Persistent effects of underground longwall coal mining on freshwater wetland hydrology

A new indicator for estimating the degree of mining-induced land subsidence: the overburden's average GSI value

Underground coal mining leads to land subsidence, which, in turn, results in damage to buildings and infrastructure, disturbs the original ecological environment, and hinders the sustainable development of coal mining cities. A reasonable estimation of land subsidence, on the other hand, is the foundation for building protection, land reclamation, and ecological environment reconstruction. However, when we applied the existing land subsidence estimation theory to the deep mining areas of the Ordos coalfield in western China, there was a significant deviation between the estimations and the measurements. To explain such unusual case, we propose using the overburden's average GSI (Geological Strength Index) value instead of the compressive strength (UCS) of rock specimens for a better representation of the overburden's overall properties. By using on-site subsidence monitoring results and historical data, we provided evidence which supports that the overburden's average GSI value has a much greater impact on subsidence rates than the UCS. Subsequently, we investigated the relationship between three typical overburden's GSI values and the subsidence rates via a calibrated numerical model, revealing the variation patterns of maximum surface subsidence when the overburden's average GSI value is set at 30, 50, and 75, respectively. Finally, on the basis of the measured and simulated results, we discussed a non-conventional strip mining method for mining subsidence control in the deep mining areas of the Ordos coalfield in western China, and explained why it is possible and what are the significant advantages behind. The proposed methods, findings, and suggestions in this paper are therefore quite helpful for researchers and engineers who wish to estimate and control the mining-induced land subsidence, as well as for those who are particularly interested in the study of environment science related to land subsidence.

Assessing differential land use impacts on soil quality: A method based on log-response ratios and polygonal projections

Soil quality indices (SQI) used for assessing soil degradation are often developed using additive scoring functions. However, these SQI may lack reference values for interpreting their outputs and the capacity to differentiate changes in specific variables. To overcome these limitations, this study introduces SQI using Log Response Ratios (LRR) as measures of size effects caused by land use in physical, chemical, and microbiological soil quality indicators. LRR vectors projected 2D polygons with condensed change measures along their perimeters. This method was tested in andosols within the southeastern region of Antioquia, Colombia. These soils were subjected to contrasting stages of degradation determined by the extent of A-horizon removal due to land use practices. This study shows that mining and agriculture have detrimental effects on soil organic carbon and water contents, and that size effects vary significantly between land uses (p < 0.05). Microbiological features also exhibit distinct size effects, such as populations of culturable mesophilic bacteria and fungi, microbial basal respiration, spore density of arbuscular mycorrhizal fungi (AMF), their diversity, and total glomalin-related soil proteins (p < 0.05). The SQI proposed exhibited a negative correlation with SQI computed from scoring additive functions either considering the entire dataset (R2 = 0.87) or a minimum dataset (R2 = 0.90). This approach underscores the utility of using LRR geometrical analysis to assess global soil quality differences among land uses (p < 0.01), offering a visual, quantifiable representation of the effects of each land use over specific soil quality indicators.

Seasonal succession of microbial community co-occurrence patterns and community assembly mechanism in coal mining subsidence lakes

Coal mining subsidence lakes are classic hydrologic characteristics created by underground coal mining and represent severe anthropogenic disturbances and environmental challenges. However, the assembly mechanisms and diversity of microbial communities shaped by such environments are poorly understood yet. In this study, we explored aquatic bacterial community diversity and ecological assembly processes in subsidence lakes during winter and summer using 16S rRNA gene sequencing. We observed that clear bacterial community structure was driven by seasonality more than by habitat, and the α-diversity and functional diversity of the bacterial community in summer were significantly higher than in winter (p < 0.001). Canonical correspondence analysis indicated that temperature and chlorophyll-a were the most crucial contributing factors influencing the community season variations in subsidence lakes. Specifically, temperature and chlorophyll-a explained 18.26 and 14.69% of the community season variation, respectively. The bacterial community variation was driven by deterministic processes in winter but dominated by stochastic processes in summer. Compared to winter, the network of bacterial communities in summer exhibited a higher average degree, modularity, and keystone taxa (hubs and connectors in a network), thereby forming a highly complex and stable community structure. These results illustrate the clear season heterogeneity of bacterial communities in subsidence lakes and provide new insights into revealing the effects of seasonal succession on microbial assembly processes in coal mining subsidence lake ecosystems.

