Carbon stock model of Pinus massoniana in the subtropical zone of China: An integrated method of biomass and carbon content coefficient

Xinhua Huang, Xiaoyu Cao, Yuxin Xiang, Shuping Wu, Zelian Zhang, Menglei Wang, Han Zhang and Liu He

Ecological Modelling, 2025, vol. 508, issue C

Abstract: The carbon content coefficient is a pivotal parameter for estimating carbon stocks based on biomass. Accurate biomass and carbon content coefficients are therefore essential for the estimation of carbon stocks. This study collated data pertaining to the biomass and carbon content coefficient of 150 Pinus massoniana trees in the subtropical region of China. The objective of this study was to formulate a precise carbon stock model for Pinus massoniana in the subtropical region of China. This was achieved by integrating a biomass model with a carbon content coefficient model, thus providing a novel approach for constructing carbon stock models for other tree species. The researchers developed 17 biomass models by integrating allometric equations and nonlinear simultaneous equations. These models were then combined with carbon content coefficient expressions, 0.5 (universal carbon content coefficient), and measured carbon content coefficients, respectively. The results show that (1) the compatibility model had a better fitting effect than the allometric model in calculating biomass or carbon storage; (2) carbon content coefficients expressed in terms of tree height and diameter at breast height were obtained by taking the quotient of the optimal independent carbon stock model and the optimal independent biomass model; and (3) the carbon stock model derived from the compatible biomass model and the carbon content coefficient expression had a better fitting effect and higher accuracy.

Keywords: Allometric equations; Nonlinear simultaneous equations; Compatibility model; Tree height (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:508:y:2025:i:c:s0304380025001954

DOI: 10.1016/j.ecolmodel.2025.111210

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