Restoration Of Mining Areas Research Articles

Biochar Organic Fertilizer Combined with Indigenous Microorganisms Enhances the Growth of Landscape Grass Cultivated in a Substrate Mixed with Iron Tailings and Mining Topsoil

Iron tailings from the mining process occupy vast land areas and pose a significant ecological risk. In order to reuse iron tailings resources and carry out in situ ecological restoration of a mine, in this study, a medium of mixed iron tailings and mining topsoil (m:m = 3:1) was used to plant landscape grasses, including Lolium perenne L. (L. perenne), Pennisetum alopecuroides (L.) Spreng. (P. alopecuroides), Melilotus officinalis (L.) Lam. (M. officinalis), and Medicago sativa L. (M. sativa). Biochar and chicken manure were used as biochar organic fertilizers and indigenous microorganisms were isolated from the rhizosphere soil of tested grasses. They were applied to enhance landscape grass growth by regulating rhizosphere microbial communities and nutrient conditions. The results showed that the biochar organic fertilizers significantly promoted the growth of the four landscape grasses, notably P. alopecuroides, increasing plant height, root length, root weight, and leaf fresh weight by 169%, 60%, 211%, and 388%, respectively. Additionally, L. perenne exhibited the greatest height increase (10%) following the application of bacterial solutions. Moreover, indigenous bacterial solutions enhanced chlorophyll content and phenylalanine ammonia-lyase (PAL) activity, with P. alopecuroides showing the highest chlorophyll increase of 58% and M. sativa exhibiting a 30.58% rise in PAL activity. The biochar organic fertilizer also significantly elevated soluble protein content in P. alopecuroides and M. sativa by 195% and 152%, respectively. It also effectively enhanced peroxidase (POD) activity in Poaceae grasses by 120% to 160%. After adding indigenous microorganisms, the rhizosphere soil of the landscape grass showed the highest Shannon–Wiener diversity index, reaching 3.561. The rhizosphere soil of M. officinalis had the highest microbial richness, with a value of 39. Additionally, the addition of indigenous microorganisms increased the nitrogen, phosphorus, and potassium content of the four plants by 8–19%, 6–14%, and 8–18%, respectively. This study offers a new approach for managing mining waste and ecological restoration in mining areas.

Assessing the true value of ecological restoration in mining areas: An input-output approach based on ecosystem service valuation

Historical unsustainable mining activities have led to significant ecological degradation, emphasizing the importance and urgency of ecological restoration and its effectiveness assessment. This study evaluates the economic, ecological, and social benefits of ecological restoration in the Longshan mining area from the perspective of ecological product value, utilizing an input–output research framework based on ecosystem service valuation. This comprehensive assessment includes consideration of restoration cost inputs, aiming to delve into the effectiveness of ecological restoration projects in mining areas. The findings reveal: (1) The indirect value of the ecological products generated by the ecological restoration is approximately 3.13 times greater than their direct value, highlighting the significantly positive impacts of the project. This underscores the necessity for future assessments of mining area ecological restoration projects to not only focus on direct economic returns but also to thoroughly examine their long-term positive impacts on social structures, environmental quality, and residents’ quality of life. (2) When considered solely from an economic benefit perspective, the input–output ratio of the project is 0.34, insufficient to cover the total cost of the project. However, after integrating economic, ecological, and social benefits, the input–output ratio increases to 1.40. This indicates the importance of exploring the mechanisms through which the indirect values of ecological and social benefits contribute directly to the project’s economic sustainability.

Analysis of geological disaster management and ecological restoration measures in mining engineering

This paper provides a comprehensive analysis of the current effective measures for managing geological disasters and ecological damage caused by mining engineering development. The discussion primarily focuses on two aspects: engineering technology and ecological management. It is clear that slope stabilization technology, drainage and waterproof system construction, vegetation restoration, and artificial humidity construction play active roles in the management of geological disasters and ecological restoration in mining areas. These measures not only effectively control geological disasters but also significantly improve the ecological environment, enhance the self-recovery capacity of regional ecosystems, and achieve harmonious development of society, economy, and environment.

