Towards an ecosystem capacity to stabilise organic carbon in soils.

Soil organic carbon (SOC) accrual, and particularly the formation of fine fraction carbon (OCfine), has a large potential to act as sink for atmospheric CO2. For reliable estimates of this potential and efficient policy advice, the major limiting factors for OCfine accrual need to be understood. The upper boundary of the correlation between fine mineral particles (silt + clay) and OCfine is widely used to estimate the maximum mineralogical capacity of soils to store OCfine, suggesting that mineral surfaces get C saturated. Using a dataset covering the temperate zone and partly other climates on OCfine contents and a SOC turnover model, we provide two independent lines of evidence, that this empirical upper boundary does not indicate C saturation. Firstly, the C loading of the silt + clay fraction was found to strongly exceed previous saturation estimates in coarse-textured soils, which raises the question of why this is not observed in fine-textured soils. Secondly, a subsequent modelling exercise revealed, that for 74% of all investigated soils, local net primary production (NPP) would not be sufficient to reach a C loading of 80 g C kg-1 silt + clay, which was previously assumed to be a general C saturation point. The proportion of soils with potentially enough NPP to reach that point decreased strongly with increasing silt + clay content. High C loadings can thus hardly be reached in more fine-textured soils, even if all NPP would be available as C input. As a pragmatic approach, we introduced texture-dependent, empirical maximum C loadings of the fine fraction, that decreased from 160 g kg-1 in coarse to 75 g kg-1 in most fine-textured soils. We conclude that OCfine accrual in soils is mainly limited by C inputs and is strongly modulated by texture, mineralogy, climate and other site properties, which could be formulated as an ecosystem capacity to stabilise SOC.

Increased straw return promoted soil organic carbon accumulation in China's croplands over the past 40 years.

Quantifying changes in soil organic carbon (SOC) stocks within croplands across a broad spatiotemporal scale in response to anthropogenic and environmental factors offers valuable insights for sustainable agriculture aimed to improve soil health. Using a validated and widely used soil carbon model RothC, we simulated the SOC dynamics across intensive croplands in China that support ∼22 % of the global population using only 7 % of the global cropland area. The modelling results demonstrate that the optimized RothC effectively captures SOC dynamics measured across 29 long-term field trials during 40 years. Between 1980 and 2020, the average SOC at the top 30 cm in croplands increased from 40 Mg C ha-1 to 49 Mg C ha-1, resulting in a national carbon sequestration of 1100 Tg C, with an average carbon sequestration rate of 27 Tg C yr-1. The annual increase rate of SOC (relative to the SOC stock of the previous year), starting at <0.2 % yr-1 in the 1980s, reached around 0.4 % yr-1 in the 1990s and further rose to about 0.8 % yr-1 in the 2000s and 2010s. Notably, the eastern and southern regions, comprising about 40 % of the croplands, contributed about two-thirds of the national SOC gain. In northeast China, SOC slightly decreased from 58 Mg C ha-1 in 1980 to 57 Mg C ha-1 in 2020, resulting in a total decline of 28 Tg C. Increased organic C inputs, particularly from the straw return, was the crucial factor in SOC increase. Future strategies should focus on region-specific optimization of straw management. Specifically, in northeast China, increasing the proportion of straw returned to fields can prevent further SOC decline. In regions with SOC increase, such as the eastern and southern regions, diversified straw utilization (e.g., bioenergy production), could further mitigate greenhouse gas emissions.

Carbon Farming practices assessment: Modelling spatial changes of Soil Organic Carbon in Flanders, Belgium.

