Microbial decomposition of soil organic carbon (SOC) is a major source of atmospheric CO2 and a key component of climate-carbon feedbacks. Understanding how SOC mineralization responds to temperature is essential for improving climate projections. Here, we compiled a global dataset of laboratory incubation experiments measuring SOC mineralization across diverse soils and temperature regimes. The dataset reveals that 84 % of samples originated from surface soils (0-30 cm), and 50 % of incubations lasted fewer than 50 d. Incubation temperatures ranged from -10 to 60 degrees C, with temperature intervals used to estimate temperature sensitivity (Q10) spanning 2-40 degrees C; notably, 81 % of Q10 estimates were based on intervals exceeding 5 degrees C. Moreover, in 61 % of cases, the lower incubation temperature for Q10 estimation differed from the mean annual temperature at the sampling site by more than 5 degrees C, indicating a mismatch with in situ conditions. Our analysis highlights critical gaps in current experimental designs, particularly the underrepresentation of subsoils (>30cm) and the use of temperature ranges that deviate from field conditions. We further evaluated the ability of 16 temperature response functions used in 69 land surface and/or carbon models to capture SOC mineralization patterns. Most models failed to reproduce empirical temperature response, especially at higher temperatures, albeit multi-term exponential functions showed relatively better performance. By coupling our dataset with a two-pool carbon model, we found that external environmental constraints and the intrinsic temperature response (including SOC decomposability and microbial processes) similarly influence the temperature sensitivity of SOC mineralization at the global scale, with their relative importance varying across ecosystem types. Our findings underscore the need for incubation experiments that better represent field conditions - both in depth and temperature range - and call for improved model parameterizations to enhance SOC feedback projections under future climate scenarios. The dataset is archived and publicly available at 10.6084/m9.figshare.25808698 (Zhang et al., 2025).

Soil organic carbon (SOC) sequestration is vital for food security and climate mitigation. However, its long-term response to fertilisation remains unclear. Using the 180-year Broadbalk Experiment (the world's longest-running fertilisation trial; Rothamsted, UK), combined with 14C labelling and metagenomics, we identified fundamentally distinct mechanisms of SOC accumulation: a microbially mediated dual pathway under organic fertilisation versus a resource-limited pathway under inorganic fertilisation. Sustained organic inputs matched inorganic fertilisers in maintaining crop yields while increasing total SOC by 160% (relative to a no-fertilisation control), far exceeding the 26% gain under inorganic fertilisation. Mechanistically, the continuous supply of labile organic matter provided an energetic surplus, allowing copiotrophic microbial communities with high carbon use efficiency to reduce investment in energy-intensive enzyme synthesis. This metabolic efficiency facilitated a dual-pathway expansion, elevating dynamic particulate organic carbon (POC) from 1.4 to 7.5 g kg-1, while microbial assimilation and necromass accumulation concurrently increased mineral-associated organic carbon (MAOC) from 6.8 to 21.5 g kg-1. Conversely, inorganic fertilisation induced an oligotrophic 'mining' strategy, in which microorganisms upregulated the degradation of complex organic matter under carbon-limited conditions, restricting sustained SOC accumulation primarily to the MAOC pool. A global meta-analysis of field experiments (0-120 years) corroborated these temporal trajectories across diverse soil types, showing that SOC under organic fertilisation increases in a time-dependent manner, reaching a 77% gain after 80 years (three-fold greater than under inorganic inputs). Overall, organic fertilisation enhances total SOC via POC and MAOC accumulation, whereas inorganic fertilisation mainly increases MAOC. Long-term SOC persistence depends not only on carbon inputs, but also on microbial community traits and necromass dynamics, suggesting that aligning nutrient inputs with these biological mechanisms is critical for sustainable carbon sequestration.

