Establishing a suitable and useful soil quality index (SQI) is the key to accurately evaluating changes in soil quality (SQ) under different land use types. In the present study, a suitable and useful SQI using a minimum data set (MDS) with two scoring methods (linear scoring method and nonlinear scoring method) and two additive models (simple additive model with same weighting value and weighted additive model with significant different weighting value) was established to compare SQ under different land uses in Longtan valley. Soil samples were collected under one dryland (DRYL), one paddy (PADD), one orchard (GRA), and one natural forest (FORE), and 13 soil properties were measured. The four land use types had the same soil type and similar environmental conditions. Land use types had significant effects on the measured 12 soil properties. The top two principal components in Principal Component Analysis were chosen, and their cumulative variance was more than 90%. Soil indicators of soil labile carbon, C/N ratio, and microaggregates were chosen as members of MDS in this study. Significant (p < 0.001) positive correlations among the four establishing SQIs were found. The values of the sensitive index ranged from 47.17% to 82.12% for the four SQIs, and the SQI established using the nonlinear scoring method and weighted additive model (SQI-NLW) had the highest values. Among the four land use types, the four SQIs had similar change trends, and the average values of SQ under FORE (0.73) and PADD (0.68) were significantly higher than those under GRA (0.54) and DRYL (0.43). These results indicated that the SQI-NLW was an effective and precise tool to assess SQ under different land uses in similar regions, and the FORE and PADD were the suitable land use types for the sustainable use of soils in karst regions.

As a critical agroforestry crop in Southern China, Moso bamboo, maintains regional timber security and bamboo shoot production, with its net ecosystem productivity (NEP) directly determining dry matter accumulation and economic yield. This study integrates 2024 continuous flux observations with XGBoost and SHAP explanations to characterize the subtropical bamboo forest carbon budget and its nonlinear driving mechanisms. The results show a weak carbon sink in 2024 with an annual cumulative NEP of 120 g C m⁻², as high respiration of 860 g C m⁻² limited organic matter conversion by consuming nearly 88% of the 980 g C m⁻² total primary production. The peak production period during May and June was offset by growth stagnation in August, caused by extreme heat and drought. Net radiation served as the primary driver, with a positive contribution threshold of 75.28 W m⁻², whereas precipitation exceeding 1.85 mm or air temperatures over 17.85 °C hindered carbon accumulation through radiation attenuation and metabolic heat loss. Strong radiation–precipitation interactions confirm that water’s impacts on yield are deeply contingent upon radiation backgrounds. These nonlinear regulatory pathways provide a scientific foundation for stabilizing bamboo forest productivity through synergistic water-radiation management and structural optimization during extreme climate events.

Surface mining activities cause severe disruption to ecosystems, resulting in the substantial destruction of surface vegetation, the loss of soil organic carbon stocks, and a decrease in the ecosystem’s ability to sequester carbon. The ecological restoration of mining areas has been found to significantly enhance the carbon storage capacity of ecosystems. This study evaluated ecological restoration strategies in Chongqing’s Tongluo Mountain mining area by integrating GF-6 satellite multispectral data (2 m panchromatic/8 m multispectral resolution) with ground surveys across 45 quadrats to develop a quadratic regression model based on vegetation indices and the field-measured biomass. The methodology quantified carbon storage variations among engineered restoration (ER), natural recovery (NR), and unmanaged sites (CWR) while identifying optimal vegetation configurations for karst ecosystems. The methodology combined the high-spatial-resolution satellite imagery for large-scale vegetation mapping with field-measured biomass calibration to enhance the quantitative accuracy, enabling an efficient carbon storage assessment across heterogeneous landscapes. This hybrid approach overcame the limitations of traditional plot-based methods by providing spatially explicit, cost-effective monitoring solutions for mining ecosystems. The results demonstrate that engineered restoration significantly enhances carbon sequestration, with the aboveground vegetation biomass reaching 5.07 ± 1.05 tC/ha, a value 21% higher than in natural recovery areas (4.18 ± 0.23 tC/ha) and 189% greater than at unmanaged sites (1.75 ± 1.03 tC/ha). In areas subjected to engineered restoration, both the vegetation and soil carbon storage showed an upward trend, with soil carbon sequestration being the primary form, contributing to 81% of the total carbon storage, and with engineered restoration areas exceeding natural recovery and unmanaged zones by 17.6% and 106%, respectively, in terms of their soil carbon density (40.41 ± 9.99 tC/ha). Significant variations in the carbon sequestration capacity were observed across vegetation types. Bamboo forests exhibited the highest carbon density (25.8 tC/ha), followed by tree forests (2.54 ± 0.53 tC/ha), while grasslands showed the lowest values (0.88 ± 0.52 tC/ha). For future restoration initiatives, it is advisable to select suitable vegetation types based on the local dominant species for a comprehensive approach.

