Topsoil Soil Organic Carbon Stocks Research Articles

European topsoil bulk density and organic carbon stock database (0–20 cm) using machine-learning-based pedotransfer functions

Abstract. Soil bulk density (BD) serves as a fundamental indicator of soil health and quality, exerting a significant influence on critical factors such as plant growth, nutrient availability, and water retention. Due to its limited availability in soil databases, the application of pedotransfer functions (PTFs) has emerged as a potent tool for predicting BD using other easily measurable soil properties, while the impact of these PTFs' performance on soil organic carbon (SOC) stock calculation has been rarely explored. In this study, we proposed an innovative local modeling approach for predicting BD of fine earth (BDfine) across Europe using the recently released BDfine data from the LUCAS Soil (Land Use and Coverage Area Frame Survey Soil) 2018 (0–20 cm) and relevant predictors. Our approach involved a combination of neighbor sample search, forward recursive feature selection (FRFS), and random forest (RF) models (local-RFFRFS). The results showed that local-RFFRFS had a good performance in predicting BDfine (R2 of 0.58, root mean square error (RMSE) of 0.19 g cm−3, relative error (RE) of 16.27 %), surpassing the earlier-published PTFs (R2 of 0.40–0.45, RMSE of 0.22 g cm−3, RE of 19.11 %–21.18 %) and global PTFs using RF models with and without FRFS (R2 of 0.56–0.57, RMSE of 0.19 g cm−3, RE of 16.47 %–16.74 %). Interestingly, we found that the best earlier-published PTF (R2 = 0.84, RMSE = 1.39 kg m−2, RE of 17.57 %) performed close to the local-RFFRFS (R2 = 0.85, RMSE = 1.32 kg m−2, RE of 15.01 %) in SOC stock calculation using BDfine predictions. However, the local-RFFRFS still performed better (ΔR2 > 0.2) for soil samples with low SOC stocks (< 3 kg m−2). Therefore, we suggest that the local-RFFRFS is a promising method for BDfine prediction, while earlier-published PTFs would be more efficient when BDfine is subsequently utilized for calculating SOC stock. Finally, we produced two topsoil BDfine and SOC stock datasets (18 945 and 15 389 soil samples) at 0–20 cm for LUCAS Soil 2018 using the best earlier-published PTF and local-RFFRFS, respectively. This dataset is archived on the Zenodo platform at https://doi.org/10.5281/zenodo.10211884 (S. Chen et al., 2023). The outcomes of this study present a meaningful advancement in enhancing the predictive accuracy of BDfine, and the resultant BDfine and SOC stock datasets for topsoil across the Europe enable more precise soil hydrological and biological modeling.

Space-time mapping of soil organic carbon stock and its local drivers: Potential for use in carbon accounting

The measurement and tracking of changes in soil organic carbon (SOC) stocks and its underpinning drivers are important in greenhouse gas accounting and carbon trading schemes. While repeated direct measurement of a location over time is the ‘gold standard’ for SOC stock change estimation, this is currently unfeasible at scale due to sample collection and analysis costs. Here, we used a data-driven, space–time digital soil mapping modelling approach (ST-DSM) coupled with an interpretive machine learning (IML) technique to both predict and quantify the relative contributions of covariates to annual SOC stocks and their uncertainty at 0–30 cm depth and at a 90 m spatial resolution for Australia between 1990 and 2018. A quantile regression forest model was calibrated using data from a datacube comprising of SOC stock values collected over the prediction years and a suite of dynamic and static environmental covariates. The evaluation of the ST-DSM model on a test set was satisfactory. Long-term annual mean (Mg C/ha), and total (Pg C) topsoil SOC stock were 37.6 (12.3 – 101.1, 90 % PI) and 28.3 (9.25 – 83.1, 90 % PI) respectively. The mean annual rate of SOC stock change over the Australian continent was 0.11 (±0.22) Mg C/ha yr−1 and the total net change was 23.5 Tg C yr−1, indicating Australia’s soils were a net sink of SOC over the 29-year period. However, SOC stocks declined in the montane ecoregion, a great concern given its fragility and high SOC stock. The long-term mean fraction of photosynthetic vegetation was the most important individual local contributor to SOC stock prediction in many parts of Australia. The aggregated effect of covariates based on the soil forming factors indicates vegetation as the principal local driver of SOC stock across most of the Australian continent, followed by climate. The evaluation of our results against independent, temporally paired field data and estimates from a nationally accepted SOC process-based model yielded promising results. Our approach demonstrates the use of readily available and inexpensive covariates to estimate SOC stock changes, as well as the underlying drivers over a larger area but at a spatial resolution suitable for decision making. This approach presents a new monitoring and verification possibility for carbon projects and national carbon accounting especially with the growing number of existing profile observations in soil databases.

