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Soil carbon sequestration is an important process of the terrestrial carbon cycle, and even slight changes in soil carbon will trigger drastic variations in the global carbon pool. In this study, we used the CiteSpace software to analyze the development of research on soil organic carbon (SOC) and its current status from various perspectives, with the goal of revealing research hotspots and trends of SOC. A total of 3909 studies published between 2014 and 2023 were included in the analysis. Results show that China and the USA lead with a significant number of publications on SOC, which underscores their considerable interest in the subject. France and the USA exhibit a very high international influence in this field, with their intermediary centrality reaching up to 0.3 and 0.21, respectively. Among institutions, the Chinese Academy of Sciences is the largest contributor in terms of the number of publications, with a high centrality of 0.09, indicating this institution has built close collaboration and significant influence in this field. Kuzyakov Yakov achieved the highest publication record, with Lal Rattan sharing the second position. The hotspots in SOC can be summarized into the following aspects: conservation tillage, carbon sequestration, microbial biomass, and driving forces. The research focus has gradually shifted from macroscopic trends to explanations based on micro-level biological dynamics. Driving forces such as soil type, land use, and environmental conditions have a significant impact on the quantity, turnover, and spatiotemporal distribution of SOC. We highlighted that more attention should be paid to the mechanism of SOC transformation and stabilization, which is essential for developing more precise models of carbon cycling in the soil and for formulating effective strategies to maintain sustainable agriculture and mitigate climate change. [ABSTRACT FROM AUTHOR]

This study aimed to assess the potential of soil organic carbon (SOC) production through organic amendments. SOC sequestration would help to achieve the net-zero emissions targets set by the Intergovernmental Panel on Climate Change (IPCC). Given the urgency to reduce greenhouse gas emissions, traditional methods that estimate SOC over 100 years must be revised. Hence, a novel fate transport numerical model was developed to forecast SOC levels relevant to individual countries' net-zero targets in various time frames. The simulation results revealed that most countries had sufficient organic amendment to mitigate the CO2 emission of that country for a year if the organic amendment was applied on 20% of the arable land. However, if a significant fraction of the total CO2 emissions needs to be mitigated before reaching the net zero target, the requirements of organic amendments need to be increased several folds. All the available agricultural land should also be brought under the organic amendment regime. Later, the dynamic LCA approach was undertaken for estimating Global Warming (GWP) from land-applied organic residue. It was observed that, depending on the dynamic LCA model, the estimated GWP was different. However, the estimated dynamic GWP was very close to the residual SOC calculated through the fate transport model. The mass of organic residues generated from a biorefinery was examined by employing a waste biorefinery model to explore further the routes of acquiring additional organic amendment. Simulated results showed that while a waste biorefinery could not provide additional organic residue compared to the original organic waste input, it was highly efficient for nutrient recovery and its uses. This study demonstrated that organic amendment-based carbon sequestration adequately mitigated residual GHG at the net-zero target. [ABSTRACT FROM AUTHOR]

Soil organic carbon (SOC) plays a vital role in the global carbon cycle and soil quality assessment. The Qinghai–Tibet Plateau is one of the largest plateaus in the world. Therefore, in this region, SOC density and the spatial distribution of SOC are highly sensitive to climate change and human intervention. Given the insufficient understanding of the spatial distribution of SOC density in the Qinghai–Tibet Plateau, this study utilized machine learning (ML) algorithms to estimate the density and distribution pattern of SOC density in the region. In this study, we first collected multisource data, such as optical remote sensing data, synthetic aperture radar) (SAR) data, and other environmental variables, including socioeconomic factors, topographic factors, climate factors, and soil properties. Then, we used ML algorithms, namely random forest (RF), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM), to estimate the topsoil SOC density and spatial distribution patterns of SOC density. We also aimed to investigate any driving factors. The results are as follows: (1) The average SOC density is 5.30 kg/m2. (2) Among the three ML algorithms used, LightGBM showed the highest validation accuracy (R2 = 0.7537, RMSE = 2.4928 kgC/m2, MAE = 1.7195). (3) The normalized difference vegetation index (NDVI), valley depth (VD), and temperature are crucial in predicting the spatial distribution of topsoil SOC density. Feature importance analyses conducted using the three ML models all showed these factors to be among the top three in importance, with contribution rates of 14.08%, 12.29%, and 14.06%; 17.32%, 20.73%, and 24.62%; and 16.72%, 11.96%, and 20.03%. (4) Spatially, the southeastern part of the Qinghai–Tibet Plateau has the highest topsoil SOC density, with recorded values ranging from 8.41 kg/m2 to 13.2 kg/m2, while the northwestern part has the lowest density, with recorded values ranging from 0.85 kg/m2 to 2.88 kg/m2. Different land cover types showed varying SOC density values, with forests and grasslands having higher SOC densities compared to urban and bare land areas. The findings of this study provide a scientific basis for future soil resource management and improved carbon sequestration accounting in the Qinghai–Tibet Plateau. [ABSTRACT FROM AUTHOR]

