Comparative study of some non-linear models for predicting the yield of Gmelina arborea plantation
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Abstract
Yield models are important for effective forest management and as such were developed for the University of Benin Gmelina arborea plantation, Nigeria. The objectives of the study were to develop, evaluate and compare predictions from some non-linear models for timber volume estimation. A total of nine non-linear models comprising of three models each for weibull, logistic and log-normal models were developed using the three independent variables combinations (Basal area and merchantable height, diameter at base and merchantable height, diameter at middle and merchantable height). The assessment criteria (correlation coefficient (R), coefficient of determination (R2), standard error of estimate (SE)) with the validation results (using percentage bias and probability plots of residuals) showed that all categories of weibull and logistic models generated in this study discovered to be very adequate for tree volume estimation. The highest R2 (93.80), lowest SE (0.25) and lowest bias% (1.29) in the study were achieved from Weibull model 1a. The log-normal models were the least adequate for tree volume estimation with the highest bias%. The one way analysis of variance revealed that there were no significant differences in the performance of the non-linear models when varying predictor variables were used. The weibull, logistic models were therefore recommended for further use in this ecosystem and in any other forest ecosystem with similar site condition.
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Gmelina arborea, Plantation, Tectona grandis, Yield models
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