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AOBPreview originally published online on August 13, 2009
Annals of Botany 2009 104(5):883-896; doi:10.1093/aob/mcp189
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© The Author 2009. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Identifying ontogenetic, environmental and individual components of forest tree growth

Florence Chaubert-Pereira1, Yves Caraglio2, Christian Lavergne3 and Yann Guédon1,*

1 CIRAD, UMR Développement et Amélioration des Plantes and INRIA, Virtual Plants, TA A-96/02, 34398 Montpellier Cedex 5, France
2 CIRAD, UMR botanique et bioinformatique de l'Architecture des Plantes, TA A-51/PS2, 34398 Montpellier Cedex 5, France
3 Montpellier 3 University, Institut de Mathématiques et de Modélisation de Montpellier, Place Eugène Bataillon, 34095 Montpellier Cedex 5, France

* For correspondence. E-mail guedon{at}cirad.fr

Received: 3 April 2009    Returned for revision: 3 June 2009    Accepted: 17 June 2009    Published electronically: 13 August 2009

Background and Aims: This study aimed to identify and characterize the ontogenetic, environmental and individual components of forest tree growth. In the proposed approach, the tree growth data typically correspond to the retrospective measurement of annual shoot characteristics (e.g. length) along the trunk.

Methods: Dedicated statistical models (semi-Markov switching linear mixed models) were applied to data sets of Corsican pine and sessile oak. In the semi-Markov switching linear mixed models estimated from these data sets, the underlying semi-Markov chain represents both the succession of growth phases and their lengths, while the linear mixed models represent both the influence of climatic factors and the inter-individual heterogeneity within each growth phase.

Key Results: On the basis of these integrative statistical models, it is shown that growth phases are not only defined by average growth level but also by growth fluctuation amplitudes in response to climatic factors and inter-individual heterogeneity and that the individual tree status within the population may change between phases. Species plasticity affected the response to climatic factors while tree origin, sampling strategy and silvicultural interventions impacted inter-individual heterogeneity.

Conclusions: The transposition of the proposed integrative statistical modelling approach to cambial growth in relation to climatic factors and the study of the relationship between apical growth and cambial growth constitute the next steps in this research.

Key words: Growth components, inter-individual heterogeneity, linear mixed model, ontogeny, Pinus nigra subsp. laricio var. corsicana, Quercus petraea, semi-Markov switching model


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