Spatial and temporal Differentiation and Driving Mechanism of Ecological Vulnerability Along Sichuan-Tibet Railway During 2010-2020 Based on SRP Model

Sun Yuqing; Yang Xin; Hao Lina

doi:10.13961/j.cnki.stbctb.2021.06.027

您当前的位置：

首页 >

文章列表页 >

Spatial and temporal Differentiation and Driving Mechanism of Ecological Vulnerability Along Sichuan-Tibet Railway During 2010-2020 Based on SRP Model

- Spatial and temporal Differentiation and Driving Mechanism of Ecological Vulnerability Along Sichuan-Tibet Railway During 2010-2020 Based on SRP Model
- Bulletin of Soiland Water Conservation Vol. 41, Issue 6, Pages: 201-208(2021)
- 作者机构：
  
  1. 成都理工大学地球勘探与信息技术教育部重点实验室,四川,成都,610059
  2. 成都理工大学地球科学学院,四川,成都,610059
- 作者简介：
- 基金信息：
- DOI：10.13961/j.cnki.stbctb.2021.06.027
  CLC： X171
- Published：2021
- 稿件说明：
移动端阅览
Sun Yuqing, Yang Xin, Hao Lina. Spatial and temporal Differentiation and Driving Mechanism of Ecological Vulnerability Along Sichuan-Tibet Railway During 2010-2020 Based on SRP Model[J]. Bulletin of Soiland Water Conservation, 2021, 41(6): 201-208.
DOI：

Sun Yuqing, Yang Xin, Hao Lina. Spatial and temporal Differentiation and Driving Mechanism of Ecological Vulnerability Along Sichuan-Tibet Railway During 2010-2020 Based on SRP Model[J]. Bulletin of Soiland Water Conservation, 2021, 41(6): 201-208. DOI： 10.13961/j.cnki.stbctb.2021.06.027.

摘要

[目的] 探究川藏铁路沿线2010—2020年生态脆弱性时空分布特征，厘清生态脆弱格局规律以及空间相关性，为沿线生态环境保护以及建后可持续发展工作提供科学依据。[方法] 以川藏线（雅安—新都桥段）为例，基于研究区实地特征和SRP模型选取与生态脆弱性密切相关的15个因子构建研究区生态脆弱性评价指标体系。综合运用空间主成分分析、空间自相关、热点分析、地理探测器等方法开展研究。[结果] ①时空分布上，研究区整体脆弱性由西向东呈递减分布，2010—2020年生态状况整体向好，重度与极度脆弱区范围较小，占总面积的3.95%，主要分布在康定市与天全县、泸定县的交界处，此处为高寒地带，冻融侵蚀最为严重； ②研究区生态脆弱性分布具有较强聚类特征，高低值集聚模式共存，西部为热点高度集聚区，东部为冷点高度集聚区； ③高程、年均气温、植被净初级生产力是导致研究区生态脆弱的主要因素。[结论] 川藏线（雅安—新都桥段）施工建设受降水和气温影响较大，地形复杂，要注意地质灾害防控并加强环境保护与生态维持。

Abstract

[Objective] The spatial and temporal distribution characteristics of ecological vulnerability along Sichuan-Tibet railway from 2010 to 2020 was explored

and the pattern and spatial correlation of ecological vulnerability was clarified

in order to provide scientific basis for ecological environment protection and sustainable development after construction.[Methods] Taking the Sichuan and Tibet railway (Ya'an-Xinduqiao section) as an example

