Non-Linear Models for Tree Aboveground Biomass and Volume Estimation in Agoi-Ibami Forest Reserve, Cross River State, Nigeria

Abstract

Tree biomass and volume estimation based on allometric equations is a widely used non-destructive technique for estimating biomass, sequestered carbon, and volume worldwide. Non-linear models for the biomass and volume of individual trees in Nigeria's Cross River State's Agoi-Ibami Forest Reserve were fitted and validated in this study. In this study, two parallel lines transect of 1500 meters in length, separated by 500 meters, were established using the systematic line transects sampling method. Along each transect, ten sample plots, each measuring 50 m by 50 m, were placed alternately at 100 m intervals. Twenty sample plots in all were thus marked for the study. The estimation of biomass using a non-destructive method was used. To calculate the aboveground green biomass for each, the diameter at breast height and total height were employed. Agoi-Ibami Forest Reserve had a total value of 391N ha-1 for number of stem per hectare, 14 tree families, mean dbh of 26.04cm, height of 15.9m, and basal area of 50.21m2ha-1. Conversion factors were used to estimate stand biomass, carbon sink, and sequestered carbon dioxide (CO2). Non-linear models were fitted for volume and aboveground biomass estimation in the study area. All of the models were evaluated and validated using some assessment statistical criteria and residual graphs, and models with good fit were suggested for use. Curve Expert Software was used for the development of the non-linear regression models. According to the assessment criteria, the forest reserve's best non-linear volume and aboveground biomass models were the Ratkowsky, Weibull, and Logistic models. Fitted models should therefore be employed for the forest reserve's efficient and successful management.