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Modelling diameter class distribution with a second-order matrix model.

Abstract : Matrix models of forest dynamics rely on four hypotheses: independence hypothesis, Markov's hypothesis, Usher's hypothesis, and temporal homogeneity hypothesis. We investigate the consequences of relaxing Markov's hypothesis, allowing the state of the tree at time t to depend on its states at time t-1 and t-2. The methodology for building and testing the relevance of second-order matrix model is thus proposed. The derivation of second-order transition probabilities turns to be sensitive to the width of the diameter classes. A strategy for choosing diameter classes is proposed. A second-order matrix model is then built for a tropical rain-forest in French Guiana. A different behaviour is detected between small (dbh =30 cm) and large trees, the smaller trees being more sensitive to their past history: small trees that have well grown have a tendency to grow well again, and small trees that have not grown tend to have a higher probability to die. The widths of the diameter classes that are selected are much less than the widths usually retained, that favour first-order selection.
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Contributor : Christophe Godin Connect in order to contact the contributor
Submitted on : Wednesday, May 29, 2013 - 11:32:46 AM
Last modification on : Wednesday, November 3, 2021 - 1:12:05 PM



Nicolas Picard, Avner Bar-Hen, Yann Guédon. Modelling diameter class distribution with a second-order matrix model.. Forest Ecology and Management, Elsevier, 2003, 180 (1-3), pp.389-400. ⟨10.1016/S0378-1127(02)00653-9⟩. ⟨hal-00827463⟩



Les métriques sont temporairement indisponibles