Research Article

Models for predicting slenderness coefficient from stump diameter for Tectona grandis stands in south-western Nigeria


Abstract

Illegal logging has continued to be a major cause of depletion of the tropical forests in developing countries. However, empirical means of estimating the growth characteristics of a removed tree, which will facilitate the conviction of illegal loggers in judicial proceedings, are lacking. This study aimed at developing a model that can predict individual tree slenderness coefficients (SC) from stump diameter (Ds) for Tectona grandis stands in Omo Forest Reserve, Nigeria, for timber valuation in case of illegal felling. Diameter at breast height (DBH; cm), Ds (cm) and total height Ht (m) were measured from all T. grandis stands with a DBH ≥ 5.0 cm, within 35 temporary sample plots (TSPs) randomly laid out in 6 age series (26, 23, 22, 16, 14 and 12 years). The least squares regression method was used to model tree SC from Ds. Six SC-Ds models were fitted and evaluated. The relationship was best described by the single logarithmic function which gave best-fit values for the adjusted coefficient of determination, the Furnival’s index and the standard error of the estimate. This study showed that tree SC estimations were possible even when the only information available was the Ds. The single logarithmic model was validated using independent data and was found to be suitable for estimating the SC of T. grandis stands in Omo Forest Reserve, south-western Nigeria. Future studies should consider developing models for predicting other tree growth variables from Ds.

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