<p>Reducing greenhouse gas (GHG) emissions in to the atmosphere to limit global warming is the big challenge of the coming decades. The focus lies on negative emission technologies to remove GHGs from the atmosphere from different sectors. Agriculture produces around a quarter of all the anthropogenic GHGs globally (including land use change and afforestation). Reducing these net emissions can be achieved through techniques that increase the soil organic carbon (SOC) stocks. These techniques include improved management practices in agriculture and grassland systems, which increase the organic carbon (C) input or reduce soil disturbances. The C sequestration potential differs among soils depending on climate, soil properties and management, with the highest potential for poor soils (SOC stock farthest from saturation).</p><p>Modelling can be used to estimate the technical potential to sequester C of agricultural land under different mitigation practices for the next decades under different climate scenarios. The ECOSSE model was developed to simulate soil C dynamics and GHG emissions in mineral and organic soils. A spatial version of the model (GlobalECOSSE) was adapted to simulate agricultural soils around the world to calculate the SOC change under changing management and climate.</p><p>Practices like different tillage management, crop rotations and residue incorporation showed regional differences and the importance of adapting mitigation practices under an increased changing climate. A fast adoption of practices that increase SOC has its own challenges, as the potential to sequester C is high until the soil reached a new C equilibrium. Therefore, the potential to use soil C sequestration to reduce overall GHG emissions is limited. The results showed a high potential to sequester C until 2050 but much lower rates in the second half of the century, highlighting the importance of using soil C sequestration in the coming decades to reach net zero by 2050.</p>
Abstract. Soil organic carbon plays a major role in the global carbon budget, and can act as a source or a sink of atmospheric carbon, thereby possibly influencing the course of climate change. Changes in soil organic carbon (SOC) stocks are now taken into account in international negotiations regarding climate change. Consequently, developing sampling schemes and models for estimating the spatial distribution of SOC stocks is a priority. The French soil monitoring network has been established on a 16 km × 16 km grid and the first sampling campaign has recently been completed, providing around 2200 measurements of stocks of soil organic carbon, obtained through an in situ composite sampling, uniformly distributed over the French territory. We calibrated a boosted regression tree model on the observed stocks, modelling SOC stocks as a function of other variables such as climatic parameters, vegetation net primary productivity, soil properties and land use. The calibrated model was evaluated through cross-validation and eventually used for estimating SOC stocks for mainland France. Two other models were calibrated on forest and agricultural soils separately, in order to assess more precisely the influence of pedo-climatic variables on SOC for such soils. The boosted regression tree model showed good predictive ability, and enabled quantification of relationships between SOC stocks and pedo-climatic variables (plus their interactions) over the French territory. These relationships strongly depended on the land use, and more specifically, differed between forest soils and cultivated soil. The total estimate of SOC stocks in France was 3.260 ± 0.872 PgC for the first 30 cm. It was compared to another estimate, based on the previously published European soil organic carbon and bulk density maps, of 5.303 PgC. We demonstrate that the present estimate might better represent the actual SOC stock distributions of France, and consequently that the previously published approach at the European level greatly overestimates SOC 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.
Summary Dynamic models of nitrogen turnover in soil are being used increasingly in agricultural science. To be of value, a model must be thoroughly evaluated, and the expected accuracy of simulated values must be defined. Frequent field measurements are time‐consuming and costly, and so models are often evaluated against only few data. However, this mismatch between the measured and simulated values can result in error statistics that are themselves subject to large errors and therefore unreliable. The dot‐to‐dot method quantifies the error associated with having too few measured values by interpolating linearly between measured data (hence, dot‐to‐dot) and evaluating the simulation at each time step using interpolated data where actual measurements are unavailable. A large error will be seen if the measured data do not capture the fluctuations predicted by the model. Other quantitative methods can be used to evaluate the performance of a model, but the dot‐to‐dot method can be used in conjunction with these to estimate whether or not the data are adequate for testing the model. If the performance of the model at the measured points is within the acceptable error, then the dot‐to‐dot method is used to judge whether there are too few points to evaluate the model's performance, and so to determine whether the evaluation of the model is valid.
A key need of the global change research community is to be able to synthesize the data collected by scientists from a wide range of disciplines and use it to make predictions about our future environment. In an agricultural and forestry context, this will allow predictions of yields under elevated atmospheric CO 2 levels and/or changed climate using data from studies of both the direct effects of global change on plant growth and physiology and indirect effects on soil fertility, water resources, pests and diseases. A conference held at the University of Reading, UK in September 1999, and organized under the auspices of Focus 3 (Global Change Impact on Agriculture, Forestry and Soils; http://mwnta.nmw.ac.uk/GCTEFocus3 ) of the IGBP Core Project “Global Change and Terrestrial Ecosystems” addressed many of these issues.
