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生态学杂志 ›› 2025, Vol. 44 ›› Issue (1): 325-336.doi: 10.13292/j.1000-4890.202501.041

• 技术与方法 • 上一篇    下一篇

基于MGWR模型的太行山脉自然保护地空间格局评价及空间优化

王成武,罗俊杰*,汪宙峰,张荞,谢亮   

  1. (西南石油大学地球科学与技术学院, 成都 610500)
  • 出版日期:2025-01-10 发布日期:2025-01-16

Spatial pattern evaluation and spatial optimization of natural protected areas in Taihang Mountains based on the MGWR model.

WANG Chengwu, LUO Junjie*, WANG Zhoufeng, ZHANG Qiao, XIE Liang   

  1. (College of Earth Science and Technology, Southwest Petroleum University, Chengdu 610500, China).

  • Online:2025-01-10 Published:2025-01-16

摘要: 太行山脉自然保护地在生态系统修复、生物多样性保护和自然遗迹保护等方面发挥了重要作用,承担了中国华北地区生态文明建设的重要功能。本研究以太行山脉300个国家级及省市级自然保护地为对象,通过莫兰指数、多距离空间聚类、核密度分析等空间分析方法研究自然保护地数量和面积的空间格局,借助多尺度地理加权回归模型(MGWR)对影响因素进行空间异质性分析,为自然保护地空间优化提供科学依据。结果表明:(1)自然保护地数量在整体上显著聚集分布(I=0.9707)。湿地公园(I湿=0.7130)和风景名胜区(I=0.5031)较其他自然保护地聚集程度更强。(2)自然保护地面积在空间上形成“双核一带”聚集格局。具体表现为以保定市(涞水县、易县)为中心的北太行东北高密度核心区、以石家庄市(灵寿县)、忻州市(五台县)为中心的西太行西北高密度核心区和以邢台县—壶关县—济源市为核心串联而形成的核心地带。(3)自然保护地面积空间格局的影响因素存在显著空间异质性。植被覆盖率和路网密度的正面影响最强,而海拔和建设用地面积的负面影响最强。因此,在自然保护地规划和建设中应区别各类保护地的属性特点,在强调提升自然保护地植被覆盖率的同时,对于城市化地区的自然保护地要关注路网密度的积极影响和建设用地的抑制作用,在高海拔地区规划与设立自然保护地要注意数量和规模适度。


关键词: 自然保护地, 空间分异, 格局优化, 多尺度地理加权回归模型, 太行山脉

Abstract: The natural protected areas in the Taihang Mountains play a critical role in ecosystem restoration, biodiversity conservation, and natural heritage protection, with consequence on the construction of ecological civilization in the north China. In this study, we analyzed the spatial patterns of the number and size of 300 natural protected areas (including national, provincial, and municipal levels) in Taihang Mountains using spatial analysis methods, including Moran’s index, multi-distance spatial clustering, and kernel density analysis. The multi-scale geographically weighted regression (MGWR) model was used to analyze the spatial heterogeneity of influencing factors, aiming to provide a scientific basis for the spatial optimization of natural protected areas. The results showed that: (1) The number of natural protected areas was significantly clustered in spatial distribution (Iglobal=0.9707). Wetland parks (Iwetland=0.7130) and scenic areas (Iscenic=0.5031) had a stronger degree of clustering than other types. (2) The area of natural protected areas formed a “double-core and one-belt” clustered pattern in space. Specifically, it was manifested as the northeastern highdensity core areas centered on Baoding City (Lushui County, Yixian County), the northwestern high-density core areas centered on Shijiazhuang City (Lingshou County) and Xinzhou City (Wutai County), and the core-belt formed by the linking of Xingtai County, Huguan County, and Jiyuan City as the core. (3) The influencing factors of the spatial pattern of the area of natural protected areas had significant spatial heterogeneity. Vegetation coverage rate and road network density had the strongest positive impact, while elevation and construction land area had the strongest negative impact. Therefore, the attribute characteristics of different types of natural protected areas should be distinguished in the planning and construction of natural protected areas. While the improvement of vegetation coverage in natural protected areas should be emphasized, we should pay attention to the positive impact of road network density and the inhibitory effect of construction land on natural protected areas in urbanized regions. In high-altitude areas, the number and scale of natural protected areas should be designed moderately.


Key words: natural protected area, spatial differentiation, pattern optimization, multi-scale geographically weighted regression (MGWR), Taihang Mountains