scholarly journals Nonlinear Simultaneous Equations for Individual-Tree Diameter Growth and Mortality Model of Natural Mongolian Oak Forests in Northeast China

Forests ◽  
2015 ◽  
Vol 6 (12) ◽  
pp. 2261-2280 ◽  
Author(s):  
Wu Ma ◽  
Xiangdong Lei
Keyword(s):  
Northeast China ◽  
Simultaneous Equations ◽  
Oak Forests ◽  
Diameter Growth ◽  
Individual Tree ◽  
Tree Diameter ◽  
Mortality Model ◽  
Nonlinear Simultaneous Equations ◽  
Mongolian Oak

Deriving Tree Diameter Growth and Probability of Survival Equations from Successive Diameter Distributions

2008 ◽  
Vol 54 (1) ◽  
pp. 31-35
Author(s):  
Thomas G. Matney ◽  
Emily B. Schultz
Keyword(s):  
General Procedure ◽  
Growth And Yield ◽  
Diameter Distribution ◽  
Diameter Growth ◽  
Individual Tree ◽  
Statistical Probability ◽  
Growth And Survival ◽  
Tree Diameter ◽  
Growth And Yield Models ◽  
Diameter Distributions

Abstract Many growth and yield models have used statistical probability distributions to estimate the diameter distribution of a stand at any age. Equations for approximating individual tree diameter growth and survival probabilities from dbh can be derived from these models. A general procedure for determining the functions is discussed and illustrated using a loblolly pine spacing study. The results from the spacing study show that it is possible to define tree diameter growth and survival probability functions from diameter distributions with an accuracy sufficient to obtain a link between the individual tree and diameter growth and yield models.

scholarly journals Individual-Tree Diameter Growth Models for Mixed Nothofagus Second Growth Forests in Southern Chile

Forests ◽  
2017 ◽  
Vol 8 (12) ◽  
pp. 506 ◽  
Author(s):  
Paulo Moreno ◽  
Sebastian Palmas ◽  
Francisco Escobedo ◽  
Wendell Cropper ◽  
Salvador Gezan
Keyword(s):  
Growth Models ◽  
Diameter Growth ◽  
Southern Chile ◽  
Individual Tree ◽  
Tree Diameter ◽  
Second Growth ◽  
Diameter Growth Models

scholarly journals Individual Tree Diameter Growth Models of Larch–Spruce–Fir Mixed Forests Based on Machine Learning Algorithms

Forests ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 187 ◽  
Author(s):  
Qiangxin Ou ◽  
Xiangdong Lei ◽  
Chenchen Shen
Keyword(s):  
Machine Learning ◽  
Tree Growth ◽  
Growth Models ◽  
Tree Size ◽  
Diameter Growth ◽  
Individual Tree ◽  
Mixed Forests ◽  
Tree Diameter ◽  
Individual Tree Growth ◽  
The Individual

Individual tree growth models are flexible and commonly used to represent growth dynamics for heterogeneous and structurally complex uneven-aged stands. Besides traditional statistical models, the rapid development of nonparametric and nonlinear machine learning methods, such as random forest (RF), boosted regression tree (BRT), cubist (Cubist) and multivariate adaptive regression splines (MARS), provides a new way for predicting individual tree growth. However, the application of these approaches to individual tree growth modelling is still limited and short of a comparison of their performance. The objectives of this study were to compare and evaluate the performance of the RF, BRT, Cubist and MARS models for modelling the individual tree diameter growth based on tree size, competition, site condition and climate factors for larch–spruce–fir mixed forests in northeast China. Totally, 16,619 observations from long-term sample plots were used. Based on tenfold cross-validation, we found that the RF, BRT and Cubist models had a distinct advantage over the MARS model in predicting individual tree diameter growth. The Cubist model ranked the highest in terms of model performance (RMSEcv [0.1351 cm], MAEcv [0.0972 cm] and R2cv [0.5734]), followed by BRT and RF models, whereas the MARS ranked the lowest (RMSEcv [0.1462 cm], MAEcv [0.1086 cm] and R2cv [0.4993]). Relative importance of predictors determined from the RF and BRT models demonstrated that the competition and tree size were the main drivers to diameter growth, and climate had limited capacity in explaining the variation in tree diameter growth at local scale. In general, the RF, BRT and Cubist models are effective and powerful modelling methods for predicting the individual tree diameter growth.

scholarly journals Precommercial Thinning in a Ponderosa Pine Stand Affected by Armillaria Root Disease in Central Oregon: 30 Years of Growth and Mortality

1999 ◽  
Vol 14 (3) ◽  
pp. 144-148 ◽  
Author(s):  
Gregory M. Filip ◽  
Stephen A. Fitzgerald ◽  
Lisa M. Ganio
Keyword(s):  
Ponderosa Pine ◽  
Tree Mortality ◽  
Basal Area ◽  
Stand Density ◽  
Root Disease ◽  
Diameter Growth ◽  
Individual Tree ◽  
Precommercial Thinning ◽  
Tree Diameter ◽  
Armillaria Root Disease

Abstract A 30-yr-old stand of ponderosa pine was precommercially thinned in 1966 to determine the effects of thinning on tree growth and mortality caused by Armillaria root disease in central Oregon. After 30 yr, crop tree mortality was significantly (P = 0.02) less in thinned plots than in unthinned plots. Tree diameter growth was not significantly (P = 0.17) increased by thinning. Crop-tree basal area/ac growth was significantly (P = 0.03) greater in thinned plots. Apparently, from a root disease perspective, precommercial thinning of pure ponderosa stands significantly decreases the incidence of crop-tree mortality after 30 yr and significantly increases basal area/ac growth but not individual tree diameter growth. Recommendations for thinning based on stand density index (SDI) are given. West. J. Appl. For. 14(3):144-148.

scholarly journals Modelling Individual Tree Diameter Growth of Quercus mongolica Secondary Forest in the Northeast of China

2021 ◽  
Vol 13 (8) ◽  
pp. 4533
Author(s):  
Xuefan Hu ◽  
Guangshuang Duan ◽  
Huiru Zhang
Keyword(s):  
Secondary Forest ◽  
Forest Growth ◽  
Site Quality ◽  
Diameter Growth ◽  
Mixed Effect ◽  
Individual Tree ◽  
Quercus Mongolica ◽  
Tree Diameter ◽  
Basic Model ◽  
Northeast Of China

Quercus mongolica secondary forest is widely distributed in the northeast of China, but it usually has low productivity, unstable structure, poor health, and low biodiversity. Diameter is a tree variable that is commonly used for forest growth measurement, to provide the basis for forest management decision. Two level generalized linear mixed effects individual diameter growth model were developed using data from two times surveys of 12 Q. mongolica secondary forest permanent plots that were distributed among Wangqing forest farms. Random effects of 14 tree species and 12 plots were introduced into the basic model consisting of three factors: tree size, competition of surrounding trees, and site quality. The results showed that initial diameter at breast height(DBH) was the most important variable affecting diameter growth, followed by competition, while the effect of site quality on diameter growth was not significant. Compared with the basic model, the prediction accuracy of the mixed effect model was improved by 17.69 %, where R2 reached to 0.6805, indicating that it is suitable for the individual-tree diameter growth prediction of the secondary forest of Q. mongolica.

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