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