Remote sensing of vegetation restoration in mining areas in the south of Russia’s Far East

Remote sensing of vegetation restoration in mining areas in the south of Russia’s Far East

Enhancing iron biogeochemical cycling for canga ecosystem restoration: insights from microbial stimuli.

The microbial-induced restoration of ferruginous crusts (canga), which partially cover iron deposits and host unique ecosystems, is a promising alternative for reducing the environmental impacts of the iron mining industry. To investigate the potential of microbial action to accelerate the reduction and oxidation of iron in substrates rich in hematite and goethite, four different microbial treatments (water only as a control - W; culture medium only - MO; medium + microbial consortium - MI; medium + microbial consortium + soluble iron - MIC) were periodically applied to induce iron dissolution and subsequent precipitation. Except for W, all the treatments resulted in the formation of biocemented blocks. MO and MI treatments resulted in significant goethite dissolution, followed by precipitation of iron oxyhydroxides and an iron sulfate phase, due to iron oxidation, in addition to the preservation of microfossils. In the MIC treatment, biofilms were identified, but with few mineralogical changes in the iron-rich particles, indicating less iron cycling compared to the MO or MI treatment. Regarding microbial diversity, iron-reducing families, such as Enterobacteriaceae, were found in all microbially treated substrates. However, the presence of Bacillaceae indicates the importance of fermentative bacteria in accelerating the dissolution of iron minerals. The acceleration of iron cycling was also promoted by microorganisms that couple nitrate reduction with Fe(II) oxidation. These findings demonstrate a sustainable and streamlined opportunity for restoration in mining areas.

Impacts of mining on vegetation phenology and sensitivity assessment of spectral vegetation indices to mining activities in arid/semi-arid areas

Measuring the impact of mining activities on vegetation phenology and assessing the sensitivity of vegetation indices (VIs) to it are crucial for understanding land degradation in mining areas and enhancing the carbon sink capacity following the ecological restoration of mines. To this end, we have developed a novel technical framework to quantify the impact of mining activities on vegetation, and applied it to the Bainaimiao copper mining area in Inner Mongolia. Phenological indices are extracted based on the VI time series data of Sentinel-2, and changes in phenological differences in various directions are used to quantify the impact of mining activities on vegetation. Finally, indicators such as mean difference, standard deviation, index value distribution interval, and concentration of index value distribution were selected to assess the sensitivity of the Enhanced Vegetation Index (EVI), Green Chlorophyll Index (GCI), Global Environmental Monitoring Index (GEMI), Green Normalized Difference Vegetation Index (GNDVI), Normalized Difference Vegetation Index (NDVI), Renormalized Difference Vegetation Index (RDVI), Red-Edge Chlorophyll Index (RECI), and Soil-Adjusted Vegetation Index (SAVI) to mining activities. The results of the study show that the impact of mining activities on surrounding vegetation extends to an area three times larger than the actual mining activity area. When compared with the reference and unaffected areas, the affected area experienced a delay of approximately 10 days in seasonal vegetation development. Environmental pollution caused by the tailings pond was identified as the primary factor influencing this delay. Significant variations in the sensitivity of each VI to assess mining activities in arid/semi-arid areas were observed. Notably, GCI, GNDVI and RDVI displayed relatively high sensitivity to discrepancies in the spectral attributes of vegetation within the affected area, while SAVI reflected the overall spectral stability of the vegetation in the affected area. The research findings have the potential to provide valuable technical guidance for holistic environmental management in mining areas and hold great significance in preventing further land degradation and supporting ecological restoration in mining areas.

Ground subsidence monitoring in based on UAV-LiDAR technology: a case study of a mine in the Ordos, China

