• Journal of Forest and Environmental Science
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• v.34 no.2
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• pp.119-125
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• 2018

The tropical forests in developing countries are faced with the problem of illegal exploitation of trees. However, dearth of empirical means of expressing the dimensions, structure, quality and quantity of a removed tree has imped conviction of offenders. This study aimed at developing a model that can effectively estimate individual tree basal area (BA) from stump diameter (Ds) for Tectona grandis stands in Omo Forest Reserve, Nigeria, for timber valuation in case of illegal felling. Thirty-six $25m{\times}25m$ temporary sample plots (TSPs) were laid randomly in six age strata; 26, 23, 22, 16, 14, and 12 years specifically. BA, Ds and diameter at breast height were measured in all living T. grandis trees within the 36 TSPs. Least square method was used to convert the counted stumps into harvested stem cross-sectional areas. Six basal area models were fitted and evaluated. The BA-Ds relationship was best described by power model which gave least values of Root mean square error (0.0048), prediction error sum of squares (0.0325) and Akaike information criterion (-15391) with a high adjusted coefficient of determination (0.921). This study revealed that basal area estimation was realistic even when the only information available was stump diameter. The power model was validated using independent data obtained from additional plots and was found to be appropriate for estimating the basal area of Tectona grandis stands in Omo Forest Reserve, Nigeria.

• Journal of Forest and Environmental Science
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• v.34 no.6
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• pp.451-456
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• 2018

The use of single component distribution to describe the irregular stand structure of degraded forest often lead to bias. Such biasness can be overcome by the application of finite mixture distribution. Therefore, in this study, finite mixture distribution was used to characterise the irregular stand structure of the Gmelina arborea plantation in Omo forest reserve. Thirty plots, ten each from the three stands established in 1984, 1990 and 2005 were used. The data were pooled per stand and fitted. Four finite mixture distributions including normal mixture, lognormal mixture, gamma mixture and Weibull mixture were considered. The method of maximum likelihood was used to fit the finite mixture distributions to the data. Model assessment was based on negative loglikelihood value ($-{\Lambda}{\Lambda}$), Akaike information criterion (AIC), Bayesian information criterion (BIC) and root mean square error (RMSE). The results showed that the mixture distributions provide accurate and precise characterisation of the irregular diameter distribution of the degraded Gmelina arborea stands. The $-{\Lambda}{\Lambda}$, AIC, BIC and RMSE values ranged from -715.233 to -348.375, 703.926 to 1433.588, 718.598 to 1451.334 and 3.003 to 7.492, respectively. Their performances were relatively the same. This approach can be used to describe other irregular forest stand structures, especially the multi-species forest.

• Journal of Forest and Environmental Science
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• v.30 no.4
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• pp.315-321
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• 2014

Forest timber production potential of any site is oftentimes measured quantitatively by site index, which is defined as dominant height of a particular stand at a specified age. A site index was developed for estimating site quality of monoculture Pinus caribaea plantations in southwestern Nigeria using a base age of 25 years. Dominant height data were collected from 60 Temporary Sample Plots (TSPs) of $20{\times}20m$ in plantations of 15 to 37 years. Linear and non-linear models as been widely applied in quantitative forest measurements were fitted to dominant height-age data and the best site index equation is : $SI=Exp^{(InHd-23.495(A^{-2}-0.04)}$. The site index curves constructed for the three sites (Omo Forest Reserve - OFR (J4), Oluwa Forest Reserve - OLFR and Shasha Forest Reserve - SFR) across the southwestern Nigeria using the chosen equation revealed that a 15 year old Pinus caribaea in the study area attained average dominant heights of 25, 22 and 21 m in OFR (J4), OLFR and SFR respectively. The site index equation and curves proffer veritable insight into better silvicultural options and management practices for the future plantations suitable sites.