scholarly journals Allometric Equations for Estimating the Above-Ground Biomass of Five Forest Tree Species in Khangai, Mongolia

Forests ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 661 ◽  
Author(s):  
Batbaatar Altanzagas ◽  
Yongkai Luo ◽  
Batbaatar Altansukh ◽  
Chimidnyam Dorjsuren ◽  
Jingyun Fang ◽  
...  
Keyword(s):  
Tree Species ◽  
Allometric Equations ◽  
Tree Level ◽  
Pinus Sibirica ◽  
Above Ground Biomass ◽  
Individual Tree ◽  
Siberian Stone Pine ◽  
Ground Biomass ◽  
Forest Region ◽  
Species Specific

Understanding the contribution of forest ecosystems to regulating greenhouse gas emissions and maintaining the atmospheric CO2 balance requires the accurate quantification of above-ground biomass (AGB) at the individual tree species level. The main objective of this study was to develop species-specific allometric equations for the total AGB and various biomass components, including stem, branch, and foliage biomass in Khangai region, northern Mongolia. We destructively sampled a total of 183 trees of five species (22–74 trees per species), including Siberian stone pine (Pinus sibirica Du Tour.), Asian white birch (Betula platyphylla Sukacz.), Mongolian poplar (Populus suaveolens Fisch.), Siberian spruce (Picea obovata Ldb.), and Siberian larch (Larix sibirica Ldb.), across this region. The results showed that for the five species, the average biomass proportion for the stems was 75%, followed by branches at 20% and foliage at 5%. The species-specific component and total AGB models for the Khangai region were developed using tree diameter at breast height (D) and D² and tree height (H) combined ( D 2 H ); and both D and H were used as independent variables. The best allometric model was lnŶ = lna + b × lnD + c × lnH for the various components and total AGB of B. platyphylla and L. sibirica, for the stems and total AGB of P. suaveolens, and for the stem and branch biomass of P. obovata. The equation lnŶ = lna + b × ln( D 2 × H ) was best for the various components and total AGB of P. sibirica, for the branch and foliage biomass of P. suaveolens, and for AGB of P. obovata. The equation lnŶ = lna + b × ln(D) was best only for the foliage biomass of P. obovata. Our results highlight that developing species-specific tree AGB models is very important for accurately estimating the biomass in the Khangai forest region of Mongolia. Our biomass models will be used at the tree level inventories with sample plots in the Khangai forest region.

Allometric relationships and community biomass estimates for some dominant eucalypts in Central Queensland woodlands

2000 ◽  
Vol 48 (6) ◽  
pp. 707 ◽  
Author(s):  
W. H. Burrows ◽  
M. B. Hoffmann ◽  
J. F. Compton ◽  
P. V. Back ◽  
L. J. Tait
Keyword(s):  
Basal Area ◽  
Carbon Stocks ◽  
Allometric Equations ◽  
Allometric Relationships ◽  
Above Ground Biomass ◽  
Greenhouse Gas Inventory ◽  
Individual Tree ◽  
Ground Biomass ◽  
Eucalyptus Crebra ◽  
The Mean

Allometric equations are presented relating stem circumference to branch, leaf, trunk, bark, total above-ground and lignotuber biomass for Eucalyptus crebra F.Muell. (woodland trees), E. melanophloia Sol. Ex Gaerth. (both woodland and regrowth community trees) and E. populnea F.Muell. (woodland trees). There were no significant differences (P > 0.05) between the slopes of individual lognormal regression lines plotting stem circumference against total above-ground biomass for E. crebra, E. melanophloia and E. populnea. Root-to-shoot ratios and leaf area indices were also determined for the stands contributing to each regression. The regressions were then applied to measured eucalypt stems in the associated plant community to give estimates of each stand’s component (eucalypt tree fraction only) biomass per hectare. These eucalypt regressions were next applied to measured stems of each species on a total of 33 woodland sites in which these eucalypts individually contributed > 75% of total site basal area. Above-ground biomass/basal area relationships averaged 6.74 0.29 t m–2 basal area for 11 E. crebra sites, 5.11 0.28 t m–2 for 12 E. melanophloia sites and 5.81 0.11 t m–2 for 10 E. populnea sites. The mean relationship for all sites was 5.86 0.18 t m–2 basal area. The allometric relationships presented at both individual tree and stand levels, along with calculated biomass : basal area relationships, enable ready estimates to be made of above-ground biomass (carbon stocks) in woodlands dominated by these eucalypts in Queensland, assuming individual stem circumferences or community basal areas are known. However, to document changes in carbon stocks (e.g. for Greenhouse Gas Inventory or Carbon Offset trading purposes), more attention needs to be placed on monitoring fluxes in the independent variables (predictors) of these allometric equations.

scholarly journals Allometric equations to estimate above-ground biomass of small-diameter mixed tree species in secondary tropical forests

2020 ◽  
Vol 13 (1) ◽  
pp. 165-174
Author(s):  
R Puc-Kauil ◽  
G Ángeles-Pérez ◽  
JR Valdéz-Lazalde ◽  
VJ Reyes-Hernández ◽  
JM Dupuy-Rada ◽  
...  
Keyword(s):  
Tropical Forests ◽  
Tree Species ◽  
Small Diameter ◽  
Allometric Equations ◽  
Above Ground Biomass ◽  
Ground Biomass

scholarly journals Modeling of Above Ground Biomass for Selected Indigenous Acacia Species in Omo-Gibe Woodland Ecosystem, South Western Ethiopia

