Evaluation of Tree Volume Equations for Gmelina arborea Roxb. Stand in Southwestern, Nigeria

Abstract

Effective and sustainable forest management is dependent on volume and yield models. This study was carried out to evaluate ten (10) different tree volume equations for the sustainable management of the Gmelina arborea stand in Oluwa forest reserve. A total of 590 trees were used in this study. The observed volume of the sample trees were calculated by the application Newton‘s formula. The performance of each model were evaluated using five fit statistics such as root mean squared error (RMSE), r-squared (R2), Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and relative rank sum were used. All the models in this study performed significantly well in volume estimation as the R2 were above 75% for all the models. Four models (model 10, 8, 6 and 7) performed best for the data set based on their evaluation statistics and as such they were selected for volume estimation of Gmelina arborea stand in Oluwa forest reserve. The evaluation test revealed that model 10 had the least RMSE of 0.2986, hence it was ranked the best model for the study. Scatter plots showed positive correlation between DBH, total height, BA and total volume. The regression residuals were normally distributed, with constant variance and a zero mean.