Environmental Challenges | |
Conventional and additive models for estimating the biomass, carbon and nutrient stock in individual Shorea robusta Gaertn. f. tree of the Sal forests of Bangladesh | |
Hossain Mahmood1  Matieu Henry2  Gael Sola2  S.M. Rubaiot Abdullah2  Md. Zaheer Iqbal3  Mohammad Raqibul Hasan Siddique4  Md. Bakhtiar Nur Siddiqui4  Mariam Akhter4  | |
[1] Corresponding author.;Bangladesh Forest Department, Bangladesh;Food and Agriculture Organization of the United Nations, Rome, Italy;Forestry and Wood Technology Discipline, Khulna University, Bangladesh; | |
关键词: Additive model; Biomass allocation; Carbon; Conventional model; Maximum likelihood; Nutrients; | |
DOI : | |
来源: DOAJ |
【 摘 要 】
Accurate tree biomass estimation is critical and crucial for calculating carbon stocking as well as for studying climate change, forest health, productivity, nutrient cycling and budget etc. A total of 50 individuals of Shorea robusta Gaertn. f. were harvested to assess the biomass of tree components (leaf, branch, bark and stem). Carbon and nutrients (N, P and K) content in the tree components were also measured. This study adopted component biomass models with cross-validation technique. Additive biomass models were developed following the modified Gaussian maximum likelihood aggregated approach using open source software R (version 4.0.1). Component and additive biomass model used D (Diameter at Breast Height) as a sole predictor performed satisfactorily, the inclusion of total tree height (H) in Da*Hb form showed its supremacy over all the models. The best fitted additive model (AGB = 0.002056*D2.923998*H−0.69278 + 0.00848*D2.3896*H0.29648 + 0.04224*D2.06986*H0.65549 + 0.00552*D2.06723*H0.70536) and conventional model (Ln (AGB) = -2.7977 + 2.1829*ln(D) + 0.5073*ln(H)) took the lowest AIC, MPE and MAE and the highest model efficiency values. The derived species-specific additive and non-additive model showed its superiority over the frequently used pan-tropical models and suggested using this model for estimating aboveground biomass of S. robusta in Bangladesh.
【 授权许可】
Unknown