Carbon sequestration in soils is a strategy to mitigate climate change and promote sustainable soil management. Since the European Union (EU) stimulates the reduction of greenhouse gases (GHG) from the atmosphere, the necessity to explore innovative approaches to sequester carbon in agricultural landscapes is becoming urgent. Carbon Farming (CF) has emerged as a promising program to mitigate climate change in agriculture but there is still a lack of agreement on which tools can be used to calculate Soil Organic Carbon (SOC) dynamics in this context. Using the RothC model a spatial analysis of SOC in the agricultural parcels of Flanders, Belgium was performed. Two among the various CF practices were simulated: a use of cover crops (CC) and the most common crop rotations adopted in the area, enriched with the use of cover crops. The performances of the model were evaluated and compared to other studies in areas with similar climate and environments. The selected CF practices can mitigate the carbon emissions from agricultural soils up to 60 % of the current projections. The most sensitive variables in the RothC model that affect the final total SOC, and thus determining the model outcome, are the Business As Usual (BAU) carbon inputs and the initial carbon content. For these variables the Pearson Correlation Coefficient with the change in SOC reached values of -0.78 and -0.50 respectively. To achieve net carbon sequestration in the agricultural soils of Flanders, Belgium, more effective solutions need to be evaluated. Furthermore, a larger amount and accessibility of data are required to reach better modelling performances.

Using process-oriented model output to enhance machine learning-based soil organic carbon prediction in space and time.

Monitoring and modelling soil organic carbon (SOC) in space and time can help us to better understand soil carbon dynamics and is of key importance to support climate change research and policy. Although machine learning (ML) has attracted a lot of attention in the digital soil mapping (DSM) community for its powerful ability to learn from data and predict soil properties, such as SOC, it is better at capturing soil spatial variation than soil temporal dynamics. By contrast, process-oriented (PO) models benefit from mechanistic knowledge to express physiochemical and biological processes that govern SOC temporal changes. Therefore, integrating PO and ML models seems a promising means to represent physically plausible SOC dynamics while retaining the spatial prediction accuracy of ML models. In this study, a hybrid modelling framework was developed and tested for predicting topsoil SOC stock in space and time for a regional cropland area located in eastern China. In essence, the hybrid model uses predictions of the PO model in unsampled years as additional training data of the ML model, with a weighting parameter assigned to balance the importance of SOC values from the PO model and real measurements. The results indicated that temporal trends of SOC stock modelled by PO and ML models were largely different, while they were notably similar between the PO and hybrid models. Cross-validation showed that the hybrid model had the best performance (RMSE = 0.29 kg m-2), with a 19 % improvement compared with the ML model. We conclude that the proposed hybrid framework not only enhances space-time soil carbon mapping in terms of prediction accuracy and physical plausibility, it also provides insights for soil management and policy decisions in the face of future climate change and intensified human activities.

Role of livestock-derived amendments in soil organic carbon stocks in forage crops.

The use of organic amendments for forage production has been promoted in recent years due to the adoption of sustainable agricultural practices and the increasing cost of mineral fertilizers. Organic manures can contribute with an extra carbon to the soil to the potential addition of carbon stocks. This study aimed to measure the capacity of different organic amendments commonly available in livestock farms for forage fertilization to influence the rate of soil organic carbon (SOC) under future climate change conditions. For this purpose, on-farm processed exogenous organic matter (EOM) was analyzed for fiber and organic carbon mineralization to obtain the percentage of decomposable EOM and resistant EOM (DEOM and REOM, respectively). The RothC model was run in grasslands and forage maize under different scenarios considering specific DEOM and REOM values. The results showed that the degradability of amendments could influence SOC dynamics. The SOC of grasslands after 38 years of simulation differed by >30 % between compost and the liquid fraction of cattle slurry. Forage crops were simulated under the RCP8.5 scenario and fertilized with amendments at the recommended amounts of nitrogen for these crops. As a result, SOC stocks had a better response to organic fertilization in grassland, except under the application of the liquid fraction, with a decrease in SOC of 16 %. In cropland, only the solid fraction from mechanical separation of slurry and compost applications increased the SOC stock from 13 % to 26 % in the 2020-2090 period. Our study provides insights into how the degradability of EOM can affect simulations of the SOC stock rate over time.

