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 ±â€¯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.

Investigation of Water Dynamics and the Effect of Evapotranspiration on Grain Yield of Rainfed Wheat and Barley under a Mediterranean Environment: A Modelling Approach.

Agro-hydrological models have increasingly become useful and powerful tools in optimizing water and fertilizer application, and in studying the environmental consequences. Accurate prediction of water dynamics in such models is essential for models to produce reasonable results. In this study, detailed simulations were performed for water dynamics of rainfed winter wheat and barley grown under a Mediterranean climate over a 10-year period. The model employed (Yang et al., 2009. J. Hydrol., 370, 177-190) uses easily available agronomic data, and takes into consideration of all key soil and plant processes in controlling water dynamics in the soil-crop system, including the dynamics of root growth. The water requirement for crop growth was calculated according to the FAO56, and the soil hydraulic properties were estimated using peto-transfer functions (PTFs) based on soil physical properties and soil organic matter content. Results show that the simulated values of soil water content at the depths of 15, 45 and 75 cm agreed with the measurements well with the root of the mean squared errors of 0.027 cm(3) cm(-3) and the model agreement index of 0.875. The simulated seasonal evapotranspiration (ET) ranged from 208 to 388 mm, and grain yield was found to correlate with the simulated seasonal ET in a linear manner within the studied ET range. The simulated rates of grain yield increase were 17.3 and 23.7 kg ha(-l) for every mm of water evapotranspired for wheat and barley, respectively. The good agreement of soil water content between measurement and simulation and the simulated relationships between grain yield and seasonal ET supported by the data in the literature indicates that the model performed well in modelling water dynamics for the studied soil-crop system, and therefore has the potential to be applied reliably and widely in precision agriculture. Finally, a two-staged approach using inverse modelling techniques to further improve model performance was discussed.

Pig slurry and mineral fertilization strategies' effects on soil quality: macroaggregate stability and organic matter fractions.

Applying pig slurry to the land as fertilizer at appropriate agronomic rates is important to close nutrient cycles and optimize the value of organic matter. However a long-term discussion has taken place about its effects on soil quality. In the north-east of Spain, eight fertilization strategies were evaluated on the soil quality parameters' aggregate stability, soil organic matter (SOM) physical fractions and soil microbial biomass (SMB). Six strategies used different pig slurries (PS) which provided organic matter from 1.7 to 2.6 t ha(-1)yr(-1), the rest (mineral N fertilization and a control) did not. Pig slurries were applied at sowing and/or at cereal tillering, as sidedressing. Field experiments were maintained for an 8-year period, in a silty loam soil devoted to a rainfed winter cereal. Soil samples were taken once, before the last sidedressing in 2011. Aggregate stability was quantified using the standard water-stable aggregate method but including a modification which meant that pre-wetting was avoided (WSA(MOD)). When using the WSA(MOD) method, we found a tendency for the percentage of water-stable aggregates to increase due to PS application (differences of up to 74% in the increment) and it was more marked the nearer they were measured to the application time (3 months vs. 12 months). The strategies which include PS show a positive effect on the SOM amount, mainly in the 0.05-0.2 mm light fraction, which increased by up to 34% with every 10 t ha(-1) organic C applied, and on SMB (up to 53% increment). There is a positive and significant linear relationship (p < 0.05, R(2) = 0.75) between the SOM light fraction (%) and the water-stable aggregates soil content (%, WSA(MOD)). Thus, the introduction of PS in fertilization strategies improves soil quality parameters. However, the soil quality benefits need to be balanced with any other potential environmental impact.