Applicability of semi-destructive method to derive allometric model for estimating aboveground biomass and carbon stock in the Hill zone of Bangladesh

• Published in: Journal of forestry research Vol. 31; no. 4; pp. 1235 - 1245
• Main Authors: Mahmood, Hossain, Siddique, Mohammad Raqibul Hasan, Islam, S. M. Zahirul, Abdullah, S. M. Rubaiot, Matieu, Henry, Iqbal, Md. Zaheer, Akhter, Mariam
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2020; Springer; Springer Nature B.V; Forestry and Wood Technology Discipline, Khulna University, Khulna 9208, Bangladesh%Forest Inventory Division, Bangladesh Forest Research Institute, Chittagong 4000, Bangladesh%Food and Agriculture Organization, Rome 00153, Italy%Bangladesh Forest Department, Bana bhaban, Agargaon,Dhaka 1207, Bangladesh
• Subjects: Allometry; Analysis; Bark; Biomass; Biomedical and Life Sciences; Branches; Carbon; Carbon sequestration; Carbon sinks; Climate change; Climate change mitigation; Climatic changes; Efficiency; Forest biomass; Forest reserves; Forestry; Forests; Leaves; Life Sciences; Methods; Model accuracy; Nondestructive testing; Original Paper; Species; Stems; Stocks; Trees; Bangladesh; Bangladesh; Biomass; Allometry; Carbon; Forest inventory
• ISSN: 1007-662X; 1993-0607
• DOI: 10.1007/s11676-019-00881-5

Biomass estimation using allometric models is a nondestructive and popular method. Selection of an allometric model can influence the accuracy of biomass estimation. Bangladesh Forest Department initiated a nationwide forest inventory to assess biomass and carbon stocks in trees and forests. The relationship between carbon storage and sequestration in a forest has implications for climate change mitigation in terms of the carbon sink in Bangladesh. As part of the national forest inventory, we aimed to derive multi-species biomass models for the hill zone of Bangladesh and to determine the carbon concentration in tree components (leaves, branches, bark and stem). In total, 175 trees of 14 species were sampled and a semi-destructive method was used to develop a biomass model, which included development of smaller branch (base dia < 7 cm) biomass allometry and volume estimation of bigger branches and stems. The best model of leaf, branches, and bark showed lower values for adjusted R 2 (0.3152–0.8043) and model efficiency (0.436–0.643), hence these models were not recommended to estimate biomass. The best fit model of stem and total aboveground biomass (TAGB) showed higher model efficiency 0.948 and 0.837, respectively, and this model was recommended for estimation of tree biomass for the hill zone of Bangladesh. The best fit allometric biomass model for stem was Ln (Stem) = − 10.7248 + 1.6094*Ln (D) + 1.323*Ln (H) + 1.1469*Ln (W); the best fit model for TAGB was Ln (TAGB) = − 6.6937 + 0.809*Ln (D^2*H*W), where DBH = Diameter at Breast Height, H = Total Height, W = Wood density. The two most frequently used pan-tropical biomass models showed lower model efficiency (0.667 to 0.697) compared to our derived TAGB model. The best fit TAGB model proved applicable for accurate estimation of TAGB for the hill zone of Bangladesh. Carbon concentration varied significantly ( p  < 0.05) by species and tree components. Higher concentration (48–49%) of carbon was recorded in the tree stem.