Increasing demands for timber and biomass production from European forests have raised concerns about the sustainability of harvesting practices, since forest nutrient stocks have decreased due to enhanced leaching of base cations driven by soil acidification from elevated nitrogen (N) and sulfur (S) deposition. We quantified the impact of three harvest intensities—high-thinning (also known as crown thinning; ∼20 % basal area removal), shelterwood (∼80 %), and clearcut (100 %)—, two harvest methods (stem-only and whole-tree harvest), and soil preparation (shallow mulching and no mulching) on post-harvest nutrient leaching in beech, Douglas fir, and Scots pine stands in the Netherlands, compared to unharvested control plots. Leaching was quantified by combining monthly dissolved nutrient measurements over a full year with a mechanistic model simulating monthly water fluxes. Leaching of macronutrients in unharvested control plots was generally higher in Douglas fir than in Scots pine and beech. Clearcutting, and to a lesser extent shelterwood harvesting, strongly increased dissolved nutrient concentrations, especially nitrate (NO3), indicating rapid mobilization of large N stocks and, to a lesser extent, S stocks. These increases were associated with accelerated soil acidification, induced by losses of base cations (calcium [Ca], magnesium [Mg] and potassium [K]) and acid cations (aluminum [Al], iron [Fe] and manganese [Mn]). Thinning, harvest method, and shallow mulching had minimal or negligible effects on post-harvest leaching, underscoring the potential of low-intensity harvests for sustainable forest use with low nutrient losses. Our study shows that high harvest intensity strongly accelerates nutrient leaching within one year after harvest, but the long-term impacts over a rotation period remain to be explored.

• Equivalent Soil Mass and soil thickness jointly refine SOC stocks. • Systematic overestimation from non-soil layers is mitigated. • The reliable SOC stock for Tibet’s 0–100 cm layer is 4.72 Pg C. • Total SOC stock for Tibet ranges between 2.58 and 47.50 Pg C. Accurate assessment of soil organic carbon (SOC) stocks is essential for understanding the global carbon cycle. However, substantial uncertainties remain in mountainous regions such as Tibet, where the commonly used fixed-depth (FD) approach overlooks spatial variability in soil thickness (ST). This omission leads to systematic overestimation in shallow soils (due to the accounting of carbon in non-existent soil layers) and underestimation in deep, incompletely sampled profiles. To address these dual biases, this study introduces an integrated framework that, for the first time, couples the equivalent soil mass (ESM) method—which corrects for bulk density–related biases—with spatial modeling constrained by ST. The methodology involved: (1) deriving point-scale ESM-based SOC stocks for standard depth intervals (0–30, 30–50, and 50–100 cm) using equal-area quadratic smoothing splines; (2) generating spatially explicit, wall-to-wall predictions at 1-km resolution through quantile regression forests, employing an inverse probability of censoring weighting QRF (IPCW-QRF) for ST and a standard QRF for SOC; and (3) performing pixel-level integration of SOC stocks constrained by the predicted ST to avoid carbon assignment to non-soil layers. The ST model achieved a validation R 2 of 0.57, revealing a distinct spatial pattern of deeper soils in the north and south and shallower soils in the central Plateau, with a mean depth of 90.40 ± 35.50 cm. The SOC model achieved a validation R 2 of 0.56 for the topsoil (0–30 cm), with accuracy decreasing in deeper layers due to sparser observations and reduced influence of surface-based covariates. After ST-constrained integration, the total SOC stock within the reliable prediction area (area of applicability, AOA) was 4.72 Pg C (90 prediction interval: 0.99–19.43 Pg C), while the total stock across Tibet ranged from 2.58 to 47.50 Pg C for the 0–100 cm layer. These findings demonstrate that explicitly incorporating ST and ESM effectively eliminates the systematic biases inherent in the FD approach, offering a robust and scalable framework for accurate carbon accounting in complex, high-relief terrains.

• Soil depth is the main controlling factor of SOC stabilization indicators. • The land-use effect is evident in the top 30 cm of soil. • The thermal analysis-derived stable C fraction is resistant to losses after land-use change. • Mineral-associated C is a dynamic pool and changes similarly to total SOC. • Glomalin-related soil proteins and amino sugars are driven by C inputs and nutrient availability. Soil organic carbon (SOC) and its dynamics are sensitive to changes in land management while assessments of SOC dynamics rely on different indicators of SOC stabilization and are often restricted to topsoil. Here, we evaluated six indicators of SOC stabilization along a 70 cm soil profile under long-term land-use change. Using an agronomic experiment including an unmanaged meadow and two cropland treatments, we quantified isotopic signatures ( 14 C and δ 13 C), size (mineral-associated OC; MaOC) and thermal (Rock-Eval® and PARTY SOC -derived centennially stable C; C S ) fractions, and biochemical composition (amino sugar-derived microbial necromass C; MNC, and glomalin-related soil proteins; GRSP). Isotopic signatures and thermal analysis indicated older SOC (+∼5000 years), a decreasing influence of fresh C (+0.7 ‰ δ 13 C) and higher proportion of C S (by 75 %) with depth. In the cropland compared to the meadow, mean SOC age increased by ∼ 250 years, δ 13 C was enriched by 0.75 ‰ and C S was 27 % higher. The proportion of MaOC reflected a slight increase in SOC stabilization with depth (6 %) but decreased in the cropland compared to the meadow (−5%). The proportions of the two biochemical indicators to total OC decreased with depth (−67 % for MNC and − 78 % for GRSP), following the same trend as bulk SOC, while the proportion of MNC decreased (−15 %) and GRSP increased but with very high uncertainties (37 ± 20 %) in the cropland compared to the meadow. Our results suggest that different indicators likely represent SOC stabilization at different scales, and their validity should be assessed across soil layers.

Belowground organisms forming complex cross-trophic ecological networks are essential for maintaining peatland carbon stability and energy flow. However, how peatland degradation affects the biodiversity and cross-trophic ecological networks of soil communities remains poorly understood. Here, we examined the degradation effects on soil prokaryotes (i.e., bacteria, archaea), fungi and nematodes in alpine peatlands on the eastern Tibetan Plateau, characterized by varying water table depths (indicating degradation levels). We found that peatland degradation, accompanied by significant shifts in soil moisture and pH (P < 0.05), reduced the taxonomic richness and phylogenetic diversity of prokaryotes, fungi, and nematodes, particularly in deeper soil layers (20–50 cm). Crucially, peatland degradation weakened potential cross-trophic interactions within bipartite networks of prokaryotes-nematodes and fungi-nematodes, resulting in less than 6.5 %–28.8 % of unchanged modules. Degradation-induced changes in soil moisture and pH were identified as primary drivers of biodiversity loss and network restructuring. Furthermore, such changes of belowground cross-trophic networks (particularly prokaryote-nematode) were significantly correlated with greenhouse gas emissions, such as decreased CO2 emissions, maintained CH4 emissions (leading to a higher CH4/CO2 ratio in deep layers), and reduced temperature sensitivity (Q10) of soil respiration. These findings underscore the critical need to protect soil biodiversity and cross-trophic networks in peatlands, particularly under the threat of climate change, to preserve peatland carbon stocks and maintain ecosystem stability. Our findings highlight that belowground cross-trophic networks are pivotal to decipher soil carbon dynamics of degraded peatlands and project the fate of peatland carbon stocks under future climate change scenarios.