Regional topsoil organic carbon content in the agricultural soils of Slovakia and its drivers, as revealed by the most recent national soil monitoring data

Soil organic carbon (SOC) is a primary constituent of soil organic matter and plays an important role in the regulation of many soil processes, including greenhouse gas emissions. Recently, SOC also became an indicator for monitoring climate change mitigation policies in the agricultural sector. The availability of up-to-date SOC inventories is thus crucial in terms of supporting SOC–related actions at country or sub-country scales. Currently, the National Monitoring System of the Agricultural Soils of Slovakia (CMS-P), whose network of 318 monitoring sites was last surveyed in 2018, is the only available source of up-to-date topsoil SOC data for agricultural land in Slovakia. Although very useful at the national scale, the number of CMS-P observations it contains is too limited for much needed sub-national SOC inventories. We hypothesized that with the aid of well-chosen macro-scale drivers of topsoil SOC accumulation in agricultural land in Slovakia, and by mapping those drivers geographically, we could upscale the CMS-P observations and produce a regional estimate of topsoil SOC. Altitude, land cover, topsoil texture, and soil type were assumed to be the key factors controlling topsoil SOC accumulation in Slovakia, and based on these, the country was classified into 14 macro-scale geographical regions. Typical ranges and mid-class values of 0–30cm topsoil SOC concentrations (%) and stocks (t ha−1) were calculated for each macro-scale region from CMS-P data. The average topsoil SOC content in agricultural land was estimated to be 2.13% (72.9 t ha−1). The highest topsoil SOC stock (> 90 t ha−1) was estimated for the lowlands of Slovakia, and the lowest (< 50 t ha−1) for the shallow and stony soils of mountain regions. When aggregated to 78 administrative regions at LAU1 level, the area-weighted averages ranged between 39.20 t ha−1 and 80.0 t ha−1, with the highest values (> 65 t ha−1) being in LAU1 regions in the south-west, south-east, and north of Slovakia where arable land is most prevalent. Total SOC storage in 0–30cm topsoil of agricultural land in Slovakia was estimated at 118.39 Mt, with two-thirds of this amount stored in arable soils in 33 south-west, south-east, and south LAU1 administrative regions. As there is no alternative and up-to-date dataset on topsoil SOC content in Slovakia, the upscaling algorithm presented in this study is an important step toward utilizing CMS-P data for sub-national SOC inventories. It may also offer a new way of providing inputs to help predict future or alternative regional topsoil SOC accumulation trajectories in Slovakian agricultural land using process-based or statistical models.

Soil organic carbon stocks in European croplands and grasslands: How much have we lost in the past decade?

The EU Soil Strategy 2030 aims to increase soil organic carbon (SOC) in agricultural land to enhance soil health and support biodiversity as well as to offset greenhouse gas emissions through soil carbon sequestration. Therefore, the quantification of current SOC stocks and the spatial identification of the main drivers of SOC changes is paramount in the preparation of agricultural policies aimed at enhancing the resilience of agricultural systems in the EU. In this context, changes of SOC stocks (Δ SOCs) for the EU + UK between 2009 and 2018 were estimated by fitting a quantile generalized additive model (qGAM) on data obtained from the revisited points of the Land Use/Land Cover Area Frame Survey (LUCAS) performed in 2009, 2015 and 2018. The analysis of the partial effects derived from the fitted qGAM model shows that land use and land use change observed in the 2009, 2015 and 2018 LUCAS campaigns (i.e. continuous grassland [GGG] or cropland [CCC], conversion grassland to cropland (GGC or GCC) and vice versa [CGG or CCG]) was one of the main drivers of SOC changes. The CCC was the factor that contributed to the lowest negative change on Δ SOC with an estimated partial effect of -0.04 ± 0.01 g C kg-1 year-1 , while the GGG the highest positive change with an estimated partial effect of 0.49 ± 0.02 g C kg-1 year-1 . This confirms the C sequestration potential of converting cropland to grassland. However, it is important to consider that local soil and environmental conditions may either diminish or enhance the grassland's positive effect on soil C storage. In the EU + UK, the estimated current (2018) topsoil (0-20 cm) SOC stock in agricultural land below 1000 m a.s.l was 9.3 Gt, with a Δ SOC of -0.75% in the period 2009-2018. The highest estimated SOC losses were concentrated in central-northern countries, while marginal losses were observed in the southeast.

