基于SRP模型的塔里木胡杨林公园生态脆弱性研究

doi:10.12118/j.issn.1000-6060.2024.573

Abstract

Abstract:

An ecological vulnerability assessment provides the foundation for sustainable regional development and restoration. This study utilized remote sensing data and socioeconomic statistics to construct an ecological vulnerability evaluation index system for the Tarim Populus euphratica Forest Park (Xinjiang, China). Based on the sensitivity-resilience-pressure model, the system incorporated 18 indicators, including ecological function, and was analyzed using a combined hierarchical analysis-entropy weighting method. This approach revealed the spatiotemporal characteristics and driving factors of the park’s ecological vulnerability from 2000 to 2020. The results are as follows: (1) The park’s average ecological vulnerability index was 0.30 in 2020, indicating a mild vulnerability level, with a spatial distribution of higher vulnerability in the eastern, western, and central areas and lower vulnerability in the southeast. (2) The park’s ecological vulnerability showed a fluctuating downward trend, moving from an index of 0.33 in 2000 to 0.47 in 2010, before improving to 0.29 in 2015 and then slightly degrading to 0.30 in 2020. Over this period, 44.52% of the area saw a decrease in vulnerability, while 28.60% experienced an increase. (3) A significant positive spatial correlation was consistently observed, with a Global Moran’s I greater than 0 (Z>2.58, P<0.01), indicating prominent low-low and high-high clustering. (4) Key single-factor drivers of vulnerability included the degree of water change, desertification, water conservation, and the vegetation index. The interactions among the factors demonstrated a non-linear and two-factor enhancement relationship. Remarkably, the synergistic effect between the degree of water change and water source conservation was the most significant driver of the park’s ecological vulnerability. These results offer a scientific reference for the ecological restoration, environmental protection, and sustainable management of the Tarim P. euphratica Forest Park.

Key words: ecological vulnerability, sensitivity-resilience-pressure model, analytic hierarchy process-entropy weight method, geodetector, Tarim Populus euphratica Forest Park

LIN Mofei, GUAN Yawen, LIAN Yifei. Ecological vulnerability assessment of Tarim Populus euphratica Forest Park based on SRP model[J].Arid Land Geography, 2025, 48(11): 2019-2030.

Figures/Tables 12

Fig. 1

Tab. 1

Tab. 2

Tab. 3

Tab. 4

Tab. 5

Interaction types"

依据	交互作用
$q X 1 ⋂ X 2 < m i n q X 1, q X 2$	非线性减弱
$m i n q X 1, q X 2 < q X 1 ⋂ X 2 < m a x q X 1, q X 2$	单因子非线性减弱
$q X 1 ⋂ X 2 > m a x q X 1, q X 2$	双因子增强
$q X 1 ⋂ X 2 = q X 1 + q X 2$	独立
$q X 1 ⋂ X 2 > q X 1 + q X 2$	非线性增强

