Using nonlinear mixed model and dummy variable model approaches to develop origin-based individual tree biomass equations

Trees ◽  
2014 ◽  
Vol 29 (1) ◽  
pp. 275-283 ◽  
Author(s):  
Wei-Sheng Zeng
Keyword(s):  
Mixed Model ◽  
Tree Biomass ◽  
Nonlinear Mixed Model ◽  
Variable Model ◽  
Individual Tree ◽  
Dummy Variable ◽  
Biomass Equations

scholarly journals Using linear mixed model and dummy variable  model approaches to construct compatible single-tree biomass equations at different scales – A case study for Masson pine in Southern China

2012 ◽  
Vol 58 (No. 3) ◽  
pp. 101-115 ◽  
Author(s):  
L.Y. Fu ◽  
W.S. Zeng ◽  
S.Z. Tang ◽  
R.P. Sharma ◽  
H.K. Li
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Southern China ◽  
Forest Biomass ◽  
Tree Biomass ◽  
Variable Model ◽  
Masson Pine ◽  
Dummy Variable ◽  
Single Tree ◽  
Biomass Models

The estimation of forest biomass is important for practical issues and scientific purposes in forestry. The estimation of forest biomass on a large-scale level would be merely possible with the application of generalized single-tree biomass models. The aboveground biomass data on Masson pine (Pinus massoniana) from nine provinces in southern China were used to develop generalized single-tree biomass models using both linear mixed model and dummy variable model methods. An allometric function requiring only diameter at breast height was used as a base model for this purpose. The results showed that the aboveground biomass estimates of individual trees with identical diameters were different among the forest origins (natural and planted) and geographic regions (provinces). The linear mixed model with random effect parameters and dummy model with site-specific (local) parameters showed better fit and prediction performance than the population average model. The linear mixed model appears more flexible than the dummy variable model for the construction of generalized single-tree biomass models or compatible biomass models at different scales. The linear mixed model method can also be applied to develop other types of generalized single-tree models such as basal area growth and volume models.  

Using the dummy variable model approach to construct compatible single-tree biomass equations at different scales — a case study for Masson pine (Pinus massoniana) in southern China

2011 ◽  
Vol 41 (7) ◽  
pp. 1547-1554 ◽  
Author(s):  
Wei Sheng Zeng ◽  
Hui Ru Zhang ◽  
Shou Zheng Tang
Keyword(s):  
Southern China ◽  
Forest Biomass ◽  
Pinus Massoniana ◽  
Biomass Estimation ◽  
Tree Biomass ◽  
Variable Model ◽  
Masson Pine ◽  
Dummy Variable ◽  
Single Tree ◽  
Biomass Equations

It is fundamental for monitoring and assessment of national forest biomass to develop generalized single-tree biomass models suitable for large-scale forest biomass estimation. However, the compatibility of forest biomass estimates among different scales is a real problem. Based on the aboveground biomass data of Masson pine (Pinus massoniana Lamb.) in southern China, generalized single-tree biomass equations applying to national and regional forest biomass estimation were constructed using the dummy variable model method, which provided an effective approach to solving the compatibility of forest biomass estimates among different scales. The results show that aboveground biomass estimates of individual trees with the same diameter are different to some extent among the forest origins and geographic regions and that a dummy model with specific (local) parameters is better than a population-average model. The dummy variable model can be applied to develop other generalized compatible models such as tree volume equations.

scholarly journals Deriving Individual-Tree Biomass from Effective Crown Data Generated by Terrestrial Laser Scanning

2019 ◽  
Vol 11 (23) ◽  
pp. 2793
Author(s):  
Yujie Zheng ◽  
Weiwei Jia ◽  
Qiang Wang ◽  
Xu Huang
Keyword(s):  
Laser Scanning ◽  
Three Dimensional ◽  
Terrestrial Laser Scanning ◽  
Tree Height ◽  
Biomass Estimation ◽  
Tree Biomass ◽  
Crown Height ◽  
Individual Tree ◽  
Cloud Data ◽  
Biomass Equations

Biomass reflects the state of forest management and is critical for assessing forest benefits and carbon storage. The effective crown is the region above the lower limit of the forest crown that includes the maximum vertical distribution density of branches and leaves; this component plays an important role in tree growth. Adding the effective crown to biomass equations can enhance the accuracy of the derived biomass. Six sample plots in a larch plantation (ranging in area from 0.06 ha to 0.12 ha and in number of trees from 63 to 96) at the Mengjiagang forest farm in Huanan County, Jiamusi City, Heilongjiang Province, China, were analyzed in this study. Terrestrial laser scanning (TLS) was used to obtain three-dimensional point cloud data on the trees, from which crown parameters at different heights were extracted. These parameters were used to determine the position of the effective crown. Moreover, effective crown parameters were added to biomass equations with tree height as the sole variable to improve the accuracy of the derived individual-tree biomass estimates. The results showed that the minimum crown contact height was very similar to the effective crown height, and an increase in model accuracy was apparent (with R a 2 increasing from 0.846 to 0.910 and root-mean-square error (RMSE) decreasing from 0.372 kg to 0.286 kg). The optimal model for deriving biomass included tree height, crown length from minimum contact height, crown height from minimum contact height, and crown surface area from minimum contact height. The novelty of the article is that it improves the fit of individual-tree biomass models by adding crown-related variables and investigates how the accuracy of biomass estimation can be enhanced by using remote sensing methods without obtaining diameter at breast height.