15 factors closely related to ecological vulnerability were selected based on the field characteristics and SRP model to construct the ecological vulnerability evaluation index system. Spatial principal component analysis (PCA)

spatial autocorrelation

hot spot analysis and geographic detector were used to carry out the research.[Results] ① In terms of spatial and temporal distribution

the overall vulnerability of the study area decreased from west to east

and the ecological status of the study area improved from 2010 to 2020. The severe and extremely vulnerable areas were small

accounting for 3.95% of the total area

and mainly distributed in the junction of Kangding City

Tianquan County and Luding County

which was an alpine zone with the most serious freezing-thawing erosion. ② The distribution of ecological vulnerability in the study area has strong clustering characteristics

with high and low values co-existing. In the west

hot spots are highly concentrated

while in the east

cold spots are highly concentrated. ③ Elevation

average annual temperature and net primary productivity of vegetation were the main factors leading to ecological fragility in the study area.[Conclusion] The construction of the Sichuan-Tibet railway (Ya'an to Xinduqiao section) was greatly affected by precipitation and temperature

and the terrain was complicated. Therefore

attention should be paid to geological disaster prevention and control

environmental protection and ecological maintenance.

关键词

Keywords

references

徐君, 李贵芳, 王育红.生态脆弱性国内外研究综述与展望[J].华东经济管理, 2016, 30(4):149-162.

Wu Shaohong, Dai Erfu, Huang Mei, et al. Ecosystem vulnerability of China under B

climate scenario in the 21st century[J]. Chinese Science Bulletin, 2007, 52(10):1379-1386.

Kirstin D. Exploring differences in our common future(s):The meaning of vulnerability to global environmental change[J]. Pergamon, 1992, 23(3)417-436.

周永娟, 仇江啸, 王姣, 等.三峡库区消落带生态环境脆弱性评价[J].生态学报, 2010, 30(24):6726-6733.

王钰, 胡宝清.西江流域生态脆弱性时空分异及其驱动机制研究[J].地球信息科学学报, 2018, 20(7):947-956.

Guo Bing, Zang Wenqian, Luo Wei. Spatial-temporal shifts of ecological vulnerability of Karst Mountain ecosystem-impacts of global change and anthropogenic interference[J]. Science of the Total Environment, 2020, 741:140256.

马真臻, 王忠静, 顾艳玲, 等.中国西北干旱区自然保护区生态脆弱性评价:以甘肃西湖、苏干湖自然保护区为例[J].中国沙漠, 2015, 35(1):253-259.

吴建寨, 李波, 张新时, 等.天山北坡生态经济的脆弱性[J].应用生态学报, 2008, 19(4):859-865.

郭婧, 魏珍, 任君, 等.基于熵权灰色关联法的高寒贫困山区生态脆弱性分析:以青海省海东市为例[J].水土保持通报, 2019, 39(3):191-199.

Zhao Jincai, Ji Guanxing, Tian Yuan, et al. Environmental vulnerability assessment for mainland China based on entropy method[J]. Ecological Indicators, 2018, 91:410-422.

楚文海, 高乃云, 鄢贵权, 等.西南岩溶山区水资源可持续利用评价指标选取及权重确定[J].水土保持通报, 2008, 28(1):59-64.

朱琪, 周旺明, 贾翔, 等.长白山国家自然保护区及其周边地区生态脆弱性评估[J].应用生态学报, 2019, 30(5):1633-1641.

杨平, 杨国静, 曾永平.川藏铁路简支梁桥地震易损性及适应性分析[J].铁道工程学报, 2015, 32(12):51-57.

薛翊国, 孔凡猛, 杨为民, 等.川藏铁路沿线主要不良地质条件与工程地质问题[J].岩石力学与工程学报, 2020, 39(3):445-468.

张广泽, 蒋良文, 宋章, 等.横断山区川藏线山地灾害和地质选线原则研究[J].铁道工程学报, 2016, 33(2):21-24.

李郎平, 兰恒星, 郭长宝, 等.基于改进频率比法的川藏铁路沿线及邻区地质灾害易发性分区评价[J].现代地质, 2017, 31(5):911-929.

卢亚灵, 颜磊, 许学工.环渤海地区生态脆弱性评价及其空间自相关分析[J].资源科学, 2010, 32(2):303-308.

罗运武, 韩鹏, 郑光玉, 等.川藏铁路雅安至康定段环保选线研究[J].铁道工程学报, 2017, 34(8):1-5.

