Heavy metal pollution is a major environmental problem facing humankind. Locating the source and distribution of heavy metal pollutants around mines can provide a scientific basis for environmental control. The structure effect and random effect of a semivariogram can be used to determine the reason for spatial differences in the heavy metal content in surface soil, and the coefficient of variation and regression analysis can be used to confirm that the verification accuracy meets the geostatistical requirements. According to the maximum difference method, the content of heavy metals in the surface soil of the mining area is higher than that of the surroundings, and Cu and Zn levels are higher than the background values for Inner Mongolia. In the present case, Zn, Mn, Pb, Cr, Ni, and Cu levels exceeded the background values for the surroundings of the study area by 65.10%, 53.72%, 52.17%, 46.24%, 33.08%, and 29.49%, respectively. The results show that human activities play a decisive role in the spatial distribution of heavy metals, leading to their spatial distribution in the form of “core periphery”. This distribution pattern was significantly affected by the slope, NDVI value, and the distance from the mining area, but the spatial distribution of Pb was significantly related to high-grade roads. The research methods and conclusions have reference significance for the sources and spatial distribution characteristics of heavy metal pollution in similar mining areas and provide a target for the prevention and control of environmental pollution in the study area.

Soil erosion is the main threat to the stability of ecological environment and the harmonious development of society in Shendong Mining Area. The main causes of this threat include the strong interference of natural characteristics and land development. Scientific soil and water conservation measures can coordinate the contradictions among coal economic development, ecological protection, and residents’ prosperity. Based on particle swarm optimization and analytic hierarchy process, the benefit evaluation system of soil and water conservation measures in Shendong Mining Area is established. The weight ratio of three kinds of benefits in Shendong coal mine collapse area is: ecological benefit > social benefit > economic benefit. The conclusion shows that the implementation of the national policy and the effect of mining area management meet the expectation. Therefore, this study provides effective reference and reasonable suggestions for soil and water conservation in Shendong Mining Area. In terms of control measures, bioengineering measures, such as increased coverage of forest and grass as well as reasonable transformation of the landscape pattern of micro landform, can improve the degree of soil erosion control, optimize the land use structure, and improve the land use rate.

The biogeophysical effects of land cover change (LCC) on land surface temperature are largely understood, especially in tropical and boreal zones, but fewer studies have reported the biogeophysical consequences of ecological restoration of mining areas located in arid and semi-arid temperate zones. In this study, we employed 2000–2015 satellite-based net radiation (Rn) and latent heat flux (LE) data from mining areas (taking Dongsheng in Inner Mongolia as an example) and adjacent ecological restoration areas to understand the biogeophysical effect of revegetation around mining areas. The results showed that revegetation increased Rn (0.25 ± 0.17 W/m²) and LE (0.43 ± 0.26 W/m²). The warming effect of increased Rn (∆Rn), however, was completely offset by the cooling effect of increased LE (∆LE), thus revegetation caused an overall cooling effect of −0.18 ± 0.17 W/m². Land surface temperature (LST) from mining areas and adjacent ecological restoration areas also showed that revegetation decreased LST (∆LST being −0.2 ± 0.1 K). The difference of ∆Rn and ∆LE explained 27% of the ∆LST variations. These findings reinforce our understanding for the potential climatic benefits of the ecological restoration around mining areas in arid and semi-arid temperate zones.

At present, the carrying capacity of resources and the environment in some areas has reached an upper limit, and the problems of ecological destruction and environmental pollution have become increasingly prominent. The overexploitation and disorderly development of land space, resulting in the spatial imbalance between the population economy and the resource environment, is one of the root causes of excessive resource consumption, ecological degradation, and environmental pollution. Resource and environmental carrying capacity and suitability evaluation of land space development is the basis of land space planning. It provides conditions for the modernization of land space governance. The framework provided by the “ Double Evaluation Guide (Trial) “ is universal. It is necessary to adapt it to local conditions and to achieve the ” Double Evalution” results, according to the characteristics of regional development. Taking Hohhot as the research area, which is based on the “Guide”, involves selecting convincing and credible evaluation factors and using the single factor integration method and the discriminant matrix method. The “double evaluation” of Hohhot was also analyzed. This provides basic data for regional high-quality development and land space planning. The results show the following: (1) The ecological function of Hohhot is good. The areas with low importance for ecological protection accounted for about 18%, the areas with medium ecological protection accounted for about 62%, and the areas with high ecological protection accounted for about 21%. (2) The carrying capacity of agricultural function in Hohhot is medium. The carrying capacity of the low polar region accounted for about 23%, the medium polar region’s carrying capacity accounted for about 71%, and the high polar region’s carrying capacity accounted for about 6%. (3) The urban function carrying capacity of Hohhot is medium. The carrying capacity of the low-grade area accounted for about 25%, the medium-grade area’s carrying capacity accounted for about 55%, and the high-grade area’s carrying capacity accounted for about 21%. (4) The overall agricultural production suitability grade of Hohhot is not suitable. (5) The suitability of urban construction in Hohhot is general. The unsuitable area accounts for about 40%, the more suitable area accounts for about 45%, and the most suitable area accounts for about 15%.