Predicting soil organic carbon stocks under future land use and climate change conditions in Northeast China

There are large uncertainties in predicting soil organic carbon (SOC) in response of future changing climate and human activities. This study estimates SOC stocks under future changing land use and climate conditions in Northeast China using a state-of-the-art digital soil mapping technique. A total of 487 soil samples and 12 environmental variables from 37 landscape units (derived from soil, topography, climate, and human activity data) combined with boosted regression trees (BRT) and random forest (RF) models are first used to map the topsoil (0–20 cm) SOC stocks in Northeast China in 2015. The primary environmental variables influencing the variability of SOC stocks are mean annual temperature, elevation, mean annual precipitation, and land use. We then applied the space-for-time substitution method in conjunction with the BRT model to predict the spatial distribution of SOC stocks under future (the 2050s and 2090s) climate and land use scenarios. SOC stocks under the scenarios of shared socioeconomic pathways (SSP245) and SSP585 (average and upper estimate of the increase in atmospheric greenhouse gases for that time) decreased by 1.5% and 4.5% in the 2050s, respectively, compared with 2015 (5293 Tg C). For the 2090s, the SOC stocks under the SSP245 scenario increased by 1.9%, and those under the SSP585 scenario decreased by 0.4%. The SOC stocks in both future periods are mainly stored in farmlands and forests, accounting for 90% and 92% of the total SOC stocks, respectively. Our high-resolution estimated SOC maps provide a scientific basis for optimizing ecological management in Northeast China.

Crop diversification effects on soil organic carbon and nitrogen storage and stabilization is mediated by soil management practices in semiarid woody crops

Crop diversification is a promising strategy to mitigate climate change through soil carbon sequestration while ensuring soil fertility maintenance and food security. Here, we assess the impact of different inter-cropping practices on soil organic carbon (SOC) and nitrogen (N) storage and stabilization under rainfed and irrigated semiarid conditions. Under rainfed conditions, an almond (Prunus dulcis Mill.) monocrop was compared with an almond inter-cropped with caper (Capparis spinosa) or with winter thyme (Thymus hyemalis). Under irrigated conditions, a mandarin (Citrus reticulata Blanco) monocrop was compared with a mandarin inter-cropped with an annual crop rotation (including Hordeum vulgare, Vicia sativa and Vicia faba) or with a triennial crop rotation (including Vicia faba, Portulaca oleracea and Vigna unguiculata L.). The SOC and N stocks, SOC mineralization rates, water-stable aggregates and associated OC and N contents were estimated at 0–10 and 10–30 cm depth in each monocrop and inter-cropping system after three years. Contrasting effects of inter-cropping on SOC and N stabilization were found in the rainfed and irrigated systems. The combination of inter-cropping and no tillage did not affect the SOC stocks or mineralization rates at any soil depth in the rainfed system, while it significantly increased the OC and N contents within the large macro-aggregates in the subsoil. Compared to the irrigated mandarin monocrop, the mandarins inter-cropped with the annual crop rotation showed a significant increase of 10% and 18% in the topsoil and subsoil N stocks, respectively, while the SOC mineralization rates were reduced by 30% at both soil depths. On the contrary, the topsoil SOC stock in the mandarins inter-cropped with the triennial crop rotation were reduced by 38% compared to the monocrop. Significant reductions ranging between 24% and 66% were also observed in the OC and N contents associated to the macro- and micro-aggregates in the topsoil and subsoil of both crop diversifications compared to the monocrop system. Our results highlight the potential of inter-cropping rainfed woody crops with perennials for boosting SOC and N storage and stabilization. In irrigated woody monocrops, inter-cropping with annual crop rotation schemes that include two or more leguminous and reducing tillage frequency operations seems to be more appropriate in terms of SOC and N stabilization.

Managing soil organic carbon in tropical agroecosystems: evidence from four long-term experiments in Kenya

Abstract. In sub-Saharan Africa, maize is one of the most important staple crops, but long-term maize cropping with low external inputs has been associated with the loss of soil fertility. While adding high-quality organic resources combined with mineral fertilizer has been proposed to counteract this fertility loss, the long-term effectiveness and interactions with site properties still require more understanding. This study used repeated measurements over time to assess the effect of different quantities and qualities of organic resource addition combined with mineral nitrogen (N) on the change of soil organic carbon (SOC) contents over time (and SOC stocks in the year 2021) in four ongoing long-term experiments in Kenya. These experiments were established with identical treatments in moist to dry climates, on coarse to clayey soil textures, and have been conducted for at least 16 years. They received organic resources in quantities equivalent to 1.2 and 4 t C ha−1 yr−1 in the form of Tithonia diversifolia (high quality, fast turnover), Calliandra calothyrsus (high quality, intermediate turnover), Zea mays stover (low quality, fast turnover), sawdust (low quality, slow turnover) and local farmyard manure (variable quality, intermediate turnover). Furthermore, the addition of 240 kg N ha−1 yr−1 as mineral N fertilizer or no fertilizer was the split-plot treatment. At all four sites, a loss of SOC was predominantly observed, likely because the sites had been converted to cropland only a few decades before the start of the experiments. Across sites, the average decline of SOC content over 19 years in the 0 to 15 cm topsoil layer ranged from 42 % to 13 % of the initial SOC content for the control and the farmyard manure treatments at 4 t C ha−1 yr−1, respectively. Adding Calliandra or Tithonia at 4 t C ha−1 yr−1 limited the loss of SOC contents to about 24 % of initial SOC, while the addition of sawdust, maize stover (in three of the four sites) and sole mineral N addition showed no significant reduction of SOC loss over the control. Site-specific analyses, however, did show that at the site with the lowest initial SOC content (about 6 g kg−1), the addition of 4 t C ha−1 yr−1 farmyard manure or Calliandra with mineral N led to a gain in SOC contents. The other sites lost SOC in all treatments, albeit at site-specific rates. While subsoil SOC stocks in 2021 were little affected by organic resource additions (no difference in three of the four sites), the topsoil SOC stocks corroborated the results obtained from the SOC content measurements (0–15 cm) over time. The relative annual change of SOC contents showed a higher site specificity in farmyard manure, Calliandra and Tithonia treatments than in the control treatment, suggesting that the drivers of site specificity in SOC buildup (soil mineralogy, soil texture, climate) need to be better understood for effective targeting management of organic resources. Farmyard manure showed the highest potential for reducing SOC losses, but the necessary quantities to build SOC are often not realistic for smallholder farmers in Africa. Therefore, additional agronomic interventions such as intercropping, crop rotations or the cultivation of crops with extended root systems are necessary to maintain or increase SOC.

