Decrease In Soil Organic Carbon Content Research Articles

Investigating Soil Water Retention and Water Content in Retrogressive Thaw Slumps in the Qinghai-Tibet Plateau, China

Retrogressive thaw slumps (RTSs) are becoming more common on the Qinghai-Tibet Plateau as permafrost thaws, but the hydraulic properties of thaw slumps have not been extensively studied. To fill this knowledge gap, we used the “space-for-time substitution method” to differentiate three stages of RTSs: original grassland, collapsing, and collapsed. Our study included on-site investigations, measurements in the laboratory, and measured and simulated analyses of soil water retention curves and estimated hydrological properties. Our findings show that the measurements and simulated analyses of soil water retention were highly consistent across RTSs, indicating the accuracy of the Van Genuchten model in reproducing soil hydraulic parameters for different stages of RTSs. The original grassland stage had the highest soil water retention and content due to its high soil organic carbon (SOC) content and fine-textured micropores. In contrast, the collapsed stage had higher soil water retention and content compared to the collapsing stage, primarily due to increased proportions of soil micropores, SOC content, and lower bulk density (BD). From original grassland stage to collapsed stage, there were significant changes on the structure of each RTS site, which resulted in a decrease in SOC content and an increase in BD in general. However, the absence of soil structure and compaction led to the subsequent accumulation of organic matter, increasing SOC content. Changes in field capacity, permanent wilting point, and soil micropore distribution aligned with variations in SOC content and water content. These findings highlight the importance of managing SOC content and water content to mitigate the adverse effects of freeze-thaw cycles on soil structure and stability at different thaw collapse stages of RTSs. Effective management strategies may include incorporating organic matter, reducing soil compaction, and maintaining optimal water content. Further research is needed to determine the most suitable management practices for different soil types and environmental conditions.

Dynamics of soil organic carbon pools following conversion of savannah to cocoa agroforestry systems in the Centre region of Cameroon

Afforestation of gramineous-woody savannah with cocoa agroforestry systems (cAFS) is a common farmer practice in Cameroon considered as sustainable. Nevertheless, the effects of afforestation of savannah with cAFS on soil organic carbon (SOC) turnover and content, and the factors controlling SOC accumulation and stabilization are unknown. SOC content at 0–10 cm soil layer, and SOC distribution in soil particle size fractions (0–20 μm fraction considered as mineral-associated organic carbon, MAOC; 50–2000 μm considered as particulate organic carbon, POC; and 20–50 μm), were compared in different systems settled on degraded savannah (orthic ferralsols). These systems included annual cropland (≈ 5 years old), cocoa monoculture (≈10 years old), and cAFS (from 20 to 60 years old) including different shade tree species such as Albizia adianthifolia, Canarium schweinfurthii, Dacryodes edulis, Milicia excelsa and Ceiba pentandra. Savannah and nearby secondary forest patches were also included in the design as controls. Soil 13C was analysed to investigate the soil carbon turnover after afforestation (C3 plants) of gramineous savannah (C4 plants).SOC significantly increased in the 0–10 cm depth from 10.6 ± 3.1 g C kg−1 in degraded savannah to 17.9 ± 5.6 g C kg−1 in cAFS reaching similar levels as in nearby secondary forests (16.3 ± 5.8 g C kg−1), while annual cropland and cocoa monoculture presented a non-significant decrease in SOC content. These changes were due to rapid loss of SOC derived from savannah plants (C4) – about 76% within the first 15 years after conversion, and higher gain of SOC derived from C3 plants in cAFS than in the other land uses (e.g. from 3.4 ± 1.5 g C kg−1 in savannah to 17.8 ± 5.7 g C kg−1 in cAFS). This SOC enrichment in cAFS was distributed in POC (64%), MAOC (30%) and the intermediate 20–50 μm soil fraction (6%). The higher annual litter input accumulated on a longer period in cAFS (20 to 60 years) than in cocoa monoculture (10 years) concomitant with the lower litter recalcitrance of associated trees compared to cocoa could explain the higher enrichment of SOC in all fractions in cAFS. The soil pH and exch. Ca2+ differed under the different shade tree species, and were positively correlated to SOC content. The highest contents of soil exch. Ca2+ induced by Ceiba and Milicia in the top 10 cm soil layer could contribute to increase SOC enrichment under those species through soil aggregation and related C stabilization. We found no strong evidence of the effect of soil texture on additional soil carbon accumulation in cAFS, especially for the more stable C pool (MAOC). Our results evidenced that savannah afforestation with cAFS appears as a valuable option for top soil carbon enrichment and should consider tree species associated to cocoa to enhance soil C sequestration, soil quality and cocoa production sustainability.

