Mixed Species Allometric Models for Estimating above-Ground Liana Biomass in Tropical Primary and Secondary Forests, Ghana

Abstract

The study developed allometric models for estimating liana stem and total above-ground (TAGB) biomass in primary and secondary forests in the Asenanyo Forest Reserve, Ghana. Liana biomass was determined for 50 individuals for each forest using destructive sampling. Various predictors involving liana diameter and length were run against liana biomass in regression analysis, and R2, RMSE, and Furnival's index of fit (FI) were used for model comparison. The equations comprised models fitted to untransformed and log-transformed data. Forest type had a significant influence (P<0.05) on liana allometric models in the current study, resulting in the development of forest-type-specific equations. There were significant and strong linear relationships between liana biomass and the predictors in both forests (R2>0.970). Liana diameter was a better predictor of biomass than liana length. Generally, the models which were based on log-transformed data showed better fit (higher FI values) than those fitted to untransformed data. Comparison of the site specific models in the current study with previously published models indicated that the models of the current study differed from the previous ones. This indicates the need for forest specific equations to be used for accurate determination of above-ground liana biomass.