Future Soil Organic Carbon Stocks Research Articles

Future soil organic carbon stocks in China under climate change

Future soil organic carbon stocks in China under climate change

Evaluation of RothC model for predicting soil organic carbon stock in north-west Ethiopia

Assessing soil organic carbon (SOC) is vital for water retention, soil health, nutrient cycling, greenhouse gas emissions, and pollutant reduction and thereby contributes to sustainable agricultural production and food security. Thus, using long-term climate, soil, and land management inputs, the Rothamsted Carbon (RothC) model was applied to assess the current and future SOC stocks in the Anjeni watershed using long term climate, soil and land management data. RothC was calibrated with long-term SOC, land management, and climatic data from the Anjeni watershed in north-west Ethiopia. The correlation coefficient between simulated and observed SOC in 1997 and 2021 were 0.77 and 0.86, respectively, suggesting that the model could characterize the SOC of the Anjeni watershed. Then, the RothC was used to estimate SOC in the watershed for 30 years, from 2022 to 2052, under three slope gradients and four land use type and carbon storage scenarios (business as usual (BAU), low, medium and high carbon inputs). The result indicated that in the lower slope gradient, the current SOC simulation is less than all future scenarios considered under all land use types. Grass/fallow land showed higher current and projected SOC than cultivated land and plantation forest. Moreover, grass/fallow land with a gentle slope gradient had higher SOC than the watershed's middle and high-elevation parts. Overall, the model projected an increase of SOC under different future scenarios that could be due to climate and land use cover changes, the long-term soil-water conservation camping works and better soil and land managements in the watershed. This future assists for water retention, soil health, nutrient cycling, soil aeration, and greenhouse gas emission reduction, which in turn could enhance agricultural productivity, food security, and sustainable development.

Modeling Climate Regulation of Arable Soils in Northern Saxony under the Influence of Climate Change and Management Practices

One approach to increasing the climate-regulating potential of the agricultural sector is carbon sequestration in agricultural soils. This involves storing atmospheric carbon dioxide in the soil in the form of soil organic carbon (SOC) through agricultural management practices (AMPs). Model simulations of area-specific current and future SOC stocks can be used to test appropriate AMPs. In this study, the CANDY Carbon Balance (CCB) model was used to determine how different AMPs could affect SOC stocks in a study area in northern Saxony, Germany. Specifically, we used scenarios with different intensities of sustainable AMPs to assess the potential effects of reduced tillage, crop cultivation, and fertilizer management, as well as the management of crop residues and by-products. The analysis was carried out for the simulation period 2020–2070, with and without consideration of climate change effects. The results showed an average carbon sequestration potential of 5.13–7.18 t C ha−1 for the whole study area, depending on the intensity of AMP implemented. While higher intensities of sustainable AMP implementation generally had a positive impact on carbon sequestration, the scenario with the highest implementation intensity only led to the second highest gains in SOC stocks. The most important factor in increasing SOC stocks was reduced tillage, which resulted in a carbon sequestration potential of 0.84 t C ha−1 by 2070. However, reduced application rates of fertilizers also proved to be critical, resulting in a reduction in carbon stocks of up to 2.2 t C ha−1 by 2070. Finally, the application of high-intensity sustainable AMPs was shown to be able to offset the negative impacts of an intermediate climate change scenario for most of the simulation period. Overall, the results not only confirmed existing knowledge on the effects of AMPs on carbon sequestration for a specific case study area, but also identified future management scenarios that stress the need for widespread adoption of sustainable management practices under changing climate conditions.