Spatial distribution and driving factors of soil organic carbon in the Northeast China Plain: Insights from latest monitoring data

Soil organic carbon (SOC) is a critical component of soil fertility and plays a crucial role in the global carbon cycle. Despite the widespread reports of a decrease in SOC content and stock in the Northeast China Plain in recent decades, the current status and driving factors of its content and distribution are unclear. In this study, the surface soil (0–20 cm) SOC content data of 1920 sampling points within the Northeast China Plain covering an area of 2.6 × 105 km2 were obtained based on the Land Quality Geochemical Monitoring Network established in 2018. Random forest model and correlation analysis were used to identify the main driving factors of SOC distribution. The results showed that the SOC content, soil organic carbon density (SOCD), and soil organic carbon storage (SOCS) in the Northeast China Plain were 13.48 g·kg−1, 3.45 kg·C·m−2, and 898.95 Tg, respectively. SOC content in paddy land was the highest among different land use types, which reached 18.77 g·kg−1. SOC content showed strong spatial dependence and gradually increased from southwest to northeast in the monitoring area. The results of the random forest analysis showed that the SiO2, mean annual temperature, and Fe2O3 explained 39.4 %, 18.9 %, and 12.8 % of the spatial variation of SOC, respectively. Although the SOCS (0–20 cm) in the Northeast China Plain has decreased by 8.68 % in the last 40 years compared to the Second National Soil Survey (1980), it's important to note that the SOCS has transitioned from a decreasing trend between 1980 and 2006 to an increasing trend from 2006 to 2018.This study provides important information for decision-makers on the spatiotemporal changes of SOC and its driving factors in the Northeast China Plain, which has a great significance for soil carbon sequestration and the development of management strategies to maintain soil fertility.

Assessing spatial variations in soil organic carbon and C:N ratio in Northeast China's black soil region: Insights from Landsat-9 satellite and crop growth information

Monitoring soil properties, especially soil organic carbon (SOC) and Carbon-to-Nitrogen (C:N) ratios, is vital for understanding degradation and developing black soil conservation strategies. Most soil mapping research has leveraged satellite imagery from limited bare-soil periods. The predictive accuracy using time-series images capturing crop growth is underexplored. Moreover, while the new Landsat-9 satellite surpasses Landsat-8, its use in soil mapping is mostly uncharted. In this study, we compared the performance of single-date bare soil imagery (Landsat-8, Landsat-9, and Sentinel-2) and multi-temporal images (Landsat-8 and Landsat-9 combined, and Sentinel-2) using three machine learning techniques (Boosted Regression Tree, BRT; Random Forest, RF; Extreme Gradient Boosting, XGBoost) for mapping SOC and C:N ratio in a typical Northeast China black soil cropland region. The results revealed that single-date Landsat-9 exhibited great potential for soil mapping with the optimal XGBoost model, improving the prediction accuracy (in terms of R2) of SOC and C:N ratio by 15.01% and 30.07%, respectively, compared to Landsat-8, while also delivering performance slightly inferior to single-date Sentinel-2. Moreover, predictors derived from multi-temporal images significantly outperformed those derived from single-date images. The XGBoost models that utilized multi-temporal Sentinel-2 predictors achieved the highest prediction accuracy for both SOC (R2 = 0.676, RMSE = 1.928 g/kg, MAE = 1.580 g/kg, RPD = 1.535) and C:N ratio (R2 = 0.713, RMSE = 0.585, MAE = 0.484, RPD = 1.718). Interestingly, the combination of Landsat-8 and Landsat-9 demonstrated similar prediction accuracy but lower uncertainties in SOC and C:N ratio mapping compared to multi-temporal Sentinel-2 images. In addition, a comparison of the contemporary prediction soil maps with historical soil data revealed a continual decrease in SOC content and C:N ratio, suggesting a concerning trajectory that is detrimental to organic matter accumulation. Overall, this study highlights the efficacy of Landsat-9 and multi-temporal imagery incorporating crop growth information in accurately predicting soil properties and assessing their spatial variability.

