Open-pit mining removes established soil horizons through severe mechanical disturbance, disrupts aggregates and generates reconstructed mine soils with extremely low and spatially heterogeneous initial soil organic carbon (SOC), heterogeneous parent materials, poor water retention and extreme microclimatic or chemical conditions. These constraints distinguish mine-land carbon reconstruction from SOC development in mature natural and agricultural soils and limit the direct application of conventional stabilization theories. This review provides a mining-specific synthesis of disturbance mechanisms, restoration pathways, coupled controls and monitoring technologies. We interpret SOC formation using the particulate organic carbon (POC), mineral-associated organic carbon (MAOC) and microbial carbon pump frameworks, emphasizing that aggregate protection and mineral binding capacity develop dynamically during substrate reconstruction. We compare vegetation restoration, substrate amendment and integrated ecological engineering, showing that single measures mainly increase carbon inputs or alleviate individual constraints, whereas combined measures better coordinate plant inputs, microbial transformation, erosion control and mineral protection. We then examine how parent material, management, climate and topography interact with restoration age to shift dominant limitations from carbon input to nutrient and decomposition regulation and, eventually, mineral protection. Finally, we evaluate the progression from chronosequences and fixed plots to process-based models, machine learning and multi-source remote sensing, including their application boundaries. Three unresolved disputes concern the persistence of MAOC under environmental change, the dynamic nature of carbon-saturation thresholds and the magnitude of microbial contributions to stable SOC. This synthesis supports restoration strategies that prioritize land stabilization and climate-resilient carbon pools rather than bulk SOC accumulation alone.
Heavy rainfall events can reorganize hydrological pathways and carbon export in hillslope critical zones. However, the correspondence between runoff partitioning and DOC transport among vegetation types and flow pathways remains poorly constrained. We conducted rainfall simulations to capture layered runoff and dissolved organic carbon (DOC) across surface runoff (SR) and subsurface runoff (SSR50 and SSR100) in rocky hillslopes with four vegetation restoration types. Results showed increasing rainfall intensity reorganized runoff partitioning in a vegetation-dependent manner. In Platycladus orientalis woodland, runoff shifted from predominantly subsurface flow (100%) at 30 mm h−1 to a mixed surface–subsurface configuration (53.29% and 46.71%) at 120 mm h−1, whereas Lagopsis supina grassland remained strongly surface-runoff (84.92–91.52%) dominated. Total DOC flux ranged from 807.50 to 4955.28 mg m−2, with SR dominating in QV, VN, and LS (51.37–87.31%), whereas SSR100 contributed ≤5.25% across all treatments. Mechanistically, DOC export was source-limited at high-intense rainfall in surface runoff, contrasting with the consistent transport-limited behaviors in deep subsurface runoff (SSR100cm). Structural equation modeling further confirmed that rainfall intensity and soil properties were most strongly associated with SR, whereas root properties were strongly associated with subsurface runoff. These findings reveal a rainfall intensity and vegetation types reorganization of layered hydrological and DOC transport pathways in rocky mountainous critical zones.
Soil organic carbon (SOC) is vital for climate change mitigation. However, management-induced carbon inputs in agricultural lands often mask climate-driven SOC changes, which represent SOC variation associated with climate and climate-related vegetation productivity. Consequently, how SOC of agricultural lands inherently responds to climate variability at the national scale remains poorly quantified. Background SOC from control treatments (CK) provides a unique opportunity to approximate such climate-driven SOC dynamics. Here, we compiled a nationwide dataset of 3963 background topsoil (0–20 cm) SOC observations spanning 1983–2024 from CK plots across China's major agricultural lands (including paddy field, upland cropland and grassland). Using a random forest coupled with residual kriging (RFK) framework, we reconstructed spatiotemporal background topsoil SOC dynamics during 2000–2024 and found that they exhibited distinct trajectories: mean SOC content declined significantly in paddy field, remained stable in upland cropland, and showed stable averages but a rapid contraction of high-SOC areas in grassland (−0.047% yr−1). Climate sensitivity followed a clear hierarchy: grassland (CV = 9.02%) was more sensitive than upland cropland (7.02%) and paddy field (3.15%). Moreover, the dominant climatic control shifted from temperature variability in grassland and upland cropland to precipitation variability in paddy field. Crucially, these results highlight the inherent limitations of relying solely on mean-based evaluations to assess soil carbon pool dynamics, as stable spatial averages can severely mask localized severe degradation and structural contractions of carbon-rich hotspots. Overall, this study provides critical insights for accurately partitioning anthropogenic and climate-driven components of terrestrial carbon dynamics.
The coupled effects of climate change and Land Use/Land Cover (LULC) change increasingly influence soil erosion. While numerous prior studies have examined these factors in isolation or within single regions, a thorough understanding of how erosion responses to LULC change vary across diverse climatic contexts is still lacking. This study addresses this gap by employing a globally comparative framework that combines the Revised Universal Soil Loss Equation (RUSLE) with six complementary statistical approaches, including fixed-effects panel regression, distributed lag analysis, class-specific dynamic models and Granger causality testing. Six major climatic zones throughout five countries (Brazil, China, the USA, India, and Australia) were examined from 2004 to 2023. The results revealed considerable variability in RUSLE-estimated erosion rates across different climate-region contexts. The relationships between LULC change and erosion differ substantially among climate zones, with agricultural expansion showing stronger positive associations in humid climates and weaker associations in arid regions. Forests exhibit variable protective effects depending on climatic conditions, with lagged associations persisting for up to eight years in some regions. Causality analysis further indicated that changes in forest cover can predict erosion dynamics in specific climate contexts, though this should be interpreted as predictive association rather than physical causation. Overall, our findings demonstrate that identical LULC transitions can produce markedly different erosion outcomes depending on climatic context, highlighting the need for climate-specific soil conservation strategies and the importance of integrating climate-land interactions into global land management frameworks.
Soil phosphorus (P) availability sustains nutrient supply, plant growth, and community persistence in alpine treeline ecosystems. Most studies emphasize spatial gradients, leaving within-season reorganization of individual P fractions and functional pools poorly resolved. We sampled 0–10 and 10–20 cm soils across three mountains and four vegetation belts in June, August, and October 2021 on the southeastern Qinghai-Tibet Plateau. Hedley fractionation separated six P fractions, which we grouped into Labile P, Moderately labile P, and Stable P. Fixed-effects models, partial η2, and sequential sums-of-squares shares compared monthly and spatial effects. The fractions changed asynchronously through the growing season. Labile P increased from June to October but retained stronger mountain and vegetation signals; Moderately labile P increased late in the growing season; and Stable P declined in October. The decline in Stable P was driven mainly by Residual P, even though HCl-P increased. The first two principal components explained 83.9% of the variation and separated samples mainly by month. Month had strong effects on Moderately labile P (partial η2 = 0.322) and Stable P (0.512), whereas mountain had a stronger effect on Labile P (0.141). Month SS shares were 73.2% for NaOH-Pi, 44.4% for NaOH-Po, 45.8% for Residual P, 27.7% for Moderately labile P, and 42.5% for Stable P, whereas mountain and vegetation effects were more pronounced for NaHCO₃-Po and Labile P. Month × vegetation significantly affected several fractions. Redundancy and relative-importance analyses further showed that the dominant soil correlates changed among months. These results reveal rapid within-season redistribution among alpine treeline ecotone soil P pools and show that temporal and spatial controls differ among fractions.
