{"title":"牧场时空趋势的特征和建模:埃塞俄比亚阿瓦什盆地中部的鹅掌楸影响。","authors":"Kalid Hassen Yasin","doi":"10.1016/j.jenvman.2024.123336","DOIUrl":null,"url":null,"abstract":"<p><p>The Middle Awash Basin (MAB) faces severe ecological degradation due to the rapid spread of the invasive Prosopis juliflora (P. juliflora), which threatens native vegetation. The study characterizes and predicts the spatiotemporal dynamics of rangelands affected by P. juliflora in the MAB. Using three Landsat images from ETM+ (2003) and OLI (2013 and 2023), we applied a supervised random forest (RF) classification technique processed on the Google Earth Engine (GEE) platform. This classification was integrated into an intensity analysis to examine temporal transitions between land use and land cover (LULC) classes. The predictive modeling included 12 variables, including climatic, topographic, edaphic, phenological, hydrological, and anthropogenic factors, using Terrset 2020. Using multitemporal satellite remote sensing, machine learning (ML), and cellular automata markov chain (CA-MC) methods, LULC was mapped from 2003 to 2023, and future scenarios were predicted up to 2060. The P. juliflora coverage quadrupled from 2.16% in 2003 to 8.61% in 2023, while rangelands were decreased by more than 25%. Models predict that P. juliflora could occupy 22% of the land by 2060 and over 40% of rangeland areas as of 2003, expanding two to three times faster than the intensities of the LULC baseline changes, primarily targeting rangelands. Our analysis is based on a single business-as-usual scenario; however, it highlights the worrying invasion patterns. The study's limitations include the absence of multiple scenarios and climate model integration, which could offer further insights into future invasion dynamics. Nonetheless, our findings indicate that the MAB faces imminent widespread ecosystem transformation without prompt action, which will severely affect pastoral livelihoods and biodiversity conservation. Therefore, we advocate for a management strategy involving prevention, eradication, and restoration measures, underpinned by policy reforms and stakeholder cooperation.</p>","PeriodicalId":356,"journal":{"name":"Journal of Environmental Management","volume":"371 ","pages":"123336"},"PeriodicalIF":8.0000,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Characterizing and modeling spatiotemporal trends in rangelands: Prosopis juliflora impact in middle Awash Basin, Ethiopia.\",\"authors\":\"Kalid Hassen Yasin\",\"doi\":\"10.1016/j.jenvman.2024.123336\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The Middle Awash Basin (MAB) faces severe ecological degradation due to the rapid spread of the invasive Prosopis juliflora (P. juliflora), which threatens native vegetation. The study characterizes and predicts the spatiotemporal dynamics of rangelands affected by P. juliflora in the MAB. Using three Landsat images from ETM+ (2003) and OLI (2013 and 2023), we applied a supervised random forest (RF) classification technique processed on the Google Earth Engine (GEE) platform. This classification was integrated into an intensity analysis to examine temporal transitions between land use and land cover (LULC) classes. The predictive modeling included 12 variables, including climatic, topographic, edaphic, phenological, hydrological, and anthropogenic factors, using Terrset 2020. Using multitemporal satellite remote sensing, machine learning (ML), and cellular automata markov chain (CA-MC) methods, LULC was mapped from 2003 to 2023, and future scenarios were predicted up to 2060. The P. juliflora coverage quadrupled from 2.16% in 2003 to 8.61% in 2023, while rangelands were decreased by more than 25%. Models predict that P. juliflora could occupy 22% of the land by 2060 and over 40% of rangeland areas as of 2003, expanding two to three times faster than the intensities of the LULC baseline changes, primarily targeting rangelands. Our analysis is based on a single business-as-usual scenario; however, it highlights the worrying invasion patterns. The study's limitations include the absence of multiple scenarios and climate model integration, which could offer further insights into future invasion dynamics. Nonetheless, our findings indicate that the MAB faces imminent widespread ecosystem transformation without prompt action, which will severely affect pastoral livelihoods and biodiversity conservation. Therefore, we advocate for a management strategy involving prevention, eradication, and restoration measures, underpinned by policy reforms and stakeholder cooperation.</p>\",\"PeriodicalId\":356,\"journal\":{\"name\":\"Journal of Environmental Management\",\"volume\":\"371 \",\"pages\":\"123336\"},\"PeriodicalIF\":8.0000,\"publicationDate\":\"2024-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Environmental Management\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1016/j.jenvman.2024.123336\",\"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":"Journal of Environmental Management","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1016/j.jenvman.2024.123336","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}
Characterizing and modeling spatiotemporal trends in rangelands: Prosopis juliflora impact in middle Awash Basin, Ethiopia.
The Middle Awash Basin (MAB) faces severe ecological degradation due to the rapid spread of the invasive Prosopis juliflora (P. juliflora), which threatens native vegetation. The study characterizes and predicts the spatiotemporal dynamics of rangelands affected by P. juliflora in the MAB. Using three Landsat images from ETM+ (2003) and OLI (2013 and 2023), we applied a supervised random forest (RF) classification technique processed on the Google Earth Engine (GEE) platform. This classification was integrated into an intensity analysis to examine temporal transitions between land use and land cover (LULC) classes. The predictive modeling included 12 variables, including climatic, topographic, edaphic, phenological, hydrological, and anthropogenic factors, using Terrset 2020. Using multitemporal satellite remote sensing, machine learning (ML), and cellular automata markov chain (CA-MC) methods, LULC was mapped from 2003 to 2023, and future scenarios were predicted up to 2060. The P. juliflora coverage quadrupled from 2.16% in 2003 to 8.61% in 2023, while rangelands were decreased by more than 25%. Models predict that P. juliflora could occupy 22% of the land by 2060 and over 40% of rangeland areas as of 2003, expanding two to three times faster than the intensities of the LULC baseline changes, primarily targeting rangelands. Our analysis is based on a single business-as-usual scenario; however, it highlights the worrying invasion patterns. The study's limitations include the absence of multiple scenarios and climate model integration, which could offer further insights into future invasion dynamics. Nonetheless, our findings indicate that the MAB faces imminent widespread ecosystem transformation without prompt action, which will severely affect pastoral livelihoods and biodiversity conservation. Therefore, we advocate for a management strategy involving prevention, eradication, and restoration measures, underpinned by policy reforms and stakeholder cooperation.
期刊介绍:
The Journal of Environmental Management is a journal for the publication of peer reviewed, original research for all aspects of management and the managed use of the environment, both natural and man-made.Critical review articles are also welcome; submission of these is strongly encouraged.