Ground subsidence in Western coal mining areas is characterized by rapid deformation, extensive damage, and a wide range of impacts. The conventional observation methods are inappropriate for surface damage monitoring in high-intensity mining areas of Western China. Therefore, it is a crucial problem to quickly, accurately, and comprehensively monitor the ground subsidence and environmental damage caused by high-intensity and large-scale mining. In this study, we propose a monitoring method for the ground subsidence of high-intensity mining with Unmanned Aerial Vehicle Lidar (UAV-LiDAR) measurement technology. Taking a mine in Ordos of China as an example, the Digital Elevation Model (DEM) is obtained by Kriging Interpolation of the ground point cloud from UAV-LiDAR. Then, the multi-stage DEM differential processing is employed to get ground subsidence. Finally, the median and bilateral filters combine for denoise to obtain the high-precision ground subsidence. The results show that the accuracy of the ground DEM generated by UAV-LiDAR is 15 mm and the mean square error of the ground subsidence basin is 39 mm. UAV-LiDAR technology can quickly obtain abundant surface data and obtain high-precision ground subsidence. Therefore, the application of this technology and method in subsidence monitoring in mining areas is feasible. And it can provide support for ecological environment monitoring, land reclamation, and ecological restoration in mining areas. The research results can provide a useful basis for monitoring the surface damage of coal mining in Western China.

Using unmanned aerial vehicle multispectral data for monitoring the outcomes of ecological restoration in mining areas

AbstractThe effective and efficient monitoring of revegetation outcomes is a key component of ecosystem restoration. Monitoring often involves labor‐intensive manual methods, which are difficult to deploy when sites are inaccessible or involve large areas of revegetation. This study aimed to identify plant species and quantify α‐diversity index on a sub‐meter scale at Manlailiang Mine Site in Northwestern China using unmanned aerial vehicles (UAVs) as a means to semiautomate large‐scale vegetation monitoring. UAVs equipped with multispectral sensors were combined with three industry‐standard supervised classification algorithms (support vector machine [SVM], maximum likelihood, and artificial neural network) to classify plant species. Spectral vegetation indices (normalized difference vegetation index [NDVI], difference vegetation index [DVI], visible‐band difference vegetation index, soil‐adjusted vegetation index, modified soil‐adjusted vegetation index, and excess green–excess red) were used to assess vegetation diversity obtained from on‐ground survey plot data (the Margalef, Pielou, Simpson, and Shannon–Wiener indices). Our results showed that SVM outperformed other algorithms in species identification accuracy (overall accuracy of 84%). Significant relationships were observed between vegetation indices and diversity indices, with the DVI performing significantly better than many more commonly used indices such as the NDVI. The findings highlight the potential of combining UAV multispectral data, spectral vegetation indices and ground surveys for effective and efficient fine‐scale monitoring of vegetation diversity in the ecological restoration of mining areas. This has significant practical benefits for improving adaptive management of restoration through improved monitoring tools.

The Responses of C, N, P and Stoichiometric Ratios to Biochar and Vermicompost Additions Differ from Alfalfa and a Mine Soil

The use of ecological stoichiometry is quite effective for exploring the nutrient dynamics and relationships between plants and soils. However, the way that the plant and soil stoichiometry changes with soil remediation in mining ecosystems remains unclear. Biochar and vermicompost are generally applied to remediate contaminated soil. In this study, a pot experiment was conducted with a mine soil planted with alfalfa. Biochar (B) and vermicompost (V) were added to the soil separately in three different proportions, equivalent to application rates (w/w) of 0% (control, CT), 2.5% (low rate, l), and 5% (high rate, h). This resulted in nine treatments, including control (CT), Bl, Bh, Vl, Vh, BlVl, BlVh, BhVl, and BhVh. The carbon (C), nitrogen (N), and phosphorus (P) concentrations and stoichiometric characteristics of the alfalfa aboveground parts (plant) and soil were investigated. The results showed that biochar application significantly increased the concentrations of soil organic C (SOC), soil total N (TN), soil total P (TP), soil C:N, and plant P concentration, but decreased plant N concentration, and plant C:P and N:P ratios. The effects of vermicompost addition on SOC, soil TN, TP, and stoichiometric characteristics depended on the biochar addition rates, but it increased plant N concentration and N:P, and decreased plant C:N under the condition of low biochar addition. Additionally, the plant N concentration was negatively correlated with soil N and total manganese (Mn) concentrations, whereas there was a positive correlation between plant and soil P concentrations. The soil total and available cadmium (Cd) were positively correlated with plant N concentration but negatively correlated with plant P concentration. The results indicated that the stoichiometric characteristics of plants and soil had diverse responses to biochar and vermicompost additions, and different soil heavy metal elements. Biochar and vermicompost application improved external P and N utilization by plants, respectively. Vermicompost addition enhanced biological N fixation in alfalfa. These findings suggest that vermicompost addition could be an optimal method by which to promote vegetation restoration in mine soils with poor N levels, and that biochar could be applied to low-P soils. The effects of heavy metals on plant and soil stoichiometric characteristics should be taken into consideration. Consequently, this study will provide scientific references for biochar and vermicompost applications in alfalfa planting and management, and vegetation restoration in mining areas.