任洋, 王栋, 李天斌, 等.川藏铁路雅安至新都桥段地应力特征及工程效应分析[J].岩石力学与工程学报, 2021, 40(1):65-76.

刘志红, Mcvicar T R, Van N, 等.专用气候数据空间插值软件ANUSPLIN及其应用[J].气象, 2008(2):92-100.

陈峰, 李红波.基于GIS和RUSLE的滇南山区土壤侵蚀时空演变:以云南省元阳县为例[J].应用生态学报, 2021, 32(2):629-637.

朴世龙, 方精云, 郭庆华.利用CASA模型估算我国植被净第一性生产力[J].植物生态学报, 2001, 25(5):603-608, 644.

李永化, 范强, 王雪, 等.基于SRP模型的自然灾害多发区生态脆弱性时空分异研究:以辽宁省朝阳县为例[J].地理科学, 2015, 35(11):1452-1459.

王钰, 胡宝清.西江流域生态脆弱性时空分异及其驱动机制研究[J].地球信息科学学报, 2018, 20(7):947-956.

乔青, 高吉喜, 王维, 等.生态脆弱性综合评价方法与应用[J].环境科学研究, 2008, 21(5):117-123.

齐姗姗, 巩杰, 钱彩云, 等.基于SRP模型的甘肃省白龙江流域生态环境脆弱性评价[J].水土保持通报, 2017, 37(1):224-228.

贾晶晶, 赵军, 王建邦, 等.基于SRP模型的石羊河流域生态脆弱性评价[J].干旱区资源与环境, 2020, 34(1):34-41.

南颖, 吉喆, 冯恒栋, 等.基于遥感和地理信息系统的图们江地区生态安全评价[J].生态学报, 2013, 33(15):4790-4798.

刘正佳, 于兴修, 李蕾, 等.基于SRP概念模型的沂蒙山区生态环境脆弱性评价[J].应用生态学报, 2011, 22(8):2084-2090.

马骏, 李昌晓, 魏虹, 等.三峡库区生态脆弱性评价[J].生态学报, 2015, 35(21):7117-7129.

付建新, 曹广超, 郭文炯.1980-2018年祁连山南坡土地利用变化及其驱动力[J].应用生态学报, 2020, 31(8):2699-2709.

Rossi B. Creating forest management units with hot spot analysis(Getis-Ord Gi

) over a forest affected by mixed-severity fires[J]. Australian Forestry, 2019, 82(4):1678714.

马世五, 谢德体, 张孝成, 等.三峡库区重庆段土地生态状况时空格局演变特征[J].生态学报, 2018, 38(23):8512-8525.

王劲峰, 徐成东.地理探测器:原理与展望[J].地理学报, 2017, 72(1):116-134.

张泽, 胡宝清, 丘海红, 等.桂西南喀斯特-北部湾海岸带生态环境脆弱性时空分异与驱动机制研究[J].地球信息科学学报, 2021, 23(3):456-466.

刘军会, 邹长新, 高吉喜, 等.中国生态环境脆弱区范围界定[J].生物多样性, 2015, 23(6):725-732.

Views

918

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Ecological Vulnerability Assessment and Its Uncertainty Analysis of Dalian City

Newly cultivated land changes and multi-scale detection of their driving mechanisms in western Jilin Province

Changes and its driving factors of ecological environment quality in Yellow River Source Park from 2000 to 2024

Spatiotemporal evolution characteristics and driving factors of farmland transfer in China

Ecological environment quality evolution and its driving factors in Qinghai Province from 2000 to 2024

Related Author

Ma Zihui

Ma Shuming

Zhang Shushen

Feng Peiyue

Liu Wenxin

Han Bingcheng

Wei Yuming

Dang Xinghai

Related Institution

大连理工大学环境学院, 工业生态与环境工程教育部重点实验室

Northeast Institute of Geography and Agroecology， Chinese Academy of Sciences

College of Resources and Environment， University of Chinese Academy of Sciences

Civil and Hydraulic Engineering College， Lanzhou University of Technology

Gansu Vocational College of Architecture

⁰