| 时空动态关系下京津冀地区社会-生态系统风险评估及管控分区 |
| 摘要点击 502 全文点击 9 投稿时间：2025-08-08 修订日期：2025-10-17 |
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| 中文关键词 生态风险 时空动态关系 社会-生态系统（SES） 京津冀（BTH）地区 管控分区 |
| 英文关键词 ecological risk spatio-temporal dynamic relationship social-ecological system （SES） Beijing-Tianjin-Hebei （BTH） Region management zoning |
| DOI 10.13227/j.hjkx.202508085 |
| 作者 | 单位 | E-mail | | 左璐 | 河北省科学院地理科学研究所, 石家庄 050021
河北省地理信息开发应用技术创新中心, 石家庄 050021 | zuol.14b@igsnrr.ac.cn | | 鲁军景 | 河北省科学院地理科学研究所, 石家庄 050021
河北省地理信息开发应用技术创新中心, 石家庄 050021 | | | 孙雷刚 | 河北省科学院地理科学研究所, 石家庄 050021
河北省地理信息开发应用技术创新中心, 石家庄 050021 | sunleigang3s@163.com | | 郝庆涛 | 河北省科学院地理科学研究所, 石家庄 050021
河北省地理信息开发应用技术创新中心, 石家庄 050021 | | | 王钦艺 | 河北省科学院地理科学研究所, 石家庄 050021
河北省地理信息开发应用技术创新中心, 石家庄 050021 | | | 张鹏飞 | 河北省科学院地理科学研究所, 石家庄 050021
河北省地理信息开发应用技术创新中心, 石家庄 050021 | | | 马晓倩 | 河北省科学院地理科学研究所, 石家庄 050021
河北省地理信息开发应用技术创新中心, 石家庄 050021 | |
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| 中文摘要 |
| 快速城市化进程中自然系统与人类社会多重风险因子相互作用，导致区域面临极大的生态风险，科学评估管理生态风险对区域生态安全与可持续发展意义重大. 基于多源风险时空动态关系视角，引入社会-生态系统框架评估分析了2000~2020年京津冀地区生态系统风险、社会系统风险及综合生态风险的时空演变特征，基于不同类型风险时空动态关联性，运用双变量空间自相关及冷热点分析法将研究区划分为6类小区和3类大区，并利用最优参数地理探测器探究全域及分区综合生态风险的驱动差异. 结果表明：①京津冀地区生态系统风险、社会系统风险和综合生态风险均值分别为0.464、0.299和0.381，分布上呈西北低东南高的空间格局，燕山-太行山沿线各类风险等级较低，平原地区风险明显高于山区且生态系统风险强于社会系统风险；②近20 a生态系统风险下降2.55%，社会系统风险增加2.01%，综合生态风险下降0.78%，其中山区西北部及平原东部滨海湿地生态风险下降明显，城市化地区呈核心区等级不变边缘区风险加剧的圈层结构；③双系统风险间空间正相关效应显著且持续增强，综合生态风险显著增大和显著减小面积占比分别为18.63%和19.06%，紧急管控区集中于城市边缘扩张区，重点管控区位于城市核心区，密切监控区分布于城市外围及滨海地带，动态调控区分布最广，预防管理区和维护保育区主要分布在燕山-太行山生态功能区；④地形地貌、城市建设和社会经济活动因素主导全域及监控区综合生态风险空间分异，城市建设对管控区影响突出，地表覆盖对防范区影响更甚；建设用地占比与坡度为全域及监控区最强交互因子，管控区建设用地占比与植被覆盖度交互作用最强，防范区植被覆盖度与裸土指数交互更强. 研究成果可为区域生态风险精准管控和社会经济可持续发展提供参考. |
| 英文摘要 |
| The interaction of multiple risk factors between natural systems and human societies during rapid urbanization poses significant ecological risk to regions. Scientifically assessing and managing these risks is crucial for regional ecological security and sustainable development. This study adopts a multi-source risk spatio-temporal dynamic relationship perspective， incorporating the social-ecological system （SES） framework to assess and analyze the spatio-temporal evolution characteristics of ecosystem risk， social system risk， and comprehensive ecological risk in the Beijing-Tianjin-Hebei （BTH） Region from 2000 to 2020. Based on the spatio-temporal dynamic correlations among different risk types， the study area is categorized into six sub-regions and three macro-regions using bivariate spatial autocorrelation and hot spot-cold spot analysis. Furthermore， optimal parameters-based Geodetector analysis is employed to investigate the driving differences of comprehensive ecological risks across the entire region and within each partitioned zone. The results show that： ① The mean values of ecosystem risk， social system risk， and comprehensive ecological risk in the BTH Region were 0.464， 0.299， and 0.381， respectively. Their distribution exhibited a spatial pattern of low values in the northwest and high values in the southeast. The risk levels of various types along the Yanshan-Taihang Mountains were relatively low， and the risk in plain areas was significantly higher than that in mountainous areas， with ecosystem risk being stronger than social system risk. ② Over the past 20 years， ecosystem risk decreased by 2.55% and social system risk increased by 2.01%， resulting in a slight decrease （0.78%） in comprehensive ecological risk. Comprehensive ecological risk decreased significantly in the northwestern mountainous areas and the coastal wetlands in the eastern plains. Urbanized areas exhibited a ring structure： constant risk levels in the core and increased risk in the peripheral zones. ③ A significant and strengthening positive spatial correlation existed between ecosystem risk and social system risk. The proportions of areas with significantly increased and decreased comprehensive ecological risks were 18.63% and 19.06%， respectively. Emergency control macro-zones were concentrated in urban expansion fringes， key control macro-zones were located within urban core areas， and close monitoring macro-zones were distributed in the urban periphery and coastal belts. Dynamic regulation macro-zones covered the most extensive area， while preventive management macro-zones and conservation macro-zones were primarily situated within the Yanshan-Taihang Mountains Ecological Functional Area. ④Topography， urban construction， and socio-economic activities dominated the spatial differentiation of comprehensive ecological risk across the entire region and within monitoring macro-zones. Urban construction exerted a particularly prominent influence within control macro-zones. Land surface cover served as the primary controlling factor in preventive macro-zones. The percentage of built-up land and slope gradient represented the strongest interactive factors for the entire region and monitoring macro-zones. Within control macro-zones， the percentage of built-up land and vegetation coverage formed the strongest interactive pair. Vegetation coverage and the bare soil index emerged as the strongest interactive factors in preventive macro-zones. The research findings provide valuable references for implementing precise ecological risk management and promoting socio-economic sustainable development in the region. |