Current and future potential soil organic carbon stocks of vegetated coastal ecosystems and their controls in the Bohai Rim Region, China

Vegetated coastal ecosystems (VCEs) have much higher organic carbon sequestration rates and storage capacities than most other earth surface ecosystems, and thus play a vital role in blue carbon sequestration for climate change mitigation. However, soil organic carbon (SOC) stock assessment in VCEs at a large regional-scale remain problematic, and the controlling mechanisms for SOC remain poorly understood. Here, we estimated current and future SOC stocks of VCEs in the Bohai Rim Region, China at a spatial resolution of 10 m, using a data-driven method based on multi-source data; and investigated the key environmental and anthropogenic controls. The total SOC stocks and SOC density of VCEs in the Bohai Rim Region were estimated to be approximately 62.7 Tg carbon and about 68.8 Mg ha−1, respectively (in the upper 1 m of soil). We found that climate and soil salinity are the most critical environmental controls of SOC stocks within VCEs in the region. Increasing temperature and soil salinity would increase SOC decomposition and decrease plant productivity, resulting in a decrease in SOC stocks. Conversely, increasing precipitation would increase SOC stocks by reducing soil salinity. We projected that the potential losses of SOC stocks due to the combined effects of climate changes, sea-level rise, and anthropogenic disturbances would be ∼ 12.2 % between 2041 and 2060 under two Shared Socioeconomic Pathway (SSP) scenarios (SSP245 and SSP585), extending to 19.3 % between 2081 and 2100. The decreases in SOC stocks would occur mainly in the higher latitude and colder regions. The study demonstrated the potential significant reduction in SOC stocks in coastal ecosystems and provided an important framework for better understanding the blue carbon ecosystems.

Evaluation of projected soil organic carbon stocks under future climate and land cover changes in South Africa using a deep learning approach

Environmental degradation and carbon emissions have become a major global concern. This has forced policymakers to consider strategic and long-term contingencies to increase carbon sequestration capacity and mitigate the effects of climate change. Soil organic carbon (SOC) provides a reliable long-lasting mechanism to ameliorate climate change and regulate carbon fluxes. However, unanticipated rates of climate change coupled with the dynamic nature of land-use transformation threatens current mitigation approaches and can jeopardise carbon stock assimilation. To effectively manage and protect SOC stocks, large-scale projections that accurately model both current and future SOC pools are necessary. Hence, this study modelled the effects of simulated climate and land-cover change on SOC inventories across South Africa up to the year 2050. A digital soil mapping strategy in concert with a deep neural network (DNN) was used to model current SOC stocks distribution. Subsequently, WorldClim general circulation models and a space-for-time substitution (SFTS) method were used to derive future SOC stocks under four shared socio-economic emission pathways. Results show a relatively high accuracy with RMSE of 7.44 t/h for current stocks, while future stocks ranged from 11.37 to 13.56 t/h. Depending on emission rates, results showed a reduction in SOC inventories, with overall SOC stocks declining from 5.64 Pg to between 4.97 and 5.38 Pg by 2050. Meanwhile, forests, which account for approximately 1.2 Pg of total SOC in South Africa, were found to have lost more than 1% of their total coverage by 2050. These findings provide a glimpse into the state of South Africa's current and future SOC stock inventories and the influence of climate and land-use change. These findings are valuable to among others policymakers, land use managers and climate change experts in assessing the long-term feasibility of South Africa's existing SOC management protocols and land-use planning agenda. However, to adequately protect future SOC stocks, current land-use planning frameworks need to be re-adjusted to prioritize pressing environmental concerns.

Soil carbon loss in warmed subarctic grasslands is rapid and restricted to topsoil

