基于异速参数概率分布的立木地上生物量估算

doi:10.11707/j.1001-7488.20140605

Abstract

Abstract:

Allometric biomass equations are widely used to predict above-ground biomass in forest ecosystems. It found the distribution of the parameters a and b of the allometry between above-ground biomass (M) and diameter at breast height(D), lnM=a + blnD, well approximated by a bivariate normal from analysis a data of 304 functions of 80 papers. ANOVA was tested to parameters in seven genera. In contrast to the parameter a, there was significant difference in parameter b. There were negative correlation between the parameter a and b, the parameter b and latitude. From this negative correlation, simultaneous-equation was used to build general model for parameters which were changed by latitude. Three methods which include established general model, minimum-least-square regression and Bayesian approach were used to fitting the above-ground biomass of Larix kaempferi in sub-tropical alpine area. The result showed that general model was the lowest precise quantifications(R²=0.892), but it could estimate the biomass where forest situated in latitude without samples. With sample size was more than 50, both Bayesian method and minimum-least-square regression was no significant difference in the mean absolute error. And it was less than 50, Bayesian method was better than minimum-least-square regression. Therefore, it was suggested that Bayesian method was used to estimate above-ground biomass when the sample size was less than 50.

Key words: allometric biomass equations, parameters, probability distribution, Bayesian method

CLC Number:

S757

Huang Xingzhao, Chen Dongsheng, Sun Xiaomei, Zhang Shougong. Estimation of Above-Ground Tree Biomass Based on Probability Distribution of Allometric Parameters[J]. Scientia Silvae Sinicae, 2014, 50(6): 34-41.

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Estimation of Above-Ground Tree Biomass Based on Probability Distribution of Allometric Parameters

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