Mixed-effects modeling for tree height prediction models of Oriental beech in the Hyrcanian forests

• Published in: Journal of forestry research 2018-09, Vol.29 (5), p.1195-1204
• Main Authors: Kalbi, Siavash, Fallah, Asghar, Bettinger, Pete, Shataee, Shaban, Yousefpour, Rassoul
• Format: Article
• Language: English
• Subjects: Beech; Bias; Biomedical and Life Sciences; Calibration; Forestry; Forests; Life Sciences; Mathematical models; Model testing; Modelling; Nonlinear equations; Original Paper; Parameter estimation; Performance prediction; Prediction models; Root-mean-square errors
• ISSN: 1007-662X; 1993-0607
• DOI: 10.1007/s11676-017-0551-z

Height–diameter relationships are essential elements of forest assessment and modeling efforts. In this work, two linear and eighteen nonlinear height–diameter equations were evaluated to find a local model for Oriental beech ( Fagus orientalis Lipsky) in the Hyrcanian Forest in Iran. The predictive performance of these models was first assessed by different evaluation criteria: adjusted R 2 (R adj 2 ), root mean square error (RMSE), relative RMSE (%RMSE), bias, and relative bias (%bias) criteria. The best model was selected for use as the base mixed-effects model. Random parameters for test plots were estimated with different tree selection options. Results show that the Chapman–Richards model had better predictive ability in terms of adj R 2 (0.81), RMSE (3.7 m), %RMSE (12.9), bias (0.8), %Bias (2.79) than the other models. Furthermore, the calibration response, based on a selection of four trees from the sample plots, resulted in a reduction percentage for bias and RMSE of about 1.6–2.7%. Our results indicate that the calibrated model produced the most accurate results.