Abstract

Gmelina arborea Roxb. is a fast-growing, deciduous tree species native to Bangladesh. It has been widely planted since 1992 for commercial production of pulpwood in hilly areas of Bangladesh. The purpose of this study was to derive well-fitting allometric models for estimation of aboveground biomass, and carbon and nutrient (nitrogen, phosphorus and potassium) stocks in G. arborea to ensure sustainable production and management of this species. Eight linear models with 64 regression equations were tested for estimation of aboveground biomass, carbon and nutrient stocks in different parts (leaves, branches, bark and stem) of the plant. The best-fitting allometric models were selected in accordance with various relevant statistical criteria.

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