Mapping mining-induced ground fissures and their evolution using UAV photogrammetry

Due to its unique geomorphological characteristics, the loess gully region is easy to produce ground fissures under the action of coal mining, destroy the ground infrastructures, induce geological disasters, and threaten the safety of people’s lives and property. Therefore, it is particularly important to accurately obtain information about the development of mining-induced ground fissures and study their spatial-temporal evolution mechanism. Based on the 1212 working face of a mining area in Yulin City, Shaanxi Province, this paper studies the extraction method and spatial-temporal evolution mechanism of ground fissures by combining remote sensing images and field survey data. The study shows that this proposed method significantly reduces noise points and mis-extraction, and the accuracy is more than 80%, improving the extraction accuracy of ground fissures and making the process more automated. By comparing the extraction accuracy of ground fissures at different flight altitudes, we determine that the optimal flight altitude for the research area is 60 m. At the beginning of the working face mining stage, the proportion of low-density areas of ground fissures continues to increase. Some low-density areas transition into high-density areas, which is consistent with the progress of the working face advancement. After the end of the working face retreat, the width of the ground fissures tends to be evenly distributed. The mining-induced ground fissures in the Loess gully and ravine region have good self-similarity. A dynamic development model of ground fissures is constructed to reveal its formation mechanism. The research conclusions can provide a technical support for geological disaster monitoring and land ecological restoration in mining areas.

Characteristics and Potential Ecological Risks of Heavy Metal Content in the Soil of a Plateau Alpine Mining Area in the Qilian Mountains

In recent years, the ecological and environmental problems caused by mining in the Qilian Mountains have attracted considerable attention, and the government has carried out a number of comprehensive ecological environment remediation projects there, among which ecological restoration in the Qilian Mountain alpine mining area is an essential task. As a result, heavy metals have been studied in the soil of the Qilian Mountain alpine mining area. This can provide a scientific basis and data support for the establishment of a demonstration index for monitoring ecological environmental restoration in mining areas. In order to understand the content and contamination status of heavy metals in the soil surrounding the alpine mining area of Qilian Mountain, 56 soil samples were collected to determine the levels of eight heavy metals, including Cd, Hg, As, Pb, Cr, Cu, Zn, and Ni. The spatial distribution of heavy metals in the soil of the study area was analyzed based on a statistical approach. The single-factor pollution index (Pi), Nemerow comprehensive pollution index (PN), geoaccumulation index (Igeo), and potential ecological risk index (RI) were used to evaluate soil heavy metal pollution and potential ecological risk. Principal component analysis (PCA), positive matrix factorization (PMF) models, and geostatistical analysis were also used to investigate the source of heavy metals. The results show that the average Cd, As, Cr, Cu, Zn, and Ni content of the grassland soil around the mining area exceeds the soil background values in both Qinghai Lake Basin and Qinghai Province. The spatial distribution of the eight heavy metal elements in soil showed an island-like pattern, with high-value areas of each metal element appearing, indicating that human activities in the study area had negative effects on the soil environment. The value of the single pollution index showed that levels of Ni, Cd, Cu, Cr, Hg, and As pollution were low, while there was no Pb or Zn pollution. The Nemerow integrated pollution index had an average value of 1.39, indicating a slight pollution trend. The average values of Cr and Zn in the geoaccumulation index ranged from 0 to 1, indicating mild to moderate contamination in the studied region. The average value of the integrated ecological risk index in the study area was 135.43, which is in the intermediate ecological risk range. In descending order of size, the average ecological risk index of each heavy metal element was Hg > Cd> As > Ni > Cu > Pb > Cr > Zn. From the perspective of the spatial distribution pattern of ecological risk, the two high-value discriminants were in the western part of the study area, close to the mining area. Zn, Cu, Pb, and Cd in soils were mainly affected by human activity, while Cr and Ni were mainly affected by soil geochemistry. Cd is the main contaminant in the study area, and soil Cd contamination of the grassland in the study area must be considered.