Feasibility of the 4 per 1000 aspirational target for soil carbon: A case study for France.

Increasing soil organic carbon (SOC) stocks is a promising way to mitigate the increase in atmospheric CO2 concentration. Based on a simple ratio between CO2 anthropogenic emissions and SOC stocks worldwide, it has been suggested that a 0.4% (4 per 1000) yearly increase in SOC stocks could compensate for current anthropogenic CO2 emissions. Here, we used a reverse RothC modelling approach to estimate the amount of C inputs to soils required to sustain current SOC stocks and to increase them by 4‰ per year over a period of 30 years. We assessed the feasibility of this aspirational target first by comparing the required C input with net primary productivity (NPP) flowing to the soil, and second by considering the SOC saturation concept. Calculations were performed for mainland France, at a 1 km grid cell resolution. Results showed that a 30%-40% increase in C inputs to soil would be needed to obtain a 4‰ increase per year over a 30-year period. 88.4% of cropland areas were considered unsaturated in terms of mineral-associated SOC, but characterized by a below target C balance, that is, less NPP available than required to reach the 4‰ aspirational target. Conversely, 90.4% of unimproved grasslands were characterized by an above target C balance, that is, enough NPP to reach the 4‰ objective, but 59.1% were also saturated. The situation of improved grasslands and forests was more evenly distributed among the four categories (saturated vs. unsaturated and above vs below target C balance). Future data from soil monitoring networks should enable to validate these results. Overall, our results suggest that, for mainland France, priorities should be (1) to increase NPP returns in cropland soils that are unsaturated and have a below target carbon balance and (2) to preserve SOC stocks in other land uses.

Optimizing multifunctional agroecosystems in irrigated dryland agriculture to restore soil carbon - Experiments and modelling.

Irrigated dryland agroecosystems could become more sustainable if crop and soil management enhanced soil organic carbon (SOC). We hypothesized that combining high inputs from cover crops with no-tillage will increase long-term SOC stocks. Caatinga shrublands had been cleared in 1972 for arable crops and palm plantations before implementing field experiments on Mango and Melon systems (established in 2009 and 2012, respectively). Each of the two experiments were managed with no-till (NT) or conventional till (CT), and three types of cover cropping, either a plant mixture of 75% (PM1) or 25% (PM2) legumes, or spontaneous vegetation (SV). The RothC model was used with a daily timestep to simulate the soil moisture dynamics and C turnover for this dry climate. Carbon inputs were between 2.62 and 5.82 Mg C ha-1 year-1 and increased the depleted SOC stocks by 0.08 to 0.56 Mg C ha-1 year-1. Scenarios of continuous biomass inputs of ca. 5 Mg C ha-1 year-1 for 60 years are likely to increase SOC stocks in the mango NT beyond the original Caatinga SOC by between 19.2 and 20.5 Mg C ha-1. Under CT similar inputs would increase SOC stocks only marginally above depletion (2.75 to 2.47 Mg C ha-1). Under melon, annual carbon inputs are slightly greater (up to 5.5 Mg C ha-1 year-1) and SOC stocks would increase on average by another 8% to 22.3 to 20.6 Mg C ha-1 under NT and by 8 Mg C ha-1 under CT. These long-term simulations show that combining NT with high quality cover crops (PM1, PM2) would exceed SOC stocks of the initial Caatinga within 20 and 25 years under irrigated melon and mango cultivation, respectively. These results present a solution to reverse prior loss of SOC by replacing CT dryland agriculture with irrigated NT plus high input cover crops agroecosystems.

Projected trends of soil organic carbon stocks in Meghalaya state of Northeast Himalayas, India. Implications for a policy perspective.

