Growth and Yield Prediction Models for Acacia auriculiformis (Akashmoni) Grown in the Plantations of Bangladesh

SM Zahirul Islam*, Mofizul Islam Khan and Abul Kalam Azad
Forest Inventory Division, Bangladesh Forest Research Institute, Chattagram-4000, Bangladesh
*Corresponding Author: SM Zahirul Islam, Forest Inventory Division, Bangladesh Forest Research Institute, Chattagram-4000, Bangladesh.

Published: September 27, 2023

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Abstract  

Akashmoni (Acacia auriculiformis A. Cunn ex Benth, family Leguminnosae) is a promising fast-growing tree species for timber use. This species of tree has occupied a unique position due to furniture manufacturing and construction work. Growth and yield of the species in Bangladesh are scientifically unknown. Therefore, the necessity of growth and yield models for the species was felt for the scientific management of the forest. The present study was conducted to derive mathematical models for growth and yield of this species in Bangladesh based on site indices. The models were derived by establishing Permanent Sample Plots (PSPs) and Temporary Sample Plots (TSPs) with an area of 0.02 ha and a circular or rectangular shape. Diameter at breast height and total height of all trees in the plots were measured by PSPs for seven consecutive years. The stepwise procedure and all probable combinations of the independent variables were used to select the most appropriate models, provided that the statistical and biological requirements were met. Models were selected to estimate the stocking ha^-1 of the canopy, the mean height of the canopy, the diameter of the canopy, the basal area of the canopy ha^-1, the yield of the canopy volume ha^-1 and the aboveground biomass of the canopy ha^-1 Estimate Akahmoni. The yield forecast models derived in the study could be used satisfactorily for Akashmoni with a stand age of 4 to 17 years and site indices of 9 to 21 meters based on a base age of 12 years. Extrapolation over this data range is not recommended. The selected models were verified against separate datasets using chi-square test, paired t-test, percent absolute deviation, and 45-degree line test. The biological principle of the model development was checked. The results suggest that the models were statistically and biologically acceptable. The developed models could safely be used for forecasting growth and yield of Akashmoni.

Keywords: Acacia auriculiformis; Growth and yield; prediction; plantation and Bangladesh

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