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 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 Predicting tree heights for biomass estimates in tropical forests – a test from French Guiana

2014 ◽  
Vol 11 (12) ◽  
pp. 3121-3130 ◽  
Author(s):  
Q. Molto ◽  
B. Hérault ◽  
J.-J. Boreux ◽  
M. Daullet ◽  
A. Rousteau ◽  
...  
Keyword(s):  
Tropical Forests ◽  
Forest Structure ◽  
French Guiana ◽  
Tree Height ◽  
Biomass Estimation ◽  
Forest Plot ◽  
Model Parameters ◽  
Forest Stands ◽  
Forest Stand Structure ◽  
Height Model

Abstract. The recent development of REDD+ mechanisms requires reliable estimation of carbon stocks, especially in tropical forests that are particularly threatened by global changes. Even though tree height is a crucial variable for computing aboveground forest biomass (AGB), it is rarely measured in large-scale forest censuses because it requires extra effort. Therefore, tree height has to be predicted with height models. The height and diameter of all trees over 10 cm in diameter were measured in 33 half-hectare plots and 9 one-hectare plots throughout northern French Guiana, an area with substantial climate and environmental gradients. We compared four different model shapes and found that the Michaelis–Menten shape was most appropriate for the tree biomass prediction. Model parameter values were significantly different from one forest plot to another, and this leads to large errors in biomass estimates. Variables from the forest stand structure explained a sufficient part of plot-to-plot variations of the height model parameters to improve the quality of the AGB predictions. In the forest stands dominated by small trees, the trees were found to have rapid height growth for small diameters. In forest stands dominated by larger trees, the trees were found to have the greatest heights for large diameters. The aboveground biomass estimation uncertainty of the forest plots was reduced by the use of the forest structure-based height model. It demonstrated the feasibility and the importance of height modeling in tropical forests for carbon mapping. When the tree heights are not measured in an inventory, they can be predicted with a height–diameter model and incorporating forest structure descriptors may improve the predictions.

scholarly journals Aboveground Biomass Allocation and Additive Allometric Models for Natural Larix gmelinii in the Western Daxing’anling Mountains, Northeastern China

Forests ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 150 ◽  
Author(s):  
Shengwang Meng ◽  
Quanquan Jia ◽  
Qijing Liu ◽  
Guang Zhou ◽  
Huimin Wang ◽  
...  
Keyword(s):  
Biomass Allocation ◽  
Aboveground Biomass ◽  
Predictive Ability ◽  
Northeastern China ◽  
Seemingly Unrelated Regression ◽  
Allometric Equations ◽  
Larix Gmelinii ◽  
Leaf Biomass ◽  
Estimation Errors ◽  
Biomass Equations

Accurate estimates of tree component and aboveground biomass strongly depend on robust and precise allometric equations. However, site-specific and suitable biomass equations are currently scarce for natural Larix gmelinii forests in the western Daxing’anling Mountains, northeastern China. This study aimed to evaluate the biomass allocation patterns within tree components and develop additive allometric biomass equations for species of L. gmelinii. A total of 58 trees were destructively sampled and measured for wood (inside bark), bark, branch and leaf biomass. For each component, we assessed the share of biomass allocated to different components by computing its ratio; we also tested two allometric equations based on diameter at breast height (dbh) alone, and dbh fitted with height (h) as independent variables. Seemingly unrelated regression methodology was used to fit an additive system of biomass allometric equations. We performed an independent dataset to evaluate the predictive ability of the best model system. The results revealed that wood biomass accounted for approximately 60% of the aboveground biomass. Wood and branch biomass ratios increased with increasing dbh, while a reverse trend was observed for bark and leaf biomass ratios. All models showed good fitting results with Adj.R2 = 0.958–0.995. Tree dbh provided the lowest estimation errors in the regressions associated with branches and leaves, while dbh2 × h generated the most precise models for stems (wood and bark). We conclude that these allometric equations will accurately predict biomass for Larix trees in the western Daxing’anling Mountains.

Compatible crown ratio and crown height models

1987 ◽  
Vol 17 (6) ◽  
pp. 572-574 ◽  
Author(s):  
Michael E. Dyer ◽  
Harold E. Burkhart
Keyword(s):  
Loblolly Pine ◽  
Tree Height ◽  
Ordinary Least Squares ◽  
Seemingly Unrelated Regression ◽  
Stand Age ◽  
Model Parameters ◽  
Crown Height ◽  
Pine Tree ◽  
Unrelated Regression ◽  
Tree Data

Several published crown ratio and crown height models were fitted to plantation loblolly pine tree data, but none were considered entirely adequate. A nonlinear model form that yields logical estimates is presented. Required inputs are stand age, tree diameter, and tree height. Both ordinary least squares and seemingly unrelated regression (SUR) were used to estimate model parameters. Cross equation constraints with the SUR procedure result in compatible estimates of crown ratio and crown height for a tree of given height.

