The Qinling–Daba Mountains serve as a crucial ecological barrier in China’s national ecological security framework. Nonetheless, the designation of conservation areas and zoning management remain insufficiently refined and inadequately aligned with ecological processes, limiting effective preservation and high-quality regional development. Utilizing high-resolution remote sensing and multi-source spatial datasets (2000–2023), we performed a comprehensive evaluation of ecosystem patterns, ecosystem quality, and essential ecosystem services, and established a zoning framework that integrates ecosystem status, functional roles, and geographic constraints by superimposing key ecological function zones and biodiversity priority areas. Results indicate that (1) forest, built-up land, and wetlands increased by 1343.18 km 2 , 1725.36 km 2 , and 488.48 km 2 , respectively; landscape dynamics exhibited stable forest connectivity, farmland evolving from contiguous blocks to a more dispersed arrangement, and intensified clustering and expansion of urban land. Ecosystem quality increased overall: regions with growing EQI represented 48.07%, whereas 5.48% showed negative trends. Enhancements were mostly seen in the Qinling–Daba mountainous region, while reductions were more prevalent in the environmentally vulnerable northwestern area. Regions designated as “very important” for water and soil conservation constituted 17.90% and 10.75% of the study area, respectively, mostly aligning with mountainous areas characterized by dense vegetation and generally favorable hydrothermal conditions. By integrating qualitative and functional change indicators with spatial limitations, we identified three functional management categories: Ecological Enhancement (EI), Ecological Stability (ES), and Ecological Degradation Risk (ED), which were further separated into 18 zoning units. This research offers a practical spatial framework for targeted restoration and management, risk assessment, and efficient distribution of conservation resources to improve ecosystem resilience and governance accuracy.
Yang et al. (Wed,) studied this question.