Agricultural and forestry activities can affect soil organic carbon (SOC) levels and CO2 emissions from terrestrial ecosystems due to land use changes. In Northeast Himalayas, studies on the effects of forest conversion to temporary agricultural lands (jhum) on the loss of SOC and soil quality degradation have received the attention of policy makers and scientific research. Presently, local communities are now oriented towards the settled plantations systems with modern cash crops such as tea and rubber, that could act as potential SOC sinks. However, no information on SOC dynamics and simulation studies after land-use change from temporary agricultural lands (jhum) to settled cultivations and under climate change (CC) conditions are available for the Meghalaya state. Applying the RothC model, we focused on four different scenarios including the conversion from jhum to settled cultivation (rubber plantations and tea gardens), as well as continuous jhum cultivation and jhum to jhum with a period of secondary succession. Simulations under CC conditions indicated that SOC stocks significantly increased by 1.20 t C ha-1 yr-1 in tea gardens compared to rubber and jhum scenarios. Conversely, SOC stocks slightly decreased by 0.07 t C ha-1 yr-1 in rubber plantations, while the regrowth of a natural vegetation cover as secondary succession following the abandonment of the jhum fields, showed a lower SOC decrease (0.18 t C ha-1 yr-1) compared to the continuous jhum cultivation (0.24 t C ha-1 yr-1). Thus, for CC mitigation in a policy perspective, tea gardens could represent the best land use to store increasing amounts of SOC in the long-term perspective and optimize farmers' incomes, while in rubber plantations SOC storage is limited in time. Jhum cultivation can benefit in terms of productivity and profitability by extending the duration of the secondary succession period.

Using measured stocks of biomass and litter carbon to constrain modelled estimates of sequestration of soil organic carbon under contrasting mixed-species environmental plantings.

Reforestation of agricultural land with mixed-species environmental plantings of native trees and shrubs contributes to abatement of greenhouse gas emissions through sequestration of carbon, and to landscape remediation and biodiversity enhancement. Although accumulation of carbon in biomass is relatively well understood, less is known about associated changes in soil organic carbon (SOC) following different types of reforestation. Direct measurement of SOC may not be cost effective where rates of SOC sequestration are relatively small and/or highly spatially-variable, thereby requiring intensive sampling. Hence, our objective was to develop a verified modelling approach for determining changes in SOC to facilitate the inclusion of SOC in the carbon accounts of reforestation projects. We measured carbon stocks of biomass, litter and SOC (0-30cm) in 125 environmental plantings (often paired to adjacent agricultural sites), representing sites of varying productivity across the Australian continent. After constraining a carbon accounting model to observed measures of growth, allocation of biomass, and rates of litterfall and litter decomposition, the model was calibrated to maximise the efficiency of prediction of SOC and its fractions. Uncertainties in both measured and modelled results meant that efficiencies of prediction of SOC across the 125 contrasting plantings were only moderate, at 39-68%. Data-informed modelling nonetheless improved confidence in outputs from scenario analyses, confirming that: (i) reforestation on agricultural land highly depleted in SOC (i.e. previously under cropping) had the highest capacity to sequester SOC, particularly where rainfall was relatively high (>600mmyear-1), and; (ii) decreased planting width and increased stand density and the proportion of eucalypts enhanced rates of SOC sequestration. These results improve confidence in predictions of SOC following environmental reforestation under varying conditions. The calibrated model will be a useful tool for informing land managers and policy makers seeking to understand the dynamics of SOC following such reforestation.

Simulating soil organic carbon stock as affected by land cover change and climate change, Hyrcanian forests (northern Iran).