Dynamic modeling of topsoil organic carbon and its scenarios forecast in global Mollisols regions

Global Mollisols regions play crucial roles in maintaining world food security, performing ecosystem services and global carbon cycling. Little is known about the spatial and temporal variability of soil organic carbon (SOC), future trends, and the driving forces of changes in each Mollisols region. The aim of this work is to trace the SOC dynamics during the 2000–2020 period and forecast its dynamics for 2020–2040 period (every 5 years) across the global Mollisols regions, highlighting the driving factors for these changes. We used bare soil images and environmental covariates to construct a robust prediction model of SOC using machine learning. The best model was used to forecast future changes in SOC content under different emission scenarios. Also, the role of different predictor variables in predicting and driving SOC changes is indicated with the help of the shapley value algorithm. Results show that SOC content in the current global Mollisols regions is 26.45 g kg−1 in Ukraine, 21.34 g kg−1 in Northeast China, 21.05 g kg−1 in the USA and 15.59 g kg−1 in Argentina. However, they have been decreasing since 2001 and showed a slowing trend, with the highest and lowest rates of 11.45% in Ukraine and 7.33% in the USA, respectively. The forecast under different climate scenarios shows a slight decrease in SOC content within a range of 0.46%–1.22%. Among them, SSP 245 is more consistent with the current trend of SOC content, while SSP585 indicates the greatest loss of SOC content. Results revealed that the driving factors for SOC prediction in descending order were meteorologic, parent material, terrain and vegetation. All soil and meteorology variables contributed by 71%, while soil texture fractions and temperature were the top 20% of these variables. The main factors driving SOC changes from high to low latitudes are temperature, precipitation, and vegetation. It can be concluded that the temporal transfer model is a powerful tool to trace and forecast the dynamics of SOC in Mollisols regions at the global scale, enabling a clear understanding and ranking the factors affecting this process under diverse climate conditions.

Improved Surface Soil Organic Carbon Mapping of SoilGrids250m Using Sentinel-2 Spectral Images in the Qinghai–Tibetan Plateau

Soil organic carbon (SOC) is a critical indicator for the global carbon cycle and the overall carbon pool balance. Obtaining soil maps of surface SOC is fundamental to evaluating soil quality, regulating climate change, and global carbon cycle modeling. However, efficient approaches for obtaining accurate SOC information remain challenging, especially in remote or inaccessible regions of the Qinghai–Tibet Plateau (QTP), which is influenced by complex terrains, climate change, and human activities. This study employed field measurements, SoilGrids250m (SOC_250m, a spatial resolution of 250 m × 250 m), and Sentinel-2 images with different machine learning methods to map SOC content in the QTP. Four machine learning methods including partial least squares regression (PLSR), support vector machines (SVM), random forest (RF), and artificial neural network (ANN) were used to construct spatial prediction models based on 396 field-collected sampling points and various covariates from remote sensing images. Our results revealed that the RF model outperformed the PLSR, SVM, and ANN models, with a higher determination coefficient (R2 of 0.82 is from the training datasets) and the ratio of performance to deviation (RPD = 2.54). The selected covariates according to the variable importance in projection (VIP) were: SOC_250m, B2, B11, Soil-Adjusted Vegetation Index (SAVI), Normalized Difference Vegetation Index (NDVI), B5, and Soil-Adjusted Total Vegetation Index (SATVI). The predicted SOC map showed an overall decrease in SOC content ranging from 69.30 g·kg−1 in the southeast to 1.47 g·kg−1 in the northwest. Our prediction showed spatial heterogeneity of SOC content, indicating that Sentinel-2 images were acceptable for characterizing the variability of SOC. The findings provide a scientific basis for carbon neutrality in the QTP and a reference for the digital mapping of SOC in the alpine region.

