• High-resolution field monitoring of soil CO 2 in soybean with varied fertilization. • HYDRUS-1D with SOILCO 2 module applied for coupled transport–production simulation. • Organic amendment enhanced microbial respiration, especially after rainfall events. • WLR gas diffusivity model reproduced soil CO 2 profiles better than Millington–Quirk model. • Gas diffusivity choice strongly affected seasonal CO 2 predictions in agricultural soils. Soil CO 2 dynamics play a crucial role in the global carbon cycle, particularly in agricultural soils where management practices influence CO 2 dynamics. This study quantified soil CO 2 concentrations and fluxes under different fertilization treatments (chemical vs. organic) in a soybean field and evaluated the performance of the SOILCO2 model with different gas diffusivity models. Soil moisture, temperature, and CO 2 concentrations were continuously monitored at multiple depths throughout the growing season. The results showed that microbial and root-associated CO 2 production were enhanced in the presence of crops and organic matter, with microbial activity significantly increasing the CO 2 concentrations, particularly after rainfall events. Gas diffusivity, a critical factor in CO 2 transport modeling, was evaluated using the Millington–Quirk (MQ) and Water Linear Reduction (WLR) models. The WLR model with fitted parameter provided better agreement with measured gas diffusivity and observed CO 2 profiles as compared to the MQ model. Sensitivity analysis demonstrated that an accurate representation of gas diffusivity is essential for a realistic simulation of soil CO 2 behavior. This study highlights the importance of high-resolution field monitoring and model calibration for improving CO 2 transport predictions, and supports the use of the WLR model for agricultural soils with varying textures and moisture conditions.

• Warming enhances evaporative fractionation and reduces soil water retention. • Supra-permafrost and ground ice increasingly dominate water sources under warming. • Dual-track warming restoration boosts alpine meadow water–soil resilience. This study quantified the dynamics and sources of soil moisture in alpine meadows under experimental warming during 2023–2024 at the observation and research Station of eco-hydrology and national park by stable isotope tracing in Qilian Mountains. Except for the shallow layer (0–10 cm) under warming plus increased precipitation (ZWZY), overall soil water content in 2024 exceeded that in 2023; in 2023, all depths in the warming treatment (ZWCK) were drier than the control (CKCK). Soil-water isotopes showed evaporative enrichment from June (δ 18 O ≈ −9.88 ‰; δ 2 H ≈ −77.41 ‰) to the peak-heat period in July (≈ −6.70 ‰; ≈ −40.46 ‰), followed by monsoon-driven depletion and isotopic convergence in August. The summer soil–water line slope (≈ 6.64) was lower than the local meteoric water line (≈ 7.71), indicating non-equilibrium evaporation, whereas rapid post-storm isotope shifts between July and October point to precipitation-pulse-dominated recharge. Among environmental controls, soil temperature was the primary driver of isotopic variability, with precipitation as a secondary control. Mechanistically, piston flow contributed ≥ 85 % in June–July and October, while heavy rainfall increased preferential flow to 38–48 % in August–September. We propose a warming-responsive restoration framework for alpine meadows: canopy retention to damp heat load, three-tier water management (surface–root zone–subsoil), and targeted night-time water supplementation to buffer future climate uncertainty.

Microbe-mediated soil phosphorus (P) mobilization and immobilization directly and strongly influence soil P availability and plant P uptake. Quantifying microbe-mediated soil P mobilization or immobilization driven by changes in soil carbon (C):P stoichiometry is a major challenge in soil science. We hypothesized that a decrease in the soil C:P ratio would decrease microbe-mediated P mobilization and immobilization and increase microbial biomass P (MBP) turnover. Herein, we assessed the quantitative relationship between the soil C:P ratio and microbe-mediated P mobilization and immobilization as well as MBP fluxes using 32P-labeling with decreasing soil C:P ratios. Results revealed that microbe-mediated gross P immobilization decreased by 54 % with a decrease in the soil C:P ratio, whereas gross and net P mobilization and MBP turnover increased by 141 %, 252 %, and 790 %, respectively. These findings indicate that a decrease in the soil C:P ratio suppresses microbe-mediated gross P immobilization while stimulating gross and net P mobilization, thereby enhancing P bioavailability. These findings provide a nature-based strategy through which soil microbial activity and P fluxes can be quantitatively adjusted by altering the C:P ratio in calcareous soils.