Impacts of straw return coupled with tillage practices on soil organic carbon stock in upland wheat and maize croplands in China: A meta-analysis

Despite numerous individual studies evaluating the impact of straw return on soil organic carbon (SOC) stock in upland wheat and maize croplands in China using no-tillage (NTS), rotary tillage (RTS), and deep tillage (DTS) practices, the results have shown inconsistency. In addition, several factors influence the effects of various tillage practices with straw return on SOC stock that are not well understand. In this study, we conducted a meta-analysis of 764 comparisons to determine the combined impact of SOC stock in the topsoil (0–20 cm) and subsoil (20–40 cm) layers, while considering factors such as climate conditions, management practices, and initial soil properties. The results indicate that straw return with different tillage practices significantly improved SOC stock in both soil layers compared to straws removal. The increase in topsoil SOC stock was nearly identical for NTS (7.38 %) and DTS (7.17 %), compared to the RTS. However, the increase in subsoil SOC stock was significantly higher for DTS (28.8 %). According to subgroup analysis, NTS has been more effective in increasing topsoil SOC stock in regions with medium temperature (10–15 °C) and low precipitation (<400 mm), when used in a single cropping system. However, in regions with higher temperature (>15 °C) and precipitation (>800 mm), DTS is more effective in increasing SOC stock in both topsoil and subsoil layers in a double cropping system. Long-term (11–20 years) DTS resulted in a significant increase in SOC stock in the topsoil (19.2 %) and subsoil (18.5 %), while the increased effects of NTS on SOC stock were only in topsoil layer (17.1 %). The effects of straw return on SOC stock were also found to be associated with soil texture, with NTS having a greater impact on sandy to loam soils, and DTS having a greater impact on clay soils. Furthermore, a significant (P < 0.01) positive linear relationship was observed between annual carbon (C) input and SOC sequestration in the topsoil under NTS, as well as in both soil layers under DTS. These findings have important implications for enhancing SOC in Chinese upland wheat and maize cropland soils through optimizing straw return, given that more than 518 million tons of crop straw are produced annually.

SOC sequestration affected by fertilization in rice-based cropping systems over the last four decades

Enhancing soil organic carbon (SOC) stocks through fertilization and crop rotation will contribute to sustaining crop productivity and mitigating global warming. In this study, we analyzed the differences in total SOC stocks and their driving factors in the topsoil (0–20 cm) with various fertilization measures in two puddled lowland rice-based cropping systems (i.e., rice-wheat rotation and double rice rotation systems) over the last four decades from seven long-term experiments in the Yangtze River catchment. The soil types include Cambisol, Luvisol, and Anthrosol. The treatments include no fertilizer application (CK), application of chemical nitrogen, phosphorus and potassium fertilizers (NPK) and a combination of NPK and manure applications (NPKM). Every year, field was ploughed to a depth of 15–20 cm before wheat sowing and rice transplanting. Residue was removed after plant harvesting. Results showed that during the last four decades, the average crop grain yield ranged from 1,151 ± 504 kg ha−1 yr−1 under CK treatment to 7,553 ± 1,373 kg ha−1 yr−1 under NPKM treatment. The topsoil SOC stock significantly increased by 8.6 t ha−1 on average under NPKM treatment in rice-wheat system and by 2.5–6.4 t ha−1 on average under NPK and NPKM treatments in double rice system as compared with CK. A higher SOC sequestration rate and a longer SOC sequestration duration were found in NPKM treatment than that in NPK treatment in both cropping systems. The highest SOC stock ratio (SOC stock in fertilizer treatments to CK) was observed under the NPKM treatment in both cropping systems, though no significant difference was found between these two cropping systems. However, the fertilization-induced relative increase of the SOC stock was 109.5% and 45.8% under the NPK and NPKM treatments, respectively in the rice-wheat system than that in the double rice system. This indicates that the rice-wheat system is more conducive for SOC sequestration. RF and SEM analyses revealed that the magnitude and influencing factors driving SOC sequestration varied between two systems. In the double rice system, continuous flooding weakens the influence of precipitation on SOC sequestration and highlights the importance of soil properties and C input. In contrast, soil properties, C input and climate factors all have important impacts on SOC sequestration in rice-wheat system. This study reveals that the rice-wheat system is more favorable for SOC sequestration despite its lower C input compared to the double rice system in China’s paddies.

