Land Use Simulation and Carbon Storage Driving Mechanisms in Resource-Based Regions Under SSP-RCP Scenarios: An Integrated PLUS-InVEST and GWR-SEM Modeling Approach

Tonghui Yu, Mengting Yang, Xinyu Li, Xuan Zhu, Mengru Wang and Jiqiang Niu ()
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Tonghui Yu: School of Business, Xinyang Normal University, Xinyang 464000, China
Mengting Yang: School of Business, Xinyang Normal University, Xinyang 464000, China
Xinyu Li: School of Business, Xinyang Normal University, Xinyang 464000, China
Xuan Zhu: School of Earth Atmosphere and Environment, Faculty of Science, Monash University, Melbourne 3800, Australia
Mengru Wang: School of Business, Xinyang Normal University, Xinyang 464000, China
Jiqiang Niu: School of Geographic Sciences, Xinyang Normal University, Xinyang 464000, China

Land, 2025, vol. 14, issue 11, 1-29

Abstract: Amid China’s dual-carbon goals and widening regional disparities, land-use/cover change (LUCC)-induced volatility in carbon storage (CS) has emerged as a binding constraint on emission reduction and the low-carbon transition in resource-based regions. Yet integrated historical-scenario assessments and rigorous evidence on spatial-heterogeneity mechanisms remain limited, which hampers targeted spatial governance. Using Shanxi Province, a resource-based province, as the study area, this study develops a coupled PLUS-InVEST framework under SSP-RCP scenarios. It integrates spatial autocorrelation, geographically weighted regression (GWR), and structural equation modeling (SEM) to characterize spatiotemporal responses of CS to LUCC and to identify underlying drivers. The results indicate that: (1) Regional CS follows an inverted U-shaped trajectory, initially increasing due to ecological restoration projects and subsequently declining owing to industrial development and urban expansion; (2) By 2030, forestland expansion under SSP126 is projected to enhance CS, whereas accelerated urbanization under SSP585 is expected to intensify CS losses; (3) Significant spatial clustering of CS remains consistent from historical periods to future projections, underscoring its sensitivity to topography, vegetation patterns, and human activities; and (4) CS is jointly shaped by natural and anthropogenic drivers, with DEM and slope providing stable protection, while population density and transport-network configuration cause ongoing disturbances. The study provides an integrated historical-scenario assessment and reveals the underlying mechanisms for resource-based regions, offering quantitative evidence to support optimization of the Ecological Conservation Redline, managing urban growth boundaries, and implementing zoned ecological restoration.

Keywords: carbon storage; SSP-RCP scenarios; PLUS-InVEST model; GWR-SEM model; Shanxi Province (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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