Tab. 5

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

References 34

[1]	习近平. 高举中国特色社会主义伟大旗帜为全面建设社会主义现代化国家而团结奋斗[N]. 人民日报, 2022-10-26(001).
	[Xi Jinping. Hold high the great banner of socialism with Chinese characteristics and strive in unity to build a modern socialist country in all respects[N]. People’s Daily, 2022-10-26(001). ]
[2]	新华社. 中华人民共和国国民经济和社会发展第十四个五年规划和2035年远景目标纲要[EB/OL]. [2021-03-13]. https://www.gov.cn/xinwen/2021-03/13/content_5592681.htm.
	[Xinhua News Agency. Outline of the 14^th Five-Year Plan (2021—2025) for national economic and social development and the long-range objectives through the year 2035 of the People’s Republic of China[EB/OL]. [2021-03-13]. https://www.gov.cn/xinwen/2021-03/13/content_5592681.htm.]
[3]	李文生. 流域水资源承载力及水循环评价研究[D]. 大连: 大连理工大学, 2008.
	[Li Wensheng. Research on water resources carrying capacity and water cycle evaluation of river basin[D]. Dalian: Dalian University of Technology, 2008. ]
[4]	中华人民共和国自然资源部. 自然资源部资源环境承载能力和国土空间开发适宜性评价指南(试行)[EB/OL]. [2020-01-19]. https://gi.mnr.gov.cn/202001/t20200121_2498502.html.
	[Ministry of Natural Resources, People’s Republic of China. Ministry of Natural Resources guidelines for evaluating resource and environmental carrying capacity and suitability for territorial space development (trial implementation)[EB/OL]. [2020-01-19]. https://gi.mnr.gov.cn/202001/t20200121_2498502.html.]
[5]	国家林业和草原局. 北方防沙带生态保护和修复重大工程建设规划(2021—2035年)[EB/OL]. [2021-12-30]. https://www.forestry.gov.cn/main/5461/20220110/163049386831091.html.
	[National Forestry and Grassland Administration. Construction plan for major ecosystem protection and restoration projects in the northern sand prevention belts(2021—2035)[EB/OL]. [2021-12-30]. https://www.forestry.gov.cn/main/5461/20220110/163049386831091.html.]
[6]	Clements F C. Research methods in ecology[M]. Lincoln: University Publishing Corporation, 1905.
[7]	商彦蕊. 自然灾害综合研究的新进展——脆弱性研究[J]. 地域研究与开发, 2000(2): 73-77.
	[Shang Yanrui. Vulnerability study: The new development of synthetized study on natural disasters[J]. Areal Research and Development, 2000(2): 73-77. ]
[8]	Basak D, Bose A, Roy S, et al. Chapter 17-understanding the forest cover dynamics and its health status using GIS-based analytical hierarchy process: A study from Alipurduar District, west Bengal, India[M]. Science of Sustainable Systems, 2023, 1: 475-508.
[9]	Das U, Behera B. Geospatial assessment of ecological vulnerability of fragile eastern Duars forest integrating GIS-based AHP, CRITIC and AHP-TOPSIS models[J]. Geomatics, Natural Hazards and Risk, 2024, 15(1): 2330529, doi: 10.1080/19475705.2024.233-0529.
[10]	Venkatesh K, John R, Chen J, et al. Optimal ranges of social-environmental drivers and their impacts on vegetation dynamics in Kazakhstan[J]. Science of the Total Environment, 2022, 847: 157562, doi: 10.1016/j.scitotenv.2022.157562.
[11]	牛文元. 生态环境脆弱带ECOTONE的基础判定[J]. 生态学报, 1989, 9(2): 97-105.
	[Niu Wenyuan. The discriminatory index with regard to the weakness, overlapness, and breadth of ecotone[J]. Acta Ecological Sinica, 1989, 9(2): 97-105. ]
[12]	马丽莎, 郑江华, 彭建, 等. 新疆生态脆弱性特征及其驱动力[J]. 生态学报, 2024, 44(20): 9053-9066.