The legacy of one hundred years of climate change for organic carbon stocks in global agricultural topsoils

Soil organic carbon (SOC) of agricultural soils is observed to decline in many parts of the world. Understanding the reasons behind such losses is important for SOC accounting and formulating climate mitigation strategies. Disentangling the impact of last century’s climate change from effects of preceding land use, management changes and erosion is difficult and most likely impossible to address in observations outside of warming experiments. However, the record of last century’s climate change is available for every part of the globe, so the potential effect of climate change on SOC stocks can be modelled. In this study, an established and validated FAO framework was used to model global agricultural topsoil (0–30 cm) SOC stock dynamics from 1919 to 2018 as attributable to climate change. On average, global agricultural topsoils could have lost 2.5 ± 2.3 Mg C ha−1 (3.9 ± 5.4%) with constant net primary production (NPP) or 1.6 ± 3.4 Mg C ha−1 (2.5 ± 5.5%) when NPP was considered to be modified by temperature and precipitation. Regional variability could be explained by the complex patterns of changes in temperature and moisture, as well as initial SOC stocks. However, small average SOC losses have been an intrinsic and persistent feature of climate change in all climatic zones. This needs to be taken into consideration in reporting or accounting frameworks and halted in order to mitigate climate change and secure soil health.

Spatial-temporal variations and driving factors of soil organic carbon in forest ecosystems of Northeast China

Forest soil carbon is a major carbon pool of terrestrial ecosystems, and accurate estimation of soil organic carbon (SOC) stocks in forest ecosystems is rather challenging. This study compared the prediction performance of three empirical model approaches namely, regression kriging (RK), multiple stepwise regression (MSR), random forest (RF), and boosted regression trees (BRT) to predict SOC stocks in Northeast China for 1990 and 2015. Furthermore, the spatial variation of SOC stocks and the main controlling environmental factors during the past 25 years were identified. A total of 82 (in 1990) and 157 (in 2015) topsoil (0–20 ​cm) samples with 12 environmental factors (soil property, climate, topography and biology) were selected for model construction. Randomly selected 80% of the soil sample data were used to train the models and the other 20% data for model verification using mean absolute error, root mean square error, coefficient of determination and Lin's consistency correlation coefficient indices. We found BRT model as the best prediction model and it could explain 67% and 60% spatial variation of SOC stocks, in 1990, and 2015, respectively. Predicted maps of all models in both periods showed similar spatial distribution characteristics, with the lower SOC in northeast and higher SOC in southwest. Mean annual temperature and elevation were the key environmental factors influencing the spatial variation of SOC stock in both periods. SOC stocks were mainly stored under Cambosols, Gleyosols and Isohumosols, accounting for 95.6% (1990) and 95.9% (2015). Overall, SOC stocks increased by 471 ​Tg ​C during the past 25 years. Our study found that the BRT model employing common environmental factors was the most robust method for forest topsoil SOC stocks inventories. The spatial resolution of BRT model enabled us to pinpoint in which areas of Northeast China that new forest tree planting would be most effective for enhancing forest C stocks. Overall, our approach is likely to be useful in forestry management and ecological restoration at and beyond the regional scale.

A precision compost strategy aligning composts and application methods with target crops and growth environments can increase global food production.

Compost represents an important input for sustainable agriculture, but the use of diverse compost types causes uncertain outcomes. Here we performed a global meta-analysis with over 2,000 observations to determine whether a precision compost strategy (PCS) that aligns suitable composts and application methods with target crops and growth environments can advance sustainable food production. Eleven key predictors of compost (carbon-to-nutrient ratios, pH and salt content electric conductivity), management (nitrogen N supply) and biophysical settings (crop type, soil texture, soil organic carbon, pH, temperature and rainfall) determined 80% of the effect on crop yield, soil organic carbon and nitrous oxide emissions. The benefits of a PCS are more pronounced in drier and warmer climates and soils with acidic pH and sandy or clay texture, achieving up to 40% higher crop yield than conventional practices. Using a data-driven approach, we estimate that a global PCS can increase the production of major cereal crops by 96.3 Tg annually, which is 4% of current production. A global PCS has the technological potential to restore 19.5 Pg carbon in cropland topsoil (0-20 cm), equivalent to 26.5% of current topsoil soil organic carbon stocks. Together, this points to a central role of PCS in current and emerging agriculture.

