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ORIGINAL RESEARCH article

Front. For. Glob. Change
Sec. Forest Management
Volume 7 - 2024 | doi: 10.3389/ffgc.2024.1298804
This article is part of the Research Topic Interactions Between Forest Management and Carbon Balance: Mechanisms, Simulation and Practice View all 7 articles

Application of GM (1,1) to predict the dynamics of stand carbon storage in Pinus. kesiya var. langbianensis natural forests

Provisionally accepted
Chunxi Gu Chunxi Gu Chang Liu Chang Liu *Wangfei Zhang Wangfei Zhang *Zhengdao Yang Zhengdao Yang *Wenwu Zhou Wenwu Zhou *Guanglong Ou Guanglong Ou
  • College of Forestry, Southwest Forestry University, Kunming, China

The final, formatted version of the article will be published soon.

    Amid global carbon reduction and climate action, precise forest carbon storage estimation is crucial for comprehending the carbon cycle. This study forecasts P. kesiya var. langbianensis forests' 2030 stand carbon storage using data from 81 permanent plots across three Yunnan Province forest surveys and remote sensing. Findings: (1) In 2000, storage ranged from 26 to 38 t•hm -2 . Central areas had higher values; southwest and southeast exceeded northwest and northeast. By 2010, storage grew eastward, receded northward. By 2020, east storage declined, southwest rose. (2) GM (1,1) model: posterior difference C 0.001, R 2 power function model 0.945, GM(1,1) P value 0.999, power function model P value 0.997. (3) Predictions: Cosivarang border forest's 2030 carbon stock 2850.804 t•hm -2 , up 103.463 t•hm -2 from 2000. At 2022's certified Emission Reduction carbon price of 60 yuan/ton, 2030's carbon asset value per unit (t•hm -2 ) approx. 6207.78 Yuan, compared to 2000. Integrating grey system theory, especially GM (1,1) model, robustly addresses "small data and uncertainty" system challenges. Introducing GM (1,1) grey theory in forestry research offers fresh insight into forest carbon sink dynamics.

    Keywords: carbon sequestration potential1, P. kesiya var. langbianensis2, GM (1, 1) grey model3, carbon storage4, Random Forest5

    Received: 22 Sep 2023; Accepted: 08 Jul 2024.

    Copyright: © 2024 Gu, Liu, Zhang, Yang, Zhou and Ou. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Chang Liu, College of Forestry, Southwest Forestry University, Kunming, China
    Wangfei Zhang, College of Forestry, Southwest Forestry University, Kunming, China
    Zhengdao Yang, College of Forestry, Southwest Forestry University, Kunming, China
    Wenwu Zhou, College of Forestry, Southwest Forestry University, Kunming, China

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