Soil organic carbon (SOC) underpins agricultural sustainability and the terrestrial carbon cycle, yet its vertical distribution and stabilization across soil depth remain poorly constrained at large spatial scales. Here, we present a nationwide, depth-resolved dataset of SOC and mineral-associated organic carbon (MAOC)-the more persistent SOC fraction-from 365 dryland cropland sites across China, sampled to 2 m depth. Contrary to the classic model of exponential SOC decline, 46% of profiles exhibited uniform or increasing SOC and MAOC with depth, highlighting a substantial role of subsoil carbon. MAOC accounted for more than half of total SOC in most layers, but its relative contribution declined below 1 m, challenging the assumption that subsoil carbon is inherently more stable. Clay + silt content was the strongest predictor for SOC, MAOC, and MAOC/SOC across depths, while vegetation productivity, a proxy for carbon inputs, was positively associated with all three. The influence of clay + silt on MAOC accumulation weakened with depth, and the positive interaction between vegetation productivity and clay + silt weakened or diminished from surface soils to deeper layers. These patterns indicate a transition from joint regulation by carbon inputs and mineral surfaces in surface soils toward an increasingly input-limited regime in deeper layers, as inferred from the depth-dependent changes in the relative importance of vegetation productivity and fine particle content. National mapping estimated ~19.9 Pg SOC stored within the 0-2 m layer in China's dryland croplands, with 75% below 0.3 m and 60% stabilized as MAOC. These results provide a benchmark for depth-explicit SOC accounting and highlight the importance of aligning carbon inputs with soil mineralogy to enhance whole-profile carbon stabilization and climate mitigation.

Pedogenic carbonates (PC) constitute an important yet underrecognized inorganic carbon pool in dryland soils. However, quantitative understanding of how PC formation responds to multiple environmental factors remains limited. Using 13CO2-labelled incubations of a calcareous agricultural soil, we quantified newly precipitated PC (PCnew) and its formation rate (PCrate) over six months across gradients of Ca2+ supply, CO2 partial pressure (pCO2), soil moisture, and enzyme additions. Calcium availability was the dominant driver, increasing PCnew by up to 33-fold and PCrate by 26-fold relative to the baseline treatment. Elevated pCO2 increased PC formation by 38% on average, primarily by accelerating early-stage CaCO3 precipitation. Notably, the Ca2+ effect intensified over time, whereas the influence of CO2 was the strongest initially and declined thereafter, revealing a clear temporal hierarchy of controls. Soil moisture modulated these responses through transport and diffusion constraints, while nitrogen and enzyme additions produced only transient or context-dependent effects. These results indicate that PC formation reflects condition-dependent coupling between biogenic CO2 supply and Ca-mediated precipitation. Short-term dynamics are governed by CO2-driven kinetic supersaturation, whereas sustained accumulation increasingly depends on Ca2+ availability. This temporal decoupling provides a process-based framework to interpret inorganic carbon dynamics in calcareous agroecosystems and to design management strategies that synchronize Ca supply with biogenic CO2 pulses.

Warming and elevated CO2 (eCO2) are two potentially opposing climate-carbon (C) feedback mechanisms that modulate the magnitude of the land C sink, with warming decreasing and eCO2 increasing C sequestration. However, their net effect on soil organic C (SOC)-the largest terrestrial C stock-remains uncertain. Here, we quantify how warming, eCO2, and their interactions influence SOC by using 5558 paired observations from 1392 global studies across ecosystem types. Our study shows that warming reduces SOC by 8.0%, primarily by suppressing aboveground C inputs (-1.0%) and decreasing microbial C use efficiency (-9.9%). Concurrent warming and eCO2 increase SOC by 7.6%-a synergistic effect larger than eCO2 alone (+4.8%), primarily contributed by croplands. This outcome may result from increases in plant C inputs and soil nitrogen availability under eCO2, which facilitate microbial C assimilation and necromass formation (+3.9%). These processes promote the accumulation of mineral-associated C (+9.9%) and offset the negative effects of warming. The combined effect of warming and eCO2 is projected to increase SOC by 27.4 Pg C by 2100. Our findings highlight that synergistic interaction between warming and eCO2 increases SOC sequestration and enhances SOC stability under future climate change.