Effects of interactions between anthropogenic stressors and recurring perturbations on ecosystem resilience and collapse

Insights into declines in ecosystem resilience and their causes and effects can inform preemptive action to avoid ecosystem collapse and loss of biodiversity, ecosystem services, and human well-being. Empirical studies of ecosystem collapse are rare and hampered by ecosystem complexity, nonlinear and lagged responses, and interactions across scales. We investigated how an anthropogenic stressor could diminish ecosystem resilience to a recurring perturbation by altering a critical ecosystem driver. We studied groundwater-dependent, peat-accumulating, fire-prone wetlands known as upland swamps in southeastern Australia. We hypothesized that underground mining (stressor) reduces resilience of these wetlands to landscape fires (perturbation) by diminishing groundwater, a key ecosystem driver. We monitored soil moisture as an indicator of ecosystem resilience during and after underground mining. After landscape fire, we compared responses of multiple state variables representing ecosystem structure, composition, and function in swamps within the mining footprint with unmined reference swamps. Soil moisture declined without recovery in swamps with mine subsidence (i.e., undermined), but was maintained in reference swamps over 8 years (effect size 1.8). Relative to burned reference swamps, burned undermined swamps showed greater loss of peat via substrate combustion; reduced cover, height, and biomass of regenerating vegetation; reduced postfire plant species richness and abundance; altered plant species composition; increased mortality rates of woody plants; reduced postfire seedling recruitment; and extirpation of a hydrophilic animal. Undermined swamps therefore showed strong symptoms of postfire ecosystem collapse, whereas reference swamps regenerated vigorously. We found that an anthropogenic stressor diminished the resilience of an ecosystem to recurring perturbations, predisposing it to collapse. Avoidance of ecosystem collapse hinges on early diagnosis of mechanisms and preventative risk reduction. It may be possible to delay or ameliorate symptoms of collapse or to restore resilience, but the latter appears unlikely in our study system due to fundamental alteration of a critical ecosystem driver. Efectos de las interacciones entre los estresantes antropogénicos y las perturbaciones recurrentes sobre la resiliencia y el colapso de los ecosistemas.

Landscape dynamics and human disturbance processes in wetlands in a mining city: a case study in Huaibei, China

Wetlands are fragile ecosystems that are sensitive to human activities. In mining cities with high groundwater tables, underground mining, urbanization, and land reclamation cause severe disturbance to wetland landscape patterns, which poses a serious threat to the integrity and sustainability of the regional wetland ecosystems. This paper extracted the dynamic patterns of wetlands in Huaibei, China, from the Landsat TM/ETM remote sensing images with a time duration of 30 years from 1991 to 2021. The land-use transfer matrix and the landscape metrics were used to analyze the dynamic evolution of the wetland landscape patterns in this typical mining city. Afterwards, the human disturbance changes in the wetlands during the past 30 years were analyzed by the human disturbance transformation index (HTI). The correlation between the HTI and the changes in the landscape metrics were analyzed to reflect the influences of different human disturbance mechanisms on the evolution of the wetland landscape patterns. The results indicated that the wetland areas gradually increased with rising human disturbance levels from 1991 to 2021. However, the wetland landscape patterns showed a trend of declining landscape connectivity and fragmentation. The human disturbance levels to the wetlands were found significantly increased from 1991 to 2005 and from 2010 to 2015, and declined from 2005 to 2010 and from 2015 to 2021. The correlation between the HTI and landscape metrics indicates that current ecological restoration planning has limitations in improving the wetland landscape patterns. In the future, it is necessary to formulate systematic wetland landscape patterns restoration planning that covers the overall area according to the evolutionary trend of wetlands.