Anthropogenic disturbances associated with land use and land cover changes negatively influence soil organic C, reducing ecosystem functionality. These adverse effects may be even more pronounced in Brazilian subtropical riparian zones due to recent changes in environmental legislation that reduced the size of these protected areas in small scale farms. This study evaluated how different land uses in riparian zones influence ecosystem services related to soil, litter, and roots C and N stocks. The field experiment was carried out in a drainage area with four land uses and cover: forest fragment (FF), plantation forest (PF), pasture (PA), and agriculture (AG). Soil, root, and litter C and N stocks were analyzed. Monocultures (PF, PA, and AG) had lower soil C and N stocks than FF. The FF and PF did not differ in litter and root C content, but FF had higher N values. Differences in the quality of plant residues were associated with a lower soil C: N ratio in FF. The lowest soil C and N stocks were observed in AG sites, and the conversion from AG to PF and PA seems to increase soil C and N stocks. Our findings indicate that, even in small forest patches, the higher quality of organic residues drives soil C and N storage, highlighting the negative effects of vegetation replacement to monocultures in riparian zones. Hence, the maintenance of riparian forests is essential for providing ecosystem services related to soil C and N cycling. [ABSTRACT FROM AUTHOR]

Organic fertilizer is utilized to improve the organic carbon levels in arable soils, which is helpful for soil quality improvement and crop yield increase. However, the after-effect of organic fertilizer varies among regions with different temperature and precipitation conditions, and the extent of the impact remains unknown. This study aimed to investigate the impact of varying temperature and rainfall conditions on the accumulation of soil organic carbon after organic fertilizer application. A meta-analysis of 168 peer-reviewed studies published between 2005 and 2022 involving a total of 464 trials was conducted. The following was discovered: (1) In the major grain-producing areas of China, there was a significant positive correlation (p < 0.01) between latitude and soil organic carbon content. Meanwhile, temperature and precipitation had a significant negative correlation (p < 0.01) with soil organic carbon content. (2) The increase in temperature inhibited the increase in soil organic carbon storage. The improvement effect of organic fertilizer application in the low-temperature areas was significantly increased by 60.93% compared with the mid-temperature areas, and by 69.85% compared with the high-temperature areas. The average annual precipitation affected the after-effect of organic fertilizer as follows: 400–800 mm > 400 mm > more than 800 mm. (3) The influence of climatic conditions on the after-effect of organic fertilizer was more significant depending on the specific tillage practice. To increase organic fertilizer use efficiency and eliminate greenhouse gas emissions, liquid organic fertilizers with abundant trace nutrients and amino acids, which take advantage of releasing nutrients more swiftly and have a better fertilization effect, could be an alternative to traditional organic fertilizers. [ABSTRACT FROM AUTHOR]

Soil organic carbon (SOC) is generally thought to act as a carbon sink; however, in areas with high spatial heterogeneity, using a single model to estimate the SOC of the whole study area will greatly reduce the simulation accuracy. The earth surface unit division is important to consider in building different models. Here, we divided the research area into different habitat patches using partitioning around a medoids clustering (PAM) algorithm; then, we built an SOC simulation model using machine learning algorithms. The results showed that three habitat patches were created. The simulation accuracy for Habitat Patch 1 (R2 = 0.55; RMSE = 2.89) and Habitat Patch 3 (R2 = 0.47; RMSE = 3.94) using the XGBoost model was higher than that for the whole study area (R2 = 0.44; RMSE = 4.35); although the R2 increased by 25% and 6.8%, the RMSE decreased by 33.6% and 9.4%, and the field sample points significantly declined by 70% and 74%. The R2 of Habitat Patch 2 using the RF model increased by 17.1%, and the RMSE also decreased by 10.5%; however, the sample points significantly declined by 58%. Therefore, using different models for corresponding patches will significantly increase the SOC simulation accuracy over using one model for the whole study area. This will provide scientific guidance for SOC or soil property monitoring with low field survey costs and high simulation accuracy. [ABSTRACT FROM AUTHOR]