	[Ma Lisha, Zheng Jianghua, Peng Jian, et al. Research on the characteristics and driving forces of ecological vulnerability in Xinjiang[J]. Acta Ecologica Sinica, 2024, 44(20): 9053-9066. ]
[13]	陆海燕, 孙桂丽, 李路, 等. 基于VSD模型的新疆生态脆弱性评价[J]. 新疆农业科学, 2020, 57(2): 292-302. doi: 10.6048/j.issn.1001-4330.2020.02.010
	[Lu Haiyan, Sun Guili, Li Lu, et al. Ecological vulnerability assessment in Xinjiang based on VSD model[J]. Xinjiang Agricultural Sciences, 2020, 57(2): 292-302. ] doi: 10.6048/j.issn.1001-4330.2020.02.010
[14]	张学渊, 魏伟, 周亮, 等. 西北干旱区生态脆弱性时空演变分析[J]. 生态学报, 2021, 41(12): 4707-4719.
	[Zhang Xueyuan, Wei Wei, Zhou Liang, et al. Analysis on spatio-temporal evolution of ecological vulnerability in arid areas of northwest China[J]. Acta Ecologica Sinica, 2021, 41(12): 4707-4719. ]
[15]	王熙, 李建松, 刘权毅, 等. 基于SRP模型的新安江流域生态脆弱性评价[J]. 水生态学杂志, 2024, 45(2): 1-9.
	[Wang Xi, Li Jiansong, Liu Quanyi, et al. Evaluation of ecological vulnerability in Xin’anjiang River Basin based on SRP modelling[J]. Journal of Hydroecology, 2024, 45(2): 1-9. ]
[16]	包微, 黄晓军, 纪王迪. 关中地区高温脆弱性评估及其时空变化研究[J]. 干旱区地理, 2024, 47(11): 1863-1875. doi: 10.12118/j.issn.1000-6060.2023.691
	[Bao Wei, Huang Xiaojun, Ji Wangdi. Evaluation of heat vulnerability and its spatial-temporal variation in the Guanzhong area[J]. Arid Land Geography, 2024, 47(11): 1863-1875. ] doi: 10.12118/j.issn.1000-6060.2023.691
[17]	Wang Z Y, Xiong H X, Zhang F W, et al. Sustainable development assessment of ecological vulnerability in arid areas under the influence of multiple indicators[J]. Journal of Cleaner Production, 2024, 436: 140629, doi: 10.1016/j.jclepro.2024.140629.
[18]	岳笑, 张良侠, 周德成, 等. 干旱-半干旱典型生态脆弱区生态脆弱性时空演变及驱动因子分析[J]. 环境生态学, 2023, 5(6): 1-9, 14.
	[Yue Xiao, Zhang Liangxia, Zhou Decheng, et al. Spatial-temporal variations and driving forces of the ecological vulnerability in the typical arid/semi-arid ecologically vulnerable areas[J]. Environmental Ecology, 2023, 5(6): 1-9, 14. ]
[19]	王鑫. 干旱区内陆河流域生态环境脆弱性演变规律研究[D]. 郑州: 华北水利水电大学, 2023.
	[Wang Xin. Study on the evolution law of ecological vulnerability patterns of inland river basins in arid areas[D]. Zhengzhou: North China University of Water Resources and Electric Power, 2023. ]
[20]	李洪广, 周旭, 肖杨, 等. 基于SRP模型的西南喀斯特山区生态脆弱性时空变化特征[J]. 生态科学, 2021, 40(3): 238-246.
	[Li Hongguang, Zhou Xu, Xiao Yang, et al. Temporal and spatial changes of ecological vulnerability in southwestern karst mountains based on SRP model[J]. Ecological Science, 2021, 40(3): 238-246. ]
[21]	卓静, 胡皓, 何慧娟, 等. 陕北黄土高原生态脆弱性时空变异及驱动因素分析[J]. 干旱区地理, 2023, 46(11): 1768-1777. doi: 10.12118/j.issn.1000-6060.2023.027
	[Zhuo Jing, Hu Hao, He Huijuan, et al. Spatiotemporal variation and driving factors of ecological vulnerability in the Loess Plateau of northern Shaanxi[J]. Arid Land Geography, 2023, 46(11): 1768-1777. ] doi: 10.12118/j.issn.1000-6060.2023.027
[22]	Zhang J X, Li H Y, Cao E J, et al. Assessment of ecological vulnerability in multi-scale and its spatial correlation: A case study of Bailongjiang Watershed in Gansu Province, China[J]. The Journal of Applied Ecology, 2018, 29(9): 2897-2906.
[23]	刘佳茹. 2005—2018年祁连山生态脆弱性遥感评价研究[D]. 兰州: 西北师范大学, 2021.