Gradient rise in seepage pollution levels in tailings ponds shapes closer linkages between phytoplankton and bacteria

A large number of tailings ponds formed by slag accumulation have become serious environmental hazards. Spatially high potential energy and long-term accumulation may result in gradient-changing seepage pollution. The assemblages of phytoplankton and bacteria are widely used as assessment indicators. In this study, we investigate the changes in phytoplankton and bacterial assemblages in tailing pollution. The results showed that there are temporal and spatial variabilities in seepage pollution. The abundance and diversity of phytoplankton and bacteria decreased with increasing pollution. However, Synedra acus (diatom) and Polynucleobacter (bacteria) were positively correlated with pollution levels (r = 0.37, P < 0.05; r = 0.24, P < 0.05). Heavy metals are the main contributors to bacterial changes (16.46%), while nutrients are for algae (13.24%). Tailings pond pollution reduced the number of phytoplankton and bacterial linkages. However, more pollution broke the originally independent modules of phytoplankton and bacteria, and they produced more positive correlations (79.39%; 87.68%). Microcystis sp. and Limnobacter were the key nodes of the co-occurrence network in the polluted areas. Exploring the interactions between bacteria and phytoplankton within different pollution levels could provide insights into biological interaction patterns and the bioremediation of tailings ponds.

Insights into the spatiotemporal differences in tailings seepage pollution by assessing the diversity and metabolic functions of the soil microbial community

The formation of tailings ponds depends on the long-term accumulation of tailing and high terrain. Its seepage pollution characteristics may have gradient variations on spatiotemporal scales. Used three nearby metal tailings ponds with different service times, we aimed to reveal seepage pollution trends on spatiotemporal scales and the response of soil microbial community. The results showed that the degree of seepage pollution was negatively correlated with the distance from the tailings pond on the spatial scale, while the seepage pollution showed higher levels in tailings ponds with longer service times on the temporal scale (RI = 248.04-2109.85). The pollution effect of seepage persisted after the tailings pond was discontinued (RI = 226.72). Soil microbial diversity increased with spatial scale expansion. The proportion of Actinomyces gradually increased and Proteobacteria decreased. Cr (r = 0.21) and Fe (r = 0.22) contributed more to the microbial community changes. Functional predictions showed that pathways related to signal transduction and energy metabolism were more abundant in the tailings pond. In contaminated areas, the proportion of nitrate respiration and cellulolysis functional communities had decreased, and some potentially pathogenic human taxa had accumulated. These results emphasized that there was pollution accumulation on temporal scale and pollution dispersion on spatial scale around tailings ponds, and the response of the microbial community further illustrated these trends.

Three-Dimensional Spatial Distribution and Influential Factors of Soil Total Nitrogen in a Coal Mining Subsidence Area

Soil nitrogen is very important for crop growth and development. However, the factors affecting the three-dimensional spatial distribution of soil total nitrogen (TN), particularly in coal mining subsidence areas, are unclear. In this study, Markov geostatistics was used to analyse the three-dimensional spatial distribution characteristics and influential factors of TN by examining 180 soil samples from the Zhaogu mine in China. The results showed that the TN content was significantly different at different soil depths (0–20, 20–40, 40–60 cm) and decreased with increasing soil depth. The variation coefficient of the TN content decreased gradually from top to bottom, ranging from 18.18 to 25.62%. In addition, the TN content was greatly affected by mining subsidence, rainfall, irrigation, fertilization and management mode. The factors that influenced the TN content also varied across different slope positions. The TN content of the upslope was the highest, and the TN content of the middle slope was the lowest. These results can provide research ideas and technical countermeasures for ecological environment improvement and sustainable land development in coal mining subsidence areas.

Spatiotemporal Variability of Human Disturbance Impacts on Ecosystem Services in Mining Areas

