Mixed effect models for predicting breast height diameter from stump diameter of Oriental beech in Göldağ

摘要: Diameter at breast height (DBH) is the simplest, most common and important tree dimension in forest inventory closely correlated with wood volume, biomass. In this study, a number of linear nonlinear models predicting diameter from stump were developed evaluated for Oriental beech (Fagus orientalisLipsky) stands located region Ayancik, northeast Turkey. A set 1,501 pairs height-stump measurements, originating 70 sample plots even-aged stands, used study. About 80 % otal data (1,160 trees 55 plots) was to fit model parameters; remaining 341 15 randomly reserved validation calibration response. The power found produce satisfactory fits Adjusted Coefficient Determination, R2adj (0.990), Root Mean Square Error, RMSE (1.25), Akaike’s Information Criterion, AIC (3820.5), Schwarz’s Bayesian BIC (3837.2), Absolute Bias (1.25). mixed-effect modeling approach R2adj(0.993), (3598), (3610.1), (0.73) (1.04) provided much better fitting precise predictions DBH than conventional fixed effect structures model. response including measurements four largest calibrated plot produced highest Bias, -5.31 %, RMSE, -6.30 greatest reduction percentage.