	[Liu Jiaru. Remote sensing evaluation of ecological vulnerability in Qilian Mountains from 2005 to 2018[D]. Lanzhou: Northwest Normal University, 2021. ]
[24]	宋川, 武胜利, 韩炜, 等. 森林公园生态旅游开发分析与评价——以塔里木胡杨林公园为例[J]. 咸阳师范学院学报, 2021, 36(6): 52-58.
	[Song Chuan, Wu Shengli, Han Wei, et al. Analysis and evaluation of eco-tourism development in forest parks: A case study of Populus euphorbiae forest park in Tarim[J]. Journal of Xianyang Normal University, 2021, 36(6): 52-58. ]
[25]	王月健, 徐海量, 杨广. 塔里木河中游地区水土资源生态安全评价[J]. 西南大学学报(自然科学版), 2011, 33(11): 111-117.
	[Wang Yuejian, Xu Hailiang, Yang Guang. Ecological security assessment of land and water resources in the region of the middle reaches of the Tarim River[J]. Journal of Southwest University (Natural Science Edition), 2011, 33(11): 111-117. ]
[26]	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.
	[Jia Jingjing, Zhao Jun, Wang Jianbang, et al. Ecological vulnerability assessment of Shiyang River Basin based on SRP model[J]. Journal of Arid Land Resources and Environment, 2020, 34(1): 34-41. ]
[27]	孙桂丽, 陆海燕, 郑佳翔, 等. 新疆生态脆弱性时空演变及驱动力分析[J]. 干旱区研究, 2022, 39(1): 258-269. doi: 10.13866/j.azr.2022.01.25
	[Sun Guili, Lu Haiyan, Zheng Jiaxiang, et al. Spatio-temporal variation of ecological vulnerability in Xinjiang and driving force analysis[J]. Arid Zone Research, 2022, 39(1): 258-269. ] doi: 10.13866/j.azr.2022.01.25
[28]	邰苏日嘎拉, 王永亮, 陈国栋, 等. 基于SRP模型的内蒙古鄂伦春地区生态脆弱性评价[J]. 中国地质, 2024, 51(1): 234-247.
	[Tai Surigala, Wang Yongliang, Chen Guodong, et al. Ecological vulnerability assessment of Oroqen Region in the Inner Mongolia based on SRP model[J]. Geology in China, 2024, 51(1): 234-247. ]
[29]	王跃, 刘家福, 周林鹏, 等. 基于AHP-SPCA熵权模型的松花江流域生态脆弱性时空演变及预测[J]. 水土保持通报, 2023, 43(2): 212-219, 360.
	[Wang Yue, Liu Jiafu, Zhou Linpeng, et al. Temporal and spatial evolution and prediction of ecological vulnerability in Songhua River Basin based on AHP-SPCA entropy weig-ht model[J]. Bulletin of Soil and Water Conservation, 2023, 43(2): 212-219, 360. ]
[30]	刘艳琦. 乌兰布和沙漠生态环境要素时空演变与生态脆弱性研究[D]. 呼和浩特: 内蒙古农业大学, 2022.
	[Liu Yanqi. Spatial-temporal evolution and ecological vulnerability of ecological environmental factors in Ulan Buh Desert[D]. Hohhot: Inner Mongolia Agricultural University, 2022. ]
[31]	邓起泉. 基于熵值法—层次分析法的重庆市生态环境质量综合评价[D]. 重庆: 西南大学, 2022.
	[Deng Qiquan. Comprehensive evaluation of ecological environment quality in Chongqing based on entropy method and AHP[D]. Chongqing: Southwest University, 2022. ]
[32]	徐至真, 王建萍, 韩积斌. 基于SRP模型的柴达木盆地生态脆弱性评价[J]. 盐湖研究, 2024, 32(3): 53-60.
	[Xu Zhizhen, Wang Jianping, Han Jibin. Ecological vulnerability assessment of the Qaidam Basin based on SRP model[J]. Journal of Salt Lake Research, 2024, 32(3): 53-60. ] doi: 10.3724/j.yhyj.2024009
[33]	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. doi: 10.11821/dlxb201701010
	[Wang Jinfeng, Xu Chengdong. Geodetector: Principle and prospective[J]. Acta Geographica Sinica, 2017, 72(1): 116-134. ] doi: 10.11821/dlxb201701010
[34]	苏悦, 刘洪, 杨武年, 等. 高原山地区域生态脆弱性研究——以四川省康定市为例[J]. 自然资源遥感, 2024, 36(3): 206-215.
	[Su Yue, Liu Hong, Yang Wunian, et al. Ecological vulnerability of highland mountain areas: A case study of Kangding City, Sichuan Province[J]. Remote Sensing for Natural Resources, 2024, 36(3): 206-215. ]

