Diameter Distribution Structure for Tectona grandis Stand in Ofutet Teak Plantation, Cross River State, Nigeria

Abstract

The study was to characterise the diameter distribution structure of the Ofutet Teak Plantation, evaluate fitted probability distribution functions for describing and predicting DBH, and assess models for projecting key stand attributes.This study was carried out at Dr Ofutet’s Teak Plantation in Ogada II, Obubra Urban, in the Obubra Local Area of Cross River State, Nigeria. The plantation was established between 1998 and 2006 with a total land area of 28 hectares. Data were generated from five compartments established between 1998 and 2006, covering an area of 28 hectares. Six sample plots (20 m × 20 m each) were randomly laid out in each compartment. In each sample plot, tree diameters and heights were measured. A total of 1,253 trees were measured for DBH (cm) and height (m). Tree diameter distribution structure and models were defined. Parameter estimates for the models were generated using Curve Expert Professional software (version 2.7.3). At tree level, 18.7 cm, 9.4 m and 0.127 m3 were estimated as the mean DBH, height and volume, respectively, while at stand level, 12.3 m, 1,044/ha, 31.02 m2/ha and 132.772 m3 were obtained for Hd, N, G and V, respectively. Diameter distribution was fairly positively skewed (0.492), with 98% of the trees having DBHequal to or less than 30 cm. The Generalised Gumbel distribution (rated as very good), with a MAD of 0.83%, was recommended for predicting DBH in the plantation. The selected models for the projection of stand attributes were logarithmically transformed Hd against the reciprocal of age; number of stems (N) against age; logarithmically transformed G against age; and logarithmically transformed V against reciprocal age, basal area (G) and dominant height (Hd) with R2(60.2, 81.2, 83.9 and 78.2%), SEE (0.027, 14.953, 0.021 and 0.014), AICC (-215.516, 162.367, -231.636 and -249.903) and Curve Expert score (598, 770, 795 and 739) for Hd , N, G and V, respectively. The selected stand attribute models provided a good fit, as the observed and predicted values of the attributes were not significantly different (p > 0.05).