Markov and semi-markov switching linear mixed models used to identify forest Tree growth components

Chaubert-Pereira Florence, Guédon Yann, Lavergne Christian, Trottier Catherine. 2010. Markov and semi-markov switching linear mixed models used to identify forest Tree growth components. Biometrics, 66 (3) : 753-762.

Quartile : Q1, Sujet : STATISTICS & PROBABILITY / Quartile : Q2, Sujet : BIOLOGY / Quartile : Q3, Sujet : MATHEMATICAL & COMPUTATIONAL BIOLOGY

Résumé : Tree growth is assumed to be mainly the result of three components: (i) an endogenous component assumed to be structured as a succession of roughly stationary phases separated by marked change points that are asynchronous among individuals, (ii) a time-varying environmental component assumed to take the form of synchronous fluctuations among individuals, and (iii) an individual component corresponding mainly to the local environment of each tree. To identify and characterize these three components, we propose to use semi-Markov switching linear mixed models, i.e., models that combine linear mixed models in a semi-Markovian manner. The underlying semi-Markov chain represents the succession of growth phases and their lengths (endogenous component) whereas the linear mixed models attached to each state of the underlying semi-Markov chain represent-in the corresponding growth phase-both the influence of time-varying climatic covariates (environmental component) as fixed effects, and interindividual heterogeneity (individual component) as random effects. In this article, we address the estimation of Markov and semi-Markov switching linear mixed models in a general framework. We propose a Monte Carlo expectation-maximization like algorithm whose iterations decompose into three steps: (i) sampling of state sequences given random effects, (ii) prediction of random effects given state sequences, and (iii) maximization. The proposed statistical modeling approach is illustrated by the analysis of successive annual shoots along Corsican pine trunks influenced by climatic covariates.

Mots-clés Agrovoc : Pinus nigra, arbre forestier

Mots-clés géographiques Agrovoc : Centre (France)

Mots-clés complémentaires : Pinus laricio

Classification Agris : U10 - Informatique, mathématiques et statistiques
K01 - Foresterie - Considérations générales
F62 - Physiologie végétale - Croissance et développement

Champ stratégique Cirad : Axe 1 (2005-2013) - Intensification écologique

Auteurs et affiliations

• Chaubert-Pereira Florence, INRIA (FRA)
• Guédon Yann, CIRAD-BIOS-UMR DAP (FRA)
• Lavergne Christian, UM2 (FRA)
• Trottier Catherine, UM2 (FRA)

Source : Cirad - Agritrop (https://agritrop.cirad.fr/558286/)

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