地理科学 ›› 2022, Vol. 42 ›› Issue (6): 1113-1123.doi: 10.13249/j.cnki.sgs.2022.06.017

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基于GWR模型的道路网络对森林碳密度干扰的地理变异

林玉英1,2,3(), 李宝银3,4, 邱荣祖5, 林金国6, 伍世代1,4,*()   

  1. 1.福建师范大学旅游学院,福建 福州 350117
    2.智慧旅游福建省高校重点实验室,福建 福州 350117
    3.福建师范大学生态学博士后科研流动站,福建 福州 350117
    4.福建师范大学地理科学学院,福建 福州 350117
    5.福建农林大学交通与土木工程学院,福建 福州 350108
    6.福建农林大学材料工程学院,福建 福州 350108
  • 收稿日期:2021-04-16 修回日期:2021-08-10 出版日期:2022-06-25 发布日期:2022-08-23
  • 通讯作者: 伍世代 E-mail:linyuying2019@fjnu.edu.cn;sdlw8726@sina.com
  • 作者简介:林玉英(1988−),女,福建龙岩人,副教授,博士后,主要从事道路景观生态、旅游地理等研究。E-mail: linyuying2019@fjnu.edu.cn
  • 基金资助:
    国家自然科学基金项目(41901221, 41971261)、福建省林业局科技项目(SC-259)、福建省水利厅科技项目(SC-290)资助

Geographic Variation of Road Network Effects on Forest Carbon Density Based on GWR Model: A Case Study of the Upstream District of the Minjiang River

Lin Yuying1,2,3(), Li Baoyin3,4, Qiu Rongzu5, Lin Jinguo6, Wu Shidai1,4,*()   

  1. 1. College of Tourism, Fujian Normal University, Fuzhou 350117, Fujian, China
    2. The Higher Educational Key Laboratory for Smart Tourism of Fujian Province, Fuzhou 350117, Fujian, China
    3. Postdoctoral Research Station of Ecology, Fujian Normal University, Fuzhou 350117, Fujian, China
    4. College of Geographical Science, Fujian Normal University, Fuzhou 350117, Fujian, China
    5. College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou 350108, Fujian, China
    6. College of Material Engineering, Fujian Agriculture and Forestry University, Fuzhou 350108, Fujian, China
  • Received:2021-04-16 Revised:2021-08-10 Online:2022-06-25 Published:2022-08-23
  • Contact: Wu Shidai E-mail:linyuying2019@fjnu.edu.cn;sdlw8726@sina.com
  • Supported by:
    National Natural Science Foundation of China (41901221, 41971261), Science and Technology Project of Fujian Provincial Department of Forestry (SC-259), Science and Technology Project of Fujian Provincial Department of Water Resources (SC-290)

摘要:

以闽江上游地区为例,在分析三明市2007—2016年森林碳密度时空动态的基础上,采用常规的以及改进后的道路网络测度指标,应用缓冲区分析方法和地理加权回归(Geographically Weighted Regression,GWR)模型,从线上和面上分别探讨道路网络对森林碳密度干扰的地理变异规律。结果表明:① 碳密度受到道路网络的较大影响,路网影响域内外碳密度的大小排序为:路网影响域内<整个研究区<路网影响域外;多条道路影响域重叠区的碳密度(26.330 Mg/hm2)明显低于单条道路影响域的碳密度(37.406 Mg/hm2);不同等级道路影响域的碳密度由大到小依次为县道>高速>省道>其它道路>国道>乡道。道路网络对2007—2016年碳密度的降低也有明显影响。② GWR模型的分析结果表明,路网对碳密度的影响程度随着样点的变化而变化,具有“空间非平稳性”。碳密度随着路网密度的增加而降低,而随着离道路距离的增加而增加。③ 研究区西北部和中部,GWR的回归系数及相关系数均较大,表明这2个区域道路对碳密度影响大且解释力皆较强。

关键词: 森林碳密度, 道路网络, 道路生态, 地理加权回归, 闽江上游

Abstract:

Taking upstream district of the Minjiang River as an example, we firstly analyze the temporal and spatial dynamics of forest carbon density from 2007 to 2016. To reveal the geographical variation of the association between road network and forest carbon density, this work studies the impacts of different road scenarios and the indexes of different road network measurement on forest carbon density using conventional and improved road network measurement indicators as well as the buffer analysis method and Geographic Weighted Regression (GWR) model. The results show that: 1) The carbon density of the study area is obviously affected by the road network and the magnitude of impact is in the order of within the road network effect zone < the entire research area < outside the road network effect zone; The carbon density of the overlapping region of multiple road effect zones (26.330 Mg/hm 2) is significantly lower than the carbon density (37.406 Mg/hm2) of the single road effect zone. The carbon density of the different grade road effect zones is in the order of county road > expressway > provincial road > other road > national road > rural road; Road construction and expansion also have a significant impact on the reduction of carbon density during 2007 to 2016. 2) The degree of influence of roads on carbon density changes with the change of sample points showed with the characteristic of “spatial non-stationarity”. Carbon density decreases with increasing road density and increases with increasing distance from the road. 3) The regression coefficients and correlation coefficients in the northwest and middle regions of the study area are large, indicating that the roads in these two regions have large impacts on carbon density and are well explained by the model. Policy makers should pay special attention when formulating forest carbon sink protection strategies.

Key words: forest carbon density, road network, road ecology, Geographic Weighted Regression (GWR), the upper Minjiang River

中图分类号: 

  • S718.55