Individual tree biomass equations and growth models sensitive to climate variables for Larix spp. in China

2017 ◽  
Vol 136 (2) ◽  
pp. 233-249 ◽  
Author(s):  
WeiSheng Zeng ◽  
HaiRui Duo ◽  
XiangDong Lei ◽  
XinYun Chen ◽  
XueJun Wang ◽  
...  
Keyword(s):  
Growth Models ◽  
Climate Variables ◽  
Tree Biomass ◽  
Individual Tree ◽  
Biomass Equations

Can crown variables increase the generality of individual tree biomass equations?

Trees ◽  
2020 ◽  
Author(s):  
David I. Forrester ◽  
Ian C. Dumbrell ◽  
Stephen R. Elms ◽  
Keryn I. Paul ◽  
Elizabeth A. Pinkard ◽  
...  
Keyword(s):  
Tree Biomass ◽  
Individual Tree ◽  
Biomass Equations

scholarly journals A practical measure for determining if diameter (D) and height (H) should be combined into D2H in allometric biomass models

2019 ◽  
Vol 92 (5) ◽  
pp. 627-634 ◽  
Author(s):  
I Dutcă ◽  
R E McRoberts ◽  
E Næsset ◽  
V N B Blujdea
Keyword(s):  
Aboveground Biomass ◽  
Prediction Accuracy ◽  
Fixed Ratio ◽  
Tree Height ◽  
Parameter Estimates ◽  
Tree Biomass ◽  
Variable Model ◽  
Individual Tree ◽  
Model Constraint ◽  
Practical Measure

AbstractTree diameter at breast height (D) and tree height (H) are often used as predictors of individual tree biomass. Because D and H are correlated, the combined variable D2H is frequently used in regression models instead of two separate independent variables, to avoid collinearity related issues. The justification for D2H is that aboveground biomass is proportional to the volume of a cylinder of diameter, D, and height, H. However, the D2H predictor constrains the model to produce parameter estimates for D and H that have a fixed ratio, in this case, 2.0. In this paper we investigate the degree to which the D2H predictor reduces prediction accuracy relative to D and H separately and propose a practical measure, Q-ratio, to guide the decision as to whether D and H should or should not be combined into D2H. Using five training biomass datasets and two fitting approaches, weighted nonlinear regression and linear regression following logarithmic transformations, we showed that the D2H predictor becomes less efficient in predicting aboveground biomass as the Q-ratio deviates from 2.0. Because of the model constraint, the D2H-based model performed less well than the separate variable model by as much as 12 per cent with regard to mean absolute percentage residual and as much as 18 per cent with regard to sum of squares of log accuracy ratios. For the analysed datasets, we observed a wide variation in Q-ratios, ranging from 2.5 to 5.1, and a large decrease in efficiency for the combined variable model. Therefore, we recommend using the Q-ratio as a measure to guide the decision as to whether D and H may be combined further into D2H without the adverse effects of loss in biomass prediction accuracy.

scholarly journals Skill Transference of a Probe-Tube Placement Training Simulator

2020 ◽  
Vol 31 (01) ◽  
pp. 040-049 ◽  
Author(s):  
Robert W. Koch ◽  
Hasan Saleh ◽  
Paula Folkeard ◽  
Sheila Moodie ◽  
Conner Janeteas ◽  
...  
Keyword(s):  
Mixed Model ◽  
Tracking System ◽  
Optical Tracking ◽  
Tube Placement ◽  
Control Group ◽  
Educational Settings ◽  
Training Simulator ◽  
Nonlinear Mixed Model ◽  
Optical Tracking System ◽  
Clinical Scenarios

AbstractProbe-tube placement is a necessary step in hearing aid verification which needs ample hands-on experience and confidence before performing in clinic. To improve the methods of training in probe-tube placement, a manikin-based training simulator was developed consisting of a 3D-printed head, a flexible silicone ear, and a mounted optical tracking system. The system is designed to provide feedback to the user on the depth and orientation of the probe tube, and the time required to finish the task. Although a previous validation study was performed to determine its realism and teachability with experts, further validation is required before implementation into educational settings.This study aimed to examine the skill transference of a newly updated probe-tube placement training simulator to determine if skills learned on this simulator successfully translate to clinical scenarios.All participants underwent a pretest in which they were evaluated while performing a probe-tube placement and real-ear-to-coupler difference (RECD) measurement on a volunteer. Participants were randomized into one of two groups: the simulator group or the control group. During a two-week training period, all participants practiced their probe-tube placement according to their randomly assigned group. After two weeks, each participant completed a probe-tube placement on the same volunteer as a posttest scenario.Twenty-five novice graduate-level student clinicians.Participants completed a self-efficacy questionnaire and an expert observer completed a questionnaire evaluating each participant’s performance during the pre- and posttest sessions. RECD measurements were taken after placing the probe tube and foam tip in the volunteer’s ear. Questionnaire results were analyzed through nonparametric t-tests and analysis of variance, whereas RECD results were analyzed using a nonlinear mixed model method.Results suggested students in the simulator group were less likely to contact the tympanic membrane when placing a probe tube, appeared more confident, and had better use of the occluding foam tip, resulting in more improved RECD measurements.The improved outcomes for trainees in the simulator group suggest that supplementing traditional training with the simulator provides useful benefits for the trainees, thereby encouraging its usage and implementation in educational settings.

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