Fire-induced changes in soil properties depend on age and type of forests

Abstract Wildfires affect different physical, chemical, and hydraulic soil properties, and the magnitude of their effects varies depending on intrinsic soil properties and wildfire characteristics. The objectives of this study are: to estimate the impact of heating temperature (50–900°C) on the properties of sandy soil (Arenosol) taken in 1) coniferous forests (Scots pine Pinus sylvestris) of different ages (30 and 100 years); and 2) coniferous (Scots pine Pinus sylvestris) and deciduous (alder Alnus glutinosa) forests of the same age (30 years). The forests are located in the central part of the Borská nížina lowland (western Slovakia), and the properties treated were soil organic carbon content (SOC), pH, and soil water repellency (measured in terms of water drop penetration time, WDPT). It was found that the impact of heating temperature on the properties of sandy soil is great and depends on both the age and type of forest. The SOC value decreased unevenly with temperature in all three soils, and it was higher in the 30-year-old deciduous forest soil than in the 30-year-old coniferous forest soil. The value of pH increased monotonously with temperature from 200 °C, and it was higher in 30-year-old coniferous forest soil than in the 100-year-old coniferous forest soil. SOC and WDPT in the 100-year-old coniferous forest soil were higher than SOC and WDPT in the 30-year-old coniferous forest soil. Results obtained (decrease in SOC, disappearance of SWR after heating to 400 °C, and increase in pH from heating temperature 200 °C) bring important information for post-fire vegetation restoration and post-fire management of Central European forests established on sandy soil.

Soil Aggregate Stability in Salt-Affected Vineyards: Depth-Wise Variability Analysis

Soil aggregate stability is an ideal integrative soil quality indicator, but little is known about the relevance of such an indicator with soil depth for salt-affected soils. The objective of this study was to determine soil aggregate stability and identify preponderant aggregation factors, both in topsoil and subsoil horizons in salt-affected conditions. We conducted field investigations by describing soil profiles in pedological pits and by collecting soil samples from different field units. Soils were sampled within different soil horizon types, from superficial tilled organo-mineral horizons to mineral horizons. For all soil samples, we determined the mean weight diameter (MWD) as an indicator of soil aggregate stability and also determined associated physical and chemical properties in some samples. The measured MWD value from 0.28 mm to 1.10 mm could be categorised as unstable, with MWD values and variability decreasing drastically from the topsoil to the deepest mineral horizons. Analysis of MWD in relation to physical and chemical properties suggested that the variability in the MWD value of A-horizons was influenced by both clay fraction abundance and soil organic carbon (SOC) content and the nature of the agricultural practices, while at deeper B-horizons, the decrease in SOC content and the variability in other soil properties with soil depth could be used to explain the overall low aggregate stability. In this study, investigations of soil pits coupled with measurements of soil aggregate stability indicated that it could be possible to restore soil structure quality by limiting deep soil profile compaction in order to improve salt leaching and exportation.

Warming Effects on Topsoil Organic Carbon and C:N:P Stoichiometry in a Subtropical Forested Landscape

Warming effects on agricultural and forest ecosystems have been well documented at broad spatiotemporal scales but less so at stand and landscape scales. To detect the changes in soil organic carbon (SOC) and carbon:nitogen:phosphorus (C:N:P) stoichiometry in response to a short-range warming gradient, we defined an inverse elevation-dependent warming gradient and developed a novel index of warming based on a common environmental lapse rate. We associated the warming gradient and warming index with the changes in SOC and C:N:P stoichiometry and tested the independence of warming effects using partial correlation analysis. SOC content and C:N:P stoichiometric ratios significantly decreased with warming, and the effect of warming on C:N:P stoichiometric ratios were stronger than on SOC content. The relationships of SOC content and C:N:P stoichiometric ratios with warming did not change after controlling for two other energy-related variables, i.e., transmitted total radiation and potential direct incident radiation. However, the strength in the relationships of C:N:P stoichiometric ratios with vegetation-related variables significantly decreased after the warming index was controlled for. As indicated by the random forest regression model, the warming index was the most important variable for predicting SOC variability and the second most important for predicting total N variability, while vegetation-related variables were the most important for predicting C:N:P stoichiometric ratios. Our results showed that warming was responsible for the decrease in SOC content and C:N:P stoichiometric ratios and the warming index was the most important variable for predicting SOC variability. Although the most important variables for C:N:P stoichiometric ratios were related to vegetation, the relationships between C:N:P stoichiometric ratios and vegetation-related variables were significantly affected by warming. These findings demonstrate that warming is the major driver of SOC variability and the decrease in SOC content, as well as of C:N:P stoichiometry, even along a short-range warming gradient.

