| 西安市生态安全格局演变驱动机制识别与多情景模拟预测 |
| 摘要点击 558 全文点击 10 投稿时间：2025-07-02 修订日期：2025-09-30 |
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| 中文关键词 生态安全格局 时空演变 驱动因子 多情景模拟 西安 |
| 英文关键词 ecological security pattern spatiotemporal evolution driving factors multi-scenario simulation Xi'an |
| DOI 10.13227/j.hjkx.202507028 |
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| 中文摘要 |
| 生态安全格局是区域生态保护与空间规划的重要基础. 现有研究多聚焦于生态安全格局的驱动因子识别，强调其演化机制，但对关键因子如何影响未来格局演变及其在空间规划中的应用价值探讨不足. 研究提出从“解释过去”转向“预测未来”的思路，基于“生态系统服务重要性-生态敏感性-景观连通性”三维识别框架，构建西安市2000~2020年生态安全格局，并运用地理探测器、普通最小二乘法与地理加权回归模型从“定性-定量-空间”三重维度递进识别生态安全格局演变的关键驱动因子. 进一步将识别出的关键驱动因子嵌入FLUS模型，在自然发展、经济优先发展和生态保护优先这3类情景下，模拟未来土地利用格局并评估生态安全响应特征. 结果表明：①西安市生态源地空间格局总体较为稳定，北部受城镇化干扰而零散分布，南部山区则相对集中；生态廊道数量与长度均有所减少，主要分布于中部平原与东部山区. ②共有6个影响因子显著影响生态源地的形成，其中高程、地形起伏度和坡度起到促进作用；土地利用类型、地形起伏度和距居民点距离则是阻力面形成的3个主要驱动因子，均表现出显著的正向影响，且空间作用主要集中于南部山区. ③情景模拟结果显示，不同情景下西安市土地利用格局存在显著差异，生态保护优先情景下林地面积实现净增长，景观多样性、连通性和聚合度最优，景观干扰风险最低，生态安全响应效果最佳. 研究识别了西安市生态安全格局演变的关键驱动因子，并将其导入FLUS模型以增强预测结果的科学性，可为西安市生态修复与可持续空间治理提供更具针对性的决策依据. |
| 英文摘要 |
| The ecological security pattern （ESP） is a crucial foundation for regional ecological protection and spatial planning. Existing research mostly focuses on the identification of driving factors of the ESP， emphasizing its evolution mechanism， but there is insufficient discussion on how key factors affect the future pattern evolution and their application value in spatial planning. The study proposes a research idea of shifting from “explaining the past” to “predicting the future.” Based on a three-dimensional identification framework of “ecosystem service importance-ecological sensitivity-landscape connectivity，” the ESP of Xi'an from 2000 to 2020 are constructed. The key driving factors of the evolution of the ESP are identified by using a geographical detector model， ordinary least squares （OLS） regression， and geographically weighted regression （GWR） in a progressive “qualitative-quantitative-spatial” analytical sequence. These key driving factors were subsequently integrated into the FLUS model to simulate the future land use patterns and assessed the ecological security response characteristics under three scenarios： business as usual （BAU）， priority economic development （PED）， and priority ecological protection （PEP）. The results show that： ① The spatial pattern of ecological source areas in Xi'an were relatively stable， with fragmented distribution in the northern areas due to urbanization disturbance， while the remaining distribution was relatively concentrated in the southern mountainous regions. The number and length of ecological corridors both decreased， mainly distributed in the central plain and eastern mountainous areas. ② There were six influencing factors that significantly affected the formation of ecological sources， among which elevation， terrain roughness， and slope played a promoting role. Land use type， terrain roughness， and distance to residential areas were the three main driving factors of resistance surface formation， all exhibiting significant positive effects， with spatial effects mainly concentrated in the southern mountainous areas. ③ The scenario simulation results showed that there were significant differences in the land use pattern of Xi'an under different scenarios. Under the PEP scenario， the forest area increased； the landscape diversity， connectivity， and aggregation degree were optimal； the landscape disturbance risk was the lowest； and the ecological security response effect was the best. The study identified the key driving factors of the evolution of Xi'an's ESP and incorporated them into the FLUS model to enhance the scientific validity of the prediction results， providing more targeted decision-making support for ecological restoration and sustainable spatial governance in Xi'an. |
