{"title":"基于改进MEDALUS - ESA模型和最优地理探测器的科尔沁沙地沙漠化敏感性多维分析","authors":"Beiying Huang , Hanchen Duan , Wanying Cao","doi":"10.1016/j.ecolind.2025.113847","DOIUrl":null,"url":null,"abstract":"<div><div>Desertification is a global ecological and environmental problem that seriously threatens ecosystems and regional socioeconomic development. Focusing on the Horqin Sandy Land in Northeast China, this study constructs and optimizes a land desertification sensitivity index system via the improved MEDALUS − EAS model. It covers five quality indices: soil, climate, vegetation, land management, and socio-economy. The analytic hierarchy process (AHP) determines factor weights. We analyzed the dynamic changes in desertification sensitivity from 2000 − 2020and used the optimal parameter geographical detector for the driving factors. The findings show that the vegetation quality index has the highest weight (0.4197), followed by the climate (0.3319) and soil (0.1309) indices, with lower weights for land management (0.0674) and the socioeconomic index (0.0502). The Horqin Sandy Land’s desertification sensitivity index ranged from 0.0695 to 1.0034 from 2000 − 2020, reversing this trend. The proportions of extremely, highly, and moderately sensitive areas decreased, whereas the proportions of slightly sensitive and nonsensitive areas stabilized or increased. Spatial differentiation detection indicates that net primary productivity (NPP) and vegetation coverage are the main drivers of significant interactive enhancement. Spatiotemporal change detection reveals that vegetation coverage and wind speed dominate the evolution of sensitivity, with strong interactions. Multifactor consideration is key for accurate assessment, offering important references for regional ecological governance.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"178 ","pages":"Article 113847"},"PeriodicalIF":7.0000,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multidimensional analysis of desertification sensitivity in the horqin sandy land based on an improved MEDALUS − ESA model and an optimal geographical detector\",\"authors\":\"Beiying Huang , Hanchen Duan , Wanying Cao\",\"doi\":\"10.1016/j.ecolind.2025.113847\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Desertification is a global ecological and environmental problem that seriously threatens ecosystems and regional socioeconomic development. Focusing on the Horqin Sandy Land in Northeast China, this study constructs and optimizes a land desertification sensitivity index system via the improved MEDALUS − EAS model. It covers five quality indices: soil, climate, vegetation, land management, and socio-economy. The analytic hierarchy process (AHP) determines factor weights. We analyzed the dynamic changes in desertification sensitivity from 2000 − 2020and used the optimal parameter geographical detector for the driving factors. The findings show that the vegetation quality index has the highest weight (0.4197), followed by the climate (0.3319) and soil (0.1309) indices, with lower weights for land management (0.0674) and the socioeconomic index (0.0502). The Horqin Sandy Land’s desertification sensitivity index ranged from 0.0695 to 1.0034 from 2000 − 2020, reversing this trend. The proportions of extremely, highly, and moderately sensitive areas decreased, whereas the proportions of slightly sensitive and nonsensitive areas stabilized or increased. Spatial differentiation detection indicates that net primary productivity (NPP) and vegetation coverage are the main drivers of significant interactive enhancement. Spatiotemporal change detection reveals that vegetation coverage and wind speed dominate the evolution of sensitivity, with strong interactions. Multifactor consideration is key for accurate assessment, offering important references for regional ecological governance.</div></div>\",\"PeriodicalId\":11459,\"journal\":{\"name\":\"Ecological Indicators\",\"volume\":\"178 \",\"pages\":\"Article 113847\"},\"PeriodicalIF\":7.0000,\"publicationDate\":\"2025-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ecological Indicators\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1470160X25007770\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Indicators","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1470160X25007770","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Multidimensional analysis of desertification sensitivity in the horqin sandy land based on an improved MEDALUS − ESA model and an optimal geographical detector
Desertification is a global ecological and environmental problem that seriously threatens ecosystems and regional socioeconomic development. Focusing on the Horqin Sandy Land in Northeast China, this study constructs and optimizes a land desertification sensitivity index system via the improved MEDALUS − EAS model. It covers five quality indices: soil, climate, vegetation, land management, and socio-economy. The analytic hierarchy process (AHP) determines factor weights. We analyzed the dynamic changes in desertification sensitivity from 2000 − 2020and used the optimal parameter geographical detector for the driving factors. The findings show that the vegetation quality index has the highest weight (0.4197), followed by the climate (0.3319) and soil (0.1309) indices, with lower weights for land management (0.0674) and the socioeconomic index (0.0502). The Horqin Sandy Land’s desertification sensitivity index ranged from 0.0695 to 1.0034 from 2000 − 2020, reversing this trend. The proportions of extremely, highly, and moderately sensitive areas decreased, whereas the proportions of slightly sensitive and nonsensitive areas stabilized or increased. Spatial differentiation detection indicates that net primary productivity (NPP) and vegetation coverage are the main drivers of significant interactive enhancement. Spatiotemporal change detection reveals that vegetation coverage and wind speed dominate the evolution of sensitivity, with strong interactions. Multifactor consideration is key for accurate assessment, offering important references for regional ecological governance.
期刊介绍:
The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published.
• All aspects of ecological and environmental indicators and indices.
• New indicators, and new approaches and methods for indicator development, testing and use.
• Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources.
• Analysis and research of resource, system- and scale-specific indicators.
• Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs.
• How research indicators can be transformed into direct application for management purposes.
• Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators.
• Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.