Vegetation as an ecological indicator in assessing environmental restoration in mining areas

As global demand for natural resources escalates, the environmental impact stemming from resource extraction has risen to the forefront of contemporary discussions. This paper probed the potential of using vegetation cover as an ecological barometer to gauge the level of environmental damage and restoration in mining areas: a decline in vegetation cover may signify detrimental impacts from intense mining activities, while an increase may indicate effective local environmental stewardship. Therefore, this paper undertook an assessment and discussion of mining damage and environmental management at China's Ta'ershan Mining Area since 2007, calculating and visualizing FVC (Fractional Vegetation Cover) of the Ta'ershan Mining Area to track changes in vegetation cover between 2007 and 2021. Changes in vegetation cover in the Ta'ershan Mining Area could act as a reflection of both mining-induced damage and subsequent successful environmental management by local authorities, providing a practical way to evaluate ecological effects in resource development.

Extraction and monitoring of vegetation coverage based on uncrewed aerial vehicle visible image in a post gold mining area

Vegetation coverage reflects the degree of environmental degradation. Timely and effective monitoring of vegetation conditions is the basis for promoting vegetation protection and improving the ecological environment of mining areas. Exploring vegetation coverage extraction methods and selecting the optimal vegetation index in mining areas can provide scientific reference for estimating vegetation coverage based on vegetation index in mining areas. Uncrewed aerial vehicles (UAVs) are widely used because of their fast real-time performance, high spatial resolution, and easy accessibility. In this study, the performances of nine visible vegetation indices and two threshold segmentation methods for extracting vegetation coverage in a post-gold mining area in the Qinling Mountains were comprehensively compared using visible spectrum UAV images. Of the nine indices, the excess green index (EXG) and visible-band difference vegetation index (VDVI) were the most effective in discriminating between vegetation and non-vegetation by visual interpretation. In addition, the accuracy of the bimodal histogram threshold method in extracting vegetation coverage was higher than that of Otsu’s threshold method. The bimodal histogram threshold method combined with EXG yielded optimal extraction results. Based on optimal methods, the total percentages of fractional vegetation coverage in 2019, 2020, and 2021 were 31.47%, 34.08%, and 42.77%, respectively, indicating that the vegetation in the mining area improved. These results provide valuable guidance for extracting vegetation information and evaluating vegetation restoration in mining areas.

A systematic review and comprehensive analysis on ecological restoration of mining areas in the arid region of China: Challenge, capability and reconsideration

The arid region in China with rich mineral resources are belongs to ecological fragile region with inadequate recovering capacity. Hundred years of continues mining of mineral resources for economic purposes, leads to the problem of land degradation caused by the spatial coupling of large-scale mining disturbance and arid fragile ecological environment. The environmental problems created by mining have not been addressed promptly, while at the same time, new problems have emerged. On the basis of our 20 years of practical experience on ecological restoration in mining areas, review and synthesis of selective literature, with interpretation and perspective, the mining situation and its ecological impacts, the factors impeding ecological restoration capability in the arid region in China were examined, the key challenges and promotion strategy were presented. The main findings of this study are as follows: Land degradation is the most prominent problem resulting in mining activities, and mainly reflected by immediate disturbance, long term effects and ecological degradation. The main challenges faced by mining area restoration in arid areas are unclear objectives of ecological restoration, lack of ecological water consumption, unreasonable selection of indigenous plants, serious land degradation and wide restoration area. Our restoration experiments in typical mining areas have proved that the micro-topography reconstruction measures can increase surface roughness, redistribute limited precipitation resources (especially snow), and make soil water and nutrients carried by surface runoff and collected in valleys to regulate soil infiltration and water supply, so as to achieve water-saving and non-irrigated vegetation restoration. The ideal restoration effects are the improvement of vegetation coverage, the increase of available land resources, and the improvement of ecosystem services in mining areas. This study would be helpful to carried out related implementation on ecological restoration and could act as a valuable reference for the researchers involved in the ecological restoration in arid region.

