ABSTRACT Background: This article aims to provide information on the diameter distribution of naturally regenerated forests of Taurus cedar (Cedrus libani A. Rich), a tree species endemic in the mountains of the Eastern Mediterranean basin and assess their prediction ability with the Johnson SB distribution. Previous research attested to the flexibility of Johnson family distributions to mimic empirical diameter data for a large set of tree species, justifying its use for the case study. A set of 134 plots (400 m2) were sampled in the most represented areas of the distribution of the species in Türkiye and diameter at breast height was measured in all the living trees. The cedar forests displayed heterogeneous diameter structures with diameters range from 10 to 116 cm and irregular shapes (e.g. unimodal, bell-shaped, left- and right-skewed, and non-uniform). Over three-quarters of the empirical diameter distributions (104 sample plots) were classified as SB distribution. The remaining were classified as bounded at the lower end, SL (16) or unbounded, SU (14). The authors essayed the 3-parameter and 4-parameter recovery methods after Parresol and Fonseca and other´s fundamental studies. The 3-parameter recovery method outperformed the 4-parameter method in the convergence criterion and error index (EI) expressed in the basal area. Results: Results show that the Johnson SB distribution can adequately reproduce the high variability in diameter for most of the distributions observed in these natural forests, providing reliable estimates which can serve as a basis for decision support systems. Conclusion: The SB distribution can represent the diameter distributions of natural cedar forests, even if the empirical distributions are not in the region covered by this distribution.

ABSTRACT Background: Diameter distribution models are one of the most important components of growth and yield models. Diameter distribution models, based on the Weibull function, were developed for even-aged mixed-oak stands (Turkey oak, Sessile oak, and Hungarian oak) in northwestern Turkey. Two modeling methods were considered. Weibull parameters were recovered from either equation predicting Dq and Dvar (method of moments) or equations predicting Dq and D 90 (hybrid method). For each modeling method, three estimation methods were considered: (a) Least Squares method, (b) CDF Regression method in which regression coefficients were estimated separately for each species, and (c) CDF Regression method in which regression coefficients were simultaneously estimated for all species. Results: Results indicated that the hybrid method coupled with the CDF Regression estimation method yield best results in this study. Similar results were obtained when the regression coefficients were estimated either separately for each species or simultaneously for all species. Conclusion: The proposed models enable one to predict diameter distribution of a given mixed-oak species stand in northwestern Turkey, using limited stand information. These models are useful tools for the inventory and management of mixed-oak stands.

ABSTRACT 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 β 1, β 3 and β 4 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.

ABSTRACT In this study, Max and Burkhart (1976)’s segmented taper model was used to describe stem profile and predict stem volume of oriental spruce in Turkey. Thirty procedures were evaluated, which include five fitting methods and six adjustment strategies. The fitting methods resulted in parameters that were optimized for (1) taper, (2) cumulative volume, (3) taper and cumulative volume, (4) taper and total volume, and (5) taper, cumulative volume, and total volume. The adjustment strategies are (1) unadjusted, and adjusted to match (2) DBH, (3) predicted total volume, (4) DBH and predicted total volume, (5) a combined estimator, and (6) DBH and a combined estimator. Results showed that, without adjustment, the model with parameters optimized for taper gave good prediction for both taper and cumulative volume. Mixed results were obtained when various adjustment strategies were used on different fitting techniques. The overall best-ranked procedure for predicting both taper and volume was the model optimized for taper and cumulative volume and then adjusted to fit the combined estimator.