Future Scenario Simulation and Optimization of Ecological Security Patterns Under Policy Drivers: A Case Study of the Henan Section of the Yellow River Basin, China
Weichen Mu, Yanglong Chen, Chenghang Li, Fen Qin, Yang Liu, Wanlong Li, Fengxue Ruan, Jinjin Du, Zhenzhen LiuUnderstanding the spatiotemporal dynamics of land-use and cover change (LUCC) and ecosystem service (ES) responses is essential for assessing ecological functions in regional landscapes. However, conventional LUCC simulations often rely on historical trends and inadequately represent the spatially heterogeneous effects of top-down policy constraints. Taking the Henan section of the Yellow River Basin (HYRB) as a case study, we developed a policy-to-rule framework that translated ecological redlines, urban development boundaries, and restoration requirements into explicit spatial constraints and land-use transition rules in the PLUS model. A policy-constrained High-Quality Development Scenario (HQDS) was established, with the Natural Growth Scenario (NGS) as a reference. Five ESs were assessed using InVEST from 1985 to 2050, and the results were integrated with the Minimum Cumulative Resistance (MCR) model and circuit theory to construct an ecological security pattern (ESP). Historical reconstruction of the 2022 land-use pattern achieved an overall accuracy of 90.18% and a Kappa coefficient of 86.39%. The five ESs remained relatively stable overall: water yield, soil conservation, and the sediment-related indicator increased, whereas habitat quality and carbon storage declined slightly. Ecological source areas expanded from 7140.54 km2 in 1985 to 12,039.17 km2 under the HQDS in 2050, a 68.6% increase. Compared with the NGS, the HQDS increased source areas by 562.42 km2 (4.9%), reduced ecological corridors from 26 to 24, and increased their total length from 1068.89 to 1099.61 km. These differences represent the projected, scenario-conditioned consequences of the specified policy constraints and provide quantitative decision support for future ecological management.