Allometric equations for estimating the above-ground biomass in tropical lowland Dipterocarp forests
Allometric equations for estimating the above-ground biomass in tropical lowland Dipterocarp forests
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DOI：
10.1016/j.foreco.2009.01.027
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发表时间：
2009-03-31
影响因子：
3.7
通讯作者：
Hussin, Y. A.
中科院分区：
文献类型：
--
作者：
Basuki, T. M.;van Laake, P. E.;Hussin, Y. A.
异速生长方程可用于估算森林的生物量和碳储量。然而，到目前为止，龙脑香林的方程还没有得到足够详细的发展。本研究以经济种属和混合种属为基础，建立了异速生长方程。单独的方程为Dipterocarpus，Hopea，Palaquium和Shorea属，和一个方程的混合这些属代表商业物种。混合物种由商业和非商业物种构成。数据收集在低地混合龙脑香林在东加里曼丹，印度尼西亚。在这项研究中取样的树木数量为122，直径（1.30英寸或以上的扶壁）从6到200厘米不等。采用破坏性取样法采集样品，以商品树干高度（CBH）和木材密度作为胸径（DBH），预测地上总生物量（TAGB）。采用赤池信息量准则（AIC）、回归方程的斜率系数、平均偏差、平均值的置信区间（CI）、配对t检验进行模型比较和选择。根据这些统计指标，最合适的模型是In（TAGB）= c + alpha ln（DBH）。该模型只使用一个单一的预测胸径，并产生一个范围内的预测值更接近观察到的平均值的上限和下限。模型1对森林管理者估算地上生物量是可靠的，因此研究结果可以外推用于与碳平衡相关的森林管理。额外的解释变量，如CBH，并没有真正增加指标对方程的拟合优度。在估计混合树种的地上生物量时，必须考虑采用另一种模式，将木材密度包括在内。将所提出的方程与先前公布的数据进行比较表明，这些当地的物种特异性和通用方程与先前公布的方程有很大不同，必须考虑特定于站点的方程，以更好地估计生物量。基于Cl的平均偏差和范围，一般方程不足以估计某一类型的森林，如低地龙脑香林的生物量。这些研究结果对于龙脑香林来说是新的，因此它们补充了以前的研究以及土地利用和土地利用的变化与林业良好做法指导意见的方法。(C)2009爱思唯尔有限公司版权所有。
Allometric equations can be used to estimate the biomass and carbon stock of forests. However, so far the equations for Dipterocarp forests have not been developed in sufficient detail. In this research, allometric equations are presented based on the genera of commercial species and mixed species. Separate equations are developed for the Dipterocarpus, Hopea, Palaquium and Shorea genera, and an equation of a mix of these genera represents commercial species. The mixed species is constructed from commercial and non-commercial species. The data were collected in lowland mixed Dipterocarp forests in East Kalimantan, Indonesia. The number of trees sampled in this research was 122, with diameters (1.30 in or above buttresses) ranging from 6 to 200 cm. Destructive sampling was used to collect the samples where commercial bole height (CBH), and wood density were used as diameter at breast height (DBH), predictors for dry weight of total above-ground biomass (TAGB). Model comparison and selection were based on Akaike Information Criterion (AIC), slope coefficient of the regression, average deviation, confidence interval (CI) of the mean, paired t-test. Based on these statistical indicators, the most suitable model is In(TAGB) = c + alpha ln(DBH). This model uses only a single predictor of DBH and produces a range of prediction values closer to the upper and lower limits of the observed mean. Model 1 is reliable for forest managers to estimate above-ground biomass, so the research findings can be extrapolated for managing forests related to carbon balance. Additional explanatory variables such as CBH do not really increase the indicators' goodness of fit for the equation. An alternative model to incorporate wood density must be considered for estimating the above-ground biomass for mixed species. Comparing the presented equations to previously published data shows that these local species-specific and generic equations differ substantially from previously published equations and that site specific equations must be considered to get a better estimation of biomass. Based on the average deviation and the range of Cl, the generalized equations are not sufficient to estimate the biomass for a certain type of forests, such as lowland Dipterocarp forests. The research findings are new for Dipterocarp forests, so they complement the previous research as well as the methodology of the Good Practice Guidance for Land Use and Land Use Change and Forestry (GPG-LULUCF). (C) 2009 Elsevier B.V. All rights reserved.