Abstract. Global warming may lead to carbon transfers from soils to the atmosphere, yet this positive feedback to the climate system remains highly uncertain, especially in subsoils (Ilyina and Friedlingstein, 2016; Shi et al., 2018). Using natural geothermal soil warming gradients of up to +6.4 ∘C in subarctic grasslands (Sigurdsson et al., 2016), we show that soil organic carbon (SOC) stocks decline strongly and linearly with warming (−2.8 t ha−1 ∘C−1). Comparison of SOC stock changes following medium-term (5 and 10 years) and long-term (>50 years) warming revealed that all SOC stock reduction occurred within the first 5 years of warming, after which continued warming no longer reduced SOC stocks. This rapid equilibration of SOC observed in Andosol suggests a critical role for ecosystem adaptations to warming and could imply short-lived soil carbon–climate feedbacks. Our data further revealed that the soil C loss occurred in all aggregate size fractions and that SOC stock reduction was only visible in topsoil (0–10 cm). SOC stocks in subsoil (10–30 cm), where plant roots were absent, showed apparent conservation after >50 years of warming. The observed depth-dependent warming responses indicate that explicit vertical resolution is a prerequisite for global models to accurately project future SOC stocks for this soil type and should be investigated for soils with other mineralogies.

Optimizing process-based models to predict current and future soil organic carbon stocks at high-resolution

From hillslope to small catchment scales (< 50 km2), soil carbon management and mitigation policies rely on estimates and projections of soil organic carbon (SOC) stocks. Here we apply a process-based modeling approach that parameterizes the MIcrobial-MIneral Carbon Stabilization (MIMICS) model with SOC measurements and remotely sensed environmental data from the Reynolds Creek Experimental Watershed in SW Idaho, USA. Calibrating model parameters reduced error between simulated and observed SOC stocks by 25%, relative to the initial parameter estimates and better captured local gradients in climate and productivity. The calibrated parameter ensemble was used to produce spatially continuous, high-resolution (10 m2) estimates of stocks and associated uncertainties of litter, microbial biomass, particulate, and protected SOC pools across the complex landscape. Subsequent projections of SOC response to idealized environmental disturbances illustrate the spatial complexity of potential SOC vulnerabilities across the watershed. Parametric uncertainty generated physicochemically protected soil C stocks that varied by a mean factor of 4.4 × across individual locations in the watershed and a − 14.9 to + 20.4% range in potential SOC stock response to idealized disturbances, illustrating the need for additional measurements of soil carbon fractions and their turnover time to improve confidence in the MIMICS simulations of SOC dynamics.

Climate Change Impacts on Crop Yield of Winter Wheat (Triticum aestivum) and Maize (Zea mays) and Soil Organic Carbon Stocks in Northern China

Agricultural system models provide an effective tool for forecasting crop productivity and nutrient budgets under future climate change. This study investigates the potential impacts of climate change on crop failure, grain yield and soil organic carbon (SOC) for both winter wheat (Triticum aestivum L.) and maize (Zea mays L.) in northern China, using the SPACSYS model. The model was calibrated and validated with datasets from 20-year long-term experiments (1985–2004) for the Loess plateau, and then used to forecast production (2020–2049) under six sharing social-economic pathway climate scenarios for both wheat and maize crops with irrigation. Results suggested that warmer climatic scenarios might be favourable for reducing the crop failure rate and increasing the grain yield for winter wheat, while the same climatic scenarios were unfavourable for maize production in the region. Furthermore, future SOC stocks in the topsoil layer (0–30 cm) could increase but in the subsoil layer (30–100 cm) could decrease, regardless of the chosen crop.

The effect of agriculture on topsoil carbon stocks is controlled by land use, climate, and soil properties in the Argentinean Pampas

The conversion of native grasslands into croplands with a high frequency of soybean (Glycine max L.) in crop rotations has diminished soil organic carbon (SOC) stocks in the Argentinean Pampas. The aims of our study were to determine the amount of SOC lost due to cultivation (dSOC) and to assess the main factors (land use, climate, and soil properties) associated with dSOC. We took paired topsoil samples (0 to 20 cm) from arable and pristine soils (n = 465) and used a path analysis approach to evaluate the direct and indirect effect of different variables on dSOC. The selected variables were SOC in pristine soils (SOCPRIS), clay content, carbon input (Cinput), relative soybean harvested area (Sb%), and mean annual precipitation and air temperature (PP and Temp, respectively). The percentage of sites with SOC < 20 g kg−1 was 29% in pristine soils and 66% in arable soils. The dSOC ranged from 0 to 82 Mg ha−1. Depending on the area, dSOC represented 25 to 36% of SOCPRIS stocks. The path analysis explained 60% of the dSOC variation, and the main factor controlling dSOC was SOCPRIS (by direct effect and indirect effects through clay, PP, and Temp), followed by Sb%. The Sb% depended on the productive potential of the area (soybean yield) which was associated with Temp and PP. As a conclusion, in the analysed temperate and fully humid environments, soils with greater SOCPRIS and high soybean frequency in the crop rotations presented a greater SOC depletion after conversion to agriculture. This information will be valuable when developing models to predict current and future SOC stocks.

