Search Results (705)

Abandoned floodplains are complex landscapes in boreal permafrost regions due to diverse biogeomorphic effects that are highly modified by permafrost aggradation and degradation. We compiled biophysical properties for 150 cores at 135 sites with depths up to ~4 m on the Tanana Flats in central Alaska and developed depth profiles for bulk density, moisture, organic carbon, pH, stable isotopes, radiocarbon age, and thaw strain. We found strong associations among biophysical components but also highly variable soil properties and ecological histories. We developed a conceptual model of the transition pathways and biophysical drivers among ecosystem types. Across sites, fluvial deposition was active from 9820 to 4290 ¹⁴C YBP, eolian silt and sand deposition prevalent from 3780 to 1890 YBP, and peat accumulation from 5330 YBP to present. Due to flat topography, water impoundment in depressions, groundwater, and ecological feedbacks, ecosystem-driven permafrost has a complex history of repeated aggradation and degradation resulting in highly fragmented landscapes. Recent thermokarst features had ages ranging from 20 to 920 YBP in collapse-scar bogs and from 50 to 250 YBP in collapse-scar fens. Abandoned floodplains with rapid thermokarst provide saturated environments for robust organic accumulation, with mean soil carbon stocks in the top 3 m being similar among thermokarst bogs (133 kg/m²), fens (108 kg/m²) and permafrost plateaus (115 kg/m²). This study contributes needed information on how permafrost dynamics and ground-ice characteristics influence landscape evolution and on the vulnerability of villages built on abandoned floodplains, infrastructure, and military use of training lands in boreal lowlands. Landscape fragmentation, complex palaeoecological histories, high spatial variability, and limited deep sampling of thermokarst features, however, restrict interpretation of how permafrost loss is affecting the soil carbon balance in an area where most permafrost will disappear in this century. Full article

Improving surface-soil carbon accumulation is important for restoring reclaimed alpine mining soils. We evaluated nine treatments in the Muli mining area, Qinghai, China: a control (CK) and eight sheep manure cake rates (0.025–0.060 m³·m⁻²). Soil total organic carbon (TOC), particulate organic carbon (POC), microbial biomass carbon (MBC), dissolved organic carbon (DOC), 0–10 cm soil organic carbon (SOC) stock, carbon pool management index (CPMI), carbon fixation genes (cbbL and cbbM), and microbial community sequencing profiles were assessed. Sheep manure cake significantly increased the measured carbon fractions and CPMI. The 0–10 cm SOC stock was highest under SM3 (75.82 ± 3.52 Mg C ha⁻¹), followed by SM4 (65.99 ± 3.49 Mg C ha⁻¹), compared with 20.74 ± 1.52 Mg C ha⁻¹ in CK. cbbL and cbbM gene copy numbers peaked under SM2 (0.030 m³·m⁻²), reaching 1.51 × 10⁹ and 1.91 × 10⁷ copies·g⁻¹, respectively. Under the prespecified equal criterion-layer weights, TOPSIS ranked SM2 first; however, sensitivity analysis showed that the leading treatment changed when criterion weights were altered. Thus, SM3–SM4 showed the strongest measured surface-carbon accumulation, whereas SM2 was the highest-ranked treatment only within the adopted TOPSIS weighting scheme. Full article

Mountain catchments integrate environmental gradients, disturbance legacies, and multiscale processes that shape how ecosystem functions vary across space and time. To better understand the role of these spatial processes, we analyzed whether ecosystem-function relationships in Patagonian headwater catchments are organized according to single multifunctionality gradients or are scale-dependent on ecosystem condition and structure. We fitted three expert-constrained Bayesian networks using field-measured ecosystem functions across three spatial resolutions: catchment (n = 12), forest clusters (n = 63), and forest plots (n = 175). Predictive performance varied strongly across scales and functions: at the catchment scale, firewood volume was best predicted (r = 0.79), whereas deadwood carbon stock, tree carbon stock, vascular richness, timber volume, and soil erosion showed negative predictive correlations (r = −0.14, −0.15, −0.33, −0.44, and −0.80, respectively). Specifically, at the forest-cluster scale, firewood volume, live tree carbon stocks, soil erosion, and deadwood carbon stocks were strongly predicted (r = 0.96, 0.81, 0.77, and 0.69). At the plot scale, firewood volume, tree carbon stock, deadwood carbon stock, and understory plant diversity showed the strongest local signal (r = 0.91, 0.67, 0.67, and 0.60). Bayesian networks revealed a recurrent positive wood–carbon structure linking tree carbon stock, firewood volume, deadwood carbon stock, tree carbon sequestration, and some soil responses. In contrast, understory plant diversity was more associated with local drivers such as elevation, canopy cover, slope, and tenure, and erosion control changed direction with scale and forest development stage. Findings show that monitoring should assess carbon- and wood-production-related functions together with biodiversity and soil-related functions across nested spatial scales, because trade-offs and synergies emerge as context- and scale-dependent relationships shaped by shared environmental and management drivers. Full article

