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Developing individual tree-based models for estimating aboveground biomass of five key coniferous species in China

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Abstract

Estimating individual tree biomass is critical to forest carbon accounting and ecosystem service modeling. In this study, we developed one- (tree diameter only) and two-variable (tree diameter and height) biomass equations, biomass conversion factor (BCF) models, and an integrated simultaneous equation system (ISES) to estimate the aboveground biomass for five conifer species in China, i.e., Cunninghamia lanceolata (Lamb.) Hook., Pinus massoniana Lamb., P. yunnanensis Faranch, P. tabulaeformis Carr. and P. elliottii Engelm., based on the field measurement data of aboveground biomass and stem volumes from 1055 destructive sample trees across the country. We found that all three methods, including the one- and two-variable equations, could adequately estimate aboveground biomass with a mean prediction error less than 5%, except for Pinus yunnanensis which yielded an error of about 6%. The BCF method was slightly poorer than the biomass equation and the ISES methods. The average coefficients of determination (R 2) were 0.944, 0.938 and 0.943 and the mean prediction errors were 4.26, 4.49 and 4.29% for the biomass equation method, the BCF method and the ISES method, respectively. The ISES method was the best approach for estimating aboveground biomass, which not only had high accuracy but also could estimate stocking volumes simultaneously that was compatible with aboveground biomass. In addition, we found that it is possible to develop a species-invariant one-variable allometric model for estimating aboveground biomass of all the five coniferous species. The model had an exponent parameter of 7/3 and the intercept parameter a 0 could be estimated indirectly from stem basic density (a 0 = 0.294 ρ).

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Acknowledgements

We acknowledge the National Biomass Modeling Program in Continuous Forest Inventory (NBMP-CFI) which was funded by the State Forestry Administration of China, for providing biomass measured data of 1055 sample trees of C. lanceolata, P. massoniana, P. yunnanensis, P. tabulaeformis and P. elliottii; and thank the reviewers and editors for their valuable comments.

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Authors and Affiliations

  1. Academy of Forest Inventory and Planning, State Forestry Administration, Beijing, 100714, People’s Republic of China

    Weisheng Zeng & Xuejun Wang

  2. Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, People’s Republic of China

    Liyong Fu

  3. Department of Ecology, Evolution & Natural Resources, Rutgers University, 14 College Farm Road, New Brunswick, NJ, 08901-8551, USA

    Ming Xu

  4. Central South Forest Inventory and Planning Institute, State Forestry Administration, Changsha, 410014, People’s Republic of China

    Zhenxiong Chen

  5. East China Forest Inventory and Planning Institute, State Forestry Administration, Hangzhou, 310019, People’s Republic of China

    Shunbin Yao

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  1. Weisheng Zeng
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  2. Liyong Fu
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Correspondence to Weisheng Zeng.

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The authors declare that they have no conflict of interest.

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Project funding: This study was funded by National Natural Science Foundation of China (Grant Nos. 31270697, 31370634, 31570628); and supported by State Forestry Administration of China (Grant No. 2030208).

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Corresponding editor: Chai Ruihai

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Zeng, W., Fu, L., Xu, M. et al. Developing individual tree-based models for estimating aboveground biomass of five key coniferous species in China. J. For. Res. 29, 1251–1261 (2018). https://doi.org/10.1007/s11676-017-0538-9

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  • DOI: https://doi.org/10.1007/s11676-017-0538-9

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