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A new probabilistic canopy dynamics model (SLCD) that is suitable for evergreen and deciduous forest ecosystems

dc.contributor.authorSainte-Marie, J.
dc.contributor.authorSaint-Andre, L.
dc.contributor.authorNouvellon, Y.
dc.contributor.authorLaclau, Jean Paul [UNESP]
dc.contributor.authorRoupsard, O.
dc.contributor.authorle Maire, G.
dc.contributor.authorDelpierre, N.
dc.contributor.authorHenrot, A.
dc.contributor.authorBarrandon, M.
dc.contributor.institutionUniv Lorraine
dc.contributor.institutionINRA
dc.contributor.institutionCIRAD
dc.contributor.institutionCATIE
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionUniv Paris 11
dc.date.accessioned2015-03-18T15:53:26Z
dc.date.available2015-03-18T15:53:26Z
dc.date.issued2014-10-24
dc.description.abstractThere are strong uncertainties regarding LAI dynamics in forest ecosystems in response to climate change. While empirical growth & yield models (G&YMs) provide good estimations of tree growth at the stand level on a yearly to decennial scale, process-based models (PBMs) use LAI dynamics as a key variable for enabling the accurate prediction of tree growth over short time scales. Bridging the gap between PBMs and G&YMs could improve the prediction of forest growth and, therefore, carbon, water and nutrient fluxes by combining modeling approaches at the stand level.Our study aimed to estimate monthly changes of leaf area in response to climate variations from sparse measurements of foliage area and biomass. A leaf population probabilistic model (SLCD) was designed to simulate foliage renewal. The leaf population was distributed in monthly cohorts, and the total population size was limited depending on forest age and productivity. Foliage dynamics were driven by a foliation function and the probabilities ruling leaf aging or fall. Their formulation depends on the forest environment.The model was applied to three tree species growing under contrasting climates and soil types. In tropical Brazilian evergreen broadleaf eucalypt plantations, the phenology was described using 8 parameters. A multi-objective evolutionary algorithm method (MOEA) was used to fit the model parameters on litterfall and LAI data over an entire stand rotation. Field measurements from a second eucalypt stand were used to validate the model. Seasonal LAI changes were accurately rendered for both sites (R-2 = 0.898 adjustment, R-2 = 0.698 validation). Litterfall production was correctly simulated (R-2 = 0.562, R-2 = 0.4018 validation) and may be improved by using additional validation data in future work. In two French temperate deciduous forests (beech and oak), we adapted phenological sub-modules of the CASTANEA model to simulate canopy dynamics, and SLCD was validated using LAI measurements. The phenological patterns were simulated with good accuracy in the two cases studied. However, IA/max was not accurately simulated in the beech forest, and further improvement is required.Our probabilistic approach is expected to contribute to improving predictions of LAI dynamics. The model formalism is general and suitable to broadleaf forests for a large range of ecological conditions. (C) 2014 Elsevier B.V. All rights reserved.en
dc.description.affiliationUniv Lorraine, UMR Inst Elie Cartan, F-54506 Vandoeuvre Les Nancy, France
dc.description.affiliationINRA, F-54280 Champenoux, France
dc.description.affiliationCIRAD, UMR Eco&Sols, F-34060 Montpellier, France
dc.description.affiliationCATIE, Trop Agr Res & Higher Educ Ctr, Turrialba 7170, Costa Rica
dc.description.affiliationUniv Estadual Sao Paulo, UNESP, Dept Recursos Nat, BR-18610307 Botucatu, SP, Brazil
dc.description.affiliationUniv Sao Paulo, USP, ESALQ, Dept Ciencias Atmosfer,IAG, BR-05508900 Sao Paulo, Brazil
dc.description.affiliationUniv Paris 11, Lab Ecol Systemat & Evolut, UMR8079, F-91405 Orsay, France
dc.description.affiliationUnespUniv Estadual Sao Paulo, UNESP, Dept Recursos Nat, BR-18610307 Botucatu, SP, Brazil
dc.description.sponsorshipMinistere de renseignement superieur et de la recherche
dc.description.sponsorshipUniversite de Lorraine
dc.description.sponsorshipOffice National des Foret
dc.description.sponsorshipFrench National Research Agency (ANR) as part of the "Investissements d'Avenir" program (Lab of Excellence ARBRE)
dc.description.sponsorshipEuropean community (CARBOAFRICA, CLIMAFRICA)
dc.description.sponsorshipFrench national network SOERE F-ORE-T
dc.description.sponsorshipIdFrench National Research Agency (ANR) as part of the Investissements d'Avenir program (Lab of Excellence ARBRE)ANR-11-LABX-0002-01
dc.format.extent121-133
dc.identifierhttp://dx.doi.org/10.1016/j.ecolmodel.2014.01.026
dc.identifier.citationEcological Modelling. Amsterdam: Elsevier Science Bv, v. 290, p. 121-133, 2014.
dc.identifier.doi10.1016/j.ecolmodel.2014.01.026
dc.identifier.issn0304-3800
dc.identifier.urihttp://hdl.handle.net/11449/116507
dc.identifier.wosWOS:000343346000014
dc.language.isoeng
dc.publisherElsevier B.V.
dc.relation.ispartofEcological Modelling
dc.relation.ispartofjcr2.507
dc.relation.ispartofsjr1,084
dc.rights.accessRightsAcesso restrito
dc.sourceWeb of Science
dc.subjectClimate changesen
dc.subjectCanopy dynamicsen
dc.subjectProbabilistic modelen
dc.subjectProcess-based model (PBM)en
dc.subjectGrowth & yield model (G&YM)en
dc.titleA new probabilistic canopy dynamics model (SLCD) that is suitable for evergreen and deciduous forest ecosystemsen
dc.typeArtigo
dcterms.licensehttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dcterms.rightsHolderElsevier B.V.
dspace.entity.typePublication
unesp.author.orcid0000-0003-1920-3847[3]
unesp.author.orcid0000-0002-8108-3519[1]
unesp.campusUniversidade Estadual Paulista (UNESP), Faculdade de Ciências Agronômicas, Botucatupt
unesp.departmentSolos e Recursos Ambientais - FCApt

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