Allometric equations for estimating above-ground biomass and carbon stock in Faidherbia albida under contrasting management in Malawi

2015 ◽  
Vol 90 (6) ◽  
pp. 1061-1076 ◽  
Author(s):  
T. L. Beedy ◽  
T. F. Chanyenga ◽  
F. K. Akinnifesi ◽  
G. W. Sileshi ◽  
B. I. Nyoka ◽  
...  
1970 ◽  
Vol 19 (2) ◽  
pp. 10-14 ◽  
Author(s):  
SK Baral ◽  
R Malla ◽  
S Ranabhat

This study assessed the above-ground carbon stock in the five major forest types, representing two physiographic regions and four districts of Nepal. Altogether, 116 circular sample plots were laid out systematically in different forests types to inventory the forest. Total above-ground biomass was derived with allometric equations. Results indicated variation in age of the stand (18-75 years), above-ground carbon stock per hectare (34.30- 97.86 dry wt. ton ha-1) and rate of carbon sequestration (1.30-3.21 t ha-1yr-1), according to different forest types. The rate of carbon sequestration by different forest types depended on the growing nature of the forest stands. Tropical riverine and Alnus nepalensis forest types demonstrated the highest carbon sequestration rates in Nepal. Key Words: Above-ground biomass; carbon; forest types; Nepal DOI: 10.3126/banko.v19i2.2979 Banko Janakari, Vol. 19, No.2 2009 pp.10-14


2020 ◽  
Vol 5 (1) ◽  
pp. 13
Author(s):  
Negar Tavasoli ◽  
Hossein Arefi

Assessment of forest above ground biomass (AGB) is critical for managing forest and understanding the role of forest as source of carbon fluxes. Recently, satellite remote sensing products offer the chance to map forest biomass and carbon stock. The present study focuses on comparing the potential use of combination of ALOSPALSAR and Sentinel-1 SAR data, with Sentinel-2 optical data to estimate above ground biomass and carbon stock using Genetic-Random forest machine learning (GA-RF) algorithm. Polarimetric decompositions, texture characteristics and backscatter coefficients of ALOSPALSAR and Sentinel-1, and vegetation indices, tasseled cap, texture parameters and principal component analysis (PCA) of Sentinel-2 based on measured AGB samples were used to estimate biomass. The overall coefficient (R2) of AGB modelling using combination of ALOSPALSAR and Sentinel-1 data, and Sentinel-2 data were respectively 0.70 and 0.62. The result showed that Combining ALOSPALSAR and Sentinel-1 data to predict AGB by using GA-RF model performed better than Sentinel-2 data.


2009 ◽  
Vol 14 (6) ◽  
pp. 365-372 ◽  
Author(s):  
Tanaka Kenzo ◽  
Ryo Furutani ◽  
Daisuke Hattori ◽  
Joseph Jawa Kendawang ◽  
Sota Tanaka ◽  
...  

2021 ◽  
Vol 11 (01) ◽  
pp. 100-113
Author(s):  
M. G. Origenes ◽  
R. L. Lapitan

It is documented that the amounts of carbon stored and its level of degradation in different forests compositions and different types of forest is mostly unknown, Philippines is no exemption as little was done in some places of this country. This study was conducted to assess carbon stock through above ground biomass of trees at different forest composition in Mt. Malindawag. There were three (3) 20m x 20m sample plots (quadrats) (400m2 equivalent to 0.04 ha) established as replicate plots provided with 50m intervals. Forest composition such as the Agroforestry area, mixed forest area and the Plantation forest were assessed in terms of the number of individuals, number of species, diameter, and height to calculate the biomass, tree biomass density as well as the carbon stock. Based on the results of the study conducted in different forest compositions of Mt. Malindawag, plantation forest has the highest carbon stocking rate. However, these results were not significantly different from the other forest composition. This was associated with a higher accumulated diameter, which resulted in higher biomass and eventually carbon stock. Species found in this forest composition are productive and have lesser number of individuals; therefore, there is lesser competition for resources such as light. Such a mechanism might contribute to the higher biomass and carbon stock. However, the result may not be right to other areas due to uncontrollable factors, anthropogenic and environmental factors. Hence, it is recommended to have further studies on areas where trees have similar age, species diversity index as well as stand development and site productivity for a more accurate and quantifiable carbon stock.


2000 ◽  
Vol 48 (6) ◽  
pp. 707 ◽  
Author(s):  
W. H. Burrows ◽  
M. B. Hoffmann ◽  
J. F. Compton ◽  
P. V. Back ◽  
L. J. Tait

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.


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