Abstract. Soil freeze-thaw cycles (FTCs) exert substantial effects on the mineralization of soil organic carbon (SOC), particularly in high-altitude and -latitude cold regions. Ongoing climate change is altering FTC frequency and duration, yet the responses of SOC mineralization to such changes remain poorly understood, limiting our ability to predict carbon cycle-climate feedbacks. Here, we incubated soils from two depths across three sites to quantify how FTC regimes regulate SOC mineralization and explore underlying controls. Across all treatments, we observed a pronounced thaw-induced pulse of CO2 release, but more frequent freeze-thaw cycles led to more cumulative CO2 release, given the same length of cumulative thaw days. Across treatments, mineralization was most strongly correlated with DOC and hydrolytic/oxidative enzyme activities, while being suppressed by mineralogical (free and amorphous Fe/Al oxides) and physical (aggregate-protected carbon) constraints. Partial correlations and path analyses revealed that DOC was the single most consistent predictor of mineralization, retaining its influence even when enzymatic, substrate quality, or mineralogical variables were controlled. Subsoil SOC mineralization was additionally shaped by molecular carbon composition and mineral protection. These findings reveal a vertical shift from DOC-mediated substrate accessibility to molecularly and physically constrained decomposition. Accounting for these depth-specific mechanisms will improve prediction of SOC-climate feedbacks under FTC shifts due to climate change.

The Qinghai-Tibet Plateau (QTP), often referred as Earth's "Third Pole," is warming nearly twice the global average, potentially amplifying carbon-climate feedbacks to a greater extent than in most other regions. However, substantial uncertainties remain regarding the magnitude, spatial distribution, and environmental controls of the region's soil organic carbon (SOC) stocks. Here we compiled a comprehensive dataset of 2442 soil profiles across the QTP and integrated it with high-resolution (90 m) environmental covariates to generate spatially explicit, depth-resolved SOC stock estimates using machine learning models. Independent validation using newly collected whole-profile SOC measurements (n = 53) demonstrated substantially improved predictive accuracy compared to existing global and regional mapping products (e.g., SoilGrids, HWSD, and WISE). Specifically, our estimates reached coefficients of determination (R2) of 0.63 and 0.49 for the 0-0.3 m topsoil and 0.3-1.0 m subsoil, respectively; while the existing mapping products only reached a R2 of 0.01-0.35 in the topsoil and 0.01-0.15 in the subsoil. Across the QTP, our results estimated a total SOC stock of 62.0 (95% confidence interval: 54.9-69.1) Pg C within the top 2 m of soil, with more than 60% stored below 0.3 m depth. This value is much larger than most of the existing estimates in the same region. Alpine meadows ecosystems accounted for approximately 38% of the total SOC stock, primarily due to their extensive coverage, while swamp meadow ecosystems exhibited the highest SOC densities. Spatial uncertainty was highest in the sparsely sampled northwestern QTP. Contemporary climate and paleoclimate factors collectively contributed over 50% to the explained variance in SOC distribution across the soil profile, highlighting the dominant role of climatic factors on SOC spatial pattern. This spatially explicit, high-resolution SOC mapping provides a baseline for constraining carbon-climate feedback assessments on the QTP and underscores the region's heightened vulnerability to ongoing climate warming.

Sustainable agriculture requires simultaneously increasing food production and mitigating climate change, yet the extent to which crop improvement strategies deliver co-benefits at regional scales remains poorly understood. Improving radiation-use efficiency (RUE) has been widely proposed as a pathway to increase crop productivity, but its potential benefits such as soil organic carbon (SOC) sequestration are not well understood. Here, we developed a hybrid modeling framework that integrates a process-based agricultural system model (APSIM) with machine learning to capture genetic × environment × management (G × E × M) interactions and their effects on crop yield and SOC dynamics across the North China Plain. The results show that improving RUE increases both crop yields and SOC, but the magnitude of these benefits is strongly modulated by nitrogen inputs and varies widely across the region. In the future period (2021–2060) under a moderate-emissions scenario SSP2-4.5, increasing RUE of current cultivars by 10% and 20% led to additional wheat yield gains of 1.1 (+16%) and 1.8 t ha−1 (+26%) and maize gains of 0.8 (+11%) and 1.1 t ha−1 (+14%), respectively. These productivity gains also translated into an increase in SOC sequestration (+10% and +26%, respectively), as a consequence of enhanced carbon inputs. Notably, the coupling between yield gains and SOC sequestration varied substantially across the region, indicating spatially differentiated benefits. Our results highlight that improving RUE can contribute to both productivity and soil carbon gains, but these co-benefits are not universal and depend on local environmental and management contexts. This study provides a scalable and feasible approach for evaluating crop improvement strategies and their environmental consequences represented by SOC dynamics, as well as demonstrate that RUE improvement offers great opportunities for sustainable agriculture.

