The Aboveground Carbon Stock of Moso Bamboo Forests Is Significantly Reduced by<i>Pantana phyllostachysae</i> Chao Stress: Evidence from Multi-source Remote Sensing Imagery

This study estimated aboveground carbon stock (AGC) using field data and integrated multi-source remote sensing imagery to understand the effects of Pantana phyllostachysae Chao (P. phyllostachysae) stress. AGC remote sensing inversion was performed while accounting for P. phyllostachysae stress, and changes were analyzed. Results indicate: (1) Carbon content coefficients of Moso bamboo leaves, branches, and culms under pest stress ranged from 0.422 to 0.543 g/g, decreasing with increased stress. (2) A random forest model using multi-source data demonstrated the best performance (R2 = 0.688), estimating average AGC at 28.427 t/ha and total carbon sequestration at 913.902 MtC (Million tons of Carbon). (3) Increased pest stress resulted in gradual reductions in AGC. (4) Pest stress is estimated to result in a carbon sequestration loss of 77.443 MtC. The AGC estimation model indicates that P. phyllostachysae significantly reduces AGC, providing crucial data for understanding carbon cycling and enhancing carbon sink management in Moso bamboo forests.

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Publication Details

Journal
Photogrammetric Engineering & Remote Sensing
Published
2025-03-27
DOI
https://doi.org/10.14358/pers.24-00107r2
Primary Topic
Land Use and Ecosystem Services
Type
article
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article

The Aboveground Carbon Stock of Moso Bamboo Forests Is Significantly Reduced byPantana phyllostachysae Chao Stress: Evidence from Multi-source Remote Sensing Imagery

Xiaoyu Guo, Zhanghua Xu, Lingyan Chen, Haitao Li et al.
Photogrammetric Engineering & Remote Sensing
Land Use and Ecosystem Services
article

The Aboveground Carbon Stock of Moso Bamboo Forests Is Significantly Reduced byPantana phyllostachysae Chao Stress: Evidence from Multi-source Remote Sensing Imagery

Xiaoyu Guo, Zhanghua Xu, Lingyan Chen, Haitao Li, Lei Sun, Yuanyao Yang, Fengying Guan, Wanling Shen, Chaofei Zhang
article en

Abstract

This study estimated aboveground carbon stock (AGC) using field data and integrated multi-source remote sensing imagery to understand the effects of Pantana phyllostachysae Chao (P. phyllostachysae) stress. AGC remote sensing inversion was performed while accounting for P. phyllostachysae stress, and changes were analyzed. Results indicate: (1) Carbon content coefficients of Moso bamboo leaves, branches, and culms under pest stress ranged from 0.422 to 0.543 g/g, decreasing with increased stress. (2) A random forest model using multi-source data demonstrated the best performance (R2 = 0.688), estimating average AGC at 28.427 t/ha and total carbon sequestration at 913.902 MtC (Million tons of Carbon). (3) Increased pest stress resulted in gradual reductions in AGC. (4) Pest stress is estimated to result in a carbon sequestration loss of 77.443 MtC. The AGC estimation model indicates that P. phyllostachysae significantly reduces AGC, providing crucial data for understanding carbon cycling and enhancing carbon sink management in Moso bamboo forests.

Photogrammetric Engineering & Remote SensingVol. 91(4)
State Forestry and Grassland Administration (CN), Sanming University (CN), Fuzhou University (CN), Wuyi University (CN)
Openalex Percentile: Top 93%
Land Use and Ecosystem Services
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The Aboveground Carbon Stock of Moso Bamboo Forests Is Significantly Reduced by<i>Pantana phyllostachysae</i> Chao Stress: Evidence from Multi-source Remote Sensing Imagery — Xiaoyu Guo, Zhanghua Xu, et al. · Photogrammetric Engineering & Remote Sensing (2025) | TGRS Research Map | TGRS