Comparison of a modified log-logistic distribution with established models for tree height prediction

The complexity of data structure from different forest stands across the world has necessitated the continuous introduction of new models in forestry. No single model is expected to provide accurate fit to all data sets. Therefore, in this study, the cumulative distribution function (cdf) of the Log-Logistic distribution was modified to construct a new height-diameter (h-d) model for Gmelina arborea Roxb plantation in Omo Forest Reserve, Nigeria. A total of 60 sample plots of 0.04 ha were used in this study. Tree diameters and heights measurement were taken on 1,189 trees. The new h-d model was termed M. LogL and its performance was compared with five established traditional h-d models that have been used in quantitative forestry study. These include: Logistic h-d, Chapman-Richards (C-R) h-d, Weibull h-d, Näslund h-d and Curtis h-d. Model assessment was based on adjusted R2, root mean squared error (RMSE), Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Hannan-Quinn Criterion (HQC). The result showed that the performance of the new M. LogL h-d was comparable to other traditional h-d models used in forestry. The adjusted R2, RMSE, AIC, BIC and HQC were 0.629, 3.343, 2555.599, 2565.527 and 2555.480, respectively. However, the Logistic h-d model had the overall best fit to the data set. The order of ranking was: Logistic > M. LogL > Curtis > C-R > Weibull > Näslund. Therefore, the M. LogL model can be used to predict tree height for the Gmelina arborea plantation.Keywords: Modified Log-Logistic, height-diameter, Gmelina arborea, Omo forest reserv

Determination of self-thinning line for Gmelina arborea Roxb stands in Nigeria

Self-thinning line defined the site occupation of species and it is an important tool for manipulation of stand density and simulating thinning regime. Few studies have defined the self-thinning line of Gmelina arborea especially in Nigeria. Therefore, in this study, the self-thinning line of G. arborea in Oluwa Forest Reserve was determined. Data were obtained from twenty-four temporary sample plots (TSPs) of 20 x 20 m size established in the G. arborea stands. Three methodologies were used to define the self-thinning line including quantile regression (QR), stochastic frontier function with half-normal and stochastic frontier function with truncated-normal. Root means squared error (RMSE), Akaike information criterion (AIC) and Bayesian information criterion were used to assess the methods. The results showed that the three methods performed relatively well in describing the self-thinning line of the stand. Stochastic frontier with halfnormal with minima AIC and BIC of -5.321 and -0.609, respectively was more suitable. It predicted maximum density of 2630, 1537 and 1079 N/ha at quadratic mean diameter of 15, 25 and 35 cm, respectively. This information would help in the manipulation of the growth condition and determination of thinning schedule of the G. arborea stands.Keywords: Quantile regression, stand density, stochastic frontier regressio

Comparison of Beta, Gamma Weibull Distributions for Characterising Tree Diameter in Oluwa Forest Reserve, Ondo State, Nigeria

This study compared the accuracy of the Beta, 2-parameter Gamma (2P) and 3-parameter Weibull (3P) distributions, fitted with the method of moments, for characterising the tree diameter of the reserve. Comparison was based on the Kolmogorov-Smirnov statistic (K-S), bias, mean absolute error (MAE), and mean square error (MSE). Distributions with location parameter were fixed as the minimum inventoried diameter of each plot.  A total of eight (8) temporary sample plots (TSPs) of size 50m x 50m were laid in the natural stand of the reserve. Systematic line transect was used in the laying of the plots. All trees with DBH ? 10.0cm in the selected plots were enumerated, identified and measured. The results from the goodness-of-fit statistics revealed that the Weibull (3P) distribution performed slightly better than the Beta distribution used in this study. The mean values for the K-S, bias, MAE, and MSE of the Weibull distribution were 0.11449, 0.00015, 0.00847, and 0.00022, respectively; as such ranked best. The Gamma (2P) distribution provided the worst fit to the dataset, with relatively large values for the goodness-of-fit statistics. It fits for the entire plot were far from the reverse J-shaped of natural forests, which implies that the Gamma (2P) distribution is inappropriate for determining the structure of the natural stand. Keywords: diameter characterisation, probability distribution, moments, natural fores

State of a Lowland Tropical Forest in South-West Nigeria

Forests play a significant role in human existence and survival. Timely and reliable information on the status of a forest is essential for assessing the extent of regeneration and degradation. However, when such information is lacking effective forest management practices becomes impossible. Therefore, this study assessed the tree species diversity, richness and structure of Oluwa forest reserve with the view of ascertaining it present state which is crucial for management and conservation purposes. To achieved these, a systematic line transect was used in the laying of eight (8) temporary sample plots (TSPs) of size 50m x 50m. Trees with Dbh≥10cm in the selected plots were enumerated, identified and measured. The results indicate that 535 individual trees were enumerated cutting across 26 families and 58 species. The reserve has the Margalef's index of species richness, Shannon-Weiner diversity Index (H') and Pielou's Species Evenness Index (EH) of 9.07, 3.43 and 0.84 respectively. The forest has a mean Dbh (cm), mean height (m), total basal area/ha (m2) and total volume/ha (m3) of 24.7, 16.9, 36.63 and 602.09 respectively. Majority of trees were found in the smaller diameter and height classes; giving rise to reverse J-shaped structure. The structure of Oluwa forest reserve has been altered significantly while the species diversity and richness seems to indicate a sign of improvement compared to previous studies. With proper management, the remaining fragmented forests could regenerate and replenish to save some of the original species composition of the reserve

Deriving Tree Crown Distributions from Diameter at Breast Height

The distribution of crown diameter is important for assessing crown social class, monitoring forest health and wildlife management. However, the direct measurement of crown diameter is relative difficult, and as such, it is often predicted from diameter at breast based on a simple relationship. Therefore, in this study, the crown diameter distribution of Parkia biglobosa was derived from Dbh using Weibull and Log-Logistic functions. A total of 284 trees were measured from Parkia biglobosa plantation in Makurdi, Nigeria. Four methods were used for Weibull distribution including maximum likelihood (MLE), moments, percentiles and cumulative distribution function regression (CDFreg). MLE and CDFreg were used for Log-Logistic function. Transformation technique was used to transform the Dbh to crown distribution based on a simple allometric relationship between the variables. Kolmogorov-Smirnov (Dn), Cramer-von Mises statistic (W2) and Reynolds error index (EI) were used to assess the derived crown diameter distribution. The result showed that the underlying diameter distribution followed Weibull and Log-Logistic distributions. The fitted allometric equation was of the form:. MLE and CDFreg were the best methods for Weibull and Log-Logistic functions, respectively. The Dn, W2 and EI were 0.071, 0.0265 and 0.3434, respectively for MLE; and 0.0931, 0.0367 and 0.4171, respectively for CDFreg. In all methods, the observed and derived crown distributions were not significant at 20% (Dα=0.339). Thus, given the diameter distribution, the tree crown distribution of Parkia biglobosa can be derived. This would be useful for determination of the crown social class