Modelling and mapping soil organic carbon stocks under future climate change in south-eastern Australia

Soil organic carbon (SOC) plays a key role in the sequestration of carbon that could otherwise be warming the atmosphere. Climate change including increased temperature and changed rainfall will greatly impact the global SOC cycle. There are still significant gaps in our knowledge of the size of the global SOC pool and how future climate will affect SOC stocks and flows in many parts of the world, including Australia. In this study, we used SOC data in a Digital Soil Mapping framework to predict current and future SOC stocks across the state of New South Wales (NSW) in south-eastern Australia. In the first phase of the study we estimated the current SOC stock using multiple linear regression (MLR) and random forest (RF) modelling, and in the second phase we projected the change of SOC stocks in the near future (2050s) and far future (2090s) under two Shared Socio-economic Pathways (SSPs) scenarios based on 25 global climate models (GCMs) from the Coupled Model Inter-comparison Project Phase 6 (CMIP6). Our spatial modelling showed that estimated current SOC stocks in NSW decreased from east to west. Multi-GCM ensemble means suggested SOC stocks would decrease by 7.6–12.9% under SSP2-4.5 and 9.1–20.9% under SSP5-8.5 across NSW under future climate. The extent of change in SOC stocks varied spatially with the largest mean decrease of SOC stocks occurring in the North Coast and South East (alpine) regions of NSW. Our findings can support decision-making in land management and climate change mitigation strategies in NSW at the regional level. Furthermore, the modelling methods can be applied to other areas where edaphic and landscape properties, land use, and climate data are available.

Dynamics and Sequestration Potential of Soil Organic Carbon and Total Nitrogen Stocks of Leguminous Green Manure-Based Cropping Systems on the Loess Plateau of China

Estimating the dynamics and future sequestration potential of soil organic carbon stocks (SOCS) and total nitrogen stocks (TNS) is useful to determine whether cropping systems can promote sustainable production in terms of improving soil fertility. The Rothamsted Carbon (RothC) model and the correlations between SOCS and TNS were used to estimate the future SOCS and TNS of green manure-based wheat production systems on the Loess Plateau of China. The field study was a split-plot design with 4 main treatments (Huai bean, soybean and mung bean grown as green manure in summer, with a fallow treatment as the control) and 4 subtreatments (synthetic N rates of 0, 108, 135 and 162 kg ha−1 applied at wheat sowing). Leguminous green manure (LGM) treatments increased the amount of carbon and nitrogen returned to the field by 67–91% and 74–125%, respectively, compared with the fallow treatment (P < 0.05). These treatments also increased SOCS by 15–23% and TNS by 12–22% (P < 0.05) after 8 years in comparison with the fallow treatment. Coupling of the RothC model and the correlations between SOCS and TNS of the 3 LGM treatments generated acceptable simulations for the dynamics of SOCS and TNS. The projected SOCS for LGM and fallow treatments at the new equilibrium are 37.67–47.29 and 13.97–17.58 Mg ha−1, respectively. The corresponding TNS for LGM treatments are 5.42–6.79 Mg ha−1. The projection also indicates that under the LGM treatments, the SOCS and TNS at the new equilibrium will be 107% and 158% higher, respectively, than the values prior to the experiment. In conclusion, growing LGM to replace summer fallow would be a useful alternative to improve soil fertility and promote sustainable crop production.