• A dataset comprising Rock-Eval® and MIR data on > 2,000 samples have been assembled. • >1800 results were used to build a model to predict stable SOC in French soils. • The proportion of stable carbon can be efficiently predicted by MIR. • Transferring the model to other (German and Finnish) datasets degrades predictions. • Large scale deployment would require calibration transfer and local calibrations. Recent work has shown that it is possible to quantify the proportion of centennially stable soil organic carbon (SOC) by using Rock-Eval® thermal analysis results as input variables for PARTYsoc, a learning model calibrated on long term experiments data. This method of quantifying SOC biogeochemical stability holds promise for improving projections of SOC stock evolutions. Here, we assessed the potential of mid-infrared spectroscopy (MIR) as a lower-cost, higher-throughput technique to facilitate its wide-scale deployment. We compiled a spectral library of over 1,800 records obtained through the scanning of samples from the French Réseau de Mesure de la Qualité des Sols to calibrate a model using MIR data to predict the proportion of centennially stable SOC. The model gave accurate predictions (RMSE = 0.06, RPD = 2.21, RPIQ = 3.26), suggesting that MIR spectra contain relevant information on SOC biogeochemical stability. We then tried to transfer this model directly to datasets acquired using another MIR spectrometer on German and Finnish soil samples. The accuracy of the predictions was degraded, even when using the CORAL data alignment method to harmonise the different spectral datasets. Our results show that it is possible to predict the proportion of centennially stable carbon determined by the PARTYsoc model using MIR spectroscopy. However, we found that the transfer of such models to different soils, scanned with different instruments or different protocols, is difficult. Large-scale deployment of such models will require careful calibration transfer, probably associated to local calibration within a similar spectral space.

Globally, soil’s contribution to ecosystem services is integral to achieving several Sustainable Development Goals (SDGs), including food security (SDG 2), water quality (SDG 6), and climate action (SDG 13). At EU level, EU Mission “A Soil Deal for Europe” seeks to restore soil health by 2030. This study, in view of assessing soil health, introduces an integrated assessment of soil ecosystem services (SESs) using the ARMOSA process-based model. ARMOSA evaluates SESs, such as Food provisioning, Water regulation, Carbon Sequestration & Climate Regulation, and Nutrient cycling, through simulations that account for diverse pedoclimatic conditions and management practices. By emphasizing multiple integrated indicators over single-point measurements, this approach captures dynamic soil-plant-atmosphere interactions, offering a nuanced framework for soil health assessment. The results demonstrate the potential of comprehensive SES evaluations to support sustainable soil management and inform strategies to meet local and global soil health goals. • This study applies a process-based model for an integrated assessment of SESs. • The presented approach captures dynamic soil-plant-atmosphere interactions. • It demonstrates the potential of SES bundles evaluations to Soil Health definition.

• Chinese milk vetch incorporation (CVI) increases net N mineralization rate. • CVI reduces potential nitrification rate and COMX clade A amoA gene and transcript. • DNA-SIP reveals that COMX clade A plays a critical role in soil nitrification. • CVI reduces COMX community richness and reshapes COMX community structure. • CVI enhances complexity and deterministic processes in COMX community assembly. Chinese milk vetch ( Astragalus sinicus L.) incorporation (CVI), straw return (SR), and nitrogen reduction (NR) are common agricultural practices, but their impacts on soil nitrogen (N) cycling processes and associated microbial communities remain poorly understood. In this study, CVI, SR, and NR effects on soil net N mineralization and potential nitrification rates, the abundance/activity of ammonia oxidizers, and comammox Nitrospira (COMX) community structure were examined. While CVI significantly increased the net N mineralization rate and acid-hydrolysable N fraction, SR and NR did not affect these values. At the same time, CVI decreased the potential nitrification rate and reduced COMX clade A amoA gene and transcript copy number, whereas SR and NR increased amoA gene copy number. DNA stable isotope probing (DNA-SIP) revealed that COMX clade A played a critical role in nitrification. COMX community richness was reduced by CVI and increased by SR. COMX community structure was also shaped by CVI, with soil NH 4 + -N and pH acting as two key moderators of these effects. Additionally, CVI increased the influence of deterministic processes on COMX community assembly. Together, these findings indicate that CVI enhances N mineralization while simultaneously reducing nitrification, potentially improving N retention. These results enhance our mechanistic understanding of N cycling, allowing for the optimization of fertilization strategies to balance agronomic productivity with environmental sustainability.