Forest Research: Open Access
Open Access

Abstract

Forest Volume-to-Above-Ground Tree Biomass Models for the Secondary Forest in Lita, Ibadan, Nigeria

Aghimien EV, Osho JSA, Hauser S and Ade-Oni VD

It is generally agreed that preservation of forest areas can contribute strongly to the mitigation of global climate change. However, studies have demonstrated that there are still uncertainties for an accurate estimation of carbon stock particularly in the tropical forest. This study aims therefore to develop some allometric equations that can be used to estimate above-ground tree biomass and carbon partitioning between major carbon pools such as tree and litter for IITA secondary forest ecosystem. Ten permanent sample plots of 20 m × 20 m were randomly laid in the forest reserve. Diameter at breast height, total height, crown diameter and wood density were measured. Forty quadrants of 1 m × 1 m for litter fall collection were also randomly laid in four locations in each permanent sample plots. Twenty four tree species present in all the permanent sample plots were selected for destructive sampling. Mean biomass of each sampled plots were pooled together to develop allometric equations to obtain biomass and carbons were also estimated using standard method. A total of nine hundred and forty seven tree species were measured in the study area. These tree species belong to sixteen different families. Allometric equations of family level and whole stand level for estimating above-ground tree biomass were therefore developed. The best fitted allometric equations were used to predict above-ground tree biomass. Model 3 indicated the highest modelling efficiency of 0.954, 0.960 and 0.984. Therefore taking this into consideration, that model 3 was selected as the best model for predicting the above-ground tree biomass with an estimation of 17698.76 g at family level. Allometric equations of whole stand level for above-ground tree biomass indicated good correlation with H, DBH, CD and WD (0.534, 0.597, 0.751, and 0.648). Model 5, 7 and 8 were designated the highest modelling efficiency of 0.898, 0.922 and 0.948. Model 8 is selected as the best models for predicting the above-ground tree biomass with an estimate of 838036.15 g. Therefore, carbon capture per hectare of above-ground tree biomass was 368280.40 g/ha. Carbon capture per hectare of litter had 2663.259 g/ha using standard method. The distributions of the standard residual values and standard error estimate with the fitted values are adequate.