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Assessment and Driving Factors of Desertification Vulnerability in the Mu Us Sandy Land,China:A MEDALUS-Based Approach
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作者 Yu Ren Xidong Chen 《Journal of Environmental & Earth Sciences》 2025年第6期213-226,共14页
As a major worldwide issue,desertification poses significant threats to ecosystem stability and long-term socioeconomic growth.Within China,the Mu Us Sandy land represents a crucial region for studying desertification... As a major worldwide issue,desertification poses significant threats to ecosystem stability and long-term socioeconomic growth.Within China,the Mu Us Sandy land represents a crucial region for studying desertification phenomena.Comprehending how desertification risks are distributed spatially and what mechanisms drive them remains fundamental for implementing effective strategies in land management and risk mitigation.Our research evaluated desertification vulnerability across the Mu Us Sandy land by applying the MEDALUS model,while investigating causal factors via geographical detector methodology.Findings indicated that territories with high desertification vulnerability extend across 71,401.7 km^(2),constituting 76.87%of the entire region,while zones facing extreme desertification hazard cover 20,578.9 km^(2)(22.16%),primarily concentrated in a band-like pattern along the western boundary of the Mu Us Sandy land.Among the four primary indicators,management quality emerged as the most significant driver of desertification susceptibility,followed by vegetation quality and soil quality.Additionally,drought resistance,land use intensity,and erosion protection were identified as the key factors driving desertification sensitivity.The investigation offers significant theoretical perspectives that can guide the formulation of enhanced strategies for controlling desertification and promoting sustainable land resource utilization within the Mu Us Sandy land region. 展开更多
关键词 Desertification Risk MEDALUS geographical Detector Method Driving Factors
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Spatial association between landslides and environmental factors over Guizhou Karst Plateau,China 被引量:2
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作者 YUE Xi-liu WU Shao-hong +4 位作者 HUANG Mei GAO Jiang-bo YIN Yun-he FENG Ai-qing GU Xiao-ping 《Journal of Mountain Science》 SCIE CSCD 2018年第9期1987-2000,共14页
Guizhou Karst Plateau is located at the center of the karst region in Asia,where landslides are a typical disaster.Affected by the local karst environment,the landslides in this region have their own characteristics.I... Guizhou Karst Plateau is located at the center of the karst region in Asia,where landslides are a typical disaster.Affected by the local karst environment,the landslides in this region have their own characteristics.In this study,3975 landslide records from inventories of the Guizhou karst plateau are studied.The geographical detector method is used to detect the dominant casual factor and predominant multi-factor combinations for the local landslides.The results show that landslides are prone to areas on slopes between 10°and 35°,of clay rock,in close proximity to gullies,and especially in areas of moderate vegetation,dryland,and mild rocky desertification.Continuous precipitation over 10 days has a great effect on landslide occurrence.Compared with the individual factors,the impact of two-factor interaction has greater explanatory power for landslide volume.The volume of earthquake-induced landslides is predominantly controlled by the interactions of faults and slopes,while that of humaninduced landslides is affected by the interactions of land cover and hydrological conditions.For rainfallinduced landslides,the dominant interactions vary in different regions.In the central karst basin,the interactions between faults and precipitation can explain over 90%of the variations in landslide volumes.In the southern hilly karst region,the interactions between lithology and slope can explain over 71%of the variations in landslide volume and those between fault and land-use can explain 50%of the variations of the landslide volumes in the northeastern mountainous karst region. 展开更多
关键词 LANDSLIDES KARST Combined impact geographical detector method Environmental factor GUIZHOU
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