Context: Filling China's massive forage gap requires intensified silage maize (Zea mays L.) production with high and stable yield. Modifying irrigation and sowing time comprise two practical, cost-effective measures for such intensification, yet their spatial effects remain insufficiently quantified. Methods: Using the APSIM Classic 7.10 version for Maize, calibrated with experimental data using a differential evolution algorithm, we assessed biomass yield potential, irrigation benefits, and sowing strategies at 10 km resolution across five regions in China (1980-2017). In addition, partial correlation analysis was employed to identify the climatic drivers of irrigation benefits, while sensitivity analysis was conducted to evaluate the effects of sowing date and climate variability on biomass yield. Results: Under full irrigation and non-nitrogen-limiting conditions, potential yield (Yp) exceeded 24 Mg/ha in Northeast (NE) and Northwest (NW) China, while rainfed potential (Yw) was highest in Southwest (SW; 20 Mg/ ha) and Southeast (SE; 18 Mg/ha). Irrigation expanded high-yield stable (HS) areas from low-yield unstable (LU) zones by 26%, particularly in arid and semi-arid northern zones, with impacts of irrigation modulated by mean annual precipitation (MAP) during growing season. Optimal sowing strategies varied by region and water regime: early sowing by 30 days most improved HS areas in North China Plain (NC; +49%), SE (+28%), and SW (+26%) under sufficient water, while NE and NW favored 20-day and 10-day advances, respectively. Under rainfed conditions, southern regions benefited from early sowing, whereas the north required moderate delays for yield stability. Sensitivity analysis further confirmed that sowing date dominated irrigated yield variability in the north, while precipitation and radiation were key limiting factors in rainfed northern (MAP < 650 mm) and southern (MAP > 1000 mm) zones, respectively. Conclusions: This study provides the first high-resolution national assessment of silage maize, offering a scientific basis for tailoring its deployment to regional climate constraints and water availability, thereby supporting resilient forage intensification under changing environmental conditions.

Soil organic carbon (SOC) underpins the global carbon cycle and represents a central lever for climate change mitigation and food security. Yet its accurate spatiotemporal quantification remains a challenge, owing to the complex interactions among biological, chemical and physical processes operating across scales. This review critically evaluates the current state of SOC spatiotemporal modelling frameworks and their limitations, and future directions. Process-based models provide mechanistic insight into carbon dynamics but are constrained by parameterisation, structural assumptions and computational demands. In contrast, machine-learning (ML) approaches excel at capturing spatial patterns from large datasets but often struggle to represent temporal kinetics, enforce physical consistency or generalise across scales and environmental contexts. We argue that the next generation of SOC modelling will emerge from the convergence of process-based understanding and data-driven inference through knowledge-guided ML and hybrid modelling strategies. We synthesise four principal integration pathways: (1) meta-modelling to accelerate computationally intensive simulations; (2) sequential hybridisation to embed mechanistic trends as dynamic covariates; (3) ensemble frameworks to reduce structural uncertainty; and (4) data assimilation to constrain model trajectories with observations. We further highlight emerging frontiers, including residual and parameter learning, physics-informed neural networks, foundation models for earth observations, and omics-informed frameworks that link microbial functional potential to carbon turnover processes. We conclude that progress toward causally interpretable, uncertainty-aware monitoring frameworks will require tighter integration of mechanistic theory, interpretable artificial intelligence and cross-scale data synthesis.

