Global-local and fixed-random parameters to model dominant height growth of Pinus pseudostrobus Lindley

Abstract

Introduction: Dominant height and site index (SI) models consider average parameters for a sample or population. The dummy variable (DV) modeling approach generates global and local parameters, while mixed-effects models (MEM) generate fixed and random ones for each tree or plot. Objective: To fit and compare dynamic dominant height equations with the DV and MEM approaches for Pinus pseudostrobus Lindley in commercial forest plantations in Nuevo San Juan Parangaricutiro, Michoacan, Mexico. Materials and methods: Three algebraic difference approach (ADA) equations and one generalized algebraic difference approach (GADA) equation, based on the Chapman-Richards model, were fitted with the SI parameter associated as local or random for each tree. The database used considered stem analysis of 41 trees. Results and discussion: The accuracy of the fitted equations with DV and MEM was similar, according to the fitting statistics and the trajectories of the SI curves at the base age of 20 years. In the ADA equations, the polymorphic curve showed greater statistical efficiency with both approaches when the growth rate parameter depended on the SI. However, the GADA equation generated curves that better described the growth pattern; the highest accuracy was obtained with the DV approach. Conclusions: The use of the GADA equation with DV is an accurate tool for classifying the productivity of commercial forest plantations, which will allow forest management planning based on site quality.