2018 ◽  
Author(s):  
Abreham Berta Aneseyee ◽  
Teshome Soromessa ◽  
Eyasu Elias
Keyword(s):  
Performance Analysis ◽  
Information Criteria ◽  
Allometric Equations ◽  
Above Ground Biomass ◽  
Generalized Model ◽  
Acacia Species ◽  
Ground Biomass ◽  
Biomass Models ◽  
Dry Biomass ◽  
Species Specific

Allometric equations are used to estimate accurate biomass and carbon stock of forests. However, in Ethiopia only few allometric equations as compared to its floral diversity and species-specific allometric equations for Acacia species are still not developed in Ethiopia. The numbers of tree marked for sampling are Fifty-four (54) using preferential sampling. Diameter at breast height, wood density and tree height were collected as independent variables to predict species specific dry biomass of Acacia species. The new species-specific allometric models have been performed using linear regression analysis in the R software. The Above ground biomass (AGB) have been validated using quantitative statically using the pantropic model. Six candidate models have been developed for each species and four best models for each species of dry biomass was selected based on goodness-of-fit statistics and equation performance analysis of the candidate models. The best model for predicting above ground biomass for Acacia seyal is 0.20636*((DBH2)Hρ) 0.53167, for Acacia polyacantha is  7.26982((DBH)2Hρ)0.21750, for  Acacia ethibcia is 29.01898*((DBH)2Hρ)0.21518 and  for Acacia toritolis is  3.82427*((DBH)2Hρ)0.16748.  The selected models are the best performing (P> 0.01) and higher adjusted R2 (>80%) and has lower Akaike’s Information Criteria (AIC) and residual standard error (RSE) values as comparing the rest of the model. The validation of new developed biomass model using Tukey test indicated that significant variation of mean biomass (P<0.05) between the new developed model and the generalized model. The statistics model performance analysis of Nash-Sutcliffe efficiency (NSE) value is approaching to one, indicating that the new developed model has better performance model as compared with generalized model. Moreover, the percent bias of the new developed models is close to zero which indicates that the site-specific biomass models have more accurate estimator and the generalized biomass models have overestimated biomass for the four Acacia species.

Allometric equations for accurate estimation of above-ground biomass in logged-over tropical rainforests in Sarawak, Malaysia

2009 ◽  
Vol 14 (6) ◽  
pp. 365-372 ◽  
Author(s):  
Tanaka Kenzo ◽  
Ryo Furutani ◽  
Daisuke Hattori ◽  
Joseph Jawa Kendawang ◽  
Sota Tanaka ◽  
...  
Keyword(s):  
Allometric Equations ◽  
Tropical Rainforests ◽  
Accurate Estimation ◽  
Above Ground Biomass ◽  
Ground Biomass

scholarly journals Forest Structure, Composition and Above Ground Biomass of Tree Community in Tropical Dry Forests of Eastern Ghats, India

2016 ◽  
Vol 8 (1) ◽  
pp. 125-133 ◽  
Author(s):  
Sudam Charan SAHU ◽  
H.S. SURESH ◽  
N.H. RAVINDRANATH
Keyword(s):  
Forest Structure ◽  
Tree Species ◽  
Basal Area ◽  
Eastern Ghats ◽  
Tropical Dry Forests ◽  
Above Ground Biomass ◽  
Importance Value ◽  
Shorea Robusta ◽  
Ground Biomass ◽  
C Stocks

The study of biomass, structure and composition of tropical forests implies also the investigation of forest productivity, protection of biodiversity and removal of CO2 from the atmosphere via C-stocks. The hereby study aimed at understanding the forest structure, composition and above ground biomass (AGB) of tropical dry deciduous forests of Eastern Ghats, India, where as a total of 128 sample plots (20 x 20 meters) were laid. The study showed the presence of 71 tree species belonging to 57 genera and 30 families. Dominant tree species was Shorea robusta with an importance value index (IVI) of 40.72, while Combretaceae had the highest family importance value (FIV) of 39.01. Mean stand density was 479 trees ha-1 and a basal area of 15.20 m2 ha-1. Shannon’s diversity index was 2.01 ± 0.22 and Simpson’s index was 0.85 ± 0.03. About 54% individuals were in the size between 10 and 20 cm DBH, indicating growing forests. Mean above ground biomass value was 98.87 ± 68.8 Mg ha-1. Some of the dominant species that contributed to above ground biomass were Shorea robusta (17.2%), Madhuca indica (7.9%), Mangifera indica (6.9%), Terminalia alata (6.9%) and Diospyros melanoxylon (4.4%), warranting extra efforts for their conservation. The results suggested that C-stocks of tropical dry forests can be enhanced by in-situ conserving the high C-density species and also by selecting these species for afforestation and stand improvement programs. Correlations were computed to understand the relationship between above ground biomass, diversity indices, density and basal area, which may be helpful for implementation of REDD+ (reduce emissions from deforestation and forest degradation, and foster conservation, sustainable management of forests and enhancement of forest carbon stocks) scheme.

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