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Modelling the impacts of climate change and harvesting on carbon dynamics in representative subtropical secondary forests: A case study from Hunan Province, China

Author

Listed:
  • Wang, Longjun
  • Liu, Haoyun
  • Liu, Zelin
  • Li, Tong
  • Li, Peng
  • Zou, Ziying
  • Zhou, Xiaolu
  • Wang, Weifeng
  • Peng, Changhui
  • Xiang, Wenhua
  • Liu, Cong

Abstract

Climate change and forest harvesting are key drivers of carbon dynamics in forest ecosystems. In this study, we applied the TRIPLEX-Management model to simulate the carbon sequestration potential of subtropical secondary forests in Hunan Province, China, from 2015 to 2060. The model was validated using data from 530 forest sample plots. Results confirm a good agreement between simulated NPP and observations (R2=0.73; P<0.01). Simulations were further conducted under three climate change scenarios (SSP126, SSP245, SSP585) and two harvesting strategies (whole-tree harvesting, WTH; and stem-only harvesting, SOH). Results showed that climate change enhanced both net primary productivity (NPP) and net ecosystem productivity (NEP). WTH generally led to higher cumulative NEP compared to no harvesting and SOH. Under the high-emission SSP585 scenario and with earlier harvesting (e.g., in 2030), the longer recovery period promoted greater NEP accumulation over the simulation period, resulting in the highest cumulative NEP. Our results suggest that combining WTH with early harvesting under projected climate change can maximize carbon sequestration. Overall, the interaction between climate change and harvesting determines the long-term carbon sink potential of subtropical secondary forests. These findings highlight that climate-smart forest management, adapted to different forest types and future climate scenarios, could significantly contribute to regional carbon neutrality goals by 2060.

Suggested Citation

  • Wang, Longjun & Liu, Haoyun & Liu, Zelin & Li, Tong & Li, Peng & Zou, Ziying & Zhou, Xiaolu & Wang, Weifeng & Peng, Changhui & Xiang, Wenhua & Liu, Cong, 2025. "Modelling the impacts of climate change and harvesting on carbon dynamics in representative subtropical secondary forests: A case study from Hunan Province, China," Ecological Modelling, Elsevier, vol. 508(C).
    • Handle: RePEc:eee:ecomod:v:508:y:2025:i:c:s0304380025002261
    DOI: 10.1016/j.ecolmodel.2025.111240
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    References listed on IDEAS

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    1. Wang, Weifeng & Peng, Changhui & Zhang, S.Y. & Zhou, Xiaolu & Larocque, Guy R. & Kneeshaw, Daniel D. & Lei, Xiangdong, 2011. "Development of TRIPLEX-Management model for simulating the response of forest growth to pre-commercial thinning," Ecological Modelling, Elsevier, vol. 222(14), pages 2249-2261.
    2. Trevor F. Keenan & David Y. Hollinger & Gil Bohrer & Danilo Dragoni & J. William Munger & Hans Peter Schmid & Andrew D. Richardson, 2013. "Increase in forest water-use efficiency as atmospheric carbon dioxide concentrations rise," Nature, Nature, vol. 499(7458), pages 324-327, July.
    3. Daigneault, Adam & Favero, Alice, 2021. "Global forest management, carbon sequestration and bioenergy supply under alternative shared socioeconomic pathways," Land Use Policy, Elsevier, vol. 103(C).
    4. Zhang, Jun & Chu, Ziyan & Ge, Ying & Zhou, Xiaolu & Jiang, Hong & Chang, Jie & Peng, Changhui & Zheng, Jiawen & Jiang, Bo & Zhu, Jinru & Yu, Shuquan, 2008. "TRIPLEX model testing and application for predicting forest growth and biomass production in the subtropical forest zone of China's Zhejiang Province," Ecological Modelling, Elsevier, vol. 219(3), pages 264-275.
    5. Lianyi Guo & Zhihong Jiang & Deliang Chen & Hervé Treut & Laurent Li, 2020. "Projected precipitation changes over China for global warming levels at 1.5 °C and 2 °C in an ensemble of regional climate simulations: impact of bias correction methods," Climatic Change, Springer, vol. 162(2), pages 623-643, September.
    6. Zhao, Meifang & Xiang, Wenhua & Deng, Xiangwen & Tian, Dalun & Huang, Zhihong & Zhou, Xiaolu & Yu, Guirui & He, Honglin & Peng, Changhui, 2013. "Application of TRIPLEX model for predicting Cunninghamia lanceolata and Pinus massoniana forest stand production in Hunan Province, southern China," Ecological Modelling, Elsevier, vol. 250(C), pages 58-71.
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