FITTING AND CALIBRATING A MIXED-EFFECTS SEGMENTED TAPER MODEL FOR BRUTIAN PINE

• Autor(a) principal: Özçelik, Ramazan
• Data de Publicação: 2020
• Outros Autores: Alkan, Onur
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Cerne (Online)
• Texto Completo: https://cerne.ufla.br/site/index.php/CERNE/article/view/2509
• topic: stem taper; localization; prediction; variance function; random parameters

Taper  models  are  one  of  several  necessary  tools  in  modern  forest  inventory,  giving  information  on  diameter  at  any  point  along  the  tree  stem  and  this  information  can  also  be used to estimate stem volume. In this study, we used nonlinear mixed-effects (NLME) modeling approach to minimize existing statistical problems in constructing taper equations. A segmented taper model of Max and Burkhart (1976) was fitted using this approach to consider  for  within-  and  between-tree  variation  in  brutian  pine  (Pinus  brutia  Ten.)  stem  taper. Based on evaluation statistics, the model including random-effects parameters β1, β3 and β4 were found to be the best. Inclusion of random parameters were not completely eliminated heterogenous variance and autocorrelation in residuals. Incorporating variance function  and  a  continuous  autoregressive  error  structure  (CAR(1))  to  NLME  Max  and  Burkhart model removed the heteroscedasticity and autocorrelation in residuals. Upper stem diameters were used to localized stem taper model to individual tree. For this, two different  measurement  scenarios  were  evaluated  as  one  and  two  upper  stem  diameter  measurements. Inclusion of random parameters were improved the predictive capability of taper model in particularly the middle and lower sections of stem based on upper stem diameter measurements. The calibration using upper stem diameter measurements can improve the tree-level accuracy of stem taper model is therefore recommended.