Land (Oct 2024)

A Simulation-Based Prediction of Land Use Change Impacts on Carbon Storage from a Regional Imbalance Perspective: A Case Study of Hunan Province, China

  • Jingyi Zhang,
  • Hanqi Ding,
  • Jingkun Xu,
  • Bohong Zheng

DOI
https://doi.org/10.3390/land13101721
Journal volume & issue
Vol. 13, no. 10
p. 1721

Abstract

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Land use imbalances are a critical driving factor contributing to regional disparities in carbon storage (CS). As a significant component of China’s Yangtze River Economic Belt, Hunan Province has undergone substantial shifts in land use types, resulting in an uneven distribution of ecosystem CS and sequestration capacity. Therefore, within the framework of the “dual carbon” strategy, examining the effects of land use changes driven by regional resource imbalances on CS holds practical importance for advancing regional sustainable development. This study focuses on Hunan Province, utilizing the PLUS-InVEST model to assess the spatiotemporal evolution of CS under land use changes from 1990 to 2020. Additionally, multiple scenario-based development modes were employed to predict county-level CS. The results indicate the following: (1) From 1990 to 2020, Hunan Province experienced continuous urban expansion, with forest land and cultivated land, which are core ecological land types, being converted into construction land. (2) Over these 30 years, the province’s total CS increased by 2.47 × 108 t, with significant spatial differentiation. High-value zones were concentrated in bands along the province’s borders, while lower values were observed in the central and northern regions. The highest CS values were recorded in forested areas at the province’s periphery, whereas the lowest values were observed in the northern water bodies. (3) The scenario-based predictions revealed notable differences, with the ecological protection scenario demonstrating a substantial carbon sink effect. By prioritizing forest and cultivated land, CS could be maximized. This research provides valuable insights for enhancing CS and optimizing land use structures in regions facing resource imbalances.

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