scholarly journals Generic additive allometric models and biomass allocation for two natural oak species in northeastern China

2020 ◽  
Author(s):  
Shengwang Meng ◽  
Fan Yang ◽  
Haibin Wang ◽  
Wei Wang ◽  
Sheng Hu ◽  
...  
Keyword(s):  
Biomass Allocation ◽  
Large Scale ◽  
Forest Biomass ◽  
Tree Height ◽  
Northeastern China ◽  
Carbon Accounting ◽  
Biomass Estimation ◽  
Stem Biomass ◽  
Biomass Models ◽  
Mongolian Oak

Abstract Background: Accurate quantification of forest biomass through allometric equations is crucial for global carbon accounting and climate change mitigation. Current models for oak species could not accurately estimate biomass in northeastern China, since they were usually established limited to Mongolian oak (Quercus mongolica) on local sites, and specifically, no biomass models were available for Liaodong oak (Quercus wutaishanica). The goal of this study was, therefore, to develop generic biomass models for both oak species on large scale and evaluate biomass allocation patterns within tree components. Results: The stem biomass accounts for about two-thirds of the aboveground biomass. The ratio of wood biomass holds constant and that of branch increases with increasing D, H, CW, CL, while a reverse trend was found for bark and foliage. The root-shoot ratio nonlinearly decreased with D, ranging from 1.06 to 0.11. Tree diameter proved to be a good predictor, especially for root biomass. Tree height is more prominent than crown size for improving stem biomass models, yet it puts negative effects on crown biomass models with non-significant coefficients. Crown width could help improve fitting results of branch and foliage biomass models. Conclusion: We conclude that the selected generic biomass models for Mongolian oak and Liaodong oak will vigorously promote the accuracy of biomass estimation.

scholarly journals Generic Additive Allometric Models and Biomass Allocation for Two Natural Oak Species in Northeastern China

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 715
Author(s):  
Shengwang Meng ◽  
Fan Yang ◽  
Sheng Hu ◽  
Haibin Wang ◽  
Huimin Wang
Keyword(s):  
Biomass Allocation ◽  
Tree Height ◽  
Northeastern China ◽  
Seemingly Unrelated Regression ◽  
Biomass Estimation ◽  
Model Parameters ◽  
Stem Biomass ◽  
Crown Width ◽  
Biomass Models ◽  
Mongolian Oak

Current models for oak species could not accurately estimate biomass in northeastern China, since they are usually restricted to Mongolian oak (Quercus mongolica Fisch. ex Ledeb.) on local sites, and specifically, no biomass models are available for Liaodong oak (Quercuswutaishanica Mayr). The goal of this study was, therefore, to develop generic biomass models for both oak species on a large scale and evaluate the biomass allocation patterns within tree components. A total of 159 sample trees consisting of 120 Mongolian oak and 39 Liaodong oak were harvested and measured for wood (inside bark), bark, branch and foliage biomass. To account for the belowground biomass, 53 root systems were excavated following the aboveground harvest. The share of biomass allocated to different components was assessed by calculating the ratios. An aboveground additive system of biomass models and belowground equations were fitted based on predictors considering diameter (D), tree height (H), crown width (CW) and crown length (CL). Model parameters were estimated by jointly fitting the total and the components’ equations using the weighted nonlinear seemingly unrelated regression method. A leave-one-out cross-validation procedure was used to evaluate the predictive ability. The results revealed that stem biomass accounts for about two-thirds of the aboveground biomass. The ratio of wood biomass holds constant and that of branches increases with increasing D, H, CW and CL, while a reverse trend was found for bark and foliage. The root-to-shoot ratio nonlinearly decreased with D, ranging from 1.06 to 0.11. Tree diameter proved to be a good predictor, especially for root biomass. Tree height is more prominent than crown size for improving stem biomass models, yet it puts negative effects on crown biomass models with non-significant coefficients. Crown width could help improve the fitting results of the branch and foliage biomass models. We conclude that the selected generic biomass models for Mongolian oak and Liaodong oak will vigorously promote the accuracy of biomass estimation.