Quantifying the spatial variation in soil organic carbon (SOC) accumulation and its determining factors is vital for improving soil fertility and quality. The Fenhe River Basin is a major grain-producing area in Shanxi province in northern China, whereas the spatial heterogeneity of SOC accumulation is poorly known. Therefore, this study investigated SOC accumulation and its driving factors in arable soils across three representative counties (JL, FY, and XF) in the upper, middle, and lower reaches of the Fenhe River, respectively, which differ in climatic conditions and soil characteristics. SOC was determined using the potassium dichromate oxidation method. Results showed that both SOC content and stock were significantly lower in JL County (27–32% and 27–29% lower, respectively) compared to FY and XF. Within each county, the coefficient of variation was the highest in JL County (37.01%), indicating the highest spatial heterogeneity. Kriging interpolation indicated apparent spatial variation in SOC accumulation across the three counties. In JL, SOC was relatively higher in the northwest and southeast, while in FY, higher values occurred in the east. In XF, SOC generally decreased from north to south. The Spearman rank correlation and Random Forest analysis showed that SOC content and stock were significantly influenced by pH and cation exchange capacity (CEC), and pH had negative influences in JL County. Notably, in XF, available phosphorus and potassium, CEC, and clay proportion had positive influences on the SOC content and stock, while sand proportion had a negative relationship. These findings highlight the divergent, spatially heterogeneous nature of SOC accumulation across the Fenhe River Basin, driven by different factors. This study emphasizes the importance of specific soil management strategies in different locations to enhance carbon sequestration at the basin scale. Full article

Mediterranean ecosystems are particularly exposed to wildfire because seasonal summer drought, high temperatures, and flammable vegetation favour fire ignition and spread. Because post-fire nutrient patterns are context dependent, this observational study compared soil organic carbon (SOC) and nitrogen (N) stocks and selected physicochemical properties among sampling campaigns conducted before and after a wildfire in Vesuvius National Park (Italy). Surface mineral soil (0–10 cm) was sampled beneath two vegetation-cover categories (shrubs and trees) before fire (2015–2017) and approximately 22, 46, and 70 months after fire. Soils were analysed for pH, water content (WC), soil organic carbon concentration (Corg), total N concentration, bulk density, Corg:N ratio, and apparent fixed-depth soil organic carbon (SOC) and N stocks. Soil properties varied primarily among sampling periods, whereas vegetation category showed a more limited association. The short-term campaign was characterised by the highest pH and the lowest WC and total N concentration, whereas total N concentration and apparent fixed-depth N stock reached the highest median values during the long-term campaign. Vegetation category was associated only with WC and Corg:N ratio, which were generally higher under trees, and no significant sampling period × vegetation interaction was detected. Corg concentration and apparent fixed-depth SOC stock did not differ significantly among sampling periods. These differences cannot be attributed exclusively to wildfire or elapsed time because contemporaneous unburnt controls were unavailable and sampling period, calendar year, and spatial variability were not fully separable. The findings nevertheless show the value of jointly monitoring element concentrations and soil physical properties when assessing Mediterranean forest soils after wildfire. Full article