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 Predicting tree heights for biomass estimates in tropical forests

2013 ◽  
Vol 10 (5) ◽  
pp. 8611-8635 ◽  
Author(s):  
Q. Molto ◽  
B. Hérault ◽  
J.-J. Boreux ◽  
M. Daullet ◽  
A. Rousteau ◽  
...  
Keyword(s):  
Tropical Forests ◽  
Stand Structure ◽  
Tree Height ◽  
Biomass Estimation ◽  
Forest Plot ◽  
Model Parameters ◽  
Global Changes ◽  
Forest Stands ◽  
Forest Stand Structure ◽  
Height Model

Abstract. The recent development of REDD+ mechanisms require reliable estimation of carbon stocks, especially in tropical forests that are particularly threatened by global changes. Even if tree height is a crucial variable to compute the above-ground forest biomass, tree heights are rarely measured in large-scale forest census because it requires consequent extra-effort. Tree height have thus to be predicted thanks to height models. Height and diameter of all trees above 10 cm of diameter were measured in thirty-three half-ha plots and nine one-ha plots throughout the northern French Guiana, an area with substantial climate and environmental gradients. We compared four different model shapes and found that the Michaelis–Menten shape was the most appropriate for the tree biomass prediction. Model parameters values were significantly different from one forest plot to another and neglecting these differences would lead to large errors in biomass estimates. Variables from the forest stand structure explained a sufficient part of the plot-to-plot variations of the height model parameters to affect the AGB predictions. In the forest stands dominated by small trees, the trees were found to have rapid height growth for small diameters. In forest stands dominated by larger trees, the trees were found to have the greatest heights for large diameters. The above-ground biomass estimation uncertainty of the forest plots was reduced by the use of the forest structure-based height model. It demonstrates the feasibility and the importance of height modeling in tropical forest for carbon mapping. Tree height is definitely an important variable for AGB estimations. When the tree heights are not measured in an inventory, they can be predicted with a height-diameter model. This model can account for plot-to plot variations in height-diameter relationship thank to variables describing the plots. The variables describing the stand structure of the plots are efficient for this. We found that variables describing the plot environment (rainfall, topography,...) do not improve the model much.

Simultaneous estimation of biomass models for 13 tree species: effects of compatible additivity requirements

2017 ◽  
Vol 47 (6) ◽  
pp. 765-776 ◽  
Author(s):  
Thomas Nord-Larsen ◽  
Henrik Meilby ◽  
Jens Peter Skovsgaard
Keyword(s):  
Ordinary Least Squares ◽  
Seemingly Unrelated Regression ◽  
Model Systems ◽  
Simultaneous Estimation ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Biomass Models ◽  
Unrelated Regression ◽  
Biomass Components ◽  
Species Specific

A desirable feature of biomass models distinguishing different tree components is compatible additivity of the component functions. Due to forcing of parameter estimates, such additivity is achieved at an expense of precision of the component functions. This study aimed to analyse the loss of precision incurred by forcing of parameters in tree biomass models due to (i) additivity constraints, (ii) combining global and species-specific parameters, and (iii) estimating component functions simultaneously as a system instead of as individual equations. Based on biomass data from 697 trees including 13 different species, we estimated a set of compatibly additive, nonlinear biomass models using simultaneous estimation and compared these with less restricted model systems. In line with other similar studies, the overall model system explained 88%–99% of the variation in individual biomass components. Compared with the unrestricted model, restricting parameters to obtain compatible additivity resulted in a change in RMSE of –0.6% to 5.4%. When restricting parameter estimates using both species-specific and global parameters, RMSE increased by 1.7%–13.1%. Estimating model parameters using simultaneous estimation (nonlinear iterated seemingly unrelated regression, NSUR) increased model bias compared with ordinary least squares estimation (OLS) for most biomass components. Contrary to expectations, NSUR estimation did not lead to a reduction in the standard error of estimates.

scholarly journals Aboveground Biomass Allocation of Boreal Shrubs and Short-Stature Trees in Northwestern Canada

Forests ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 234
Author(s):  
Linda Flade ◽  
Christopher Hopkinson ◽  
Laura Chasmer
Keyword(s):  
Short Stature ◽  
Biomass Allocation ◽  
Aboveground Biomass ◽  
Leaf Biomass ◽  
Sectional Area ◽  
Plant Component ◽  
Cross Sectional ◽  
Allometric Models ◽  
Stem Biomass ◽  
Model Fits