CONTEXT: Excessive nitrogen use in high-input agriculture has led to nitrogen loss, methane emissions, and soil degradation in rice paddies. While high soil quality can enhance rice yields and reduce environmental impacts, the level of improvement needed to ensure sustainable rice production in China remains unclear. OBJECTIVE: This study aims to: (i) assess soil quality and sustainability of rice production systems in China; (ii) quantify the impact of soil quality improvement on rice production systems under various nitrogen application rates; and (iii) optimize soil quality and nitrogen application rate across subregions to meet yield, environmental, economic and sustainable targets. METHODS: Using national field datasets (1981-2020) from China's rice production systems, we assess soil quality (integrating organic matter, total nitrogen, pH, and bulk density), rice yield and carbon footprint through process-based modeling and life cycle assessment. To evaluate the sustainability of rice production systems, we construct a sustainability index (SI) that incorporates socioeconomic, environmental, and cultivation return dimensions. Building on these assessments, we apply structural equation modeling to quantify the effects of climate, soil, and management on achieving yield, environmental, economic and sustainable targets. RESULTS AND CONCLUSIONS: Low-to medium-quality soils account for approximately 80 % of the cultivated farmland across China's major rice-growing regions. Our findings demonstrate that improving soil quality can increase rice yields by an average of 9 % and reduce yield-scaled carbon emissions by 6 %, with the most substantial yield gains observed in low-quality soils. Additionally, improved soil quality enables reductions in nitrogen input ranging from 20 to 116 kg N.ha-1 across subregions without compromising sustainability outcomes. Soil organic matter, total nitrogen, and an optimal soil pH are positively associated with rice yield, economic return, and long-term sustainability, whereas higher bulk density and excessive nitrogen rates contribute to increased carbon emissions. SIGNIFICANCE: This study highlights soil quality improvement as a long-term strategy for sustainable rice intensification, with regional integration of soil and nitrogen management contributing to resource-efficient and low-carbon agriculture in China.

Soil organic carbon (SOC) comprises particulate (POC) and mineral-associated organic carbon (MAOC), which differ in formation, stabilization, and loss mechanisms. While the current global distribution of POC and MAOC is characterized, their vulnerability under future climate scenarios remains unclear. Using 3284 topsoil (0-30 cm) observations from six continents, we identify high-latitude soils as global hotspots of SOC vulnerability under shared socioeconomic pathway scenarios (SSP126, SSP245, and SSP585). Under a high-emission scenario (SSP585), high-latitude soils are projected to lose substantial POC by 2100, accounting for about 81 ± 10% of total SOC losses. These declines are driven by the high proportion of SOC stored as POC (fPOC) and its high temperature sensitivity. We show that fPOC is a robust indicator of SOC vulnerability to climate change. Globally, the projected POC decline corresponds to a cumulative carbon dioxide (CO2) release of 81.34 Pg CO2-equivalent by 2100, highlighting the importance of preserving POC to mitigate climate feedbacks.

Soil organic carbon is crucial for climate mitigation and agroecosystem sustainability, yet its depletion is concerning and its response to long-term fertilization remains unclear. Here we leverage the Broadbalk Classical Experiment at Rothamsted (UK), the world’s longest-running continuous winter wheat fertilization trial, along with 14C labelling, metagenomics and metabolomics to determine how 180 years of nitrogen (N) and phosphorus (P) fertilization impact soil organic carbon dynamics. Compared with no fertilization, long-term P, N and combined NP fertilization increased the soil organic carbon content by 10

Soils can be either a source or sink of atmospheric CO2 depending on how soil organic carbon (SOC) responds to climate warming and changes in plant productivity. Whereas warming typically accelerates SOC decomposition, the effect of plant productivity changes remains unclear. Here we use a space-for-change substitution approach to analyse a global dataset of SOC measurements down to 1 metre. We find that warming-induced SOC reduction in the 0–0.3-m topsoil is gradually offset by increasing plant productivity but exacerbated in the 0.3–1-m subsoil until plant productivity increase crosses a threshold of 30

The joint effects of simultaneous warming and precipitation shifts on soil organic carbon (SOC)-the largest terrestrial carbon pool-remain poorly understood across large spatial extents. By evaluating a global dataset of SOC measurements in the top meter of soil through a space-for-change substitution approach, we show that, averaging across the globe, increased precipitation compensates for warming-induced SOC reductions regardless of soil depth and vice versa. Although additive effects between these two factors are predominant, negative interactive effects, which exacerbate SOC losses, are also common, particularly in tropical and subtropical grasslands/savannas and Mediterranean/montane shrublands. SOC responses vary widely across the globe, primarily correlated to baseline SOC content and local climatic conditions. Notably, SOC responses in tundra systems are opposite the responses in other ecosystems, showing positive and negative responses to warming and precipitation increases, respectively. Under a scenario of 2°C air warming with projected precipitation changes, global SOC stocks in the 0-1 m depth are projected to decrease by 13.1% ± 6.6% (mean ± 95% confidence interval, or 351 ± 100 Pg C). These results demonstrate that accurately predicting SOC dynamics under climate change necessitates explicit consideration of local climatic conditions and existing SOC content in relation to concurrent precipitation shifts and warming.

