Evaluation of four regression techniques for stem taper modeling of Dahurian larch (Larix gmelinii) in Northeastern China

He, Pei; Hussain, Amna; Shahzad, Muhammad Khurram; Jiang, Lichun; Li, Fengri

doi:10.1016/j.foreco.2021.119336

Cited by 19 publications

(10 citation statements)

References 77 publications

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“…The variable-exponent taper equation is critical for providing a more accurate estimate of the stem form. In this study, 12 different forms of variable-exponent taper equations (Table 2) were fitted to the larch plantation data, and the fitting precision of the Kozak (2004) variable-exponent taper equation was higher than that of the others (Table 4), which is consistent with the conclusions of previous studies (Özçelik and Crecente-Campo, 2016;Liu et al, 2020;Shahzad et al, 2020;He et al, 2021). The Kozak (2004) variable-exponent taper equation well describes the stem form of larch (Larix gmelinii), lebanon cedar (Cedrus libani A.…”

Section: Selection Of the Optimal Basic Modelsupporting

confidence: 88%

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Incorporating stand density effects and regression techniques for stem taper modeling of a Larix principis-rupprechtii plantation

Wang²,

Liu³

et al. 2022

Front. Plant Sci.

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Stem form is the shape of the trunk, differs among tree species and mainly affected by stand density factor. Accurate taper equations are crucial for estimating the stem diameter, form and tree volume, which is conducive to timber utilization and sustainable forest management and planning. Larch (Larix principis-rupprechtii Mayr.) is a valuable afforestation species under large-scale development in North China, but no study on the effect of density on its stem taper has been reported yet. The dataset included 396 analytical trees from 132 standard plots of larch plantation in Saihanba, Hebei Province. Based on 12 different forms of models, we explored the optimal basic equation for plantations and the effects of the stand density, basal area, canopy density and different forms of stand density on the prediction accuracy of the variable-exponent models. The variable-exponent taper equation that includes Sd (stand density) was constructed by using nonlinear regression, a nonlinear mixed effect model and the nonlinear quantile regression method. The results indicate that the Kozak’s 2004 variable-exponent taper equation was the best basic model for describing changes in the stem form of larch plantations, and the density factor in the form of Sd improved the prediction accuracy of the basic model. Among the three regression methods, the quantile regression method had the highest fitting accuracy, followed by the nonlinear mixed effect model. When the quantile was 0.5, the nonlinear quantile regression model exhibited the best performance which provides a scientific basis for the rational management of larch plantations.

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Section: Selection Of the Optimal Basic Modelsupporting

confidence: 88%

“…In most cases, different regression techniques affect the prediction accuracy of the taper model (He et al, 2021). Although nonlinear regression is the most commonly used method, the data used in this method must meet the assumptions of independent error terms (Yang et al, 2009).…”

Section: Effects Of Regression Techniquesmentioning

confidence: 99%

Incorporating stand density effects and regression techniques for stem taper modeling of a Larix principis-rupprechtii plantation

Wang²,

Liu³

et al. 2022

Front. Plant Sci.

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“…However, the Kozak (2004) variable exponent taper equation is flexible and easily used ( Xu et al., 2022 ). It has been proven to be applicable to many species in different countries ( Huang et al., 2000 ; Klos et al., 2007 ; Jiang and Liu, 2011 ; He et al., 2021 ).…”

Section: Discussionmentioning

confidence: 99%

“…Compared with simple taper functions and segmented taper functions, variable exponent taper equations are more effective because they are highly flexible at predicting the stem diameter with minimum local deviation at any given height from the ground ( Bi, 2000 ; Sharma and Oderwald, 2001 ; Jiang et al., 2005 ; Corral-Rivas et al., 2007 ; Lumbres et al., 2017 ). In many different forms of variable exponential taper equations, different forms of Kozak’s taper equations have been proven to be suitable for most tree species and are highly accurate at making predictions ( Klos et al., 2007 ; Fonweban et al., 2012 ; He et al., 2021 ). Therefore, three forms of Kozak’s variable exponential taper equations were selected for our study.…”

Section: Methodsmentioning

confidence: 99%

Biomass allometric models for Larix rupprechtii based on Kosak’s taper curve equations and nonlinear seemingly unrelated regression

Wang

Zhang

et al. 2023

Front. Plant Sci.