Soil organic carbon (SOC) monitoring is important for climate change mitigation and sustainable agricultural management, but site-specific observations and Intergovernmental Panel on Climate Change (IPCC) inventory estimates need not define the same quantity. This study quantified paired changes in laboratory-measured organic carbon concentrations in the 0–20 cm layer between spring 2023 and late autumn 2025, alongside an IPCC Tier 1 accounting benchmark. The study covered a 528.06 ha mixed-tillage commercial farm in Southeastern Lithuania, comprising 19 agricultural fields. In each campaign, 119 georeferenced composite samples were collected within fixed management-zone footprints established using the EM38-MK2 apparent electrical conductivity, Sentinel-2 Normalized Difference Vegetation Index data, and geographic information system data. Laboratory-determined total organic carbon was used operationally as SOC. The whole-farm area-weighted mean SOC concentration decreased from 3.003% to 2.866%, and area-weighted field-level paired changes showed a downward shift (Wilcoxon signed-rank test, p = 0.040), with carbon stock-determined values of 71.82 and 66.76 Mg C ha⁻¹ (difference, −5.05 Mg C ha⁻¹; field-level p = 0.049). In comparison, the IPCC Tier 1 scenario forecast yielded +0.0382 to +0.0440 Mg C ha⁻¹ yr⁻¹ for 0–30 cm under the default 20-year transition. However, the measured stocks represented the 0–20 cm layer over three growing seasons, whereas the IPCC estimates represented the 0–30 cm layer and a default 20-year transition period. Parallel presentation therefore illustrates an estimated mismatch and associated monitoring requirements compared to Tier 1 predictive performance. Continued, seasonally aligned sampling to 30 cm, campaign-specific bulk density measurement, and explicit uncertainty analysis are required to evaluate persistent SOC stock trends. Full article

Climate change is altering soil organic carbon stocks and the associated carbon fluxes of cropland ecosystems—including organic matter mineralization, microbial respiration rates, and CO₂ emissions—through shifts in temperature and moisture regimes. Ecosystem respiration, the main pathway linking terrestrial carbon pools to atmospheric CO₂, directly governs the carbon source–sink balance of croplands. As integral components of the agroecosystem, soil microorganisms directly participate in ecosystem respiration and organic carbon transformation: they contribute to heterotrophic respiration through the decomposition of organic matter, while also synthesizing new organic compounds, forming microbial biomass, and promoting organic carbon stabilization, with their community composition and metabolic activity adjusting to changing environmental conditions. To synthesize research progress and clarify how the field has evolved over the past three decades, we analyzed 290 publications (1991–2025) from the Web of Science Core Collection, combining bibliometric tools (CiteSpace 7.0, VOSviewer 1.6.20) with a structured evidence synthesis to map the research landscape, knowledge structure, hotspot evolution, and mechanistic understanding of the microbial processes underlying cropland ecosystem respiration. Publication output has grown steadily, led by China (161 publications; 55.5%) and the United States (47; 16.2%), which together account for 71.7% of the sample. The knowledge structure has coalesced around five core themes (ecosystem respiration, soil microbial communities, soil organic carbon, carbon cycling, and agricultural management), corresponding to 14 major thematic clusters (Q = 0.668, S = 0.778). Rather than strictly sequential stages, these thematic areas developed largely in parallel, with a gradual shift in research emphasis over time: early work centered on fundamental carbon-cycle processes, including soil respiration flux, organic matter decomposition, and CO₂ release, whereas later research increasingly emphasized microbial community structure, functional mechanisms, carbon use efficiency, soil organic carbon stabilization, carbon sequestration, fungal communities, and ecological stoichiometry. The responses of cropland respiration to climate change are context-dependent: under specific conditions their direction and magnitude may be dominated by a single limiting factor, whereas overall they emerge from the coordinated interplay of temperature, moisture, substrate supply, and agricultural management, within which microbial processes play a central but still incompletely resolved role. Future research should prioritize long-term in situ observations, multi-factor coupling experiments, and functional validation of microbial processes, and integrate microbial mechanisms into ecosystem models to strengthen predictions of cropland carbon cycling and support agricultural emission reduction, carbon sequestration, and sustainable management. Full article

Soil organic carbon (SOC) in mountain forest ecosystems exerts critical controls over regional carbon balance and climate feedback loops. This study collected 209 stratified topsoil (0–30 cm) samples across temperate mountain forests of Northeast China, conducted a boosted regression tree (BRT) modeling framework integrated with space-for-time substitution, and established 15 combined thermopluviometric sensitivity scenarios to simulate SOC shifts under diversified climate disturbances. Tenfold cross-validation yielded a model mean R² of 0.62, revealing mean annual temperature (MAT, RI = 35.31%) as the most influential predictor of SOC spatial variation, followed by elevation (ELE, RI = 19.11%), while single-season NDVI and soil particle fractions showed weak predictive capacity. Multi-scenario spatial simulation outputs demonstrated that simultaneous warming and aridification drastically reduce the coverage of high SOC zones, whereas increased precipitation can partially offset temperature-induced carbon mineralization losses. Terrain-mediated SOC spatial stratification remained stable across all climate backgrounds. This study quantifies the layered environmental association hierarchy of mountain SOC and generates spatially explicit modeled carbon sink projections under climate change. The terrain-dependent SOC response patterns provide operable differentiated carbon regulation guidance: humid low-lying convergence zones require long-term soil moisture conservation, while arid steep ridges need native mixed forest restoration to lift baseline carbon storage capacity, supporting precise watershed climate adaptation and targeted forest carbon sink management for temperate mountain regions. Full article

