of modes. (c) 2006 Elsevier B.V. All rights reserved.
Centre Interfacultaire de Recherches en Océanologie - MARE - GHER
http://hdl.handle.net/2268/4304
10.1016/j.ecolmodel.2006.02.014

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