Large-scale eco-environmental assessment requires not only long-term monitoring but also an understanding of short-term predictability and spatially heterogeneous environmental associations. Here, we evaluated the Remote Sensing Ecological Index (RSEI) across China from 2002 to 2024 and integrated spatiotemporal trend analysis, one-year-ahead prediction, and interpretable machine learning. The national area-weighted mean RSEI increased from 0.6385 in 2002 to 0.6614 in 2024, although the magnitude and timing of change varied markedly among climatic zones. Under a spatially and temporally held-out test design, XGBoost achieved the best predictive performance, with a weighted of 0.9712 and an RMSE of 0.0262, reducing RMSE by 13.67% relative to a persistence baseline. Variance decomposition showed that 97.39% of total RSEI variability was attributable to between-pixel spatial differences, whereas only 2.61% reflected within-pixel interannual variation. Interpretable modelling further revealed contrasting association structures: elevation, warm-season temperature and land cover were most important for spatial-level differences, whereas warm-season precipitation, land cover and potential evapotranspiration dominated interannual variability. These relationships also differed substantially among climatic zones. Our results show that RSEI dynamics are highly predictable at a one-year horizon, but the factors associated with persistent spatial patterns differ from those linked to year-to-year ecological fluctuations, highlighting the need to distinguish spatial baseline conditions from interannual environmental variability in large-scale ecological assessment.

The traditional ecological reclamation measurements and assessments for the grassland areas damaged by open-pit mining often fall short in revealing the dynamics of plant communities affected by environmental filters during reconstruction, making reclamation efforts crucial. The trait-based community framework has been widely applied due to its great potential to predict the restoration process and provide insight into its mechanisms, but how the traits and environmental factors interact to form communities over time is still uncertain. Therefore, to make this process clear, we used the trait-based community framework, defining target species, non-target species, and common grass species, examining how the mix seed sowing and environment (two surface-covering materials applied to mine dump) affect re-vegetation composition, diversity, and functional traits in 14 years. Four treatments were tested: bio-fence surface-covering materials + sowing (BFS), plant-barrier surface-covering materials + sowing (PBS), sowing without any surface-covering materials (SOW), and a control without seeding and covering (CK). Natural grassland sites were regarded as reference (REF). Our findings indicated that the mix seed sowing and the interaction of surface-covering and time were primarily driving the dynamics of the plant community, affecting composition, the value of diversity, coverage, numbers, richness, and functional traits, such as the community-weighted mean (CWM) and functional diversity (FD), which increased and approached the sites REF. There were significant differences between the treatments and CK for the most traits. Although several results in the treatments approached the REF, significant differences still remained in the last observation year. With the sowing and surface-covering treatment, the re-built communities became more resource-acquisitive in terms of the CWM traits; even the value of the specific leaf area (SLA) exceed the REF after 14 years reclamation. We found those communities were dominated by target species that had a higher traits value than the non-target species, while the CK treatment became more resource-conservative over time due to non-target species dominating. The CWM in treatments tended toward reference levels for specific leaf area (SLA), leaf dry matter content (LDMC), and root dry matter content (RDMC), but not for seed mass (SM), thereby indicating that the above- and below-ground productivity of restored sites gradually overcame abiotic (surface-covering) and biotic (sowing) filters and approached target values. The functional diversity (FD) generally increased, with higher multivariate functional dispersion in the treatments containing more target species, suggesting that re-built communities achieve more resistance to invasion and disturbance over time. Hence, the trajectory of species and communities changing highlights the effectiveness of a trait-based approach in identifying better reclamation treatments and candidate species and provides a positive outlook for future re-vegetation community succession.