Revealing the coordination relationship between land use/land cover (LULC) and carbon storage (CS) under diverse climate scenarios is crucial for climate change adaptation in topographically complex regions. This study developed an integrated framework combining the System Dynamics (SD) model, Patch-generating Land Use Simulation (PLUS) model, and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, enabling a closed-loop analysis of driving forces, spatial simulation, and ecological feedback. This study systematically assessed LULC evolution and ecosystem CS along China’s National Highway 318 (G318) from 2000 to 2020, and projected LULC and CS under three SSP-RCP scenarios (SSP1-1.9, SSP2-4.5, SSP5-8.5) for 2030. Results show the following: (1) Historical LULC change was dominated by rapid urban expansion, cropland loss, and nonlinear grassland fluctuation, exerting strong impacts on ecosystem dynamics. Future scenario simulations revealed distinct thresholds of ecological pressure. (2) Regional CS exhibited a decline–recovery pattern during 2000–2020, with all 2030 scenarios projecting CS reduction, although ecological-priority pathways could mitigate losses. (3) Coordination between land-use intensity and CS improved gradually, with SSP2-4.5 emerging as the optimal strategy for balancing development and ecological sustainability. Overall, the coupled SD-PLUS-InVEST framework provides a practical tool for policymakers to optimize land use patterns and enhance CS in complex terrains.

Under climate change, the demand for high-quality urban ecological security is rising. This study focuses on how rapid urbanization and climate change affect ecological risk, resilience, and land use functions (LUFs) spatial co-variation in the Pearl River Delta. Land use was simulated under Shared Socioeconomic Pathways (SSPs) using system dynamics (SD) and the interaction network–Patch-generating Land Use Simulation (intPLUS) model. Ecological risk was quantified via the landscape ecological risk index (LERI) and habitat degradation index (HDI), while ecological resilience was obtained using an adaptability–resistance–recovery framework, producing a comprehensive ecological risk–resilience index (CERRI). Ecosystem services were assessed using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. Spearman correlation, geographically weighted regression (GWR), constraint lines, and extreme gradient boosting with SHapley Additive exPlanations (XGBoost-SHAP) revealed LUFs patterns, nonlinear relationships and threshold effects, and driving factors. The results indicate that construction land expands mainly at the expense of cropland (~4049–4157 km²) from 2023 to 2035, while woodland and water remain largely stable. CERRI shows a concentric pattern (2023 domain mean = 0.638), with safer peripheral belts and a more risk-dominated central–southern core; under coupling-weight uncertainty with 2023-fixed common-reference normalization, SSP245 was preferred in all Monte Carlo iterations (best-scenario probability = 1.000). EF–LF, EF–PF and LF–PF retain stable nonlinear forms. Elevation, economic vitality and transport accessibility are the leading drivers, with model-derived breakpoints near low-elevation, high-vitality and moderately accessible transport nodes. This study provides the CERRI framework to support ecological security monitoring and adaptive land-use management, contributing to more sustainable regional development under climate change.