Rejuvenation of iron oxides enhances carbon sequestration by the ‘iron gate’ and ‘enzyme latch’ mechanisms in a rice-wheat cropping system

The ‘enzyme latch’ theory believes that oxygen constraints on phenol oxidase can restrain the activity of hydrolytic enzymes responsible for decomposition, while the ‘iron (Fe) gate’ theory suggests that Fe oxidation can decrease phenol oxidase activity and enhance Fe-lignin complexation under oxygen exposure. The objective of this study was to explore the roles of the ‘enzyme latch’ and ‘Fe gate’ mechanisms in regulating soil organic carbon (SOC) sequestration in a rice-wheat cropping system subjected to six fertilization treatments: control (CT), chemical fertilizer (CF), CF plus manure (CFM), CF plus straw (CFS), CF plus manure and straw (CFMS), and CF plus organic-inorganic compound fertilizer (OICF). Soil samples were collected after the rice and wheat harvests and wet sieved into large macroaggregates, small macroaggregates, microaggregates, and silt and clay particles. Variations in amorphous and free Fe oxides, Fe-bound organic carbon and phenol oxidase activity were examined. After nine years, compared with the initial soil, the activation degree of free Fe oxides increased by 1.3- to 1.6-fold and the topsoil SOC stock increased by 13–61% across all treatments. Amorphous Fe oxide content, phenol oxidase activity and aggregate mean-weight diameter were higher after the wheat harvest than after the rice harvest. Amorphous Fe oxide content was positively correlated with Fe-bound organic carbon content (P < 0.001) but negatively correlated with phenol oxidase activity (P < 0.001). Therefore, seasonal alternation of wetting and drying can progressively drive the rejuvenation of Fe oxides and simultaneously affect the activity of phenol oxidase. Oxidative precipitation of amorphous Fe oxides promoted the formation of organo-Fe complexes and macroaggregates, while flooding of the paddies decreased the activity of phenol oxidase, thereby resulting in year-round hindered decomposition. Organic fertilization strengthened the roles of the ‘Fe gate’ and ‘enzyme latch’ mechanisms, and thus accelerated SOC sequestration in the rice-wheat cropping system.

Isotope analysis reveals differential impacts of artificial and natural afforestation on soil organic carbon dynamics in abandoned farmland

A multitude of studies analyzed the dynamics of soil organic carbon (SOC), but their methodology does not provide sufficient understanding of the differential impact of artificial and natural afforestation on SOC dynamic. We investigated the SOC dynamics following artificial (AR) and natural (NQ) afforestation on abandoned farmland (AF) in China’s Loess Plateau in an attempt to evaluate the effects of these afforestation methods. We characterized soil structure and stoichiometry using stable isotope carbon and radiocarbon models. We aim to compare SOC dynamics, clarify SOC sources under different afforestation, examine comparability of the study areas and ascertain how soil aggregate size classes control SOC dynamics. The 0-10 cm and 10-20 cm SOC stocks were significant higher in NQ than AR and AF. At other depths, there is no significant difference among the three land-use systems. Total topsoil SOC stocks, C:N and C:P of differently sized soil aggregates significantly increased following afforestation. Carbon isotope analysis results indicated that the SOC decomposition rate and the new SOC input rate were lower under NQ than AR. Afforestation can lead to SOC accumulation in soil depths up to 1m mainly because the topsoil (0-20 cm) changes significantly. SOC resources are mainly from macroaggregate formation provided by fresh plant residues. The comparability of study sites is validated, so the“space-for-time substitution” method is applicable in this study.

Soil organic carbon stocks and dynamics in a mollisol region: A 1980s–2010s study

Mollisols are globally distributed in grain-producing regions, and soil organic carbon (SOC) dynamics in mollisol regions are closely related to food security. Regional climate, land use and cover, and field management practice have massively changed since the 1980s in mollisol region in Northeast China, however, the dynamics of topsoil and profile SOC stocks and their distribution have not updated. To explore the dynamics of SOC stocks and their horizontal and vertical distributions in the 1980s–2010s, we took the mollisol region in Northeast China as an example location to conduct profile-scale soil surveys. The in situ surveys indicated that the topsoil SOC stock (0–20 cm) remained relatively stable throughout the 1980s, 2000s, and 2010s, and was 57.3 ± 5.5, 58.2 ± 3.3, and 57.4 ± 4.4 t C ha−1, respectively. The average profile SOC stock (1 m) increased from 148.9 ± 18.5 t C ha−1 in the 1980s to 162.0 ± 14.0 t C ha−1 in the 2010s. A slowdown in land reclamation and implementation of conservation tillage helped maintain and restore SOC stocks. Although the overall SOC stock tended to accumulate, the study area suffered an increasingly unbalanced redistribution of SOC related to severe soil erosion. Soil particles and SOC at erosional positions such as backslope were stripped from the soil surface, leading to attenuated soil thickness and SOC stock; SOC-rich sediment accumulated and was buried at depositional positions, especially at the foot-slope, increasing the soil thickness and SOC stock. These results confirmed that not only the total SOC stock, but also changes in SOC spatial distribution deserve great attention. This study provides a platform to examine and modify the simulation effectiveness of carbon-cycling models, as well as solid foundations for optimal global mollisols management.

