Allometric relationship for estimating above-ground biomass of Aegiali- tis rotundifolia Roxb. of Sundarbans mangrove forest, in Bangladesh

Tree biomass plays a key role in sustainable management by providing different aspects of ecosystem. Estimation of above ground biomass by non-destructive means requires the dex;elopment of allometric equations. Most researchers used DBH （diameter at breast height） and TH （total height） to develop a...

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Bibliographic Details
Published in:林业研究：英文版 2012, Vol.23 (1), p.23-28
Main Author: Mohammad Raqibul Hasan Siddique ~ Mahmood Hossain
Format: Article
Language:English
Subjects:
回归方程
圆叶决明
地上生物量
地上部生物量
孟加拉国
模型估计
生长关系
红树林
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Summary:Tree biomass plays a key role in sustainable management by providing different aspects of ecosystem. Estimation of above ground biomass by non-destructive means requires the dex;elopment of allometric equations. Most researchers used DBH （diameter at breast height） and TH （total height） to develop allometric equation for a tree. Very few spe- cies-specific allometric equations are currently available for shrubs to estimate of biomass from measured plant attributes. Therefore, we used some of readily measurable variables to develop allometric equations such as girth at collar-height （GcH） and height of girth measuring point （GMH） with total height （TH） for A. rotundifolia, a mangrove species of Sundarbans of Bangladesh, as it is too dwarf to take DBH and too ir- regular in base to take Girth at a fixed height. Linear, non-linear and logarithmic regression techniques were tried to determine the best re- gression model to estimate the above-ground biomass of stem, branch and leaf. A total of 186 regression equations were generated from the combination of independent variables. Best fit regression equations were determined by examining co-efficient of determination （R：）, co-efficient of variation （Cv）, mean-square of the error （Ms~r）, residual mean error （Rmax）, and F-value. Multiple linear regression models showed more efficient over other types of regression equation. The performance of regression equations was increased by inclusion of GMn as an independ- ent variable along with total height and GCH.
ISSN:1007-662X
1993-0607