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The Estimation of Forest Carbon Sink Potential and Influencing Factors in Huangshan National Forest Park in China

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  • Wenduo Huang

    (Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China)

  • Xiangrong Wang

    (Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China)

  • Dou Zhang

    (School of Civil Engineering and Architecture, Zhejiang Sci-Tech University, Hangzhou 310018, China)

Abstract

In this study, the biomass expansion factor (BEF) method was combined with the tree growth function in order to obtain a more accurate growth function of tree species through the fitting of different growth functions to tree growth, and to determine the characteristics of the forest carbon stock as well as the carbon sink potential of Huangshan National Forest Park (HNFP) in China. The carbon sink potential of each tree species and the integrated influencing factors, such as the stand and soil, were directly represented by structural equation modelling (SEM) to clarify the size and path of each influencing factor against the carbon sink potential. The results showed the following: (1) the logistic growth function fitting results for the seven major tree species in HNFP were better than those from the Richard–Chapman growth function, and the R 2 was greater than 0.90. (2) In 2014, the total carbon stock of the forest in HNFP was approximately 9.59 × 10 5 t, and the pattern of carbon density, in general, was higher in the central region and the northeastern region and lower in the northern and southern regions, while the distribution of carbon density was lower in the northern and southern regions. The carbon density pattern generally showed a higher distribution in the central and northeastern regions and a lower distribution in the northern and southern regions; most of the high-carbon-density areas were distributed in blocks, while the low-carbon-density areas were distributed sporadically. (3) The total carbon sink of the forest in HNFP was 8.26 × 10 3 t in 2014–2015, and due to the large age structure of the regional tree species, the carbon sinks of each tree species and the total carbon sink of HNFP showed a projected downward trend from 2014 to 2060. (4) For different tree species, the influencing factors on carbon sink potential are not the same, and the main influence factors involve slope position, slope, altitude, soil thickness, etc. This study identified the carbon stock and carbon sink values of the forest in HNFP, and the factors affecting the carbon sink potential obtained by SEM can provide a basis for the selection of new afforestation sites in the region as well as new ideas and methods to achieve peak carbon and carbon neutrality both regionally and nationally in the future.

Suggested Citation

  • Wenduo Huang & Xiangrong Wang & Dou Zhang, 2024. "The Estimation of Forest Carbon Sink Potential and Influencing Factors in Huangshan National Forest Park in China," Sustainability, MDPI, vol. 16(3), pages 1-19, February.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:3:p:1351-:d:1333965
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    References listed on IDEAS

    as
    1. Yugang He & Xiang Li & Panpan Huang & Jingnan Wang, 2022. "Exploring the Road toward Environmental Sustainability: Natural Resources, Renewable Energy Consumption, Economic Growth, and Greenhouse Gas Emissions," Sustainability, MDPI, vol. 14(3), pages 1-16, January.
    2. Xiaohui Tian & Brent Sohngen & Justin Baker & Sara Ohrel & Allen A. Fawcett, 2018. "Will U.S. Forests Continue to Be a Carbon Sink?," Land Economics, University of Wisconsin Press, vol. 94(1), pages 97-113.
    3. Olimpia Neagu & Mircea Constantin Teodoru, 2019. "The Relationship between Economic Complexity, Energy Consumption Structure and Greenhouse Gas Emission: Heterogeneous Panel Evidence from the EU Countries," Sustainability, MDPI, vol. 11(2), pages 1-29, January.
    4. Geng He & Zhiduo Zhang & Qing Zhu & Wei Wang & Wanting Peng & Yongli Cai, 2022. "Estimating Carbon Sequestration Potential of Forest and Its Influencing Factors at Fine Spatial-Scales: A Case Study of Lushan City in Southern China," IJERPH, MDPI, vol. 19(15), pages 1-22, July.
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