Agricultural soil organic carbon stocks in the north-eastern Iberian Peninsula: Drivers and spatial variability

Estimating soil organic carbon (SOC) stocks under agriculture, assessing the importance of their drivers and understanding the spatial distribution of SOC stocks are crucial to predicting possible future SOC stocks scenarios under climate change conditions and to designing appropriate mitigation and adaptation strategies. This study characterized and modelled SOC stocks at two soil depth intervals, topsoil (0–30 cm) and subsoil (30–100 cm), based on both legacy and recent data from 7245 agricultural soil profiles and using environmental drivers (climate, agricultural practices and soil properties) for agricultural soils in Catalonia (NE Spain). Generalized Least Square (GLS) and Geographical Weighted Regression (GWR) were used as modelling approaches to: (i) assess the main SOC stock drivers and their effects on SOC stocks; (ii) analyse spatial variability of SOC stocks and their relationships with the main drivers; and (iii) predict and map SOC stocks at the regional scale. While topsoil variation of SOC stocks depended mainly on climate, soil texture and agricultural variables, subsoil SOC stocks changes depended mainly on soil attributes such us soil texture, clay content, soil type or depth to bedrock. The GWR model revealed that the relationship between SOC stocks and drivers varied spatially. Finally, the study was only able to predict and map topsoil SOC stocks at the regional scale, because controlling factors of SOC stocks at the subsoil level were largely unavailable for digital mapping. According to the resulting map, the mean SOC stock value for Catalan agriculture at the topsoil level was 4.88 ± 0.89 kg/m2 and the total magnitude of the carbon pool in agricultural soils of Catalonia up to 30 cm reached 47.9 Tg. The present study findings are useful for defining carbon sequestration strategies at the regional scale related with agricultural land use changes and agricultural management practices in a context of climate change.

Assessment of soil organic carbon stocks under future climate and land cover changes in Europe

Soil organic carbon plays an important role in the carbon cycling of terrestrial ecosystems, variations in soil organic carbon stocks are very important for the ecosystem. In this study, a geostatistical model was used for predicting current and future soil organic carbon (SOC) stocks in Europe. The first phase of the study predicts current soil organic carbon content by using stepwise multiple linear regression and ordinary kriging and the second phase of the study projects the soil organic carbon to the near future (2050) by using a set of environmental predictors. We demonstrate here an approach to predict present and future soil organic carbon stocks by using climate, land cover, terrain and soil data and their projections. The covariates were selected for their role in the carbon cycle and their availability for the future model. The regression-kriging as a base model is predicting current SOC stocks in Europe by using a set of covariates and dense SOC measurements coming from LUCAS Soil Database. The base model delivers coefficients for each of the covariates to the future model. The overall model produced soil organic carbon maps which reflect the present and the future predictions (2050) based on climate and land cover projections. The data of the present climate conditions (long-term average (1950–2000)) and the future projections for 2050 were obtained from WorldClim data portal. The future climate projections are the recent climate projections mentioned in the Fifth Assessment IPCC report. These projections were extracted from the global climate models (GCMs) for four representative concentration pathways (RCPs). The results suggest an overall increase in SOC stocks by 2050 in Europe (EU26) under all climate and land cover scenarios, but the extent of the increase varies between the climate model and emissions scenarios.