Soil health encompasses the effects the uppermost part of the land have on human wellbeing in a broad sense, because soil is where most food ultimately comes from, and because it more inconspicuously fulfils other ecological functions, as important as feeding, for our planet's welfare, which is ours. Viticulture exploits the soil's resources from which wine, its most valuable produce, boasts to obtain some of its unique quality traits, which are wrapped within the terroir concept. However, using conventional methods, viticulture also has harsh impacts on the soil, thus jeopardizing its sustainability. How long will the terroir expression remain unchanged as vineyard soil degradation goes on? While this question is difficult to answer because of the complex nature of terroirs, it is undeniable that conventional soil management practices in viticulture leave, in general, ample room for improvement, in their impact on vineyards as much as on the environment. In response, viticulture must adopt practices that enable the long-lasting preservation of its grounds for both on-farm and off-farm benefits. In this regard, the increase in the soil's organic matter alongside the enhancement of the soil's biological community are key because they benefit many other soil properties of a physical, chemical, and biological nature, thus determining the soil's healthy functioning, where the vines may thrive for a long time, whereas its surroundings remain minimally disturbed. In the present review, the importance of soil health as it relates to vineyards is discussed, the soil degradation factors and processes that threaten winegrowing areas are presented, successful soil-health enhancement practices are shown, and future research trends are identified for the benefit of researchers and stakeholders in this special agricultural industry. [ABSTRACT FROM AUTHOR]

A proper understanding of soil parameters under different production systems of the world is necessary for efficient soil management. We, therefore, carried out the present study to assess the status of some selected soil properties (soil pH and electrical conductivity (EC)), phyto-available nutrients (available nitrogen (AN), available potassium (AK), exchangeable calcium (Ex. Ca), exchangeable magnesium (Ex. Mg), available sulfur (AS), and soil organic carbon (SOC) pools (SOC, total organic carbon (TOC), very labile C, labile C, less labile C, and non-labile C) and to establish relationships among the measured soil parameters at different depths of Vertisols of India under various land uses. A total of 150 composite soil samples (from 25 plots including nine from agricultural land, nine from horticultural land, three from forest land, and four from grassland) were collected from 6 soil depths viz, 0–10, 10–20, 20–40, 40–60, 60–80, and 80–100 cm under agriculture, horticulture, forest, and grassland land uses present in Central India and analyzed. The values of soil pH, EC, AN, AK, Ex. Ca, Ex. Mg, and AS in various soil depths under different land uses varied widely. The values of SOC (0.19 to 1.00%), TOC (0.58 to 2.42%), very labile C (0.14 to 0.83%), labile C (0.05 to 0.25%), less labile C (0.05 to 0.26%) and non-labile C (0.23 to 1.42%) in various soil depths under different land uses also varied significantly. Forest and grassland land uses had higher levels of SOC, TOC, very labile, and non-labile C content in all the soil depths in comparison to SOC, TOC, very labile, and non-labile C content in different soil depths under agriculture and horticulture land use. The levels of SOC, TOC, very labile, and non-labile C content under all the land uses decreased with increasing soil depths. SOC was positively and significantly correlated with AN, AK, AS, and estimated SOC pools in surface soil layers. Principal component analysis (PCA) of soil parameters in different soil depths resulted in 5 principal components (PCs) with > 1 eigenvalue and accounting for > 75% variability. This information could be used for managing SOC status and phyto-available nutrients in Vertisols under different land uses. [ABSTRACT FROM AUTHOR]

