Carbon Storage Effects of Land Use in Xinjiang — 2030 Multi-Scenario Simulation Based on the PLUS-InVEST Model

Under the global climate change and the "Dual Carbon" strategy background, land use and land cover change serves as a core driver of terrestrial ecosystem carbon storage changes, and its spatiotemporal differentiation mechanism is of great significance for carbon sink assessment and territorial spatial planning in arid regions. This study takes Xinjiang, a typical arid region, as the research object, integrates the Patch-generating Land Use Simulation (PLUS) model and the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, and based on land use data from 2000-2024, reveals and predicts the land use patterns and carbon storage changes under three scenarios for 2030: natural development, economic development, and ecological protection. The results show that: (1) From 2000 to 2024, land use in Xinjiang was dominated by unused land and grassland, accounting for over 90% of the total area. The area of grassland and unused land decreased, while cropland and construction land expanded significantly by 28.80×10³ km² and 4.29×10³ km², respectively. (2) From 2000 to 2024, carbon storage showed a slow upward trend, increasing from 96.05×10⁸ t to 97.13×10⁸ t. High-value areas were concentrated in the forest belts and lake basins of the Tianshan, Altai, and Kunlun Mountains, while low-value areas were distributed in the Tarim and Junggar Basins. Level 3 carbon storage, as the core carbon sink, remained stable, and Level 2 and Level 4 carbon storage maintained a dynamic balance. (3) The carbon storage under the three scenarios in 2030 is 97.14×10⁸ t, 97.11×10⁸ t, and 97.44×10⁸ t respectively. The ecological protection scenario reduced carbon loss by 0.41×10⁶ t under expansion control, revealing the key role of strengthening the protection of high-carbon-density land classes and promoting the conversion of low-carbon land classes to forest and grassland in enhancing the carbon sink in arid regions, providing a scientific basis for territorial spatial optimization and carbon neutrality pathways in arid regions.