Soil seed bank responses to anthropogenic disturbances and its vegetation restoration potential in the arid mining area

Close-to-nature restoration of mining areas is becoming widely recognized for its promotion of ecosystem resilience and risk mitigation of biodiversity losses. Soil seed banks can serve as a direct source of natural restoration, as well as a buffer against environmental changes in vulnerable ecosystem. However, in arid mining area, it remains unclear how the anthropogenic disturbances affect the seed banks and what its potential for vegetation restoration. We conducted a field study to investigate the variation of aboveground plant communities and seed banks along the disturbance gradient in an opencast mining area in arid desert of northwestern China. Furthermore, we detected the influence path of disturbance on seed bank density and richness at different layers. The seed bank had considerable density, with persistent seed accounting for 46%. The density had no significant differences along the none-to-moderate disturbance gradient but decreased significantly at the severe level. Meanwhile, the richness had significant differences among all disturbance levels with the highest value at mild level. There were low similarities between soil seed bank and aboveground vegetation, and their species composition was distinctly different. The anthropogenic disturbances reduced soil seed bank directly. Besides, it indirectly decreased the density of persistent seed bank at shallow layer via the negative impact on silt content. In contrast, disturbance indirectly reduced transient seed density and richness mainly via the positive effect on aboveground vegetation. Briefly, mild-to-moderate disturbance had limited negative effects on the soil seed bank and its restoration potential in the arid mining region. Our study highlights the soil seed banks as supplementary indicator to reflect ecological degradation and the significance for ecosystem recovery. The results could be useful in protection and management projects for the restoration of arid mining areas.

Influence of the freeze–thaw process on coal gangue–based ecological restoration materials: performance and ecological risk assessment of heavy metals

Materials made from coal gangue (CGEr) can be used for ecological restoration in mining areas. This paper comprehensively analyzed the influence of the freeze-thaw process on the performance of CGEr and the environmental risk of heavy metals. The safety of CGEr was assessed by sediment quality guidelines (SQGs), geological accumulation index (Igeo), potential ecological risk index (RI), and risk assessment code (RAC). The freeze-thaw process reduced the performance of CGEr, that the water retention of CGEr decreased from 1.07 (g water/g soil) to 0.78 (g water/g soil), and the loss rate of soil and water increased from 1.07 to 4.30%. The freeze-thaw process reduced the ecological risk of CGEr, the Igeo of Cd and Zn decreased from 1.14 to 0.13 and 0.53 to 0.3, respectively, and the RI of Cd decreased by 50% from 0.297 to 0.147. Reaction experiments and correlation analysis showed that the freeze-thaw process destroyed the pore structure of the material, resulting in the degradation of its properties. Water molecules undergo phase transformation during freeze-thaw, and particles were squeezed by ice crystals to form agglomerates. The formation of granular aggregates resulted in the enrichment of heavy metals in the aggregates. Influenced by the freeze-thaw process, specific functional groups such as -OH were more exposed on the surface of the material, which affected the occurrence form of heavy metals and thus reduced the potential ecological risk of the material. This study provides an important basis for the better application of ecological restoration materials of CGEr.

Study on the Restoration and Control of Yulin Landscape, Forest, Field, Lake and Grass System

Yulin city is a national high-end energy and chemical industry base. After more than 40 years of development of coal mining area, the geological disasters and ecological environment damage caused by the original coal mine goaf have become the urgent ecological environment problems that perplex the sustainable development of Yulin city. The traditional ecological governance mode of mining area, with high governance cost, large implementation resistance and poor ecological benefits, can not meet the requirements of Yulin mining area With the new requirements of ecological environment and economic development, it is urgent to explore a new model of ecological governance in mining areas. On the basis of ecological restoration in mining area, this paper puts forward the development mode of ecological restoration and multi industry integration in mining area, and analyzes it based on SWOT model, in order to provide a practical way for the sustainable development of mining area in Yulin City, so as to make sustainable use of resources and sustainable development of ecological environment.

