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 Increased Individual Tree Growth Maintains Stand Volume Growth after B-Level Thinning and Crop-Tree Management in Mature Oak Stands

2019 ◽  
Vol 65 (6) ◽  
pp. 784-795
Author(s):  
Jeffrey S Ward ◽  
Jessica Wikle
Keyword(s):  
Tree Growth ◽  
Growth Response ◽  
Volume Growth ◽  
Diameter Growth ◽  
Red Oak ◽  
Individual Tree ◽  
Stand Volume ◽  
Tree Management ◽  
Individual Tree Growth ◽  
Partial Release

AbstractSix study areas were established in 80–125-year-old upland oak stands on average sites to compare stand and individual tree growth response following two active treatments (B-level thinning, crop tree) with an unmanaged control. Initial stocking of 104 percent was reduced to 62 percent and 60 percent on the B-level and crop-tree-management plots, respectively. Approximately 7,200 board feet per acre (International ¼) were harvested on the actively managed plots with upland oaks accounting for 81 percent of pre- and 86 percent of residual stand. Eleven-year diameter and volume growth of oak sawtimber trees was greater on actively managed plots. Growth response increased with degree of release and was maintained for the length of the study. Because of the increased individual tree growth of oaks in response to release, stand volume growth of oak sawtimber did not differ between treatments. In contrast to an 11-year decline of poletimber stocking on unmanaged plots, poletimber stocking increased on managed plots as diameter growth increased in response to partial release. This may increase difficulty of regenerating oak in the future. For those mature red oak stands where traditional regeneration prescriptions will not be implemented or will be delayed, commercial harvests can be conducted without compromising stand volume growth of oak.

Stochastic structure and individual-tree growth models

2001 ◽  
Vol 154 (1-2) ◽  
pp. 261-276 ◽  
Author(s):  
Julian C. Fox ◽  
Peter K. Ades ◽  
Huiquan Bi
Keyword(s):  
Tree Growth ◽  
Growth Models ◽  
Stochastic Structure ◽  
Individual Tree ◽  
Individual Tree Growth

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 Comparison of Spatially and Nonspatially Explicit Nonlinear Mixed Effects Models for Norway Spruce Individual Tree Growth under Single-Tree Selection

Forests ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1338
Author(s):  
Simone Bianchi ◽  
Mari Myllymaki ◽  
Jouni Siipilehto ◽  
Hannu Salminen ◽  
Jari Hynynen ◽  
...  
Keyword(s):  
Norway Spruce ◽  
Tree Growth ◽  
Cross Validation ◽  
Growth Models ◽  
Forest Growth ◽  
Individual Tree ◽  
Selection Cutting ◽  
Single Tree ◽  
Individual Tree Growth ◽  
Single Tree Selection

Background and Objectives: Continuous cover forestry is of increasing importance, but operational forest growth models are still lacking. The debate is especially open if more complex spatial approaches would provide a worthwhile increase in accuracy. Our objective was to compare a nonspatial versus a spatial approach for individual Norway spruce tree growth models under single-tree selection cutting. Materials and Methods: We calibrated nonlinear mixed models using data from a long-term experiment in Finland (20 stands with 3538 individual trees for 10,238 growth measurements). We compared the use of nonspatial versus spatial predictors to describe the competitive pressure and its release after cutting. The models were compared in terms of Akaike Information Criteria (AIC), root mean square error (RMSE), and mean absolute bias (MAB), both with the training data and after cross-validation with a leave-one-out method at stand level. Results: Even though the spatial model had a lower AIC than the nonspatial model, RMSE and MAB of the two models were similar. Both models tended to underpredict growth for the highest observed values when the tree-level random effects were not used. After cross-validation, the aggregated predictions at stand level well represented the observations in both models. For most of the predictors, the use of values based on trees’ height rather than trees’ diameter improved the fit. After single-tree selection cutting, trees had a growth boost both in the first and second five-year period after cutting, however, with different predicted intensity in the two models. Conclusions: Under the research framework here considered, the spatial modeling approach was not more accurate than the nonspatial one. Regarding the single-tree selection cutting, an intervention regime spaced no more than 15 years apart seems necessary to sustain the individual tree growth. However, the model’s fixed effect parts were not able to capture the high growth of the few fastest-growing trees, and a proper estimation of site potential is needed for uneven-aged stands.

scholarly journals The SOHARC Model System for Growth and Yield of Southern Hardwoods

2008 ◽  
Vol 32 (4) ◽  
pp. 173-183 ◽  
Author(s):  
John Paul McTague ◽  
David O'Loughlin ◽  
Joseph P. Roise ◽  
Daniel J. Robison ◽  
Robert C. Kellison
Keyword(s):  
Tree Growth ◽  
Growth Models ◽  
Basal Area ◽  
Tree Height ◽  
Growth And Yield ◽  
Permanent Plots ◽  
Red Maple ◽  
Yellow Poplar ◽  
Individual Tree ◽  
Individual Tree Growth

Abstract A system of stand level and individual tree growth-and-yield models are presented for southern hardwoods. These models were developed from numerous permanent growth-and-yield plots established across 13 states in the US South on 9 site types, in even-aged (age classes from 20 to 60 years), fully stocked, naturally regenerated mixed hardwood and mixed hardwood-pine stands. Nested plots (⅕ and ac) were remeasured at 5-year intervals. The system of permanent plots was established and maintained by private and public members in the North Carolina State University Hardwood Research Cooperative. Stand level models are presented for dominant height, survival, basal area prediction and projection, and the ingrowth component. Individual tree diameter growth and tree height models were constructed for the most common species: sweetgum, tupelo, yellow-poplar, blackgum, and red maple. All other species were grouped according to growth dynamics into four species groups using cluster analysis. A ranking variable was incorporated into the individual tree growth models to account for competition.

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