Abstract
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.
Highlights
Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.), a fast growing evergreen coniferous tree, is one of the most important tree species for timber production in southern China
Many different biotic and abiotic factors introduce variability in tree biomass model, suggesting that parameters of allometric equations are better represented by probability distributions (Fig. 2) rather than fixed values as classical method
Established over a broad geographical range, the national Chinese fir resource encompasses large variations in climatic, edaphic conditions, silviculture and genetic stock that affect biomass accumulation. These different biotic and abiotic factors introduce variability in Chinese fir biomass model, suggesting that parameters of allometric equations are better represented by probability distributions rather than fixed values
Summary
Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.), a fast growing evergreen coniferous tree, is one of the most important tree species for timber production in southern China. As an important native tree, Chinese fir has been widely planted extending over more than 1000 years [1]. It produces excellent quality timber, with straight shape, high resistance of bending and cracking, and processing trait. Because of its high commercial value, the planting area of Chinese fir in China is around 9.215 million ha, accounted for 28.54% of all forested land [2]. The estimation of tree biomass is needed for both sustainable planning of forest resources and for studies on the energy and nutrients flows in ecosystems. The reliability of the forest carbon stock estimates and the understanding of ecosystem carbon dynamics can be improved by biomass equations [5], [6]. The biomass equations can be applied directly to tree level inventory data (diameter, height)
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