Topography and land use impact erosion and soil organic carbon burial over decadal timescales

To provide a more accurate assessment of soil organic carbon (SOC) stocks in agroecosystems, sampling strategies should be designed in a way that accounts for topographic variability and soil redistribution via erosion and deposition. While the importance of topography for influencing soil properties is long established, recent advances in digital elevation models (DEMs) permit more rapid assessment of topographic attributes. We determined primary terrain attributes from a 3 m DEM to guide sampling in cultivated fields and nearby grasslands in Southeastern Minnesota, USA. Soil samples were analyzed to quantify SOC stocks and activity of Cs-137, a radioisotope employed to track soil movement over decadal timescales. In addition to soil depth, digital terrain attribute values were important for developing predictive models in both cropland and grassland sites but contributed more to predictions in cropland soils. Profile and planform curvature were significant terms in the regression model for both cropland and grassland soils. Additionally, percent slope was also significant in models for cropland soils. Overall, regression models were able to explain 90% and 73% of variability in SOC stocks observed in grassland and cropland sites, respectively. Soil profile 137Cs inventories were correlated with SOC stocks in both land cover types and show that soil movement can explain SOC variability in upland soils. Soil erosion or deposition rates (based on Cs-137 inventories) ranged from 34.8 (erosion) to-70.1 (deposition) t ha(-1) yr(-1) in cropland sites and from 11.7 to-17.2 t ha(-1) yr(-1) in grassland sites. Results from this study showed that soil redistribution can result in burial of eroded OC-rich surface soil in depositional locations characterized by low slopes and concave curvature in agricultural fields.

Automated summary

To accurately assess soil organic carbon (SOC) stocks in agroecosystems, sampling strategies should consider topographic variability and soil redistribution through erosion and deposition. This study used digital elevation models (DEMs) to determine primary terrain attributes for guiding sampling in cultivated fields and nearby grasslands. Results showed that digital terrain attribute values were important for predicting SOC stocks in both cropland and grassland soils, with profile and planform curvature being significant factors. The study also found that soil movement can explain SOC variability in upland soils.