Projected changes in soil organic carbon stocks of China's croplands under different agricultural managements, 2011–2050

The timing, magnitude, and regional distribution of soil organic carbon (SOC) changes are uncertain when factoring in climate change and agricultural management practices. The goal of this study is to analyze the implications of changes in climate and agricultural management for Chinese soil carbon sequestration over the next 40 years. We used the Agro-C model to simulate climate and agricultural management scenarios to investigate the combined impacts of climate change and management on future SOC stocks in China's croplands.The model was run for croplands on mineral soils in China, which make up a total of 130Mha of cropland. The model used climate data (years 2011–2050) from the FGOALS and PRECIS climate models based on four Intergovernmental Panel on Climate Change (IPCC) emissions scenarios. Three equidistant agricultural management scenarios were used. S0 was a current scenario, and S2 was an optimal scenario. Under the S2 scenario, crop yields increased annually by 1%, the proportion of crop residue retained in the field reached 90% by 2050, and the area of no-tillage increased to 50% of the cultivated area by 2050. The S1 scenario applied half of the increased rates in crop yields, residue retention and no-tillage area values that were used in the S2 scenario.Across all croplands in China, the results suggest that SOC will increase under all combinations of climate and management and that the effect of climate change is much smaller than the effect of changes in agricultural management. Most croplands in China show a significant increase in SOC stocks, while very few zones (mainly in northeastern China) show a decrease. Rice paddy soils under the intensive farming management scenario show higher rates of carbon sequestration than dry-land soils. The maximum carbon sequestration potential of the croplands of China is estimated to be 2.39PgC under S2. Annual increases in SOC stocks could offset a maximum of 2.9% of the CO2 emissions from fossil-fuel combustion in 2009. These results suggest that China's croplands, especially rice paddies, may play an important role in C sequestration and future climate change mitigation.

Simulation of Salinity Effects on Past, Present, and Future Soil Organic Carbon Stocks

Soil organic carbon (SOC) models are used to predict changes in SOC stocks and carbon dioxide (CO(2)) emissions from soils, and have been successfully validated for non-saline soils. However, SOC models have not been developed to simulate SOC turnover in saline soils. Due to the large extent of salt-affected areas in the world, it is important to correctly predict SOC dynamics in salt-affected soils. To close this knowledge gap, we modified the Rothamsted Carbon Model (RothC) to simulate SOC turnover in salt-affected soils, using data from non-salt-affected and salt-affected soils in two agricultural regions in India (120 soils) and in Australia (160 soils). Recently we developed a decomposition rate modifier based on an incubation study of a subset of these soils. In the present study, we introduce a new method to estimate the past losses of SOC due to salinity and show how salinity affects future SOC stocks on a regional scale. Because salinity decreases decomposition rates, simulations using the decomposition rate modifier for salinity suggest an accumulation of SOC. However, if the plant inputs are also adjusted to reflect reduced plant growth under saline conditions, the simulations show a significant loss of soil carbon in the past due to salinization, with a higher average loss of SOC in Australian soils (55 t C ha(-1)) than in Indian soils (31 t C ha(-1)). There was a significant negative correlation (p < 0.05) between SOC loss and osmotic potential. Simulations of future SOC stocks with the decomposition rate modifier and the plant input modifier indicate a greater decrease in SOC in saline than in non-saline soils under future climate. The simulations of past losses of SOC due to salinity were repeated using either measured charcoal-C or the inert organic matter predicted by the Falloon et al. equation to determine how much deviation from the Falloon et al. equation affects the amount of plant inputs generated by the model for the soils used in this study. Both sets of results suggest that saline soils have lost carbon and will continue to lose carbon under future climate. This demonstrates the importance of both reduced decomposition and reduced plant input in simulations of future changes in SOC stocks in saline soils.