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The diameter at breast height (DBH) is the most important independent variable in biomass allometry models based on metabolic scaling theory (MST) or geometric theory. However, the fixed position DBH can be misleading in its use of universal scaling laws and lead to some deviation for the biomass model. Therefore, it is still an urgent scientific problem to build a high-precision biomass model system. A dataset of 114 trees was destructively sampled to obtain dry biomass components, including stems, branches, and foliage, and taper measurements to explore the applicability of biomass components to allometric scaling laws and develop a new system of additive models with the diameter in relative height (DRH) for each component of a Larch (Larix principis-rupprechtii Mayr) plantation in northern China. The variable exponential taper equations were modelled using nonlinear regression. In addition, applying nonlinear regression and nonlinear seemingly unrelated regression (NSUR) enabled the development of biomass allometric models and the system of additive models with DRH for each component. The results showed that the Kozak’s (II) 2004 variable exponential taper equation could accurately describe the stem shape and diameter in any height of stem. When the diameters in relative height were D0.2, D0.5, and D0.5 for branches, stems, and foliage, respectively, the allometric exponent of the stems and branches was the closest to the scaling relations predicted by the MST, and the allometric exponent of foliage was the most closely related to the scaling relations predicted by geometry theory. Compared with the nonlinear regression, the parameters of biomass components estimated by NSUR were lower, and it was close to the theoretical value and the most precise at forecasting. In the study of biomass process modelling, utilizing the DRH by a variable exponential taper equation can confirm the general biological significance more than the DBH of a fixed position.

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“…BLUP requires the measurement of a certain number of new data in a site or sample area to be calibrated, especially when estimating the random-effect parameter (He et al 2021). In particular, the determination of the trees (thickest, thinnest or near-median diameter trees) to be measured in the sample areas is referred to as the "calibration response" of the mixed-effects models.…”

Section: Calibration Responsesmentioning

confidence: 99%

Modeling compatible taper and stem volume of pure Scots pine stands in Northeastern Turkey

Saygili¹,

Kahriman²

2023

iForest

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Compatible taper and volume equations for pure and natural Scots pine stands in the northeastern part of Turkey (Ardahan Province) were developed using a nonlinear mixed-effects modeling approach. Experimental data were obtained from 137 felled sample trees in different diameter and height classes. The most successful model (Jiang et al. 2005) explained 98.3% of the variance in stem diameter estimation and the RMSE, ME, MAE, AIC and BIC value obtained using this model were 1.955 cm, 0.043 cm, 1.300 cm, 9783.8 and 9812.6, respectively. Considering the criterion values of AIC, BIC and -2LnL, the model with random-effects in two parameters (b1 and b3) was the most successful for Scots pine. While the mixed model including random parameters did not completely solved the problem of the autocorrelation of errors in this study, the use of the autoregressive error structure AR(1) eliminated the autocorrelation in the residuals. In addition, the best estimation results among 20 different calibration options were obtained using the option of measuring two tree diameters at d1.30 and d5.30 with validation data. The most successful model explained 99.18% of the total variance in stem volume estimation in Scots pine.

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Evaluation of four regression techniques for stem taper modeling of Dahurian larch (Larix gmelinii) in Northeastern China

Cited by 19 publications

References 77 publications

Incorporating stand density effects and regression techniques for stem taper modeling of a Larix principis-rupprechtii plantation

Incorporating stand density effects and regression techniques for stem taper modeling of a Larix principis-rupprechtii plantation

Biomass allometric models for Larix rupprechtii based on Kosak’s taper curve equations and nonlinear seemingly unrelated regression

Modeling compatible taper and stem volume of pure Scots pine stands in Northeastern Turkey

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