Organic amendments can alter soil structure, root development, and carbon cycling, yet their coordinated effects remain unclear. Based on a long-term field microplot experiment established in 2009, four amendment systems with equivalent annual N, P, and K inputs but differing in amendment properties and nominal annual organic-material C inputs were compared: maize straw with NPK (CS), pig manure compost with NPK (PMC), biochar with NPK (BIO), and biochar-based fertilizer (BF). After 15 years, dry-sieved aggregate distribution, CT-resolved air-filled pores (>30 μm), peanut root morphology, and easily oxidizable organic carbon (EOC), microbial biomass carbon (MBC), and dissolved organic carbon (DOC) were determined. PMC had the highest CT-resolved total and connected porosities (19.01% and 10.86%), a greater proportion of small macroaggregates, and the largest root surface area. CS produced a greater proportion and mean size of large dry-sieved aggregates and the highest bulk-soil MBC content. BIO and BF showed lower CT-resolved total porosity but greater isolated porosity, anisotropy, mean pore diameter, and pore fractal dimension (collectively termed CT-resolved macropore heterogeneity); these treatments were also associated with greater root volume or length and increased EOC and DOC contents in small macroaggregate- and microaggregate-sized fractions. Root length correlated more strongly with macropore heterogeneity than with total porosity. Because measurements were obtained once from 12 microplots, these relationships and SEM results represent exploratory associations rather than causal pathways. Overall, traditional amendments were associated with aggregation or macropore connectivity, whereas carbonized amendments were associated with greater macropore heterogeneity. BF had the highest percentage of EOC in TOC (52.45%), indicating a greater relative contribution of labile carbon, not increased stable carbon stock. Full article

Soil organic carbon (SOC) stocks are strongly influenced by land use, vegetation condition and climate, particularly in heterogeneous mountain catchments. This study quantified SOC stocks and simulated long-term SOC dynamics in the Çapakçur micro-catchment, eastern Türkiye, by integrating field assessment, geostatistical prediction, uncertainty analysis, inverse RothC calibration and scenario modelling. A total of 428 soil samples were collected from the 0–30 cm layer across forest, degraded forest, and pasture areas. SOC stocks were calculated from SOC concentration, bulk density and soil depth, and spatially predicted using ordinary kriging of log-transformed SOC stocks. RothC was calibrated for each land-use class to estimate the annual carbon inputs required to maintain observed SOC stocks, followed by 50-year restoration and climate-sensitivity simulations. SOC stocks ranged from 7.69 to 247.68 Mg C ha⁻¹, averaging 55.52 Mg C ha⁻¹. Forest had the highest mean SOC stock (78.5 Mg C ha⁻¹), followed by pasture (55.9) and degraded forest (50.2 Mg C ha⁻¹). Required annual carbon inputs were 5.17, 4.58 and 3.29 Mg C ha⁻¹ yr⁻¹, respectively. Increasing degraded forest carbon inputs to forest-equivalent levels increased SOC by 14.76 Mg C ha⁻¹ over 50 years, equivalent to 37.77 Gg C or 138.49 Gg CO₂eq at the catchment scale. A stronger restoration scenario increased this potential to 63.77 Gg C. Warming caused SOC losses, with +2 °C reducing catchment SOC by 56.78 Gg C. These findings demonstrate the potential of degraded forest restoration for SOC sequestration while highlighting the vulnerability of long-term SOC gains to climate warming. Full article