数据名称	分辨率	数据来源
遥感影像	30 m	地理空间数据云（https://www.gscloud.cn/）
高程数据	30 m	欧洲航天局（https://www.esa.int/）
土地覆盖数据	30 m	中国科学院资源环境科学数据中心（https://www.resdc.cn/）
气象数据	1 km	中国科学院资源环境科学数据中心（https://www.resdc.cn/）
植被数据	30 m	中国科学院资源环境科学数据中心（https://www.resdc.cn/）
社会经济数据	1 km	中国科学院资源环境科学数据中心（https://www.resdc.cn/）
人口密度数据	1 km	WordPop（https://hub.worldpop.org/）
道路水系数据	-	开源地图数据库（https://www.openstreetmap.org）
森林生态系统数据	-	中国生态系统评估与生态安全格局数据库（http://www.ecosystem.csdb.cn）

目标层	标准层	特征层	指标	方向
生态脆弱性	敏感性	地形因子	高程	正向
			坡度	正向
			地形起伏度	正向
		地表因子	土地利用	定性
			沙漠化程度	正向
			水体变化程度	负向
		气象因子	年均降水量	负向
			年均气温	负向
			年均蒸发量	正向
	恢复力	活力因子	植被指数	负向
			植被生产力	负向
			水网密度	正向
		功能因子	生物多样性	负向
			水源涵养	负向
			水土保持	负向
	压力度	社会因子	人口密度	正向
			人均GDP	正向
			公路密度	正向

指标	层次分析法权重	熵权法权重	综合权重
高程	0.0130	0.0085	0.0107
坡度	0.0237	0.0516	0.0377
地形起伏度	0.0342	0.0268	0.0305
土地利用	0.1219	0.0460	0.0839
沙漠化程度	0.1219	0.0479	0.0849
水体变化程度	0.0151	0.3869	0.2010
年均降水量	0.0348	0.0132	0.0240
年均气温	0.0256	0.0133	0.0195
年均蒸发量	0.0480	0.0128	0.0304
植被指数	0.0847	0.0069	0.0458
植被生产力	0.1121	0.0072	0.0596
水网密度	0.0225	0.0082	0.0153
生物多样性	0.0686	0.0215	0.0450
水源涵养	0.0822	0.0363	0.0593
水土保持	0.0529	0.0089	0.0309
人口密度	0.0155	0.0946	0.0551
人均GDP	0.0109	0.0330	0.0219
公路密度	0.1124	0.1764	0.1444

等级	取值范围	生态特征
微度	[0.00, 0.22)	生态系统稳定，抗干扰能力及恢复能力强，生态脆弱性低
轻度	[0.22, 0.32)	生态系统较稳定，抗干扰能力及恢复能力较强，生态脆弱较性较低
中度	[0.32, 0.42)	生态系统较不稳定，抗干扰能力及恢复能力较弱，生态脆弱性较高
重度	[0.42, 0.55)	生态系统不稳定，抗干扰能力及恢复能力弱，生态脆弱性高
极度	[0.55, 1.00]	生态系统极不稳定，抗干扰能力及恢复能力差，生态脆弱性极高

Ecological vulnerability assessment of Tarim Populus euphratica Forest Park based on SRP model