Enhanced rock weathering is regarded as a promising carbon dioxide removal method because of its potential to sequester soil inorganic carbon (SIC). However, the influence of enhanced rock weathering on changes in soil organic carbon (SOC) content, fractions and stability remains poorly understood. A randomized block experiment design employing five basalt addition rates (0 (CK), 2.5, 5, 10 and 20 kg·m⁻²) and four replicates was designed to investigate the influences of basalt addition on SOC and SIC content and stocks, SOC fractions and SOC stability in subtropical cropland, where Zea mays L. and Brassica juncea (L.) Czern were annually rotated. Soil samples were collected from depths of 0–15 cm and 15–30 cm one year after the addition of basalt. The results showed that enhanced rock weathering increased the total carbon content and stock by increasing both the SOC and SIC in a one-year field experiment. Compared with CK, basalt addition rates of 2.5, 5, 10 and 20 kg·m⁻² increased the SOC stock by 16%, 23%, 21% and 19%, respectively, and the SIC stock by 37%, 30%, 35% and 32%, respectively. The labile carbon fraction was the primary organic carbon fraction, which accounted for more than 40% of the total SOC content. Enhanced rock weathering altered the content of the very labile carbon fraction due to its high sensitivity to basalt addition, but had little effect on the stable carbon fraction content in a one-year field experiment. Compared with CK, basalt addition increased the very labile carbon fraction content by 12% and 46%, respectively, according to samples from depths of 0–15 cm and 15–30 cm. Under basalt addition rates of 2.5, 5, 10 and 20 kg·m⁻², the SOC stability index was 26%, 21%, 17% and 20%, respectively, lower than that under the 0-addition rate in a one-year field experiment, which was 1.63, indicating that enhanced rock weathering reduced the SOC stability. Our findings indicated that enhanced rock weathering increased soil carbon (both of SOC and SIC) sequestration, but reduced the SOC stability in a one-year field experiment in subtropical croplands. These observed trends in changes in soil carbon will be further tested and evaluated as the experiment continues in the future.

Leaf functional traits are widely used to describe interspecific variation in plant resource-use strategies and photosynthetic performance. We examined leaf traits and photosynthetic characteristics in 21 common woody species (11 tree and 10 shrub species; two individuals per species) sampled from subtropical secondary-forest vegetation in Chongqing, southwestern China. Maximum net photosynthetic rate (Pnmax), apparent quantum yield (AQY), light saturation point (LSP), and light compensation point (LCP) were derived from species-level fitted light-response curves. Among the 17 species with accepted fits, Pnmax ranged from 3.35 to 12.93 μmol m⁻² s⁻¹. Estimates for Jacaranda mimosifolia and Vitex negundo var. cannabifolia were extrapolated beyond the measured irradiance range (14.66 and 16.23 μmol m⁻² s⁻¹, respectively). No finite Pnmax was defined for Osmanthus fragrans or Rhododendron simsii because β was estimated at zero; their fitted asymptotic net photosynthetic rates were 3.33 and 4.29 μmol m⁻² s⁻¹, respectively. Nitrogen content per unit leaf area (Narea) ranged from 0.46 to 2.28 g m⁻². Trait analyses used species means as independent observations. Spearman correlations were evaluated with Benjamini–Hochberg false discovery rate correction, and prespecified candidate regression models were compared using adjusted R², AICc, and leave-one-species-out cross-validation. After FDR correction, Narea was positively associated with Pnmax (Spearman’s ρ = 0.673, q = 0.0137) and AQY (ρ = 0.666, q = 0.0137). No statistically significant differences in photosynthetic parameters remained between trees and shrubs after correction for multiple testing. Among the prespecified candidate models, the Narea-only model had the lowest AICc for Pnmax (adjusted R² = 0.440). For AQY, the Narea-only and Narea + LA models had similar support (ΔAICc = 0.41), and the data did not clearly distinguish between them. Adding LA did not significantly improve either model in the incremental F-tests (p = 0.486 for Pnmax and p = 0.135 for AQY). The positive Pnmax–Narea association remained after controlling for LMA using partial Spearman correlation (partial ρ = 0.762, p < 0.001), indicating that shared LMA normalization alone did not explain the association in this dataset. These species-level associations are observational and do not establish causation.