Human activities pose significant impacts on ecosystem services (ESs) in mining areas, which will continually increase over time and space. However, the mechanism of ES change on spatiotemporal scales post-disturbance remains unclear, especially in the context of global climate change. Here, we conducted a global literature review on the impact of two of the most frequent disturbance factors (mining and restoration) on 27 different ESs, intending to synthesize the impacts of human disturbance on ESs in mining areas via a meta-analysis, and analyze the spatiotemporal variability of ESs after disturbance. We screened 3204 disturbance studies published on the Web of Science between 1950 and 2020 and reviewed 340 in detail. The results of independence test showed that human disturbance had a significant impact on ESs in the mining areas (p < 0.001). The impacts (positive and/or negative) caused by mining and restoration differed considerably among ESs (even on the same ESs). Additionally, spatiotemporal scales of human disturbance were significantly related to spatiotemporal scales of ES change (p < 0.001). We found that the positive and negative impacts of disturbances on ESs may be interconversion under specific spatiotemporal conditions. This seems to be associated with spatiotemporal variability, such as the temporal lag, spatial spillover, and cumulative spatiotemporal effects. Climate changes can lead to further spatiotemporal variability, which highlights the importance of understanding the changes in ESs post-disturbance on spatiotemporal scales. Our research presents recommendations for coping with the twofold pressure of climate change and spatiotemporal variability, to understand how ESs respond to human disturbance at spatiotemporal scales in the future, and manage disturbances to promote sustainable development in mining areas.

Effects of Underground Coal Mining on Soil Spatial Water Content Distribution and Plant Growth Type in Northwest China

The impact of coal mining subsidence on surface ecology involves the influence of several ecological elements such as water, soil, and vegetation, which is systematic and complex. Given the unclear understanding of the synergistic change patterns of the water-soil-vegetation ecological elements in the influence of coal mining in the west, this paper investigates the impact of coal mining on the surface ecology, especially the distribution of soil water content (SWC). In 2020, this study collected 3000 soil samples from 60 sampling points (at depth of 0-10 m) and tested the SWC. All samples come from three different temporal and spatial areas of coal mining subsidence in the desert mining area of Northwest China where soil types are mainly aridisols. At the same time, the interactions among deep SWC and surface soil physical and chemical properties, surface SWC and soil fertility, and pH were analyzed. The spatial variability of soil moisture is reflected by kriging interpolation, and SWC values at different depths are predicted as a basis for monitoring the environmental impact of different coal mining subsidence years. The research has shown that the ground subsidence leads to a decrease in SWC value and changes in surface soil pH, physical and chemical properties, and covering vegetation, which have occurred from the beginning of coal mining. The impact of coal mining on the SWC of the unsaturated zone is mainly at the depth of 0-6 m, where SWC is not directly related to the nutrient content of the surface soil. The overall settlement of the ground will stir up simultaneous decline in the quality of deep SWC and topsoil. The findings of this investigation suggest that changes in the soil structure caused by coal mining subsidence are the key factor in SWC loss. Timely monitoring and repairing 0-6 m ground fissures, as well as selecting shrubs on the surface is the best choice for the restoration of the ecological environment and prevention of soil erosion in this area.

Effects of multi-factors on the spatiotemporal variations of deep confined groundwater in coal mining regions, North China

Natural processes and anthropogenic activities simultaneously control the long-term spatial and temporal variations of groundwater hydrogeochemistry in coalfields. In this study, the spatiotemporal variations and primary controlling factors of deep groundwater hydrogeochemistry in the Carboniferous limestone aquifer of the Huaibei coalfield, North China were investigated using cluster analysis combined with geological conditions, water-rock interactions and mining activities. The analysis data of 176 groundwater samples collected over five years from 20 monitoring wells were subdivided into six clusters through hierarchical cluster analysis. Moreover, principal component analysis, box plots and Piper and Stiff diagrams were employed to analyze the statistical and hydrogeochemical characteristics of each cluster, and to reveal the differences and connections between the clusters. The results show that there are significantly spatial variations in groundwater hydrogeochemistry, while the temporal variations are not evident with only a few notable exceptions. Geological conditions dominate the groundwater hydrogeochemistry by controlling the hydraulic connection between groundwater and meteoric water and the flow conditions of groundwater. Moreover, the types and degrees of diverse water-rock interactions in different regions are another important factor controlling the spatial variations of groundwater hydrogeochemistry. Anthropogenic activities are mainly pumping and drainage, which has led to the overall decline in groundwater levels and the temporal variations of hydrogeochemistry in some zones. The findings of this study not only have important implications for deep groundwater resources management in the Huaibei coalfield, but also provide a research template for other highly exploited coalfields in North China.