In arid mountainous areas with stony soils in the Eastern Tibetan Plateau, intensively managed orchards (which include the need for plowing, irrigation, and soil stone removal), eco-forests, and grasslands, all converted from croplands, are becoming increasingly popular. We randomly collected soil samples at 0–15, 15–30, 30–45, and 45–60 cm depths from the four land-use types on the northern and southern slopes in the region. Differences in soil organic carbon (SOC) content/stock, soil water content (SWC), and rock fragment content (RFC) in land-use types and slopes were analyzed using two-way ANOVA. The factors' contributions to SOC variation were assessed using mixed-effect models. Results showed the following: (1) In topsoil (0–30 cm), SOC contents followed the order eco-forest > orchard > grassland ≈ cropland; in subsoil (30–60 cm), the order was orchard > eco-forest > cropland ≈ grassland. SOC stocks (0–60 cm) were higher in orchards (93.72 Mg ha−1) and eco-forests (92.44 Mg ha−1) than in grasslands (53.65 Mg ha−1) and croplands (53.05 Mg ha−1). Contributions of SOC stocks at the 0–15 cm depth level to total SOC were above 40% for GL and EF and between 27 and 35% for OL and CL; at the 45–60 cm level, OL contributed 16–20% and was higher than 10–15% for the other land-use types. (2) Eco-forests and grasslands showed increased SOC contents/stocks at all soil layers on the northern slope than on the southern one. Orchards and croplands, however, showed no differences in contents between slopes. (3) Land-use types, TN, SWC, RFC, slope aspect, and management practices significantly affected SOC variation. Our results suggest that forest plantations (orchards and eco-forests) in arid mountainous regions, through active management practices (e.g., irrigation and fertilization), are vital for improving soil carbon sinks and achieving peak carbon/carbon neutrality goals. [ABSTRACT FROM AUTHOR]

The present work was designed to study a soil sequence in Mount Mandara, in order to identify the influence of altitude, soil characteristics, and land use on the accumulation of soil organic carbon (SOC). The study was conducted in four sites in the Far-North region of Cameroon, including Zamai, Kossohone, Sir, and Rhumsiki. Three pits were dug down to the weathering horizons in three positions (upslope, mid-slope, and footslope) along a representative toposequence in each site. Samples were taken from each pit at regular increment of 25 cm from the soil surface. The total SOC stock (T-SOCS) contents are 128.63 ± 5.25 Mg ha−1 in Arenosols at Zamai (608 m a.s.l.), 158.248 ± 10.52 Mg ha−1 in Leptosols at Kosohone (865 m a.s.l.), 158.99 ± 13.25 Mg ha−1 in Luvisols at Sir (970 m a.s.l.), and 144.79 ± 24.23 Mg ha−1 in Regosols at Rhumsiki (1050 m a.s.l.). The main secondary minerals are smectite, kaolinite, sepiolite, lepidocrocite, hematite, and calcite. Clay minerals and iron oxides are good receptacle for SOC and might constitute a major asset for the accumulation and the sequestration of SOC. Increase in elevation leads to decrease in the annual temperature which affect microbial activity, leading thus to a slow rate of soil organic matter (SOM) decomposition, which thereby affected SOCS. This is confirmed by the significant correlation between altitudinal gradient and T-SOCS (r = 0.70), with altitude contributing to the accumulation of SOC for 49.68%. Texture also plays a central role in carbon sequestration in the studied area, confirmed by the significant and positive correlation between silt fraction and SOM. Under Regosols, there is a decrease in T-SOCS value as a result of a reduction of the quantity of organic matter returned to the soil and more rapid SOM decomposition due to ploughing. This research provides a preliminary assessment for SOC stock at Mount Mandara. It suggests that altitudinal gradient, land use, and soil characteristics should be included in SOCS models and estimations at local and regional scales. [ABSTRACT FROM AUTHOR]

Rapid and accurate mapping of soil organic carbon (SOC) is of great significance to understanding the spatial patterns of soil fertility and conducting soil carbon cycle research. Previous studies have dedicated considerable efforts to the spatial prediction of SOC content, but few have systematically quantified the effects of environmental covariates selection, the spatial scales and the model types on SOC prediction accuracy. Here, we spatially predicted SOC content through digital soil mapping (DSM) based on 186 topsoil (0–20 cm) samples in a typical hilly red soil region of southern China. Specifically, we first determined an optimal covariate set from different combinations of multiple environmental variables, including multi-sensor remote sensing images (Sentinel-1 and Sentinel-2), climate variables and DEM derivatives. Furthermore, we evaluated the impacts of spatial resolution (10 m, 30 m, 90 m, 250 m and 1000 m) of covariates and the model types (three linear and three non-linear machine learning techniques) on the SOC prediction. The results of the performance analysis showed that a combination of Sentinel-1/2-derived variables, climate and topographic predictors generated the best predictive performance. Among all variables, remote sensing covariates, especially Sentinel-2-derived predictors, were identified as the most important explanatory variables controlling the variability of SOC content. Moreover, the prediction accuracy declined significantly with the increased spatial scales and achieved the highest using the XGBoost model at 10 m resolution. Notably, non-linear machine learners yielded superior predictive capability in contrast with linear models in predicting SOC. Overall, our findings revealed that the optimal combination of predictor variables, spatial resolution and modeling techniques could considerably improve the prediction accuracy of the SOC content. Particularly, freely accessible Sentinel series satellites showed great potential in high-resolution digital mapping of soil properties. [ABSTRACT FROM AUTHOR]

