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Modeling non-spatial forest stand structure is important for prescribing silvicultural treatments and harvesting regimes. It requires identification of a suitable distribution model to provide reliable estimates. Therefore, in this study, we evaluated the performance of various distribution models in describing the structure of the Gmelina arborea stands in the Oluwa Forest Reserve, Nigeria. Data were collected from twenty-five sample plots of 0.04 ha in five stands (aged 19, 24, 29, 34, and 39 years). Five distributions, including Weibull, Generalized Weibull, Johnson SB, Logit-logistic (LL), and generalized beta were fitted to diameter data from the individual stands. Model assessment was based on negative log-likelihood, Kolmogorov-Smirnov, Cramer-von Mises, Anderson-Darling, and Bayesian Information Criterion. The results showed that Johnson SB had the smallest rank sum of the fit indices. Kolmogorov-Smirnov and Anderson-Darling values ranged from 0.0333 to 0.0441, and 0.0217 to 0.0522, respectively. As such, the Johnson SB distribution was identified as the most suitable model for the G. arborea stands. Generalized beta, LL, Weibull, and generalized Weibull distributions performed equally well. The application of the Johnson SB model with a fitted Näslund height-diameter model provided information on class volume per hectare. This information is important for making decisions on product specification and overall management of the G. arborea.

Modeling the non-spatial structure of Gmelina arborea Roxb Stands in the Oluwa Forest Reserve, Nigeria