Soil organic carbon (SOC) contains a considerable portion of the world's terrestrial carbon stock, and is affected by changes in land cover and climate. SOC modeling is a useful approach to assess the impact of land use, land use change and climate change on carbon (C) sequestration. This study aimed to: (i) test the performance of RothC model using data measured from different land covers in Hyrcanian forests (northern Iran); and (ii) predict changes in SOC under different climate change scenarios that may occur in the future. The following land covers were considered: Quercus castaneifolia (QC), Acer velutinum (AV), Alnus subcordata (AS), Cupressus sempervirens (CS) plantations and a natural forest (NF). For assessment of future climate change projections the Fifth Assessment IPCC report was used. These projections were generated with nine Global Climate Models (GCMs), for two Representative Concentration Pathways (RCPs) leading to very low and high greenhouse gases concentration levels (RCP 2.6 and RCP 8.5 respectively), and for four 20year-periods up to 2099 (2030s, 2050s, 2070s and 2090s). Simulated values of SOC correlated well with measured data (R2=0.64 to 0.91) indicating a good efficiency of the RothC model. Our results showed an overall decrease in SOC stocks by 2099 under all land covers and climate change scenarios, but the extent of the decrease varied with the climate models, the emissions scenarios, time periods and land covers. Acer velutinum plantation was the most sensitive land cover to future climate change (range of decrease 8.34-21.83tCha-1). Results suggest that modeling techniques can be effectively applied for evaluating SOC stocks, allowing the identification of current patterns in the soil and the prediction of future conditions.

Simulating effects of changing climate and CO(2) emissions on soil carbon pools at the Hubbard Brook experimental forest.

Carbon (C) sequestration in forest biomass and soils may help decrease regional C footprints and mitigate future climate change. The efficacy of these practices must be verified by monitoring and by approved calculation methods (i.e., models) to be credible in C markets. Two widely used soil organic matter models - CENTURY and RothC - were used to project changes in SOC pools after clear-cutting disturbance, as well as under a range of future climate and atmospheric carbon dioxide (CO(2) ) scenarios. Data from the temperate, predominantly deciduous Hubbard Brook Experimental Forest (HBEF) in New Hampshire, USA, were used to parameterize and validate the models. Clear-cutting simulations demonstrated that both models can effectively simulate soil C dynamics in the northern hardwood forest when adequately parameterized. The minimum postharvest SOC predicted by RothC occurred in postharvest year 14 and was within 1.5% of the observed minimum, which occurred in year 8. CENTURY predicted the postharvest minimum SOC to occur in year 45, at a value 6.9% greater than the observed minimum; the slow response of both models to disturbance suggests that they may overestimate the time required to reach new steady-state conditions. Four climate change scenarios were used to simulate future changes in SOC pools. Climate-change simulations predicted increases in SOC by as much as 7% at the end of this century, partially offsetting future CO(2) emissions. This sequestration was the product of enhanced forest productivity, and associated litter input to the soil, due to increased temperature, precipitation and CO(2) . The simulations also suggested that considerable losses of SOC (8-30%) could occur if forest vegetation at HBEF does not respond to changes in climate and CO(2) levels. Therefore, the source/sink behavior of temperate forest soils likely depends on the degree to which forest growth is stimulated by new climate and CO(2) conditions.

Soil salinity decreases global soil organic carbon stocks.

Saline soils cover 3.1% (397 million hectare) of the total land area of the world. The stock of soil organic carbon (SOC) reflects the balance between carbon (C) inputs from plants, and losses through decomposition, leaching and erosion. Soil salinity decreases plant productivity and hence C inputs to the soil, but also microbial activity and therefore SOC decomposition rates. Using a modified Rothamsted Carbon model (RothC) with a newly introduced salinity decomposition rate modifier and a plant input modifier we estimate that, historically, world soils that are currently saline have lost an average of 3.47 tSOC ha(-1) since they became saline. With the extent of saline soils predicted to increase in the future, our modelling suggests that world soils may lose 6.8 Pg SOC due to salinity by the year 2100. Our findings suggest that current models overestimate future global SOC stocks and underestimate net CO2 emissions from the soil-plant system by not taking salinity effects into account. From the perspective of enhancing soil C stocks, however, given the lower SOC decomposition rate in saline soils, salt tolerant plants could be used to sequester C in salt-affected areas.