scholarly journals The Effects of Combining the Variables in Allometric Biomass Models on Biomass Estimates over Large Forest Areas: A European Beech Case Study

Forests ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1428
Author(s):  
Erick O. Osewe ◽  
Ioan Dutcă
Keyword(s):  
Nonlinear Models ◽  
Forest Biomass ◽  
Tree Height ◽  
European Beech ◽  
Biomass Estimation ◽  
Parameter Estimates ◽  
Variable Model ◽  
Separate Variable ◽  
Biomass Models ◽  
Fagus Sylvatica L

Effective initiatives for forest-based mitigation of climate change rely on continuous efforts to improve the estimation of forest biomass. Allometric biomass models, which are nonlinear models that predict aboveground biomass (AGB) as a function of diameter at breast height (D) and tree height (H), are typically used in forest biomass estimations. A combined variable D2H may be used instead of two separate predictors. The Q-ratio (i.e., the ratio between the parameter estimates of D and parameter estimates of H, in a separate variable model) was proposed recently as a measure to guide the decision on whether D and H can be safely combined into D2H, being shown that the two model forms are similar when Q = 2.0. Here, using five European beech (Fagus sylvatica L.) biomass datasets (of different Q-ratios ranging from 1.50 to 5.05) and an inventory dataset for the same species, we investigated the effects of combining the variables in allometric models on biomass estimation over large forest areas. The results showed that using a combined variable model instead of a separate variable model to predict biomass of European beech trees resulted in overestimation of mean AGB per hectare for Q > 2.0 (i.e., by 6.3% for Q = 5.05), underestimation for Q < 2.0 (i.e., by –3.9% for Q = 1.50), whereas for Q = 2.03, the differences were minimum (0.1%). The standard errors of mean AGB per hectare were similar for Q = 2.03 (differences up to 0.2%), and the differences increased with the Q-ratio, by up 10.2% for Q = 5.05. Therefore, we demonstrated for European beech that combining the variables in allometric biomass models when Q ≠ 2.0 resulted in biased estimates of mean AGB per hectare and of uncertainty.

scholarly journals Removing the Scaling Error Caused by Allometric Modelling in Forest Biomass Estimation at Large Scales

Forests ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 602
Author(s):  
Carl Zhou ◽  
Xiaolu Zhou
Keyword(s):  
Large Scale ◽  
Forest Ecosystems ◽  
Forest Biomass ◽  
Field Measurements ◽  
Allometric Equation ◽  
Biomass Estimation ◽  
Allometric Relationships ◽  
Data Errors ◽  
Pinus Yunnanensis

To estimate the responses of forest ecosystems, most relationships in biological systems are described by allometric relationships, the parameters of which are determined based on field measurements. The use of existing observed data errors may occur during the scaling of fine-scale relationships to describe ecosystem properties at a larger ecosystem scale. Here, we analyzed the scaling error in the estimation of forest ecosystem biomass based on the measurement of plots (biomass or volume per hectare) using an improved allometric equation with a scaling error compensator. The efficiency of the compensator on reducing the scaling error was tested by simulating the forest stand populations using pseudo-observation. Our experiments indicate that, on average, approximately 94.8% of the scaling error can be reduced, and for a case study, an overestimation of 3.6% can be removed in practice from a large-scale estimation for the biomass of Pinus yunnanensis Franch.

Indirect methods of large-scale forest biomass estimation

2006 ◽  
Vol 126 (2) ◽  
pp. 197-207 ◽  
Author(s):  
Z. Somogyi ◽  
E. Cienciala ◽  
R. Mäkipää ◽  
P. Muukkonen ◽  
A. Lehtonen ◽  
...  
Keyword(s):  
Large Scale ◽  
Forest Biomass ◽  
Biomass Estimation ◽  
Indirect Methods

scholarly journals Separating Regressions for Model Fitting to Reduce the Uncertainty in Forest Volume-Biomass Relationship

