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- W3089271019 endingPage "100035" @default.
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- W3089271019 abstract "Globally allometric equations based biomass estimation is a popular non-destructive method for estimating biomass and sequestered carbon. However, the destruction process is involved in the development of allometric models. This study developed allometric models of aboveground biomass (AGB) for five frequently planted homestead tree species in Bangladesh. The tree species were Aphanamixis polystachya, Ficus hispida, Mangifera indica, Melia azedarach, and Swietenia mahagoni. Fifteen individuals from each species were randomly selected and felled. The felled trees were cut into manageable sections and processed for calculation of fresh and dry biomass. The considered explanatory variables were diameter at breast height (DBH), total height (TH), DBH × TH, and DBH2 × TH. For each category of fresh and dry biomass of the five tree species, the study developed a total of 40 models. However, based on the goodness-of-fit statistics, the study primarily selected 17 models for fresh biomass and 22 models for dry biomass. Finally, the best-fit model for each species was selected based on the Akaike Information Criterion (AIC) and Residual Standard Error (RSE). The whole study shows that a combination of Diameter at Breast Height (DBH) at 1.3 m above the ground and the total height of the trees are the essential explanatory variable for most of the species. The relationship between the AGB and the selected dendrometric variables were significant at p < 0.05 levels. The allometric models developed by this study will be useful for better estimation of biomass and sequestered carbon in the plain land homestead forests of Bangladesh." @default.
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- W3089271019 date "2020-12-01" @default.
- W3089271019 modified "2023-10-16" @default.
- W3089271019 title "Allometric models for estimating aboveground biomass of selected homestead tree species in the plain land Narsingdi district of Bangladesh" @default.
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- W3089271019 doi "https://doi.org/10.1016/j.tfp.2020.100035" @default.
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