Enhancing ecological sustainability in ion-adsorption rare earth mining areas: A multi-scale model for assessing spatiotemporal dynamics and ecological resilience

IF 2.6 3区 环境科学与生态学 Q2 ECOLOGY
Yaoyao Jiang , Hengkai Li , Zhiwei Zhang , Guogang Ren , Jianying Zhang
{"title":"Enhancing ecological sustainability in ion-adsorption rare earth mining areas: A multi-scale model for assessing spatiotemporal dynamics and ecological resilience","authors":"Yaoyao Jiang ,&nbsp;Hengkai Li ,&nbsp;Zhiwei Zhang ,&nbsp;Guogang Ren ,&nbsp;Jianying Zhang","doi":"10.1016/j.ecolmodel.2025.111038","DOIUrl":null,"url":null,"abstract":"<div><div>With the increasing global demand for Rare Earth (RE) resources, ionic RE deposits, characterized by a high concentration of medium and heavy RE elements, have become critical to strategic resource planning. These deposits are primarily located in southern China's hilly and mountainous regions, where RE elements are adsorbed onto clay minerals in an ionic state. The deposits are small, scattered, and predominantly mined through solution leaching, a method effective for resource extraction but with severe ecological repercussions, including soil, vegetation, and water degradation. Currently, quantitative assessment methods for evaluating the Ecological carrying capacity (ECC) of ionic RE mining areas on a regional scale remain limited. To address this gap, this paper presents an ECC evaluation model based on the Driver-Pressure-State-Impact-Response (DPSIR) framework, tailored specifically for ionic RE mining areas. Twenty-two ecological indicators were selected to capture the unique environmental conditions of these sites, forming a comprehensive ECC evaluation model applicable to ion-adsorbed RE mining areas. Using Lingbei in Dingnan County, China, as a case study, we conducted a long-term dynamic analysis of the mining area's ECC and employed geospatial analysis to identify the key drivers and their multidimensional interactions across various periods, examining the evolution patterns of critical ecological factors. The results reveal that: (1) from 2000 to 2020, the ECC of the Lingbei RE mining area exhibited a general trend of initial decline followed by improvement. From 2000 to 2010, ECC consistently declined, with moderate ECC zones shifting to poor categories. Since 2010, however, ECC has gradually improved, with the poor ECC zones recovering to moderate levels by 2020. (2) Throughout 2000–2020, vegetation cover (S1) was consistently the primary driver of ECC in the mining area. Early-stage ecological degradation was driven primarily by vegetation loss and desertification (P3), with additional impacts from climatic factors such as surface heat (D3) and precipitation (D5). After 2010, vegetation recovery contributed to improved ECC, while pressures from desertification and climate stress eased. Contributions from biodiversity (S4) and soil organic matter (S3) also increased, and interactions between any two factors had a significantly greater effect on ECC than single factors alone. This study highlights the critical role of vegetation recovery and environmental interactions in improving the ECC of ionic RE mining areas. The findings provide insights into key drivers and pressures, offering guidance for mitigating environmental degradation and promoting sustainable development in RE mining regions.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"502 ","pages":"Article 111038"},"PeriodicalIF":2.6000,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Modelling","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0304380025000249","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

With the increasing global demand for Rare Earth (RE) resources, ionic RE deposits, characterized by a high concentration of medium and heavy RE elements, have become critical to strategic resource planning. These deposits are primarily located in southern China's hilly and mountainous regions, where RE elements are adsorbed onto clay minerals in an ionic state. The deposits are small, scattered, and predominantly mined through solution leaching, a method effective for resource extraction but with severe ecological repercussions, including soil, vegetation, and water degradation. Currently, quantitative assessment methods for evaluating the Ecological carrying capacity (ECC) of ionic RE mining areas on a regional scale remain limited. To address this gap, this paper presents an ECC evaluation model based on the Driver-Pressure-State-Impact-Response (DPSIR) framework, tailored specifically for ionic RE mining areas. Twenty-two ecological indicators were selected to capture the unique environmental conditions of these sites, forming a comprehensive ECC evaluation model applicable to ion-adsorbed RE mining areas. Using Lingbei in Dingnan County, China, as a case study, we conducted a long-term dynamic analysis of the mining area's ECC and employed geospatial analysis to identify the key drivers and their multidimensional interactions across various periods, examining the evolution patterns of critical ecological factors. The results reveal that: (1) from 2000 to 2020, the ECC of the Lingbei RE mining area exhibited a general trend of initial decline followed by improvement. From 2000 to 2010, ECC consistently declined, with moderate ECC zones shifting to poor categories. Since 2010, however, ECC has gradually improved, with the poor ECC zones recovering to moderate levels by 2020. (2) Throughout 2000–2020, vegetation cover (S1) was consistently the primary driver of ECC in the mining area. Early-stage ecological degradation was driven primarily by vegetation loss and desertification (P3), with additional impacts from climatic factors such as surface heat (D3) and precipitation (D5). After 2010, vegetation recovery contributed to improved ECC, while pressures from desertification and climate stress eased. Contributions from biodiversity (S4) and soil organic matter (S3) also increased, and interactions between any two factors had a significantly greater effect on ECC than single factors alone. This study highlights the critical role of vegetation recovery and environmental interactions in improving the ECC of ionic RE mining areas. The findings provide insights into key drivers and pressures, offering guidance for mitigating environmental degradation and promoting sustainable development in RE mining regions.
求助全文
约1分钟内获得全文 求助全文
来源期刊
Ecological Modelling
Ecological Modelling 环境科学-生态学
CiteScore
5.60
自引率
6.50%
发文量
259
审稿时长
69 days
期刊介绍: The journal is concerned with the use of mathematical models and systems analysis for the description of ecological processes and for the sustainable management of resources. Human activity and well-being are dependent on and integrated with the functioning of ecosystems and the services they provide. We aim to understand these basic ecosystem functions using mathematical and conceptual modelling, systems analysis, thermodynamics, computer simulations, and ecological theory. This leads to a preference for process-based models embedded in theory with explicit causative agents as opposed to strictly statistical or correlative descriptions. These modelling methods can be applied to a wide spectrum of issues ranging from basic ecology to human ecology to socio-ecological systems. The journal welcomes research articles, short communications, review articles, letters to the editor, book reviews, and other communications. The journal also supports the activities of the [International Society of Ecological Modelling (ISEM)](http://www.isemna.org/).
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信