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

摘要/Abstract

摘要： 生态脆弱性评价是区域发展规划和生态治理修复的基础。基于遥感数据和社会经济统计数据，引入生态系统服务价值中的生态功能指标，选取18个评价指标，利用敏感性-恢复力-压力度（SRP）模型构建生态脆弱性评价指标体系，结合层次分析-熵权法，揭示2000—2020年塔里木胡杨林公园生态脆弱性时空演变特征与驱动因素。结果表明：（1）2020年塔里木胡杨林公园生态脆弱性指数均值为0.30，生态脆弱性整体处于轻度水平，具体呈“东、西部边缘和中部高，东南部低”的分布特征。（2）2000、2010、2015年和2020年塔里木胡杨林公园生态脆弱性指数分别为0.33、0.47、0.29和0.30，生态脆弱性呈波动下降趋势，具体表现为“显著恶化-逐步改善-再度退化”，其中生态脆弱性等级下降区域占44.52%，等级上升区域占28.60%。（3）2000—2020年塔里木胡杨林公园生态脆弱性的全局莫兰指数均大于0，Z值大于2.58，P值小于0.01，说明公园生态脆弱性具有显著空间正相关性，以低-低聚集和高-高聚集为主。（4）单因子指标中水体变化程度、沙漠化程度、水源涵养和植被指数是塔里木胡杨林公园生态脆弱性的主要驱动力。各因子间交互作用呈非线性增强和双因子增强关系，其中水体变化程度与水源涵养的协同效应对公园生态脆弱性驱动力最大。研究结果可为塔里木胡杨林公园生态环境的修复保护和可持续发展提供科学参考。

关键词: 生态脆弱性, 敏感性-恢复力-压力度模型, 层次分析-熵权法, 地理探测器, 塔里木胡杨林公园

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

林墨飞, 关雅文, 连艺霏. 基于SRP模型的塔里木胡杨林公园生态脆弱性研究[J]. 干旱区地理, 2025, 48(11): 2019-2030.

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.

图/表 12

图1

表1

表2

表3

表4

表5

交互作用类型"

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

表5

图2

图3

图4

图5

图6

图7

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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