基于VSD的近20 a来浑善达克沙地生态脆弱性变化研究

doi:10.13866/j.azr.2021.05.29

摘要/Abstract

摘要：

如何协调区域社会经济和人口、资源环境发展,已成为生态环境建设面临的紧迫任务,识别特定地区的脆弱性则是实现有效生态系统管理的前提。以京津风沙源——浑善达克沙地为研究区,采用“暴露-敏感-适应”（VSD）模型建立评价指标体系,结合Moran’s I指数与主成分分析,对2000—2019年该沙地生态脆弱性进行评价和驱动机制分析。结果表明：浑善达克沙地生态脆弱性20 a间呈现增加的趋势;其生态脆弱性空间上呈集聚现象,表现为西部高-高聚集、东部低-低聚集的分布格局,且具有明显的空间相关性;生态脆弱性的时空分布的异质性是由不同程度的人类活动与气候因素的叠加效应造成的。该研究为浑善达克沙地的生态建设和生态恢复提供理论依据,并提出因地制宜的治理建议和措施。

关键词: 生态脆弱性, 时空格局, 驱动机制, 浑善达克沙地

Abstract:

The question of how to coordinate social and economic development, population growth, resource consumption, and environmental protection has become an urgent topic for regional sustainability development. Identifying the ecological vulnerability (EV) of specific areas is the precondition to achieving effective ecosystem management for sustainability. However, the driving forces of EV, including climate change, environmental protection policies, and land use, may change over a long period of time, affecting the spatio-temporal patterns of EV. Taking Otindag Sandy Land as the research area, we used the “Vulnerability Scoping Diagram” framework to establish the evaluation index system. Using Moran’s I index and principal component analysis (PCA), we evaluated the spatio-temporal distribution patterns of EV of this sandy land, and we also analyzed its driving mechanism from 2000 to 2019. The findings revealed that: (1) the EV of Otindag Sandy Land has exhibited an increasing trend over the past two decades; (2) the EV of this area presents an agglomeration distribution pattern with obvious spatial auto-correlation on spatial extent, in which the high-high cluster of EV is distributed in the western region, and the low-low cluster of EV is located in the eastern region; (3) the heterogeneity of the temporal and spatial distribution of EV is due to the synergistic effect of human activities and climate factors at different levels. According to the factor loadings matrix of PCA, after 2010 or 2015, the influence of indicators such as the population density, the number of livestock, and the per capita grassland area on the EV of this region has either weakened or been restrained by the implementation of ecological restoration projects and ecological policies. Meanwhile climate factors have gradually highlighted the leading role in driving EV in this region. This study provides a theoretical basis for the ecological construction and ecological restoration of Otindag Sandy Land, and puts forward some suggestions and measures for ecosystem management. At the regional level, from the perspective of future spatial planning, the EV in the eastern part of Otindag Sandy Land is mild to moderate, and ecological management measures should focus on harmonizing rational utilization of grassland resources with ecological protection. Meanwhile, the EV in the central and western regions of this area is severe to extreme, and it is thus necessary to strengthen ecological restoration projects and ecological migration to reduce grazing pressure on sandy land. At the local level, while comprehensively considering the demographic factors, pasture size, and grassland quality of herdsmen households, we should optimize grassland property rights and coordinate the interests of herdsmen with the goal of ecological conservation to achieve the fine administrative management “one household, one eco-management measures”.

Key words: ecological vulnerability, spatio-temporal pattern, driving forces, Otindag Sandy Land

陈臻琦,张靖,张贻龙,刘睿. 基于VSD的近20 a来浑善达克沙地生态脆弱性变化研究[J]. 干旱区研究, 2021, 38(5): 1464-1473.

CHEN Zhenqi,ZHANG Jing,ZHANG Yilong,LIU Rui. Spatio-temporal patterns variation of ecological vulnerability in Otindag Sandy Land based on a vulnerability scoping diagram[J]. Arid Zone Research, 2021, 38(5): 1464-1473.

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目标层（权重）	要素层（权重）	指标层^a	指标方向	指标权重
暴露度（0.4934）	B1人口社会压力（0.2470）	人口密度/（人·km^-2）	+	0.0384
		人均草地面积/（km²·人^-1）	-	0.0488
		牲畜数量/（头·km^-2）	+	0.1598
	B2干旱灾害（0.2465）	地温/℃	+	0.0156
		年降水变化率/（mm·a^-1）	+	0.1027
		生长季降水间隔/d	+	0.1112
		极端最高温天数/d	+	0.0170
敏感性（0.3108）	B3植被覆盖（0.1726）	NDVI	-	0.0940
		景观多样性	-	0.0245
		景观破碎度	+	0.0541
	B4气候（0.1382）	年均降水量/mm	-	0.1382
适应能力（0.1958）	B5自我调节（0.1958）	NPP/（g·m^-2·a^-1）	-	0.1305
适应能力（0.1958）	B5自我调节（0.1958）	NDVI变化率	+	0.0653

土地利用类型（2019年面积比）	2000年	2005年	2010年	2015年	2019年	平均值
耕地（3.18%）	0.377	0.356	0.447	0.424	0.425	0.406
林地（0.83%）	0.375	0.363	0.430	0.413	0.419	0.400
草地（77.96%）	0.407	0.412	0.469	0.463	0.498	0.450
水域（1.69%）	0.419	0.437	0.482	0.470	0.521	0.466
居民工矿用地（0.31%）	0.386	0.371	0.455	0.435	0.446	0.419
未利用土地（16.03%）	0.410	0.417	0.472	0.469	0.508	0.455

评价指标	2000年		2005年		2010年		2015年		2019年
评价指标	PC1	PC2	PC1	PC2	PC1	PC2	PC1	PC2	PC1	PC2
人口密度	0.76		0.77
人均草地面积			0.86				0.71
牲畜数量	0.84		0.90		0.81
地温			0.79		0.77		0.81		0.80
年降水变化率			0.90						0.91
生长季降水间隔	0.92		0.93		0.89		0.93		0.94
极端最高温天数	0.84				0.92		0.87		0.82
NDVI	0.83		0.84		0.85		0.87		0.85
景观多样性		-0.71		-0.79
景观破碎度
年均降水	0.96		0.96		0.96		0.95		0.95
NPP			0.88		0.85		0.87		0.83
NDVI变化率
贡献率/%	51.62	10.46	59.33	9.76	54.14	10.94	53.73	10.74	53.86	11.01