MODELLING SIZE-CLASS DISTRIBUTIONS AND CARBON STOCK IN OMO FOREST RESERVE, OGUN STATE, NIGERIA

Abstract

Models are important tools used in forestry for estimating growing stock and depicting size-class distribution. They facilitate decision-making to ensure sustainable forest management. The purpose of this study was to develop models for depicting size-class distribution and carbon stock estimation for live trees in the strict nature reserve and buffer zone of Omo forest reserve, Nigeria. Cluster sampling was adopted for the research, four clusters encompassing three plots each were established. Plot size of 35 m x 35 m was used for enumeration of trees with diameter at breast height (dbh) of 40 cm and above. The plot was nested by establishing sub-plots of 25 m x 25 m and 7 m x 7 m within it for enumeration of trees with dbh of 20 cm to 40 cm and 5 cm to 20 cm, respectively. The dbh of each tree was measured and converted into volume, using the volume equation from the Nigeria’s Forest Resources Study. Wood density values for each tree species were obtained from literature and used to multiply the tree volumes to obtain tree biomass. Using appropriate ratios, carbon stock and carbon dioxide equivalents were computed for the strict nature reserve and the buffer zone. Ten diameter distribution functions were fitted to the dbh data and compared on the basis of Kolmogorov-Smirnov, Anderson Darling and Chi-Squared statistics. The results showed that three-parameter Weibull distribution function ranked the best in depicting the diameter distribution for the study area. Similarly, the volume of trees in the strict nature reserve was 94.25m3/ha while that of the buffer zone was 55.08m3/ha. The carbon stock was estimated as 165.81ton/ha and 106.46ton/ha for the strict nature reserve and buffer zone, respectively. Regression analysis was also carried out to develop equations for estimating carbon stock from diameter at breast height. Out of the nine equations fitted for computing and validating carbon stock, the best was C = 13.41-1.65(dbh)+0.17(dbh2). The equation has the least value of percentage bias (1.59%). Student paired t-test for paired means indicated that there was no significant difference between the observed and predicted values of carbon stock.