Tree biomass estimation of Chinese fir (Cunninghamia lanceolata) based on Bayesian method.

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 W...

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Autores principales:	Xiongqing Zhang, Aiguo Duan, Jianguo Zhang
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/557ea81b15dc4d2fa599e14f3710ab7a
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spelling	oai:doaj.org-article:557ea81b15dc4d2fa599e14f3710ab7a2021-11-18T08:45:31ZTree biomass estimation of Chinese fir (Cunninghamia lanceolata) based on Bayesian method.1932-620310.1371/journal.pone.0079868https://doaj.org/article/557ea81b15dc4d2fa599e14f3710ab7a2013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24278198/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Chinese 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 W = a(D2H)b 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.Xiongqing ZhangAiguo DuanJianguo ZhangPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 11, p e79868 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Xiongqing Zhang Aiguo Duan Jianguo Zhang Tree biomass estimation of Chinese fir (Cunninghamia lanceolata) based on Bayesian method.
description	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 W = a(D2H)b 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.
format	article
author	Xiongqing Zhang Aiguo Duan Jianguo Zhang
author_facet	Xiongqing Zhang Aiguo Duan Jianguo Zhang
author_sort	Xiongqing Zhang
title	Tree biomass estimation of Chinese fir (Cunninghamia lanceolata) based on Bayesian method.
title_short	Tree biomass estimation of Chinese fir (Cunninghamia lanceolata) based on Bayesian method.
title_full	Tree biomass estimation of Chinese fir (Cunninghamia lanceolata) based on Bayesian method.
title_fullStr	Tree biomass estimation of Chinese fir (Cunninghamia lanceolata) based on Bayesian method.
title_full_unstemmed	Tree biomass estimation of Chinese fir (Cunninghamia lanceolata) based on Bayesian method.
title_sort	tree biomass estimation of chinese fir (cunninghamia lanceolata) based on bayesian method.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/557ea81b15dc4d2fa599e14f3710ab7a
work_keys_str_mv	AT xiongqingzhang treebiomassestimationofchinesefircunninghamialanceolatabasedonbayesianmethod AT aiguoduan treebiomassestimationofchinesefircunninghamialanceolatabasedonbayesianmethod AT jianguozhang treebiomassestimationofchinesefircunninghamialanceolatabasedonbayesianmethod
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Tree biomass estimation of Chinese fir (Cunninghamia lanceolata) based on Bayesian method.

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