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International Journal of Forestry Research
Volume 2012, Article ID 902381, 12 pages
Research Article

Modeling Dominant Height Growth in Planted Pinus pinea Stands in Northwest of Tunisia

1National Institute of Research in Rural Genius, Waters and Forests, BP 10, Ariana 2080, Tunisia
2Mediterranean Regional Office of the European Forest Institute (EFIMED), Sant Pau Historic Site, Santa Victoria Pavilion, St. Antoni M. Claret, 167, 08025 Barcelona, Spain
3Forest Science Center of Catalonia (CTFC), Ctra. de Sant Llorenç de Morunys, Km 2, 25280 Solsona, Spain
4University of Lleida, Avenida Rovira Roure 177, 25198 Lleida, Spain

Received 27 July 2011; Accepted 4 October 2011

Academic Editor: John Sessions

Copyright © 2012 Sghaier Tahar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Six generalized algebraic difference equations (GADAs) derived from the base models of log-logistic, Bertalanffy-Richards, and Lundqvist-Korf were used to develop site index model for Pinus pinea plantations in north-west of Tunisia. To assure the base-age invariance of the model parameter estimates, a dummy variable approach was used. Data from stem analysis, corrected with Carmean's method, were used for modelling. To take into account the inherent autocorrelation of the longitudinal data, a second-order continuous-time autoregressive error structure was used, which allows the models to be applied to irregularly spaced, unbalanced data. Both a qualitative analysis based on the biological realism of the models and numerical and graphical analyses based on the accuracy of the models as well were used to evaluate the performance of candidate models. The relative error in site index predictions was used to select 30 years as the best reference age. Based on the analysis, a generalized algebraic difference equation (GADA) derived from the base model of Lundqvist-Korf realized the best compromise between biological and statistical constraints, producing the most adequate site index curves. It is a polymorphic model with site-dependent asymptotes. This model is therefore recommended for height growth prediction and site classification of Pinus pinea plantations in north-west of Tunisia.