ABSTRACT

Aquilaria malaccensis: Lam. is an important commercial tree species of Bangladesh. This species is widely planted for the increased demand for an essential oil locally knows as “Agar”. A nondestructive method was adopted to derive the allometric biomass model for A. malaccensis. Stem volume of 254 trees and the model of biomass expansion factor (BEF) were used to estimate the total above-ground biomass (TAGB). A total of five allometric equations with natural logarithm were tested to derive best-fit biomass models for crown, stem, and total above-ground biomass (TAGB). The best-fit allometric model was selected based on the lowest value of akaike information criteria (AIC), residual standard error (RSE), and the highest value of the coefficient of determination (R²) and akaike information criteria weighted (AICw). The best-fit model of BEF was BEF = exp(2.112318 – (DBH*TH)^0.1066121). The best-fit allometric biomass models for crown, stem and TAGB were crown biomass = exp(−0.6031 + 0.4279*Ln(DBH^2*TH), steam biomass = exp(−3.2483 + 1.7910*Ln(DBH) + 0.7881*Ln(TH) and TAGB = exp(−1.9121 + 1.5937*Ln(DBH) + 0.6152*Ln(TH). The best-fit TAGB model showed the highest efficiency in biomass estimation compared to commonly used pan-tropical biomass models in terms of model prediction error (MPE), model efficiency (ME).

摘要

马六甲沉香：林。是孟加拉国重要的经济树种。由于对当地称为“琼脂”的精油的需求增加，该物种被广泛种植。采用无损方法推导出马六甲曲霉菌异速生长的生物量模型。254棵树的茎体积和生物量扩展因子（BEF）模型被用来估计总地上生物量（TAGB）。测试了总共五个具有自然对数的异速生长方程，以获得最适合树冠、茎和总地上生物量 (TAGB) 的生物量模型。根据赤池信息标准（AIC）的最低值、残差标准误差（RSE）和决定系数的最高值（R ²) 和 akaike 信息标准加权 (AICw)。BEF 的最佳拟合模型是 BEF = exp(2.112318 – (DBH*TH)^0.1066121)。冠、茎和 TAGB 最适合的异速生长生物量模型是冠生物量 = exp(-0.6031 + 0.4279*Ln(DBH^2*TH)，蒸汽生物量 = exp(-3.2483 + 1.7910*Ln(DBH) + 0.7881* Ln(TH) 和 TAGB = exp(−1.9121 + 1.5937*Ln(DBH) + 0.6152*Ln(TH)。与常用的泛热带生物量模型相比，最佳拟合 TAGB 模型在生物量估计方面的效率最高模型预测误差 (MPE)、模型效率 (ME)。