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 12

References 34

Related Articles 15

Metrics

Comments

Recommended 0

[1]	WANG Xiaofei, PI Huawei, LI Sisi. Spatiotemporal characteristics and driving factors of soil wind erosion potential on the Qinghai-Xizang Plateau [J]. Arid Land Geography, 2025, 48(9): 1589-1599.
[2]	XIA Ziyang, XIA Yunfan, WANG Ning, LIN Wei, MA Lina, TAN Xiaoping, ZHANG Yanzhen, JIAO Rui. Spatial pattern and influencing factors of tourism elements in the urban agglomeration on the northern slope of Tianshan Mountains based on POI [J]. Arid Land Geography, 2025, 48(7): 1243-1254.
[3]	Wujisiguleng , Narisu , LI Na, YIN Shan, Wuyundalai , LI Mingxing, LAI Shaojie. Spatiotemporal pattern evolution of land desertification sensitivity in Hulun Buir grassland from 2001 to 2020 [J]. Arid Land Geography, 2025, 48(5): 825-837.
[4]	PANG Jiapeng, LI Mengyuan. Spatial differences and causes of tourism and leisure blocks in China [J]. Arid Land Geography, 2025, 48(5): 905-915.
[5]	HUANG Xueyu, XIU Lina, LU Zhixiang. Effects and driving factors of ecosystem service trade-offs in the Longdong Loess Plateau, China [J]. Arid Land Geography, 2025, 48(3): 480-493.
[6]	LIU Wei, LING Hongbo, GONG Yanming, CHEN Fulong, SHAN Qianjuan. Evaluation of ecological environment quality in the mainstream of Tarim River based on improved remote sensing ecological index [J]. Arid Land Geography, 2025, 48(2): 271-282.
[7]	LI Kangning, LIN Yilin, ZHAO Junsan, WANG Jian, GE Feng. Driving mechanisms of vegetation change and ecological vulnerability in the Three-River Headwater Region [J]. Arid Land Geography, 2025, 48(2): 283-295.
[8]	CHENG Yunjie, YANG Linjie. Spatial evolution and differences in driving factors of tourism dual circulation market efficiency in China [J]. Arid Land Geography, 2024, 47(9): 1606-1616.
[9]	ZHU Lei, LI Yannan, XU Jiahui, HU Jing, ZHU Fang, LIANG Mangmang. Spatial distribution pattern and causes of ice and snow tourism in China [J]. Arid Land Geography, 2024, 47(8): 1399-1410.
[10]	ZHANG Xiaodong, WU Dan, WANG Ying, ZHAO Yinxin, MA Yu, MA Yuxue, NI Hailing. Spatiotemporal evolution characteristics and influencing factors of habitat quality in Yinchuan City by coupling InVEST and Geodetector models [J]. Arid Land Geography, 2024, 47(7): 1242-1251.
[11]	ZHAO Xuechun, JU Chunyan. Coupling coordination relationship between park green spaces and urban functional spaces and its influencing factors: A case of Urumqi City [J]. Arid Land Geography, 2024, 47(5): 898-908.
[12]	LU Dongyan, ZHU Xiufang, TANG Mingxiu, GUO Chunhua, LIU Tingting. Assessment of drought risk changes in China under different temperature rise scenarios [J]. Arid Land Geography, 2024, 47(3): 369-379.
[13]	ZHOU Xiaoming, ZHANG Zhe, ZHANG Yue, WANG Yuning. TVDI-based analysis of drought and influencing factors in Turpan City in the last 20 years [J]. Arid Land Geography, 2024, 47(12): 2104-2114.
[14]	YANG Yu, SONG Futie, ZHANG Jie. Spatial structure characteristics and influencing factors of financial network of China based on geodetectors [J]. Arid Land Geography, 2023, 46(9): 1524-1535.
[15]	KONG Deming, HAO Lisha, XIA Siyou, LI Hongbo. Food security in the argo-pastoral ecotone of northern China from the perspective of grain yield [J]. Arid Land Geography, 2023, 46(5): 782-792.