diameter growth models
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2021 ◽  
Vol 24 (6) ◽  
pp. 629-638
Author(s):  
Su Young Jung ◽  
Kwang Soo Lee ◽  
Hyun Soo Kim

Background and objective: This study was conducted to develop diameter growth models for thinned Quercus glauca Thunb. (QGT) stands to inform production goals for treatment and provide the information necessary for the systematic management of this stands.Methods: This study was conducted on QGT stands, of which initial thinning was completed in 2013 to develop a treatment system. To analyze the tree growth and trait response for each thinning treatment, forestry surveys were conducted in 2014 and 2021, and a one-way analysis of variance (ANOVA) was executed. In addition, non-linear least squares regression of the PROC NLIN procedure was used to develop an optimal diameter growth model.Results: Based on growth and trait analyses, the height and height-to-diameter (H/D) ratio were not different according to treatment plot (p > .05). For the diameter of basal height (DBH), the heavy thinning (HT) treatment plot was significantly larger than the control plot (p < .05). As a result of the development of diameter growth models by treatment plot, the mean squared error (MSE) of the Gompertz polymorphic equation (control: 2.2381, light thinning: 0.8478, and heavy thinning: 0.8679) was the lowest in all treatment plots, and the Shapiro-Wilk statistic was found to follow a normal distribution (p > .95), so it was selected as an equation fit for the diameter growth model.Conclusion: The findings of this study provide basic data for the systematic management of Quercus glauca Thunb. stands. It is necessary to construct permanent sample plots (PSP) that consider stand status, location conditions, and climatic environments.


Forests ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 344 ◽  
Author(s):  
Keiko Fukumoto ◽  
Tomohiro Nishizono ◽  
Fumiaki Kitahara ◽  
Kazuo Hosoda

Understanding the tree growth process is essential for sustainable forest management. Future yields are affected by various forest management regimes such as thinning; therefore, accurate predictions of tree growth are needed under various thinning intensities. This study compared the accuracy of individual-level distance-independent diameter growth models constructed for different thinning intensities (thinning intensity-dependent multiple models: TDM model) against the model designed to include all thinning intensities (thinning intensity-independent single model: TIS model) to understand how model accuracy is affected by thinning intensity. We used long-term permanent plot data of Japanese cedar (Cryptomeria japonica) stands in Japan, which was gathered from four plots where thinning was conducted at different thinning intensities: (1) intensive (41% and 38% of trees removed at 25 and 37 years old, respectively), (2) moderate (38% and 34%), (3) light (32% and 34%), and (4) no thinning. First, we specified high interpretability distance-independent competition indices, and we compared the model accuracy both in TDM and TIS models. The results show that the relative spacing index was the best competition index both in TDM and TIS models across all thinning intensities, and the differences in the RMSE (Root mean square error) and rRMSE (relative RMSE) in both TDM and TIS models were 0.001–0.01 cm and 0.2–2%, respectively. In the TIS model, rRMSE varied with thinning intensity; the rRMSE was the lowest for moderate thinning intensity (45.8%) and the highest for no thinning (59.4%). In addition, bias values were negative for the TIS model for all thinning intensities. These results suggest that the TIS model could express diameter growth regardless of thinning intensities. However, the rRMSE had varied with thinning intensity and bias had negative values in the TIS model. Therefore, more model improvements are required for accurate predictions of long-term growth of actual Japanese cedar stands.


Forests ◽  
2017 ◽  
Vol 8 (12) ◽  
pp. 506 ◽  
Author(s):  
Paulo Moreno ◽  
Sebastian Palmas ◽  
Francisco Escobedo ◽  
Wendell Cropper ◽  
Salvador Gezan

2014 ◽  
Vol 60 (No. 8) ◽  
pp. 307-317 ◽  
Author(s):  
H. Ivancich ◽  
G.J. Martínez Pastur ◽  
M.V. Lencinas ◽  
J.M. Cellini ◽  
P.L. Peri

Tree growth is one of the main variables needed for forest management planning. The use of simple models containing traditional equations to describe tree growth is common. However, equations that incorporate different factors (e.g. site quality of the stands, crown classes of the trees, silvicultural treatments) may improve their accuracy in a wide range of stand conditions. The aim of this work was to compare the accuracy of tree diameter growth models using (i) a family of simple equations adjusted by stand site quality and crown class of trees, and (ii) <br /> a unique global equation including stand and individual tree variables. Samplings were conducted in 136 natural even-aged Nothofagus antarctica (Forster f.) Oersted stands in Southern Patagonia (Argentina) covering age (20&ndash;200 years), <br /> crown class and site quality gradients. The following diameter growth models were fitted: 16 simple equations using two independent variables (age and one equation for each stand site quality or crown class) based on Richards model, plus a unique global equation using three independent variables (age, stand site quality and crown class). Simple equations showed higher variability in their accuracy, explained between 54% and 92% of the data variation. The global model presented similar accuracy like the better equations of the simple growth models. The unification of the simple growth models into a unique global equation did not greatly improve the accuracy of estimations, but positively influenced the biological response of the model. Another advantage of the global equation is the simple use under a wide range of natural stand conditions. The proposed global model allows to explain the tree growth of N. antarctica trees along the natural studied gradients. &nbsp; &nbsp;


2008 ◽  
Vol 38 (1) ◽  
pp. 101-113 ◽  
Author(s):  
G. Gea-Izquierdo ◽  
I. Cañellas ◽  
G. Montero

Despite Quercus ilex L. being one of the most widespread tree species in the Mediterranean basin, there are no growth models in the literature for this species. In this study, we compare age-dependent and age-independent dynamic diameter growth models and discuss the concept of dominance in open stands. A posteriori dominance was determined to fit potential age-dependent growth models and a site index based on diameter growth was defined. Formulations derived from power decline base models (Korf and Hossfeld) best described diameter growth. The best approach for age-dependent models was a polymorphic and with variable asymptotes generalized algebraic difference approach formulation. Residual errors in trees between 20 and 55 cm ranged from ~7.0% in potential growth models to ~15% in age-independent models expanded by density. Using a unique age-dependent dynamic equation for all trees, regardless of dominance, did not increase the error very much. In age-independent models, the inclusion of the defined site index reduced the prediction error but requires that the age of trees is estimated to determine the site index. The difficulty of estimating Q. ilex age makes age-independent models very attractive for system modelling. Age-independent models could be useful in other ecosystems where age estimation is problematic.


2006 ◽  
Vol 36 (6) ◽  
pp. 1551-1562 ◽  
Author(s):  
James A Westfall

Tree diameter growth models are widely used in forestry applications, often to predict tree size at a future point in time. Also, there are instances where projections of past diameters are needed. A relative diameter growth model was developed to allow prediction of both future and past growth rates. Coefficients were estimated for 15 species groups that cover most tree species in the northeastern United States. Application of the model to independent data generally showed slight underprediction of growth, although the bias was negligible. Correlated observations were accounted for via a mixed-effects modeling approach, and an error function was specified to address heterogeneous variance. The models use a minimum amount of field-collected data, thus keeping data acquisition costs low and facilitating use in many forest growth applications.


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