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Bishnu Hari Wagle,Ram P. Sharma 한국산림과학회 2012 Forest Science And Technology Vol.8 No.1
Individual tree growth models are important decision-making tools for forest management. We developed individual tree basal area growth models with Blue pine (Pinus wallichiana) data from Lete and Kunjo areas of Mustang district in Nepal. The sample trees were identified from all applicable ages, sizes, site qualities, and stand conditions and were cut. Diameters and ages were measured on the cut surface of stump (at 30 cm above ground). With the application of the auto-regressive error-structured modelling approach, we fitted Bertalanffy function to the data from 94 stumps by using basal area growth per year as dependent variable and stump age or stump diameter as independent variable. The age-independent individual tree basal area growth model showed better fits (R^2_adj=0.8324) than its agedependent counterpart (R^2_adj=0.8174). Because of having better fits and being easier for application, the ageindependent model is recommended for predicting basal area growth per year at an individual tree level for Blue pine across Lete and Kunjo areas of Mustang district.