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As a fundamental resource underpinning national food security and ecological civilization, cultivated land performs multiple functions with complex supply–demand relationships. However, existing research has yet to systematically reveal the spatiotemporal evolution of regional cultivated land multifunction (CLM) and its simulation under alternative development scenarios. This study develops a supply–demand framework for CLM in the Yangtze River Delta (YRD). Based on a grid-based supply–demand index (SDI), it evaluates the spatiotemporal evolution of production, ecological, and landscape–culture functions from 2000 to 2020, identifying long-term trends and spatial disparities. Using an improved PLUS (Patch-generating Land Use Simulation) model driven by localized SDI indicators, it further simulates the supply–demand dynamics from 2030 to 2050 under multiple development scenarios, revealing functional transition pathways and policy-dependent trajectories. Results show that (1) the production and landscape–culture functions maintain a relatively stable, surplus-oriented relationship, whereas the ecological function faces an increasingly severe supply–demand deficit. Spatially, production remains strong in agricultural landscapes, ecological deficits intensify along urbanized gradients, and landscape–culture functions maintain moderate surpluses in culturally and environmentally endowed areas.; (2) scenario-specific drivers exert distinct effects: conservation-oriented development enhances ecological performance and supply–demand coordination, whereas the economic-priority scenario exacerbates mismatch risks; and (3) dominant functions shift from production-dominant toward ecological and cultural-dominant types, following clear pathways of functional coupling and synergy. Integrating relational adequacy assessment and land-use transition simulation, this study shifts multifunctional evaluation from static capacity ranking to dynamic structural diagnosis, providing a theoretically and policy-relevant framework for CLM governance.
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Sun et al. (2026) studied this question.
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