Variations in soil δ13C with alpine meadow degradation on the eastern Qinghai–Tibet Plateau

The alpine swampy meadow is a unique meadow type on the eastern Tibetan Plateau and is undergoing degradation. However, little is known about the responses of soil δ13C to alpine meadow degradation. Monitoring the β value, which is the slope of the linear regression relating soil δ13C to the logarithm of soil organic carbon (SOC) content, provides an approach to infer SOC dynamics. In this study, we investigated soil δ13C and SOC contents along a soil profile (0–50 cm), together with several soil physicochemical and biomass properties in a swampy meadow (SM), a grassland meadow (GM), and a degraded meadow (DM). Then, the variations in soil δ13C and β values and the main factors affecting them were analyzed. The results showed that soil δ13C increased with soil depth, but SOC decreased. The soil δ13C in the surface layer (0–10 cm) was comparable between GM and DM but was significantly lower in SM, and soil moisture was the major factor influencing the surface soil δ13 value. The three meadow types could be ranked, from highest β value to lowest, as follows: GM > SM > DM. The soil C/N ratio and soil texture explained large proportions of the variations in β value. Our results demonstrated that the degradation of alpine meadows affects biomass and soil physicochemical properties, leading to a reduction in C inputs and an accelerated rate of SOC decomposition, followed by a decrease in SOC content. Our findings also indicated that monitoring changes in soil δ13C is an effective method to evaluate the degradation of alpine meadows, but it should be used with caution. This study provides a more comprehensive understanding of soil δ13C and SOC dynamics with alpine meadow degradation.

Soil properties influencing erodibility of soils in the Ntabelanga area, Eastern Cape Province, South Africa

ABSTRACTSoil erosion has serious off-site impacts caused by increased mobilization of sediment and delivery to water bodies causing siltation and pollution. To evaluate factors influencing soil erodibility at a proposed dam site, 21 soil samples collected were characterized. The soils were analyzed for soil organic carbon (SOC), exchangeable bases, exchangeable acidity, pH, electrical conductivities, mean weight diameter and soil particles’ size distribution. Cation exchange capacity, exchangeable sodium percentage, sodium adsorption ratio, dispersion ratio (DR), clay flocculation index (CFI), clay dispersion ratio (CDR) and Ca:Mg ratio were then calculated. Soil erodibility (K-factor) estimates were determined using SOC content and surface soil properties. Soil loss rates by splashing were determined under rainfall simulations at 360 mmh−1 rainfall intensity. Soil loss was correlated to the measured chemical and physical soil properties. There were variations in soil form properties and erodibility indices showing influence on soil loss. The average soil erodibility and SOC values were 0.0734 t MJ−1 mm−1 and 0.81%, respectively. SOC decreased with depth and soil loss increased with a decrease in SOC content. SOC significantly influenced soil loss, CDR, CFI and DR (P < .05). The soil loss rate was 5.60 t/ha per 8 minute rainstorm of 360 mmh−1. Addition of organic matter stabilize the soils against erosion.

To what extent do physical measurements match with visual evaluation of soil structure?

Soil structure quality can be scored by visual examinations or measured with soil physical properties. To investigate the relationships between these two approaches, we adapted the VESS (Visual Evaluation of Soil Structure, Guimarães et al., 2011) to the scoring of cores (CoreVESS) on which shrinkage analysis was also performed. Scoring was performed blindly after equilibrating the samples at −100hPa matric potential and was compared to soil texture, soil organic carbon content (SOC), soil hydrostructural stability, structural porosity, plasma porosity, bulk soil porosity or density, and water content at standard matric potential. A large geographical area of Cambi-Luvisols was sampled at 55 locations with different soil management in western Switzerland. VESS was performed on the pits and layers prior to sampling undisturbed cores. Sandy soils presented medium CoreVESS scores compared to clayey soils. Only soils with more than 20% clay content obtained good scores in this study. The relationships between CoreVESS scores, SOC and most physical properties followed a broken-stick regression, with most breaking points close to score 3. Most regressions were significant and highly determined with R2 above 0.45. Linear decrease with CoreVESS scores was observed for total porosity and bulk density of air-dried soil and for water content at −10hPa. The underlying model of structural quality decrease can be summarized as follows. From score 1 to 3 the decrease in structure quality corresponds to a decrease in SOC. From score 1 to 2 occurs most of the decrease in coarse porosity volume. From score 3 to 5 the decrease of structure quality corresponds to a loss of structural porosity, which converges to 0cm−3g−1 for score 5, and to a collapse of the samples upon drying between scores 3 and 4, thus denoting a loss of hydrostructural stability. VESS scores of pits and layers were poorly correlated to CoreVESS scores and physical properties, probably due to local variability of the sampled layers. Our results suggest that the relation between visual scoring and physical properties is not site specific, and underline the need for standardizing the moisture conditions in soil structure quality assessment.