Factors controlling soil organic carbon stocks in hardwood floodplain forests of the lower middle Elbe River

We assessed key relationships of soil organic carbon (SOC) stocks to hydromorphic features, soil texture, C/N ratio, pH, and forest age in hardwood floodplain forests. Floodplain ecosystems play a significant role in the global carbon cycle, particularly due to their SOC storage potential. Interactions between heterogeneous micro-relief and anthropogenically affected vegetation and the hydrologic situation of floodplains make predicting SOC stocks difficult without field validation. Especially within hardwood floodplain forests, the controlling factors for SOC storage remain understudied, whereas these floodplain types can be the largest reservoir for carbon and have a substantial SOC sequestration potential. To determine the controlling factors for SOC storage, we selected 38 hardwood floodplain forest and 11 floodplain grasslands of the lower middle Elbe River and categorized them according to vegetation type (grassland, young forest, or old forest) and hydrologic situation (low-lying or high elevated and active or former floodplain). Profile SOC stocks were determined to a depth of 1 m, and topsoil SOC stocks were related to vegetation and soil characteristics, particularly pedological traits (e.g., hydromorphic features).Forest SOC stocks ranged between 99 and 149 t ha−1. SOC stocks decreased with depth throughout all categories and were unaffected by vegetation type within the same hydrologic situation. Vegetation parameters such as age, basal area, or leaf litter carbon stock had no direct effect on SOC stocks. An active connection to the river had the strongest effect on SOC stocks, with former floodplain sites storing 33% less SOC than the active sites. Within the active floodplains, low sites stored 50% more SOC than high sites. This effect was mainly controlled by relief-affected features such as flooding duration and fine texture, which also were the strongest univariate predictors for SOC stocks (R2 = 0.39 and 0.63). A multiple linear regression showed that fine texture, pH, C/N ratio and forest age can be used to explain 86% of variance in SOC stocks.We conclude that proxies for relief and sedimentation (i.e., hydromorphic features, flooding duration, soil texture, C/N ratio, and pH) are the strongest factors controlling SOC stocks in hardwood floodplain forests. Both can be related to allochthonous carbon inputs, increasing SOC stabilization through the accumulation of fine soil particles, and decreasing aerobic carbon mineralization potential through oxygen scarcity, while vegetation plays only a subordinate role.

Estimating soil organic carbon stock change at multiple scales using machine learning and multivariate geostatistics

Many national and international initiatives rely on spatially explicit information on soil organic carbon (SOC) stock change at multiple scales to support policies aiming at land degradation neutrality and climate change mitigation. In this study, we used regression cokriging with random forest and spatial stochastic cosimulation to predict the SOC stock change between two years (i.e. 1992 and 2010) in Hungary at multiple aggregation levels (i.e. point support, 1 × 1 km, 10 × 10 km square blocks, Hungarian counties and entire Hungary). We also quantified the uncertainty associated with these predictions in order to identify and delimit areas with statistically significant SOC stock change. Our study highlighted that prediction of spatial totals and averages with quantified uncertainty requires a geostatistical approach and cannot be solved by machine learning alone, because it does not account for spatial correlation in prediction errors. The total topsoil SOC stock for Hungary was predicted to increase between 1992 and 2010 with 14.9Tg, with lower and upper limits of a 90% prediction interval equal to 11.2Tg and 18.2Tg, respectively. Results also showed that both the predictions and uncertainties of the average SOC stock change were smaller for larger spatial supports, while spatial aggregation also made it easier to obtain statistically significant SOC stock changes. The latter is important for carbon accounting studies that need to prove in Measurement, Reporting and Verification protocols that observed SOC stock changes are not only practically but also statistically significant.

Spatial variation and temporal decline (1985–2017) of soil organic carbon stocks (SOCS) in relation to land use types in Tombel area, South-West Cameroon

In carbon cycle and soil fertility management, SOCS play an important role. A better understanding of spatial variation and temporal decline of SOCS is indispensable for sustainable soil resource management. The purpose of this study was to assess the SOCS spatial distribution and quantify its temporal decline in the Tombel (South-West, Cameroon) area over 32 years (between 1985 and 2017) in relation to land use changes. Quantile Regression Forest (QRF) was applied to map the spatial distribution of SOCS in topsoil (0–30 cm), and its temporal dynamics over 32 years was assessed. A set of 91 and 100 soil samples were included for models calibration for 1985 and 2017, respectively, and models performances were assessed using a 10-fold cross-validation, as well as prediction uncertainties. Over three decades, agricultural and built up area (area such as a town or city with a lot of buildings) experienced a fast expansion, with respective land area increasing rates of 83 % and 81 %. The total SOCS in the study area changed from 22.33 Tg (Tera grams) to 14.68 Tg. Accuracies in the assessment showed good performances for 1985 (R² = 0.62, ME = - 0.06 and RMSE = 11.61 Mg ha−1) and 2017 (R² = 0.58, ME = - 0.03 and RMSE = 13.15 Mg ha−1). Climatic and terrain attributes were the most important predictors of the SOCS distribution. There was on average, about 1.3 Mg ha-1 yr-1 of SOCS decrease between 1985 and 2017, likely due to land use change and controlled by exacerbated agricultural land extension and rapid urbanization. The study provided a sound baseline for land management and decision making for soil quality, carbon accounting and carbon sequestration potential.

