Vegetation dynamics and land use information are significant for a better understanding of the ecological consequences of multiple mining activities. However, the high spatial heterogeneity of mine sites and diverse disturbance and recovery pathways make it a challenge to understand the dynamics of multiple mine sites over large areas. Here, we proposed a general framework for continuous monitoring of land use and vegetation dynamics in multiple mine sites and applied it to Pingxiang, China. First, annual land use and land cover (LULC) maps from 2000 to 2019 were generated using a modified Continuous Change Detection and Classification approach (CCDC). Second, the locations and extents of 86 mine sites on different scales were mapped individually and then aggregated into five groups according to the similarity and differences of vegetation change. Vegetation dynamics showed great heterogeneity across sites driven primarily by the spatial‐temporal variation in types and intensity of land use activities in and around the mine sites. We found the impact distance was typically 500–700 m in the region, but can be smaller than the potential impact distance in areas with land use activities. The long‐term slow recovery of vegetation conditions at some sites indicates that it might be a challenge to improve vegetation conditions naturally in a short time and human‐assisted restoration measures may be required. The systematic framework proposed in this study can be used to establish comprehensive and spatially‐explicit mine datasets at the regional scale, essential for understanding the dynamics and ecological consequences of multiple mining activities and coordinated management and restoration of heterogeneous mine sites.

Coal gangue dumps, a byproduct of coal mining, contribute significantly to heavy metal contamination, impacting soil and water quality. In order to assess the levels of heavy metal contamination in soils at different stages of abandonment, this study investigated the role of Miscanthus floridulus (M. floridulus) in the spatial distribution and remediation of six heavy metals (Cd, Cr, Mn, Ni, Cu, and Pb) in coal gangue dump soils abandoned for 0, 8, and 12 years in Pingxiang City, Jiangxi Province, China. Fieldwork was conducted at three sites operated by the Pingxiang Mining Group: Anyuan (active, barren), Gaokeng (8 years, natural vegetation), and Qingshan (12 years, partially remediated). Anyuan remains largely barren, while Gaokeng supports natural vegetation without formal remediation. In contrast, Qingshan supports diverse plant species, including M. floridulus, due to partial remediation. Using a randomized design, root exudates, heavy metal concentrations, and soil properties were analyzed. The results showed that Cd poses the highest ecological risk, with concentrations of 64.56 mg kg⁻¹ at the active site, 25.57 mg kg⁻¹ at the 8-year site, and 39.13 mg kg⁻¹ at the 12-year site. Cu and Pb showed accumulation, while Cr and Mn decreased over time. Root exudates from M. floridulus enhanced metal bioavailability, influencing Cd, Cr, and Ni concentrations. These findings highlight the importance of rhizosphere processes in metal mobility and inform sustainable remediation strategies for post-mining landscapes.

Climate change is intensifying the frequency and severity of extreme weather events, posing significant challenges to crop productivity and agroclimatic management in subtropical regions. However, quantitative insights into how different cropping systems respond to climate extremes remain limited. In this study, crop net primary productivity (CNPP) of two representative cropping systems, early–late rice (ER–LR) and dry rapeseed–sweet potato (DR–SP), was analyzed in Pingxiang, a typical subtropical agricultural region of China. Nineteen extreme temperature and precipitation indices were evaluated using an integrated Trend–Prediction–Sensitivity–Threshold (TPST) framework combining statistical and machine learning approaches. CNPP exhibited an upward trend (slope = 4.29 g C m⁻² yr⁻¹) from 2000 to 2023, with ER–LR showing faster growth (slope = 4.54 g C m⁻² yr⁻¹) and higher stability (high-volatility area: 1.25%) than DR–SP (slope = 4.11 g C m⁻² yr⁻¹; 4.94%). Temperature extremes were the dominant drivers, exhibiting nonlinear responses with threshold effects. DR–SP was more climate-sensitive, while ER–LR showed greater tolerance, highlighting the role of cropping systems in enhancing resilience. The TPST framework provides a transferable approach for assessing agroecosystem productivity responses to climate extremes and supports climate-resilient cropland management in subtropical regions.