半干旱区湖盆景观格局脆弱性及其影响因素——以凉城县为例
收稿日期: 2022-01-26
修回日期: 2022-03-04
网络出版日期: 2022-09-26
基金资助
第二次青藏高原综合科学考察研究项目(2019QZKK0603)
Landscape pattern vulnerability and its influencing factors on a semi-arid lake basin: A case study of Liangcheng County
Received date: 2022-01-26
Revised date: 2022-03-04
Online published: 2022-09-26
基于1980—2020年6期景观类型数据,分析了凉城县湖盆景观及其变化过程;利用景观敏感度指数和景观适应度指数构建了一种景观脆弱性综合指数,分析了县域景观格局脆弱性时空分异及其影响因素。研究表明：（1） 近40 a来凉城县景观类型变化差异明显。除未利用地外,1980—1995年耕地、林地及草地动态度最大,1995—2010年各景观类型动态度均较大,2010—2020年水域、建设用地动态度最大。（2） 1980—2020年全县景观格局脆弱性均以中、较高为主,面积达到70%以上,高值区集中分布在凉城中部和东南部,低值区位于岱海及其北部;景观脆弱性综合指数呈先下降后升高再下降趋势,区域生态环境开始好转。（3） 研究区生态环境脆弱性在不同景观类型、地形上差异显著。零散分布的林、草地脆弱性较高,水域最低;海拔<1300 m、坡度<5°的区域景观格局脆弱性最低,海拔1700~1900 m、坡度25°~40°区域的最高。（4） 总人口数、水域面积和耕地面积是湖盆景观格局脆弱性的主要影响因子;相对气候因子,人类活动对研究区生态环境的影响更大。因此,优化景观结构、减少过度扰动、保护水资源及水环境等,是降低凉城景观格局脆弱性和强化生态保护建设的主要手段。
关键词： 湖盆景观; 景观格局脆弱性; 景观格局脆弱性综合指数; 影响因素; 凉城县
张云霞,张金茜,巩杰 . 半干旱区湖盆景观格局脆弱性及其影响因素——以凉城县为例[J]. 干旱区研究, 2022 , 39(4) : 1259 -1269 . DOI: 10.13866/j.azr.2022.04.26
Research on landscape spatiotemporal variation and its pattern vulnerability can provide a scientific basis for regional landscape optimization and ecological protection. Based on six periods of landscape type data from 1980 to 2020, this paper analyzes the lake basin landscape and its variation process in Liangcheng County. Moreover, a comprehensive evaluation index of landscape vulnerability is constructed by using landscape sensitivity and adaptability indexes to analyze the spatiotemporal differentiation characteristics and influencing factors of landscape pattern vulnerability in the entire county. The main findings are listed below. (1) The landscape types of Liangcheng County have significantly changed over the past 40 years. Except for the unused land, the dynamic degree of cultivated land, forestland, and grassland from 1980 to 1995, that of each landscape type from 1995 to 2010, and that of waters and construction land from 2010 to 2020 are the largest, which indirectly reflects the life and production modes of the study area in different periods. (2) The landscape pattern vulnerability was mainly medium and high-grade with an area of more than 70% in Liangcheng Country from 1980 to 2020. The areas of high landscape pattern vulnerability were mainly concentrated in the central and southeast of Liangcheng, and the low-value areas were located in the Daihai and its northern parts. The landscape vulnerability integrated index generally decreased first; this index then increased and finally decreased. Moreover, the spatial aggregation increased, indicating that the ecological environment began to improve. (3) The vulnerability of ecological environments is significantly different in various landscape types and topographies in the study area. Forestland and grassland have more higher vulnerability and water has the lowest vulnerability among all landscape types. The landscape pattern vulnerability is the lowest in the area with an altitude of <1300 m and a slope of <5° and the highest with an altitude of 1700-1900 m and a slope of 25°-40° on different altitudes and slopes. (4) The gray correlation analysis revealed that the population, water area, and farmland area are the leading factors that affected the landscape pattern vulnerability, indicating that human activities significantly impacted the ecological environment more than climatic factors in the study area. Optimizing landscape structure, reducing excessive disturbance, and protecting water resources and their environment are the primary ways to reduce the vulnerability of landscape patterns and ecological protection in Liangcheng Country.
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