scholarly journals Individual tree biomass equations or biomass expansion factors for assessment of carbon stock changes in living biomass – A comparative study

2012 ◽  
Vol 270 ◽  
pp. 78-84 ◽  
Author(s):  
Hans Petersson ◽  
Sören Holm ◽  
Göran Ståhl ◽  
David Alger ◽  
Jonas Fridman ◽  
...  
2019 ◽  
Vol 11 (23) ◽  
pp. 2793
Author(s):  
Yujie Zheng ◽  
Weiwei Jia ◽  
Qiang Wang ◽  
Xu Huang

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.


2017 ◽  
Vol 136 (2) ◽  
pp. 233-249 ◽  
Author(s):  
WeiSheng Zeng ◽  
HaiRui Duo ◽  
XiangDong Lei ◽  
XinYun Chen ◽  
XueJun Wang ◽  
...  

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

2019 ◽  
Vol 51 (01) ◽  
pp. 91-96
Author(s):  
M. A. QURESHI ◽  
A. M. PIRZADA ◽  
M. M. QURESHI ◽  
N. A. SAMOON ◽  
M. H. ZUBERI ◽  
...  

2014 ◽  
Vol 14 (2) ◽  
Author(s):  
Lauro Rodrigues Nogueira Júnior ◽  
Vera Lex Engel ◽  
John A. Parrotta ◽  
Antonio Carlos Galvão de Melo ◽  
Danilo Scorzoni Ré

Restoration of Atlantic Forests is receiving increasing attention because of its role in both biodiversity conservation and carbon sequestration for global climate change mitigation. This study was carried out in an Atlantic Forest restoration project in the south-central region of São Paulo State - Brazil to develop allometric equations to estimate tree biomass of indigenous tree species in mixed plantations. Above and below-ground biomass (AGB and BGB, respectively), stem diameter (DBH: diameter at 1.3 m height), tree height (H: total height) and specific wood density (WD) were measured for 60 trees of 19 species. Different biomass equations (linear and nonlinear-transformed) were adjusted to estimate AGB and BGB as a function of DBH, H and WD. For estimating AGB and BGB, the linear biomass equation models were the least accurate. The transformed nonlinear biomass equation that used log DBH2, log H and log WD as predictor variables were the most accurate for AGB and the transformed nonlinear biomass equations that used log DBH2*WD as predictor variables were the most accurate for BGB. It is concluded that these adjusted equations can be used to estimate the AGB and BGB in areas of the studied project. The adjusted equations can be recommended for use elsewhere in the region for forest stands of similar age, tree size ranges, species composition and site characteristics.


2018 ◽  
Vol 6 ◽  
pp. 61-67
Author(s):  
Karishma Gubhaju ◽  
Dipesh Raj Pant ◽  
Ramesh Prasad Sapkota

Forests store significant amount of atmospheric carbon in the form of above and below ground biomass and the amount of carbon stored in forests differs along spatial continuum which provides important information regarding forest quality. This study was carried out to estimate the carbon stock of Shree Rabutar Forest of Gaurishankar Conservation Area, Dolakha, Nepal. In total, 20 circular sampling plots with an area 250 m2 were randomly laid in the study area. Ten tree species were observed in the sampling plots laid in the forest. The higher values of density, frequency, abundance and basal area were observed for Rhododendron arboreum, Alnus nepalensis, Pinus roxburghii and Pinus wallichiana. On the basis of Important Value Index, the dominant tree in the forest was Alnus nepalensis followed by Rhododendron arboreum and Pinus roxburghii. Shannon Index of general diversity of trees in the forest was 0.74 with equal value of Evenness Index, whereas the index of dominance was low (0.22) in the forest. Mean biomass of the forest was 464.01±66.71 tonha-1 contributed by above ground tree biomass (384.44 tonha-1), leaf litter, herbs and grasses biomass (2.69±0.196 tonha-1) and below ground tree biomass (76.88±11.13 tonha-1). Mean carbon stock was 262.77±30.79 tonha-1 including soil carbon stock 44.69±2.25 tonha-1. Individuals of trees with 20-30 cm DBH class were observed in maximum number, which shows that the forest has high potential to sequester carbon over time. Carbon stock estimation and forest management can be one of the potential strategies for climate change mitigation especially through carbon dioxide absorption by the forests.


2018 ◽  
Vol 24 ◽  
pp. 174-183 ◽  
Author(s):  
Jose Alan A. Castillo ◽  
Armando A. Apan ◽  
Tek Narayan Maraseni ◽  
Severino G. Salmo

Forests ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 41 ◽  
Author(s):  
Bin Yang ◽  
Wenyan Xue ◽  
Shichuan Yu ◽  
Jianyun Zhou ◽  
Wenhui Zhang

We studied the effects of stand age on allocation and equation fitting of aboveground and below-ground biomass in four Quercus acutissima stands (14, 31, 46, and 63 years old) in the Central Loess Plateau of China. The stem wood, stem bark, branch, foliage, and belowground biomass of each of the 20 destructive harvesting trees were quantified. The mean total biomass of each tree was 28.8, 106.8, 380.6, and 603.4 kg/tree in the 14-, 31-, 46-, and 63-year-old stands, respectively. Aboveground biomass accounted for 72.25%, 73.05%, 76.14%, and 80.37% of the total tree biomass in the 14-, 31-, 46-, and 63-year-old stands, respectively, and stem wood was the major component of tree biomass. The proportion of stem (with bark) biomass to total tree biomass increased with stand age while the proportions of branch, foliage, and belowground biomass to total tree biomass decreased with stand age. The ratio of belowground biomass to aboveground biomass decreased from 0.39 in the 14-year-old stand to 0.37, 0.31, and 0.24 in the 31-, 46-, and 63-year-old stands, respectively. Age-specific biomass equations in each stand were developed for stem wood, stem bark, aboveground, and total tree. The inclusion of tree height as a second variable improved the total tree biomass equation fitting for middle-aged (31-year-old and 46-year-old) stands but not young (14 years old) and mature (63 years old) stands. Moreover, biomass conversion and expansion factors (BCEFs) varied with stand age, showing a decreasing trend with increasing stand age. These results indicate that stand age alters the biomass allocation of Q. acutissima and results in age-specific allometric biomass equations and BCEFs. Therefore, to obtain accurate estimates of Q. acutissima forest biomass and carbon stocks, age-specific changes need to be considered.


2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Biplab Brahma ◽  
Gudeta W. Sileshi ◽  
Arun Jyoti Nath ◽  
Ashesh Kumar Das

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