Individual tree biomass model by tree origin, site classes and age groups

Abstract A previously developed sampling method utilizing randomized branch and importance sampling for the purpose of quickly estimating tree biomass was tested on five loblolly pine (Pinus taeda L.) trees. Results show a wide range of per-tree sampling error, ranging from 5.3 to 28.9%. Largevariation in foliage content among selected branches per treee may be a major source of error. However, the sampling error for the total biomass of the five trees tested was only 3.3%. This sampling method appears to be reliable and efficient in obtaining precise estimates of the total biomassof a population of trees. Increased sampling intensity per tree is necessary to obtain precise estimates of individual tree biomass. South. J. Appl. For. 13(4):181-184.

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

Remote Sensing ◽

10.3390/rs11232793 ◽

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.

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

European Journal of Forest Research ◽

10.1007/s10342-017-1024-9 ◽

2017 ◽

Vol 136 (2) ◽

pp. 233-249 ◽

Cited By ~ 24

Author(s):

WeiSheng Zeng ◽

HaiRui Duo ◽

XiangDong Lei ◽

XinYun Chen ◽

XueJun Wang ◽

...

Keyword(s):

Growth Models ◽

Climate Variables ◽

Tree Biomass ◽

Individual Tree ◽

Biomass Equations

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Does individual-tree biomass growth increase continuously with tree size?

Forest Ecology and Management ◽

10.1016/j.foreco.2020.118717 ◽

2021 ◽

Vol 481 ◽

pp. 118717

Author(s):

David I. Forrester

Keyword(s):

Tree Size ◽

Biomass Growth ◽

Tree Biomass ◽

Individual Tree ◽

Growth Increase

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Construction of compatible and additive individual-tree biomass models for Pinus tabulaeformis in China

Canadian Journal of Forest Research ◽

10.1139/cjfr-2016-0342 ◽

2017 ◽

Vol 47 (4) ◽

pp. 467-475 ◽

Cited By ~ 11

Author(s):

WeiSheng Zeng ◽

LianJin Zhang ◽

XinYun Chen ◽

ZhiChu Cheng ◽

KeXi Ma ◽

...

Keyword(s):

Aboveground Biomass ◽

Belowground Biomass ◽

Pinus Tabulaeformis ◽

Stem Volume ◽

Mean Annual Precipitation ◽

Mean Annual Temperature ◽

Tree Biomass ◽

Individual Tree ◽

Chinese Pine ◽

Biomass Models

Current biomass models for Chinese pine (Pinus tabulaeformis Carr.) fail to accurately estimate biomass in large geographic regions because they were usually based on limited sample trees on local sites, incompatible with stem volume, and not additive among components and total biomass. This study was based on mensuration data of individual-tree biomass from large samples of Chinese pine. The purpose was to construct compatible and additive biomass models using the nonlinear error-in-variable simultaneous equations and dummy variable modeling approach. This approach could ensure compatibility of an aboveground biomass model with a biomass conversion factor (BCF) and a stem volume model and compatibility of a belowground biomass model with a root-to-shoot ratio (RSR) model. Also, stem, branch, and foliage biomass models were additive to the aboveground biomass model. Results showed that mean prediction errors (MPEs) of the developed one- and two-variable aboveground biomass models were less than 4% and MPEs of the three-component (stem, branch, and foliage) and belowground biomass models were less than 10%. Furthermore, the effects of main climate variables on above- and below-ground biomass were analyzed. Aboveground biomass was related to mean annual temperature (MAT), while belowground biomass had no significant relationship with either MAT or mean annual precipitation (MAP). The developed models provide a good basis for estimating biomass of Chinese pine forests.

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Models for biomass prediction of Cunninghamia lanceolata tree and stands in Southeastern China

10.7287/peerj.preprints.1767v1 ◽

2016 ◽

Author(s):

Mei Guangyi ◽

Sun Yujun

Keyword(s):

Wood Density ◽

Forest Stand ◽

Chinese Fir ◽

Cunninghamia Lanceolata ◽

Biomass Estimation ◽

Tree Biomass ◽

Estimation Model ◽

Individual Tree ◽

Natural Logarithm ◽

Total Tree

Large uncertainties still remain when using existing biomass equations to estimate total tree and forest stand scale. In this paper, we develop individual-tree biomass models for Chinese fir (Cunninghamia lanceolata （Lamb.）Hook.) stands in Fujian Province, southeast of China. For this, we used 74 previously established models that are most commonly used to estimate tree biomass, and selected the best fit models and modified it. The results showed the published model with ln(B) (biomass), ln(D) (diameter at breast height), (ln(H)) 2, (total height) (ln(H))3 and ln(WD) (wood density) to be the best fitting model for estimating the tree biomass of Chinese fir. Furthermore, we observed that variables D, H (height), WD significantly correlated with the total tree biomass estimation model, as a result of it portraying the natural logarithm structure to be the best tree biomass structure. Finally, when a multi-step improvement on tree biomass model was performed, the analytic model with TV (tree volume), WD and BECF (biomass wood density conversion factor), achieved the highest accuracy simulation. Therefore, when combined with TV, WD and BECF to tree biomass volume coefficient bi for Chinese fir, the optimal model is the forest stand biomass (SB) estimation model, model with variables of stand volume (SV) and coefficient bi.

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Allometric equations for estimating biomass of community forest tree species in Madiun, Indonesia

Biodiversitas Journal of Biological Diversity ◽

10.13057/biodiv/d210947 ◽

2020 ◽

Vol 21 (9) ◽

Author(s):

Pandu Wirabuana ◽

RAHMANTA SETIAHADI ◽

RONGGO SADONO ◽

MARTIN LUKITO ◽

DJOKO SETYO MARTONO ◽

...

Keyword(s):

Tree Species ◽

Forest Tree ◽

Allometric Equations ◽

Tree Biomass ◽

Community Forest ◽

Individual Tree ◽

Community Forests ◽

Forest Tree Species ◽

Diameter At Breast Height ◽

Breast Height

Abstract. Wirabuana PYAP, Setiahadi R, Sadono R, Lukito M, Martono DS, Matatula J. 2020. Allometric equations for estimating biomass of community forest tree species in Madiun, Indonesia. Biodiversitas 21: 4291-4300. The capability of community forests for offsetting carbon emissions highly depends on their biomass production. Unfortunately, the measurement of tree biomass in community forests using a destructive method is expensive and time-consuming. It is also almost impossible to conduct this method for all trees in the observation area. Therefore, the development of allometric equations is essential to support tree biomass estimation in community forests. This study was designed to construct specific models for predicting individual tree biomass in community forests, located in Madiun, Indonesia. We destructively sampled approximately 120 trees from four different species (30 trees for each species), i.e., Falcataria moluccana, Melia azedarach, Swietenia macrophylla, and Tectona grandis. For every tree sample, the measurement of biomass was conducted in each tree’s component, namely roots, stem, branches, and leaves. The allometric equations were developed with regression analysis using predictor variables, like diameter at breast height (D), squared diameter at breast height combined with tree height (D2H), as well as D and H separately. Results found that for four species, the mean biomass in the stem was 50.3%, followed by branches 25.4%, roots 15.9%, and leaves 8.3%. The best equation for estimating biomass in every component and total of four species was different. However, our study showed that the equation lnŶ = -3.037 + 1.430 lnD + 1.684 was reliable to estimate total individual tree biomass of four species in the surveyed area since this model had accuracy of 90.8%. Referring to these findings, we recommended the utilization of an allometric equation as an alternative method for facilitating more efficient biomass measurement in the community forests.

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