Arid
DOI10.1016/j.ecolind.2021.107404
Driving factors of desertification in Qaidam Basin, China: An 18-year analysis using the geographic detector model
Han, Jinjun; Wang, Jianping; Chen, Liang; Xiang, Jiangyun; Ling, Zhiyong; Li, Qingkuan; Wang, Erlong
通讯作者Wang, JP (corresponding author), Chinese Acad Sci, Qinghai Inst Salt Lakes, Key Lab Comprehens & Highly Efficient Utilizat Sa, Xining 810008, Peoples R China. ; Wang, JP (corresponding author), Qinghai Prov Key Lab Geol & Environm Salt Lake, Xining 810008, Peoples R China.
来源期刊ECOLOGICAL INDICATORS
ISSN1470-160X
EISSN1872-7034
出版年2021
卷号124
英文摘要The Qaidam Basin is a cornucopia of salt mineral resources in China, but desertification in the basin has seriously impacted residents' lives and economic development. Comprehensive analyses of the spatial distribution characteristics of desertification and its driving factors will improve understanding of the causes of desertification. To explore these causes and related driving factors, we used the geographical detector model and geographical information system (GIS) techniques to quantify the relative importance and interactions of driving factors, including meteorological, environmental, and human factors. We found that desertification in the southern Kunlun Mountains, eastern Qilian Mountains, and front of the alluvial fan in the northern Kunlun Mountains was low. This was mainly due to the relatively abundant water resources in these areas. Desertification in the central and western Qaidam Basin was high primarily on account of the abnormally high evaporation. The power of determinant value showed that evaporation (0.481) had the strongest impact on desertification, followed by precipitation (0.460), vegetation type (0.360), soil type (0.293), and temperature (0.251). Evaporation has significantly positive effect on the level of desertification, and precipitation has significantly negative effect. Meteorological factors had the greatest impact on desertification, followed by environmental factors, whereas human factors were the least influential. Despite the small population in the basin and limited economic development, the impact of human activities on desertification cannot be ignored. Our results further indicated that the interactions between the driving factors could enhance the evaluation of desertification. This study comprehensively considered three types of impact factor and a total of nine driving factors. It also analyzed the spatial distribution characteristics and driving factors of desertification in the basin, which improved understanding of desertification in such arid and semi-arid regions in northwest China.
英文关键词Desertification Driving factors Qaidam Basin Geographical detector model Fractional vegetation cover (FVC)
类型Article
语种英语
开放获取类型gold
收录类别SCI-E
WOS记录号WOS:000624335600001
WOS类目Biodiversity Conservation ; Environmental Sciences
WOS研究方向Biodiversity & Conservation ; Environmental Sciences & Ecology
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/349995
作者单位[Han, Jinjun; Wang, Jianping; Chen, Liang; Xiang, Jiangyun; Ling, Zhiyong; Li, Qingkuan; Wang, Erlong] Chinese Acad Sci, Qinghai Inst Salt Lakes, Key Lab Comprehens & Highly Efficient Utilizat Sa, Xining 810008, Peoples R China; [Han, Jinjun; Wang, Jianping; Chen, Liang; Xiang, Jiangyun; Ling, Zhiyong; Li, Qingkuan; Wang, Erlong] Qinghai Prov Key Lab Geol & Environm Salt Lake, Xining 810008, Peoples R China; [Han, Jinjun; Xiang, Jiangyun; Wang, Erlong] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714
Han, Jinjun,Wang, Jianping,Chen, Liang,et al. Driving factors of desertification in Qaidam Basin, China: An 18-year analysis using the geographic detector model[J],2021,124.
APA Han, Jinjun.,Wang, Jianping.,Chen, Liang.,Xiang, Jiangyun.,Ling, Zhiyong.,...&Wang, Erlong.(2021).Driving factors of desertification in Qaidam Basin, China: An 18-year analysis using the geographic detector model.ECOLOGICAL INDICATORS,124.
MLA Han, Jinjun,et al."Driving factors of desertification in Qaidam Basin, China: An 18-year analysis using the geographic detector model".ECOLOGICAL INDICATORS 124(2021).
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