Post-fire plantations play a crucial role in recovering carbon stocks, yet how carbon is partitioned among vegetation, litter, and soil pools during stand growth dynamics remains insufficiently resolved for Quercus acutissima plantations. Forest ecosystems play a crucial role in the global carbon cycle. This study quantified carbon-storage allocation and identified stand characteristics and soil factors associated with carbon recovery in fire-affected Q. acutissima plantations. Using a chronosequence design, we compared five stand-age classes (4, 10, 25, 45, and 50 years) on Huangfu Mountain, China, and measured carbon stocks in tree organs, understory vegetation, litter, and the 0–30 cm soil layer. Ecosystem carbon stock increased from 31.64 t ha⁻¹ in 4-year-old stands to 230.66 t ha⁻¹ in 50-year-old stands, representing a 629% increase. Soil was the dominant carbon pool, with 0–30 cm soil carbon rising from 25.32 to 126.56 t ha⁻¹ (a 400% increase). The contribution of soil carbon to total ecosystem storage declined from approximately 80% in 4-year-old stands to 55% in 50-year-old stands, indicating a shift in allocation toward vegetation biomass over time. Carbon accumulation was primarily concentrated in the 0–10 cm layer. Tree basal area was significantly associated with ecosystem carbon stocks, identified as a key structural factor linked to carbon accumulation through potential direct and indirect pathways involving light availability and soil carbon. Soil organic matter and nitrogen were also positively correlated with carbon accumulation. These findings suggest that stand development and topsoil carbon formation are closely linked to post-fire carbon recovery processes. Future management measures should optimize stand density, maintain soil fertility, and protect surface carbon to enhance long-term carbon sequestration. Full article

Understanding the dynamics of carbon (C), nitrogen (N), and phosphorus (P) stoichiometry and C stocks along a stand development chronosequence has been extensively studied in forest ecosystems. However, despite the global economic and ecological importance of apple orchards, such knowledge remains limited for these intensively managed perennial agroecosystems. We examined C, N, and P concentrations and stoichiometric ratios in tree tissues (root, stem, branch, foliage) and soils (0–100 cm depth), as well as ecosystem C stocks, across a chronosequence of 4, 8, 12, and 16 yr old Malus pumila orchards in the eastern Yan Mountains, Hebei Province, North China. The results showed that C concentrations exhibited no consistent age-dependent trend in tree tissues. In contrast, N and P concentrations in all tree tissues decreased significantly with stand age, while their C:N and C:P ratios increased. The leaf N:P ratios suggested progressive P limitation as orchards aged. In soil, C, N, and P concentrations first decreased and then increased along the chronosequence, with the highest values observed in the 16 yr stands. This U-shaped trajectory reflected the dynamic interplay between stand development and anthropogenic management. Intercropping and intensive fertilization in the 4 yr orchards initially elevated soil nutrient levels, while the cessation of intercropping and nutrient removal via fruit harvesting in the 8 yr stands led to a decline. Thereafter, accumulation of litter decomposition and root turnover, combined with continued organic matter inputs, progressively replenished soil nutrient pools in the 12 and 16 yr stands. The total ecosystem C stocks ranged from 70.80 to 136.13 Mg ha⁻¹, initially declining from 4 to 8 years and then increasing at 12 and 16 years, with soil contributing 84.7–99.7% of the total. Plant and soil nutrient concentrations showed predominantly negative correlations, indicating weak coupling between tree and soil nutrient pools. Our findings demonstrated that stand age profoundly influenced C:N:P stoichiometry and C stocks in apple orchard ecosystems and that prolonged orchard development enhanced both tree biomass C and soil C stocks. These results provide a scientific basis for nutrient optimization and sustainable management of apple orchards in temperate regions. Full article

Agricultural lands in Russia are increasingly being converted into fallow areas, making the study of potentially mineralizable carbon (PMC) in fallow soils essential for understanding post-agrogenic ecosystem functioning. This study provides a comparative assessment of the spatial and temporal dynamics of PMC in soils of the Leningrad and Novgorod regions (Bankovo, Belogorka, and Borovichi sites) under different land-use types, including fallows of various ages, arable, garden, pasture, hayfield soils, and secondary forests. Total carbon content was determined by high-temperature dry combustion, while basal respiration was measured using a standard incubation method. PMC parameters were estimated using biokinetic fractionation of soil organic matter (SOM), and cumulative carbon release was calculated as the sum of emissions over the incubation period. The highest basal respiration values among the studied fallow soils were observed in fallow soils at the Bankovo site (1.44–1.66 µg CO₂–C g⁻¹ h⁻¹). Carbon stocks in most fallow soils were lower than those of the corresponding background soils, although the magnitude of differences varied among sites. Both the size of the PMC pool and its mineralization rate varied among fallow soils depending on post-agrogenic succession, vegetation type, and site-specific environmental conditions. The highest cumulative C-CO₂ production was recorded in degraded pasture soils and secondary forests at Borovichi. Restorative ecosystems generally showed higher carbon-mineralizing activity than arable and garden soils, although turnover characteristics varied among sites. Region-specific patterns related to parent material and environmental conditions were identified. Even after long-term fallowing (up to 120 years), several soil properties remained different from background conditions, indicating prolonged and site-dependent recovery of organic matter dynamics. Full article