Potential of fallow chronosequence in shifting cultivation to conserve soil organic carbon in northeast India

Secondary forest in shifting cultivation might influence soil organic carbon (SOC) stock. However, information with respect to SOC accumulation or depletion in fallow stand with secondary forest in shifting cultivation is insufficient. We, therefore, undertaken this experiment with the objective to evaluate the impact of secondary forest on SOC stock and its allocation into pools of different oxidizability [very labile (CVL), labile (CL), less labile (CLL) and nonlabile C (CNL)] along soil depth using three fallow chronosequences of shifting cultivation located in subtropical mid-hills of northeast India. Results showed that SOC content in 0–0.45m depth increased with age of the fallow stand [the values being 78.4, 91.5 and 102.8Mgha−1 in young (5–9years), mid-aged (18–20years) and old (28–33years) secondary forest, respectively] after land clearing (slashing and burning of forest) and exhaustive cropping (75.9kgha−1). There was a decrease in SOC content with increasing soil depth, constituting 49.0, 27.8 and 23.2% of the total (for 0–0.45m) for 0–0.15, 0.15–0.30 and 0.30–0.45m, respectively. Among the analyzed C pools CVL, CL and CLL were influenced by the fallow period and the active pools (CVL+CL) constituted 65.7% of the SOC. Most of the SOC pools were significantly correlated with each other and with fallow age. Results thus indicate that soil in shifting fallow conserves increasing amount of organic C during regeneration of forest vegetation and majority of the SOC is in active or labile pools of shorter residence time.

Comparison of Soil Physical Properties between a Permanent Fallow and a Long-Term Rice–Wheat Cropping with Inorganic and Organic Inputs in the Humid Subtropics of Eastern India

A comparison was made between a long-term rice–wheat cultivation with fertilizer nitrogen–phosphorus–potassium (NPK) or added organics [farmyard manure (FYM), paddy straw (PS), green manure (GM)] and a permanent fallow on bulk density (BD), saturated hydraulic conductivity (Ksat), available water capacity (AWC), maximum water-holding capacity (MWHC), aggregation, and soil organic carbon (SOC) dynamics on an Inceptisol of humid subtropics of eastern India. Continuous cropping caused a net decrease in SOC content. Undisturbed fallow was comparable to soils with FYM, PS, and GM amendments in structural and hydrophysical properties. Maximum WHC and AWC values were in the order of FYM followed by PS, GM, fallow, NPK, and control. The relative efficacy of the organics for physical buildup was FYM > PS > GM, which increased structural indices. This study represents further steps toward understanding the ecological importance of fallow management and integrated use of balanced fertilizer and organics.

Direct measurement of soil organic carbon content change in the croplands of China

Agricultural soils in China have been estimated to have a large potential for carbon sequestration, and modelling and literature survey studies have yielded contrasting results of soil organic carbon (SOC) stock change, ranging from −2.0 to +0.6% yr−1. To assess the validity of earlier estimates, we collected 1394 cropland soil profiles from all over the country and measured SOC contents in 2007–2008, and compared them with those of a previous national soil survey conducted in 1979–1982. The results showed that average SOC content in the 0–20 cm soil increased from 11.95 g kg−1 in 1979–1982 to 12.67 g kg−1 in 2007–2008, averaging 0.22% yr−1. The standard deviation of SOC contents decreased. Four major soil types had statistically significant changes in their mean SOC contents for 0–20 cm. These were: +7.5% for Anthrosols (paddy soils), +18.3% for Eutric Cambisols, +30.5% for Fluvisols, and −22.3% for Chernozems. The change of SOC contents showed a negative relationship with the average SOC contents of the two sampling campaigns only when soils in the region south of Yangtse River were excluded. SOC contents of the two major soil types in the region south of Yangtse River, i.e., Haplic Alisols/Haplic Acrisols and Anthrosols (paddy soils), changed little or significantly increased, though with a high SOC content. We suggest that the increase of SOC content is mainly attributed to the large increase in crop yields since the 1980s, and the short history as cropland establishment is mainly responsible for the decrease in SOC content for some soil types and regions showing a SOC decline.