Spatial and temporal evolution and obstacle factors of ecological livability level in Wuling Mountain area

doi:10.14088/j.cnki.issn0439-8114.2024.07.006

Abstract

Abstract: Wuling Mountain area was selected as the research object, and 22 indicators were selected to construct the evaluation index system of the ecological livability level of Wuling Mountain area from the four aspects of economic construction level, ecological development level, social service and security, residents' life and cultural environment. The spatial-temporal evolution law of ecological livability level in Wuling Mountain area from 2013 to 2021 was explored by the entropy weight method and TOPSIS model, combined with ArcGIS for visual analysis. In addition, the main obstacle factors were analyzed by the obstacle factor diagnosis model. The results showed that, from 2013 to 2021, the ecological livability level of Wuling Mountain area showed a dynamic change trend of first decreasing, then increasing and decreasing again. Among them, the ecological livability level of Enshi Prefecture, Qianjiang District and Tongren City showed an upward trend; the ecological livability level of Huaihua City and Xiangxi Prefecture showed a “V” curve change with time, and the overall trend was downward; the ecological livability level of Zhangjiajie City continued to decline. The regional ecological livability level showed a downward trend in the east and central-southern regions, and the concentrated areas with high ecological livability level shifted from the east in 2013 to the northwest in 2021. From the perspective of obstacle factor analysis, the obstacle degree of the first-level index of ecological livability level in Wuling Mountain area from large to small was economic construction level, residents' life and cultural environment, social service and security, and ecological development level. The five main obstacle factors were per capita local fiscal general budget revenue, number of schools per 10 000 people, highway mileage per 10 000 people, total fixed asset investment per capita, and the proportion of the tertiary industry in GDP.

Key words: ecological livability, entropy-TOPSIS model, ArcGIS, obstacle factor, Wuling Mountain area

CLC Number:

F061.5

DENG Ming-rong, HE Bi-hu, ZHANG He-li, ZHU Shen-hai. Spatial and temporal evolution and obstacle factors of ecological livability level in Wuling Mountain area[J]. HUBEI AGRICULTURAL SCIENCES, 2024, 63(7): 36-47.

References

[1] 李静芝, 杨丹.荆南三口地区生态系统服务价值时空特征分析[J/OL].安全与环境学报,1-13[2022-04-23].DOI:10.13637/j.issn.1009-6094.2021.1582.
[2] 刘春雨, 董晓峰, 刘英英. 西北干旱区土地利用结构变化及生态服务价值的响应——以民乐县为例[J].兰州大学学报(自然科学版), 2013,49(5):675-681.
[3] 李庆,张鹏.南昌市土地利用与生态系统服务价值的关联性分析[J].江西科学,2021,39(4):632-640.
[4] 焦春萌, 谢明阳, 焦峰, 等.1990—2020年延安市土地利用结构时空偏移及生态系统服务价值变化[J].水土保持通报,2021,41(6):274-281.
[5] 王泽宇,陈旭阳,马彩诗,等.陕北榆林市退耕还林前后土壤侵蚀及生态服务价值变化[J].西北林学院学报,2021,36(3):59-67.
[6] 姜晗, 吴群.基于LUCC的江苏省生态系统服务价值评估及时空演变特征研究[J].长江流域资源与环境, 2021,30(11):2712-2725.
[7] 陈睿, 杨灿, 杨艳, 等.洞庭湖生态经济区生态系统服务价值的时空演绎及其驱动因素[J].应用生态学报,2022,33(1):169-179.
[8] 薛朝浪, 赵宇鸾, 魏小芳, 等.基于CCA的太行山区土地利用变化驱动机制分析[J].贵州师范大学学报(自然科学版),2019, 37(1):93-103.
[9] 余汛, 王莉, 景海涛, 等.太行山区NDVI时空变化及其对气候因子的响应[J].江苏农业科学, 2020,48(16):260-268.
[10] 周鹏. 太行山区国土空间格局优化与功能提升路径研究[D].北京:中国科学院大学, 2020.
[11] 郑德凤, 万巨影, 白丽娜, 等.燕山—太行山区生态系统服务价值权衡/协同关系的多尺度分析[J].生态与农村环境学报,2022(4):409-417.
[12] 蒙莉娜,郑新奇.区域土地利用动态变化分析的新方法研究——以北京市为例[A].中国土地学会,中国土地勘测规划院,国土资源土地利用重点实验室.2008年中国土地学会学术年会论文集[C].2008.284-295.
[13] 许洁,韦燕飞, 童新华, 等.广西左右江流域土地利用变化对生态系统服务价值的影响[J].国土资源情报, 2021(6):8-17.
[14] 谢高地,张彩霞,张雷明, 等.基于单位面积价值当量因子的生态系统服务价值化方法改进[J].自然资源学报, 2015,30(8):1243-1254.
[15] 刘倩, 李葛, 张超, 等.基于系数修正的青龙县生态系统服务价值动态变化研究[J].中国生态农业学报(中英文),2019,27(6):971-980.
[16] 徐丽芬, 许学工, 罗涛, 等.基于土地利用的生态系统服务价值当量修订方法——以渤海湾沿岸为例[J].地理研究, 2012,31(10):1775-1784.
[17] 李鲁冰, 林文鹏, 任晨阳, 等.两种生态系统服务价值评估方法的比较研究——以环杭州湾地区为例[J].水土保持研究,2022,29(3):228-234,243.
[18] 张杰,李清泉,吴祥茵,等.基于土地利用的粤港澳大湾区生态系统服务价值及承载力演变分析[J].生态学报,2021,41(21):8375-8386.
[19] 贾艳艳,于东明,王明杰,等.泰安市景观格局和生境质量时空演变及其关联分析[J].西北林学院学报,2022,37(2):229-237.