The vertical transport (VT) of soil organic carbon (SOC) mixes carbon pools of varying depth‐origin and decomposability, regulating whole‐profile SOC dynamics through altered carbon pool interactions, such as the priming effect (PE). However, quantifying this process in situ is challenging. Using global data sets on SOC stocks and carbon inputs, we trained a depth‐resolved SOC model incorporating VT and PE to assess the vertical gradient of VT and PE, and explore their roles in regulating whole‐profile SOC dynamics in response to climate change. The results indicate that VT‐induced redistribution of SOC is essential for capturing observed profile distribution of SOC stocks. Transported carbon from neighboring layers accounted for 8%–27% of total layer‐specific carbon inputs, varying by depth and ecosystem type, and regulated SOC turnover behavior via the PE, especially in deeper layers. Precipitation emerged as the most important factor influencing layer‐specific VT. While the PE was higher in upper layers, it was far from its maximum potential in deeper layers, making SOC dynamics in these layers more sensitive to carbon input changes. If VT and PE gradients are not considered, the sensitivity of whole‐profile SOC to warming will be underestimated, and the impact of carbon input changes will be overestimated, particularly in deeper layers. Our findings highlight the critical role of VT and PE in controlling whole‐profile SOC dynamics, underscoring the need to explicitly include these processes in Earth system models for reliable whole‐profile SOC predictions under climate change.

Soil organic carbon (SOC) mineralization, driven by soil microbial communities, plays a crucial role in the global carbon cycle. However, the temperature sensitivity of microbial preferences for SOC substrates remains poorly understood, limiting our ability to predict SOC dynamics under climate change. Here we combined bacterial community profiling, laboratory incubations, and a pool-based carbon model to investigate the relationships between bacterial species abundances and two SOC pools with fast and slow decay rates, respectively, at different incubation temperatures. Only about half of identified bacterial species is significantly (P < 0.05) associated with the mineralization of the two pools and their temperature sensitivity (Q10). More importantly, we find that the association of the species with the two pools shifts in terms of both magnitude and direction with incubation temperature. The proportion of species associated with the Q10 of fast pool decreased, while those associated with the Q10 of slow pool increased with warming. Meanwhile, species specifically associated with the fast pool exhibit stronger temperature sensitivity compared to species specifically associated with the slow pool at lower temperatures, and vice versa at higher temperatures. These results suggest that common bacterial species associated with SOC mineralization adjust their substrate preferences in response to temperature variations, potentially impacting SOC composition and dynamics under warming.

Agricultural soils have great potential to sequester carbon, mitigating climate change while enhancing soil health. Subsoil layers are particularly promising for long-term carbon storage due to their lower carbon density and slower carbon turnover compared to topsoil. The reduced subsoil carbon density primarily results from limited carbon inputs at depth, while slower turnover is driven by 1) stronger physiochemical constraints on microbial decomposition, and 2) limited availability of high-quality, energy-rich substrates. These factors underscore the opportunities to target management practices that either increase carbon inputs to subsoil layers or reduce carbon turnover rates to enhance subsoil carbon sequestration. Advancing this field requires understanding the vertical distribution of carbon input quality and quantity, as well as the processes driven vertical carbon transport within soil profiles. Additionally, it is critical to elucidate how substrate properties (e.g., energy and nutrient content) and vertical environmental constraints (e.g., hydrothermal regimes and oxygen availability) influence microbial efficiency. Addressing these knowledge gaps will enable the design of effective management practices, unlocking the full potential of whole-profile carbon sequestration in agricultural systems.

Balancing soil health and food production is a struggle for agriculture. The practice of burying crop residues in subsoil offers a dual win: richer carbon storage and higher yields.