Soil organic carbon stocks in Laos: spatial variations and controlling factors

AbstractSurface soils, which contain the largest pool of terrestrial organic carbon (C), may be able to sequester atmospheric C and thus mitigate climate change. However, this remains controversial, largely due to insufficient data and knowledge gaps in respect of organic C contents and stocks in soils and the main factors of their control. Up to now and despite numerous evaluations of soil organic carbon (SOC) stocks worldwide, the sloping lands of southeast Asia, one of the most biogeochemically active regions of the world, remain uninvestigated. Our main objective was to quantify SOC stocks and to evaluate the impact of various environmental factors. We, therefore, selected Laos with 230 566 km2of mostly forested steep slopes, and where cultivation is still mainly traditional, i.e. a system of shifting cultivation without fertilization or mechanical tillage. Analytical data from 3471 soil profiles demonstrated that the top 1 m of soil depth holds an estimated 4.64 billion tons of SOC, 65% of which is in the first 0.3 m. SOC stocks to 0.3 m exhibit a high coefficient of variation (CV=62%) with values from 1.8 to 771 Mg C ha−1and a mean at 129 Mg C ha−1. Furthermore, these stocks are significantly (atP&lt;0.05 level) affected by land use as shown by principal components analysis andt‐tests with the largest amount being found under forest, less under shifting cultivation and the smallest under continuous cultivation. Moreover, SOC stocks correlated regionally to total annual rainfalls and latitude, and locally at the hill‐slope level to the distance to the stream network and the slope angle. It is hypothesized that this correlation is through actions on mineral weathering, soil clay content, soil fertility and SOC redistributions in landscapes. These relationships between SOC stocks and environmental factors may be of further use in (1) predicting the impact of global changes on future SOC stocks; and (2) identifying optimal strategies for land use planning so as to minimize soil C emissions to the atmosphere while maximizing carbon sequestration in soils.

Assessing scale effects on modelled soil organic carbon contents as a result of land use change in Belgium

AbstractThis paper explores the influence of spatial scale on modelled projections of soil organic carbon (SOC) content. The effect of land use change (LUC) on future SOC stocks was estimated using the Rothamsted Carbon model for a small area of southern Belgium. The study assumed no management change and used a single climate change scenario. Three model experiments were used to identify how data scale affects predicted SOC stocks: (i) using European LUC datasets at a resolution of 10′ and assuming equal distribution of change within the study area, (ii) using more accurate regional data aggregated to the 10’ resolution, and (iii) using the regional data at a spatial resolution of 250 m. The results show that using coarse resolution (10′) data is inappropriate when modelling SOC changes in the study area as only the methods using precise data predict a change in SOC stocks similar to those reported in the literature. This is largely because of differences in model parameterisation. However, precisely locating LUC does not significantly affect the results. The model, using either pan‐European or region‐specific precise data predicts an average SOC increase of 1 t C ha−1 (1990–2050), mainly resulting from afforestation of 13% of agricultural land.

Influence of agricultural management on soil organic carbon: A compendium and assessment of Canadian studies

To fulfill commitments under the Kyoto Protocol, Canada is required to provide verifiable estimates and uncertainties for soil organic carbon (SOC) stocks, and for changes in those stocks over time. Estimates and uncertainties for agricultural soils can be derived from long-term studies that have measured differences in SOC between different management practices. We compiled published data from long-term studies in Canada to assess the effect of agricultural management on SOC. A total of 62 studies were compiled, in which the difference in SOC was determined for conversion from native land to cropland, and for different tillage, crop rotation and fertilizer management practices. There was a loss of 24 ± 6% of the SOC after native land was converted to agricultural land. No-till (NT) increased the storage of SOC in western Canada by 2.9 ± 1.3 Mg ha-1; however, in eastern Canada conversion to NT did not increase SOC. In general, the potential to store SOC when NT was adopted decreased with increasing background levels of SOC. Using no-tillage, reducing summer fallow, including hay in rotation with wheat (Triticum aestivum L.), plowing green manures into the soil, and applying N and organic fertilizers were the practices that tended to show the most consistent in creases in SOC storage. By relating treatment SOC levels to those in the control treatments, SOC stock change factors and their levels of uncertainty were derived for use in empirical models, such as the United Nations Intergovernmental Panel on Climate Change (IPCC). Guidelines model for C stock changes. However, we must be careful when attempting to extrapolate research plot data to farmers’ fields since the history of soil and crop management has a significant influence on existing and future SOC stocks. Key words: C sequestration, tillage, crop rotations, fertilizer, cropping intensity, Canada