The essential roles of Fe oxides in stabilizing long-term soil organic carbon (SOC), especially aromatic dissolved organic carbon (DOCaro), are well-established in forest soils and sediments. We chose to focus on these processes in agricultural soils in which the input and translocation of native DOC to deeper soils are impacted by management practices. We quantified SOC, Fe oxide bound SOC (Fe-bound OC), and the DOCaro sorption in a forest, a cropland, and a pasture soil at 0–10 and 10–25 cm. Significantly larger amounts of Fe oxides in the cropland soil were observed compared to the forest and pasture soils at both depths (p < 0.05). Land management practices and depth both significantly influenced the Fe-bound OC percentage (p < 0.05). Larger maximum sorptions of DOC in the cropland (315.0 mg kg−1) and pasture (395.0 mg kg−1) soils than the forest soil (96.6 mg kg−1) at 10–25 cm weres found. DOCaro sorption decreased in the three soils at 0–10 cm (slope of −0.002 to −0.014 L2 mg−2 m−1) as well as the forest soil at 10–25 cm (−0.016 L2 mg−2 m−1) with increasing equilibrium DOC concentration. Conversely, the cropland and pasture soils at 10–25 cm increased (0.012 to 0.014 L2 mg−2 m−1). The different sorption behaviors of DOCaro in these surface soils indicate that the forest, cropland, and pasture-managed soils may have more complex and various sorption behaviors in stabilizing DOCaro and non-DOCaro. [ABSTRACT FROM AUTHOR]

Soil organic carbon (SOC) plays a crucial role in global carbon cycling. The amount of SOC is influenced by many factors (climate, topography, forest type, forest disturbance, etc.). To investigate this potential effect, we performed a multiple regression model using six different predictor variables in the third national-level forest resource assessment data of Nepal. We found a significant correlation between the SOC and altitude (r = 0.76) followed by crown cover and slope. The altitude alone explains r2 = 58 percent of the variability of the SOC and shows an increasing rate of change of SOC with the increase of altitude. Altitude was identified as a suitable predictor of SOC for large areas with high altitudinal variation followed by crown cover and slope. Increasing amounts of SOC with increasing altitude shows the significance of high-altitude forests in the perspective of climate change mitigation. Altitude, a proxy of temperature, provides insights into the influence of changing temperature patterns on SOC due to future climate change. Further study on forest types and SOC along the altitudinal gradient in Nepal is recommended to deal with the climate change problem in the future. [ABSTRACT FROM AUTHOR]

Soil salinization is closely related to land degradation, and it is supposed to exert a significant negative effect on soil organic carbon (SOC) stock dynamics. This effect and its mechanism have been examined at site and transect scales in previous studies while over a large spatial extent, the salinity-induced changes in SOC stock over space and time have been less quantified, especially by machine learning and remote sensing techniques. The main focus of this study is to answer the following question: to what extent can soil salinity exert an additional effect on SOC stock over time at a larger spatial scale? Thus, we employed the extreme gradient boosting models (XGBoost) combined with field site-level measurements from 433 sites and 41 static and time-varying environmental covariates to construct methods capable of quantifying the salinity-induced SOC changes in a typical inland river basin of China between the 1990s and 2020s. Results showed that the XGBoost models performed well in predicting the soil electrical conductivity (EC) and SOC stock at 0–20 cm, with the R2 value reaching 0.85 and 0.81, respectively. SOC stock was found to vary significantly with increasing soil salinity following an exponential decay function (R2 = 0.27), and salinity sensitivity analysis showed that soils in oasis were expected to experience the largest carbon loss (−137.78 g m−2), which was about 4.84, 14.37, and 25.95 times higher than that in the saline, bare, and sandy land, respectively, if the soil salinity increased by 100%. In addition, the decrease in the soil salinity (−0.32 dS m−1) from the 1990s to the 2020s was estimated to enhance the SOC stock by 0.015 kg m−2, which contributed an additional 10% increase to the total SOC stock enhancement. Overall, the proposed methods can be applied for quantification of the direction and size of the salinity effect on SOC stock changes in other salt-affected regions. Our results also suggest that the role of soil salinization should not be neglected in SOC changes projection, and soil salinization control measures should be further taken into practice to enhance soil carbon sequestration in arid inland river basins. [ABSTRACT FROM AUTHOR]