ABSTRACT
Wood quality is an important indicator for modern sawmills. Internal wood characteristics can be derived from their correlations with external appearances. In this study, we developed linear regression models to predict knot size from surface features of Mongolian oak (Quercus mongolica) using data collected from 53 trees. For this, manual measurements and X-ray computed tomography scanning technology was respectively used to obtain internal and external features of 1,297 knots. Our results showed that Mongolian oak knots were generally concentrated in the middle part of oak stems, with fewer knots observed at the top and base. The parameters of knot and scar showed significant correlations (P < 0.01), where length and diameter of the corresponding external scar increase with increasing the length and diameter of a knot. The corresponding external scar can be used as an effective indicator to predict the internal value of oak logs. The accuracy of our constructed model is more than 95% when assessed against independent test samples. These models thus can be applied to improve the practical production of oak timber and reduce commercial loss caused by knots. These additional data can improve the estimation of the influence of knots on wood quality and provide a theoretical foundation for investigating the characteristics of hardwood knots.
Subject(s)
Quercus , Cicatrix , Wood , Trees , Tomography, X-Ray ComputedABSTRACT
Developing outer crown profile prediction models of typical urban greening tree species will lay a foundation for the spatial allocation optimization of urban greening. In this study, Pinus tabuliformis, a typical greening tree species in Shenyang, was selected as the research object. Based on the Crown Window device, a total of 60 sample trees were selected to measure the crown shape, with power equation, segmented polynomial equation, and modified Kozak equation as the basic models. By introducing crown structure variables (the maximum crown radius) and neighbour competition variables (mean tree height, mean diameter at breast height, mean crown width, number for the neighbour trees, and mean crown contact height between sample trees and neighbour trees) through reparameterization, we constructed an outer crown shape model of P. tabuliformis that incorporates neighbour tree competition and maximum crown radius. The results showed that modified Kozak equation had the largest Ra2 and the smallest RMSE, as well as good stability. After introducing the maximum crown radius and the mean DBH of neighbour trees into the basic model through reparameterization, the Ra2 of the model increased by 0.0693 and the MSER was 14.4%. The maximum crown radius had a great influence on the crown shape, while the crown radius increased with the increases of the maximum crown radius. The influence of mean DBH of neighbour trees on crown shape was weaker than that of maximum crown radius. The upper part of crown increased and the lower part of crown decreased with increasing neighbour tree competition. In this study, the marginal regression outer crown profile model of P. tabuliformis coupled with neighbour tree competition and the maximum crown radius showed good goodness of fit and could reasonably simulate and predict the crown shape of planted P. tabuliformis.
Subject(s)
Pinus , TreesABSTRACT
Crown width is a critical variable in reflecting the individual tree growth status and in developing forest growth and yield models. With the crown width base model as reference, we developed the crown width quantile regression models for different quantiles (0.50, 0.90, 0.93, 0.95, 0.96, 0.99) based on the data of 2763 Korean pines in 66 permanent plots from the 10-55 years old plantations in Dabiangou forest farm, mountainous areas of eastern Liaoning Province. We used the reparameterization method by introducing the single tree competition index (Rd) and used the dummy variable method by introducing stand density and forest layer variables. We then selected optimal quantile of maximum crown width in the stand by comparing our model developed routine to the traditional methods. The final crown width linear mixed effect quantile regression model was developed based on the optimal quantile at the plot level. The influence of each variable on crown width was analyzed to reflect the difference of crown width among individual trees in the stand. The models with different stand densities and forest layers had significant difference based on F statistical test: the Ra2 of the model increased by 0.0104, the root mean square error decreased by 0.0115 and the mean square error reduction was 7.4%, after the variables of forest layer, forest density, and competition being incorporated into the basic model. The developed quantile regression model performed better than that of the ordinary least square method in simulating the maximum crown width of a single tree in the forest stand. The selected best quantile of the quantile regression model for the upper forest layer and lower forest layer was 0.96 and 0.93, respectively. The linear quantile regression model with the mixed effect was superior to the traditional quantile regression model in Akaike, Bayesion and HQ information criterion and other evaluation para-meters, the standard error for the parameters of estimates was significantly reduced, and the introduced mixed effect well explained differences among different plots. For the upper forest layer and lower forest layer, the maximum crown width decreased with increasing stand density, increased with increasing relative diameters. The influence of stand density on the crown width of the lower forest layer was greater than that of the upper forest layer. The crown width would increase first and then decrease with the increases of DBH when the stand density was large enough. The mixed effect of the quantile regression model developed here could significantly improve the fitting stability of the model. The sustainable development of Korean pine plantation in the mountainous area of eastern Liaoning Pro-vince should be realized by adjusting stand density and moderate tending and thinning in the future.
Subject(s)
Forests , Pinus , China , Linear Models , Republic of Korea , TreesABSTRACT
Based on 378 permanent and 415 temporary plots from Northeast China, the relationship of maximum stand density and quadratic mean diameter at breast height of treesfor Larix olgensis plantation was developed. Linear quantile regression model with different quantiles (τ=0.90, 0.95, 0.99) was used and the optimal model for the maximum density-size line model was selected. The ordinary least square (OLS) and maximum likelihood (ML) regression were also employed to develop the maximum density-size line by using the arbitrary selected data. Generalized Pareto model of extreme value theory was used to calculate the number of limited maximum trees based on the current stands so that the limited density-size line was developed. The linear quantile regression model was compared with the other methods. The results showed that selecting 5 points within the whole diameter class for the maximum density-size line model development would get the satisfying prediction model. The fitting line would deviate from the maximum density-size line with the increasing points selected. The method of ML was superior to OLS in parameter estimation. The linear quantile regression model with the quantile of 0.99 achieved similar fitting results compared with ML regression and the estimation results was much stable. Traditional approach that selecting fittng data was considered arbitrary so that linear quantile regression with quantile of 0.99 was selected as the best model to construct the maximum density-size line with the estimates for the parameters as k=11.790 and ß=-1.586, and k=11.820 and ß=-1.594 for the limited density-size line model. The determined limited density-size line was above the maximum density-size line but the difference was not pronounced. The validation results by using the data of permanent sample plots showed the models were suitable to predict the maximum and limited density line of the current forest stands, which would provide basis for the sustainable management of L. olgensis plantation.
