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Spatiotemporal Dynamics and Non-Linear Drivers of Carbon Storage in the Pisha Sandstone Area: A Coupled PLUS–InVEST and XGBoost–SHAP Framework

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  • Lu Zhang

    (College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Jiayi Xu

    (College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Bin Peng

    (College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Jiaqi Han

    (College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Wenjie Yang

    (College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

Abstract

While terrestrial carbon storage is vital for achieving global carbon neutrality, its spatiotemporal evolution in ecologically fragile regions—such as the Pisha sandstone area—is complicated by intense erosion and complex environmental drivers. Widely known as the Pisha sandstone area, often referred to as the “Earth’s ecological cancer” due to its unique geological instability (“hard as rock when dry, soft as mud when wet”), this area is a critical but vulnerable carbon sink in the Yellow River Basin. This study aims to clarify these dynamics and identify their non-linear driving mechanisms by integrating a coupled PLUS–InVEST model with an XGBoost–SHAP framework to simulate land-use cover change and quantify carbon sequestration potential from 1990 to 2040. Our results reveal: (1) a robust path dependence in land use, where grassland remained the dominant landscape matrix (>75%), which partly explains the stable regional carbon-stock structure and the moderate FoM value of the PLUS validation; (2) carbon storage followed a fluctuating but overall increasing trajectory, projected to reach a peak of 3.19 × 10 5 tC by 2040 under the Ecological Conservation Scenario (ECS), which significantly outperforms the economic-driven and natural growth modes; (3) hot spot analysis showed that statistically notable low-carbon cold spots were concentrated mainly along valley corridors, marginal transition zones, and locally disturbed patches, whereas high-carbon hot spots were spatially limited; and, (4) crucially, XGBoost–SHAP results should be interpreted as model-based associations rather than direct causal proof; the whole-region model and the regional models jointly suggest that topography, water availability, socioeconomic pressure, and erosion-related factors contribute differently across bare, loess-covered, and sand-covered Pisha sandstone units. These findings support differentiated land-use and restoration strategies rather than uniform regional management. The findings suggest that future management in the Pisha sandstone area should transition from general restoration toward targeted and differentiated regulation to improve regional ecosystem services.

Suggested Citation

  • Lu Zhang & Jiayi Xu & Bin Peng & Jiaqi Han & Wenjie Yang, 2026. "Spatiotemporal Dynamics and Non-Linear Drivers of Carbon Storage in the Pisha Sandstone Area: A Coupled PLUS–InVEST and XGBoost–SHAP Framework," Sustainability, MDPI, vol. 18(13), pages 1-24, June.
  • Handle: RePEc:gam:jsusta:v:18:y:2026:i:13:p:6595-:d:1978668
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