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Allometric Models for Total-tree and Component-tree Biomass of Alnus nepalensis D. Don in Nepal


     

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Quantification of forest biomass is important for both practical forestry issues and scientific purposes. This study aimed at developing biomass models for Alnus nepalensis tree's total and component (leaf, branch, crown, stem, bark, ischolar_main) biomass using diameter at breast height (dbh) as input variable to the models. Data from twenty-seven destructively sampled Alnus nepalensis trees in Nepal were fitted to eight different non-linear models using least square regression techniques. A model of the form y = b0xb1 showed the best fits for total-tree and component-tree biomass in both fresh and dry weight conditions. This model explained most of the variability (Radj2 ≥ 0.96) of biomass in both fresh and dry weight conditions. This model can precisely predict biomass for normal Alnus nepalensis trees within a range of modelling data (dbh 4.5 - 45.2 cm; total-height 5.8 - 33.5 m), but bias would occur if applied beyond the range.

Keywords

Alnus nepalensis, Allometric Biomass Models, Nepal, least Square Regression Techniques
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Ram P. Sharma


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  • Allometric Models for Total-tree and Component-tree Biomass of Alnus nepalensis D. Don in Nepal

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Authors

Abstract


Quantification of forest biomass is important for both practical forestry issues and scientific purposes. This study aimed at developing biomass models for Alnus nepalensis tree's total and component (leaf, branch, crown, stem, bark, ischolar_main) biomass using diameter at breast height (dbh) as input variable to the models. Data from twenty-seven destructively sampled Alnus nepalensis trees in Nepal were fitted to eight different non-linear models using least square regression techniques. A model of the form y = b0xb1 showed the best fits for total-tree and component-tree biomass in both fresh and dry weight conditions. This model explained most of the variability (Radj2 ≥ 0.96) of biomass in both fresh and dry weight conditions. This model can precisely predict biomass for normal Alnus nepalensis trees within a range of modelling data (dbh 4.5 - 45.2 cm; total-height 5.8 - 33.5 m), but bias would occur if applied beyond the range.

Keywords


Alnus nepalensis, Allometric Biomass Models, Nepal, least Square Regression Techniques