Land use and management effects on soil carbon in U.S. Lake States, with emphasis on forestry, fire, and reforestation.

There is growing need to quantify and communicate how land use and management activities influence soil organic carbon (SOC) at scales relevant to, and in the tangible control of landowners and forest managers. The continued proliferation of publications and growth of data sets, data synthesis and meta-analysis approaches allows the application of powerful tools to such questions at ever finer scales. In this analysis, we combined a literature review and effect-size meta-analysis with two large, independent, observational databases to assess how land use and management impact SOC stocks, primarily with regards to forest land uses. We performed this work for the (Great Lakes) U.S. Lake States, which comprise 6% of the land area, but 7% of the forest and 9% of the forest SOC in the United States, as the second in a series of ecoregional SOC assessments. Most importantly, our analysis indicates that natural factors, such as soil texture and parent material, exert more control over SOC stocks than land use or management. With that for context, our analysis also indicates which natural factors most influence management impacts on SOC storage. We report an overall trend of significantly diminished topsoil SOC stocks with harvesting, consistent across all three data sets, while also demonstrating how certain sites and soils diverge from this pattern, including some that show opposite trends. Impacts of fire grossly mirror those of harvesting, with declines near the top of the profile, but potential gains at depth and no net change when considering the whole profile. Land use changes showing significant SOC impacts are limited to reforestation on barren mining substrates (large and variable gains) and conversion of native forest to cultivation (losses). We describe patterns within the observational data that reveal the physical basis for preferential land use, e.g., cultivation of soils with the most favorable physical properties, and forest plantation establishment on the most marginal soils, and use these patterns to identify management opportunities and considerations. We also qualify our results with ratings of confidence, based on their degree of support across approaches, and offer concise, defensible tactics for adapting management operations to site-specific criteria and SOC vulnerability.

Projecting the urbanization effect on soil organic carbon stocks in polar and steppe areas of European Russia by remote sensing

This paper describes the effect of urbanization on soil organic carbon (SOC) stocks by projecting the main urban land cover classes over the initial pre-urban soil maps. Two cities different in climate and soil conditions as well as in availability of SOC data were chosen as the case studies. Rostov-on-Don is the center of Russian South, where croplands and natural steppes have been conventionally thoroughly studied by soil scientists. In contrast, soils of Murmansk located in Russian Arctics have always been overlooked due to low suitability for agriculture. Global, national and regional soil maps and databases were used to estimate pre-urban SOC stocks in the areas. The outcomes based on Harmonized World Soil Database were highly uncertain, underestimating 0-100 cm SOC stocks in the polar region and overestimating them in the steppe region, whereas the results based on Digital Soil Map of Russia and regional maps were comparable. Land cover structures of Rostov-on-Don and Murmansk were mapped based on the stepwise per-pixel and sub-pixel classification algorithms applied to Sentinel-2 and included the following classes: sealed soils, green lawns, trees and shrubs, bare soils and water. Murmansk was dominated by trees and shrubs (58.1%) with the proportion of area 17.5% covered by sealed soils. In Rostov-on-Don, less than 30% of the total area was covered by trees and shrubs which is also comparable with bare soils (19.6%)_and lawns (23.4%), whereas almost one third of the territory was sealed (27.6%). These land cover structures had a different impact on the topsoil SOC stocks: a 30-50% increase in Murmansk compared to the 18% decrease in Rostov-on-Don. An increase of the 0-100 cm SOC stocks was shown for both regions, however in the polar conditions it was two times higher compared to the steppe. In polar conditions, conversion of natural soils into urban non-sealed soils increased SOC stocks from 30% to more than 4 times in 0-10 cm layer and from 47% to almost 3 times in the 0-100 cm layer. The highest increase was reported for the lawns, whereas SOC under trees and shrublands were considerably lower. In Rostov-on-Don , sealed and bare soils stored less SOC compared to the initial natural soils. The conversion of natural areas into urban green infrastructure increased SOC up to 50-70%. Although the absolute SOC values based on the global and national legacy data are highly uncertain, especially for the polar areas, the research outcomes clearly reveal possible patterns in SOC changes induced by different urbanization pathways in contrast climatic conditions and highlight the complexity of the urbanization effect on soils