Tree biomass estimation of Chinese fir (Cunninghamia lanceolata) based on Bayesian method.
Tree biomass estimation of Chinese fir (Cunninghamia lanceolata) based on Bayesian method.
复制标题
基于贝叶斯方法的杉木生物量估算
DOI：
10.1371/journal.pone.0079868
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发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Zhang J
中科院分区：
文献类型：
--
作者：
Zhang X;Duan A;Zhang J
Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) is the most important conifer species for timber production with huge distribution area in southern China. Accurate estimation of biomass is required for accounting and monitoring Chinese forest carbon stocking. In the study, allometric equation was used to analyze tree biomass of Chinese fir. The common methods for estimating allometric model have taken the classical approach based on the frequency interpretation of probability. However, many different biotic and abiotic factors introduce variability in Chinese fir biomass model, suggesting that parameters of biomass model are better represented by probability distributions rather than fixed values as classical method. To deal with the problem, Bayesian method was used for estimating Chinese fir biomass model. In the Bayesian framework, two priors were introduced: non-informative priors and informative priors. For informative priors, 32 biomass equations of Chinese fir were collected from published literature in the paper. The parameter distributions from published literature were regarded as prior distributions in Bayesian model for estimating Chinese fir biomass. Therefore, the Bayesian method with informative priors was better than non-informative priors and classical method, which provides a reasonable method for estimating Chinese fir biomass.
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