Seasonal and spatial variations in soil biochemical properties in areas with different degrees of mining subsidence in Central China

Land subsidence due to underground mining results in soil nutrient loss and reduced soil fertility. Land reclamation, which refers to the improvement of soil nutrients through targeted measures, requires spatial and temporal distribution information on the soil properties. However, this has not yet been studied. Therefore, the spatial autocorrelation of soil chemical and biological properties was examined in the Pingdingshan coal mining area during four seasons in China from 80 collected and analyzed soil samples. The spatial autocorrelation was determined by the global and local Moran’s indices. Spatial clustering and variability were analyzed with ArcGIS 10.2 (Environmental Systems Research Institute, ESRI, USA) and GeoDa 7.0 software (Center for Spatial Data Science in University of Chicago, USA). Soil pH and the soil total carbon (TC) content, soil total nitrogen (TN) content, soil available phosphorus (AP) content, and soil alkali-hydrolyzable nitrogen (AN) content were measured as soil chemical properties. The soil biological properties included the quantities of bacteria, actinomycetes, and fungi. The soil chemical and biological properties showed a strong spatial autocorrelation during the four seasons. “High-high” and “low-low” were the dominant autocorrelation types that were distributed in serious and light subsidence areas. The soil properties decreased as the mining subsidence degree increased. Both the soil TC and soil AP contents were highest in spring, the soil TN content was highest in autumn, and the soil AN content was highest in summer. These results provide a reliable theoretical reference for land reclamation and ecological restoration in mining areas.

Evaluation Study of Ecological Resilience in Southern Red Soil Mining Areas Considering Rare Earth Mining Process

Ion-adsorption rare earth mining areas are located in southern China’s ecologically fragile red soil hills region. For a long time, under the influence of multiple factors such as low mining technology and indiscriminate mining, this area has experienced serious environmental problems. Therefore, it is crucial for the ecological management and restoration of mining areas to accurately conduct a quantitative evaluation of ecological restoration status. We used remote sensing and geographic information data to establish an ecosystem resilience evaluation index system consisting of five criteria (land stress, vegetation conditions, surface conditions, biodiversity, and air pollution) and 17 evaluation factors. The Lingbei rare earth mining area in Dingnan County in the red soil hill region was used as a case study since it is a representative ion adsorption rare earth mining area. The restoration status of the mining area was evaluated from 2000 to 2020. The results showed the following: (1) From 2000 to 2020, the ecological resilience level of the mining area was 0.695, 0.685, 0.664, 0.651, and 0.657, exhibiting a decrease followed by an increase. (2) Spatially, the ecological resilience was low at the mine site and increased with increasing distance, indicating that rare earth mining adversely affected ecological resilience in the mining area. (3) The regional ecological resilience has improved over time due to the implementation of green development policies. However, the rate of improvement is slow and ecological restoration of mining areas will remain an ongoing challenge in the future. This study can provide a scientific basis and practical reference for the ecological protection and restoration of mining areas.

Effects of Underground Mining on Soil–Vegetation System: A Case Study of Different Subsidence Areas

The influence of coal mining subsidence on the surface ecological environment can be characterized as the evolution of a complex system. Examining the ecological damage caused by coal mining subsidence from the perspective of internal soil–vegetation system relationships is important for the ecological protection and restoration of mining areas. We investigated vegetation coverage, surface soil water and nutrient content, and vadose zone soil moisture in uniform and nonuniform areas of coal mining subsidence. Subsidence reduced vegetation coverage, surface soil moisture and nutrient content, and vadose zone soil moisture while increasing their spatial variability. These effects are more pronounced in areas with nonuniform subsidence. Subsidence also reduced the degree of soil–vegetation system correlation, which was also more pronounced in areas of nonuniform subsidence. Furthermore, a higher degree of soil–vegetation correlation was linked to decreased variability in soil moisture and nutrient content. Areas of nonuniform subsidence were characterized by greater preferential flow during rain infiltration, which contributed to the spatial variability of soil moisture and nutrient content and damage to vegetation growth. Our findings revealed that coal mining subsidence reduces both the quality of environmental factors and the degree of internal correlation between these factors, of which the preferential flow effect is an important underlying mechanism. These findings provide a theoretical basis for ecosystem management and the restoration of land damaged by coal mining subsidence.