In this follow-on study on aboveground biomass of shrubs and short-stature trees, we provide plant component aboveground biomass (herein ‘AGB’) as well as plant component AGB allometric models for five common boreal shrub and four common boreal short-stature tree genera/species. The analyzed plant components consist of stem, branch, and leaf organs. We found similar ratios of component biomass to total AGB for stems, branches, and leaves amongst shrubs and deciduous tree genera/species across the southern Northwest Territories, while the evergreen Picea genus differed in the biomass allocation to aboveground plant organs compared to the deciduous genera/species. Shrub component AGB allometric models were derived using the three-dimensional variable volume as predictor, determined as the sum of line-intercept cover, upper foliage width, and maximum height above ground. Tree component AGB was modeled using the cross-sectional area of the stem diameter as predictor variable, measured at 0.30 m along the stem length. For shrub component AGB, we achieved better model fits for stem biomass (60.33 g ≤ RMSE ≤ 163.59 g; 0.651 ≤ R2 ≤ 0.885) compared to leaf biomass (12.62 g ≤ RMSE ≤ 35.04 g; 0.380 ≤ R2 ≤ 0.735), as has been reported by others. For short-stature trees, leaf biomass predictions resulted in similar model fits (18.21 g ≤ RMSE ≤ 70.0 g; 0.702 ≤ R2 ≤ 0.882) compared to branch biomass (6.88 g ≤ RMSE ≤ 45.08 g; 0.736 ≤ R2 ≤ 0.923) and only slightly better model fits for stem biomass (30.87 g ≤ RMSE ≤ 11.72 g; 0.887 ≤ R2 ≤ 0.960), which suggests that leaf AGB of short-stature trees (<4.5 m) can be more accurately predicted using cross-sectional area as opposed to diameter at breast height for tall-stature trees. Our multi-species shrub and short-stature tree allometric models showed promising results for predicting plant component AGB, which can be utilized for remote sensing applications where plant functional types cannot always be distinguished. This study provides critical information on plant AGB allocation as well as component AGB modeling, required for understanding boreal AGB and aboveground carbon pools within the dynamic and rapidly changing Taiga Plains and Taiga Shield ecozones. In addition, the structural information and component AGB equations are important for integrating shrubs and short-stature tree AGB into carbon accounting strategies in order to improve our understanding of the rapidly changing boreal ecosystem function.

TRIPLOID APPLE VARIETIES OF SUMMER RIPENING SELECTION VNIISPK ON CLONAL ROOTSTOCK 54-118

1970 ◽  
pp. 34-36
Author(s):  
А. M. Galasheva ◽  
Е. N. Sedov
Keyword(s):  
Tree Height ◽  
Projection Area ◽  
Cross Sectional ◽  
Crown Width ◽  
Crown Volume ◽  
The World ◽  
Apple Cultivars ◽  
Crown Projection Area ◽  
Academy Of Sciences ◽  
First Time

For the first time in the world and in Russia, Academician of the Russian Academy of Sciences, breeder Evgeny Nikolaevich Sedov created a series of triploid apple cultivars from intervalent crosses 2х × 4х. Triploid apple cultivars bear fruit more regularly, have higher self-fruitfulness and have fruits of high marketability. The article presents data on the study of triploid apple cultivars of the summer ripening period of the VNIISPK breeding - Augusta, Daryona, Maslovskoye, Osipovskoye, Zhilinskoye, Spasskoye and Yablochny Spas as well as the control Canadian cultivar Melba on a semi-dwarf clone rootstock 54-118. Maslovskoye, Zhilinskoye, Spasskoye and Yablochny Spas have immunity to scab. The orchard was planted in 2014, the garden planting scheme was 5 x 2 m. The indicators of the growth force (tree height, crown width and stem diameter) and the yield of trees were studied. At the age of six, the trees of triploid cultivars reached a height of 2.2 m (Maslovskoye) to 3.0 m (Yablochny Spas) on a semi-dwarf rootstock 54-118. The highest indicators of crown volume (3.3-5.3 m3), crown projection area (4.2-5.3 m2) and the cross-sectional area of the stem (46.5-52.8 cm2) were in Osipovskoye, Yablochny Spas, Zhilinskoye and Spasskoye. The highest yield in an average of three years was given by triploid scab-immune apple cultivars on a semi-dwarf rootstock 54-118: Maslovskoye, Zhilinskoye, Spasskoye and Yablochny Spas.

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