Dynamic growth model for Scots pine ( Pinus sylvestris L.) plantations in Galicia (north-western Spain)

• Published in: Ecological modelling 2006-01, Vol.191 (2), p.225-242
• Main Authors: Diéguez-Aranda, Ulises, Castedo Dorado, Fernando, Álvarez González, Juan Gabriel, Rojo Alboreca, Alberto
• Format: Article
• Language: English
• Subjects: Algebraic difference equations; Animal, plant and microbial ecology; Biological and medical sciences; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; Methods and techniques (sampling, tagging, trapping, modelling...); Pinus sylvestris; Scots pine; Stand growth model; Weibull function
• ISSN: 0304-3800; 1872-7026
• DOI: 10.1016/j.ecolmodel.2005.04.026

In this study we developed a dynamic growth model for Scots pine ( Pinus sylvestris L.) plantations in Galicia (north-western Spain). The data used to develop the model were obtained from a network of permanent plots, of between 10 and 55-year-old, which the Unidade de Xestión Forestal Sostible (Sustainable Forest Management Unit) of the University of Santiago de Compostela has set up in pure plantations of this species of pine in its area of distribution in Galicia. In this model, the initial stand conditions at any point in time are defined by three state variables (number of trees per hectare, stand basal area and dominant height), and are used to estimate stand volume, classified by commercial classes, for a given projection age. The model uses three transition functions expressed as algebraic difference equations of the three corresponding state variables used to project the stand state at any point in time. In addition, the model incorporates a function for predicting initial stand basal area, which can be used to establish the starting point for the simulation. This alternative should only be used when the stand is not yet established or when no inventory data are available. Once the state variables are known for a specific moment, a distribution function is used to estimate the number of trees in each diameter class, by recovering the parameters of the Weibull function, using the moments of first and second order of the distribution (arithmetic mean diameter and variance, respectively). By using a generalized height–diameter function to estimate the height of the average tree in each diameter class, combined with a taper function that uses the above predicted diameter and height, it is then possible to estimate total or merchantable stand volume.