Forests ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 658
Author(s):  
Caixia Liu ◽  
Xiaolu Zhou ◽  
Xiangdong Lei ◽  
Huabing Huang ◽  
Carl Zhou ◽  
...  
Keyword(s):  
Field Data ◽  
Forest Biomass ◽  
Model Fitting ◽  
Graphical Analysis ◽  
Biomass Estimation ◽  
Allometric Relationship ◽  
Stem Biomass ◽  
Intermediate Variable ◽  
Growing Stock ◽  
Pseudo Data

The method of forest biomass estimation based on a relationship between the volume and biomass has been applied conventionally for estimating stand above- and below-ground biomass (SABB, t ha−1) from mean growing stock volume (m3 ha−1). However, few studies have reported on the diagnosis of the volume-SABB equations fitted using field data. This paper addresses how to (i) check parameters of the volume-SABB equations, and (ii) reduce the bias while building these equations. In our analysis, all equations were applied based on the measurements of plots (biomass or volume per hectare) rather than individual trees. The volume-SABB equation is re-expressed by two Parametric Equations (PEs) for separating regressions. Stem biomass is an intermediate variable (parametric variable) in the PEs, of which one is established by regressing the relationship between stem biomass and volume, and the other is created by regressing the allometric relationship of stem biomass and SABB. A graphical analysis of the PEs proposes a concept of “restricted zone,” which helps to diagnose parameters of the volume-SABB equations in regression analyses of field data. The sampling simulations were performed using pseudo data (artificially generated in order to test a model) for the model test. Both analyses of the regression and simulation demonstrate that the wood density impacts the parameters more than the allometric relationship does. This paper presents an applicable method for testing the field data using reasonable wood densities, restricting the error in field data processing based on limited field plots, and achieving a better understanding of the uncertainty in building those equations.

scholarly journals Field methods for sampling tree height for tropical forest biomass estimation

2018 ◽  
Vol 9 (5) ◽  
pp. 1179-1189 ◽  
Author(s):  
Martin J. P. Sullivan ◽  
Simon L. Lewis ◽  
Wannes Hubau ◽  
Lan Qie ◽  
Timothy R. Baker ◽  
...  
Keyword(s):  
Tropical Forest ◽  
Forest Biomass ◽  
Tree Height ◽  
Biomass Estimation ◽  
Field Methods

Konkurrenz zwischen Stieleiche und Buche auf Lothar-Sturmflächen | Competition between pedunculate oak and European beech on Lothar windthrow areas

2009 ◽  
Vol 160 (5) ◽  
pp. 114-123 ◽  
Author(s):  
Daniel Otto ◽  
Sven Wagner ◽  
Peter Brang
Keyword(s):  
Large Scale ◽  
Early Stage ◽  
Tree Height ◽  
European Beech ◽  
Threshold Value ◽  
Test Methods ◽  
Permanent Plots ◽  
Pedunculate Oak ◽  
Competitive Pressure ◽  
Competition Index

The competitive pressure of naturally regenerated European beech (Fagus sylvatica) saplings on planted pedunculate oak (Quercus robur) was investigated on two 1.8 ha permanent plots near Habsburg and Murten (Switzerland). The plots were established with the aim to test methods of artificial oak regeneration after large-scale windthrow. On both plots, 80 oaks exposed to varying levels of competitive pressure from at most 10 neighbouring beech trees were selected. The height of each oak as well as stem and branch diameters were measured. The competitive pressure was assessed using Schütz's competition index, which is based on relative tree height, crown overlap and distance from competing neighbours. Oak trees growing without or with only slight competition from beech were equally tall, while oaks exposed to moderate to strong competition were smaller. A threshold value for the competition index was found above which oak height decreased strongly. The stem and branch diameters of the oaks started to decrease even if the competition from beech was slight, and decreased much further with more competition. The oak stems started to become more slender even with only slight competition from beech. On the moderately acid beech sites studied here, beech grow taller faster than oak. Thus where beech is competing with oak and the aim is to maintain the oak, competitive pressure on the oak must be reduced at an early stage. The degree of the intervention should, however, take the individual competitive interaction into account, with more intervention if the competition is strong.

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