Soil organic carbon (SOC) stock is a key component of terrestrial ecosystems, playing a critical role in climate regulation and ecosystem productivity. Despite its economic importance, the impacts of the expansion of khat (Catha edulis) cultivation at the expense of other land uses and its intensive management practices on the depletion of soil carbon content are overlooked in Eastern Ethiopia. This study aimed to estimate and map SOC stocks using multispectral Sentinel-2 and RapidEye imagery, combined with environmental, soil, and topographic variables, across khat-dominated landscapes in the Haramaya District of Eastern Ethiopia. A total of 88 soil samples were collected and analyzed to quantify SOC stocks. Random Forest (RF) and extreme gradient boosting (XGBoost) algorithms were employed to predict SOC stocks. The dataset was stratified into training (70%) and an independent validation (30%) subset. Model development was performed using five-fold cross-validation on the training dataset, while final performance was assessed on the independent validation set using the coefficient of determination (R²), root mean square error (RMSE) and mean absolute error (MAE). Laboratory-measured SOC stocks ranged from 24.99 to 65.94 Mg C ha⁻¹, with a mean value of 36.88 Mg C ha⁻¹. The predicted spatial SOC stocks ranged from 30.4 to 50.4 Mg C ha⁻¹ using RapidEye data and from 32.8 to 51.5 Mg C ha⁻¹ using Sentinel-2, with Sentinel-2 producing slightly higher mean estimates. The lowest SOC stocks were consistently observed in bare, grass, and shrub land-use types across both datasets. RF demonstrated superior performance compared with XGBoost, achieving moderate predictive performance for both the RapidEye (R² = 0.56, RMSE = 5.91 Mg C ha⁻¹) and Sentinel-2 (R² = 0.42, RMSE = 6.90 Mg C ha⁻¹) datasets. This result indicates that RF provided greater robustness for SOC stock prediction under the heterogeneous environmental conditions of khat-dominated agricultural landscapes. Topographic and soil-related variables, particularly the Topographic Wetness Index (TWI), land surface temperature (LST), and clay content, were identified as the most influential predictors in both models. Although less consistent, remote sensing indices such as GNDVI, BSI, and NDWI also contributed to SOC prediction. While both sensors proved effective for SOC mapping, a measurable sensor-related effect was observed. The findings demonstrate the effectiveness of integrating multisource remote sensing, environmental, soil, and topographic variables with machine learning for SOC stock mapping in khat-dominated landscapes. This approach provides valuable spatial information to understand SOC variability and support sustainable land management and climate change mitigation strategies in Eastern Ethiopia. Full article

Cold alpine salt-affected soils may retain carbon through mineral protection or suppressed microbial decomposition, but these processes remain difficult to distinguish. We measured soil physicochemical properties, four extracellular enzyme activities, soil organic carbon (SOC), and its dissolved (DOC), particulate (POC), and mineral-associated (MAOC) fractions across five soil types on the Qiangtang Plateau. Multivariate analyses and five XGBoost models interpreted using Shapley additive explanations (SHAP) characterized carbon-enzyme associations and identified leading predictors and nonlinear response transition points. Model performance varied among response variables (CV-R² = 0.4094–0.8815). Soda (SD) soil had a distinct carbon-pool composition, and no significant carbon-enzyme correlations remained after Benjamini–Hochberg correction. pH was the leading predictor of SOC and its fractions, whereas total nitrogen and total phosphorus ranked highest for overall enzyme activity. The fitted SHAP contributions changed from negative to positive between pH 8.50 and 9.00 for the carbon variables and at a total nitrogen concentration of 0.71 g·kg⁻¹ for enzyme activity. These model-dependent transition points indicate that carbon-pool restructuring and nutrient-related changes in enzyme activity occur over different environmental ranges. SD soil contained the highest carbon concentrations but the smallest MAOC proportion and the largest POC and DOC proportions, indicating relative enrichment of labile carbon fractions. By jointly analyzing carbon fractions and enzyme activity within an interpretable XGBoost-SHAP framework, this study helps distinguish high carbon stocks from stable sequestration and shows why total SOC alone may overestimate long-term carbon stability in alpine salt-affected soils. Full article