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

Authors: Dalzell, Brent; FISSORE, CINZIA - Whittier College; NATER, EDWARD - University Of Minnesota

Submitted to: Catena
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/10/2022
Publication Date: 8/22/2022
Citation: Dalzell, B.J., Fissore, C., Nater, E. 2022. Topography and land use impact erosion and soil organic carbon burial over decadal timescales. Catena. 218. Article 106578. https://doi.org/10.1016/j.catena.2022.106578.
DOI: https://doi.org/10.1016/j.catena.2022.106578

Interpretive Summary: At the landscape scale, accounting for the impacts of soil cultivation, erosion, and deposition is important because these processes not only redistribute soil organic carbon (SOC) in the landscape, but they can also change the rate of SOC turnover. While SOC disturbance via cultivation is often associated with increased mineralization of carbon to the atmosphere, accelerated soil mixing and burial in cultivated landscapes can also result in SOC stabilization. In this study, we compared landscape and soil profile distributions of SOC and 137Cs activity (a method of measuring soil erosion) to determine topographic and land use effects on SOC distribution in loess soils in southeastern Minnesota, USA. We showed that primary digital terrain attributes of slope, profile curvature, and planform curvature can be used to predict SOC profiles in the upper 1.5 m of grassland and cropland soils. Cropland soils showed greater variability in SOC stocks at different landscape positions, with depositional sites showing SOC accumulation. While % SOC is less in cropland surficial soils, additional analyses indicate that it may be more stabilized than grassland surficial SOC because of the role that soil minerals can play in protecting SOC from decomposition. This work illustrates a framework for quantifying and predicting SOC at the landscape scale while striking a balance between having a manageable number of sampling sites and capturing SOC heterogeneity in cultivated landscapes. It is likely that this framework will vary with differences in climate, soils, and management practices. However, a similar terrain-guided sampling approach could be employed at other sites or land uses and may potentially yield insight into which digital terrain attributes are most important for predicting SOC stocks across a range of topographic features and land use settings. Results from these predictive approaches may be helpful for constraining broader regional SOC budgets as well as helping to identify pools of SOC that may be vulnerable to mineralization as well as to identify and prioritize opportunities or conservation or SOC sequestration.

Technical Abstract: In order 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 potential 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 terrain attributes from a 3 m DEM to guide sampling in cultivated fields and nearby grasslands in Southeastern Minnesota. Soils were sampled to a depth of 1.5 m and SOC profiles were compared against a suite of terrain attributes to determine suitability for developing predictive models of landscape-scale SOC stocks. Soil erosion and deposition history were determined from the abundance of 137Cs, a radioisotope that can be employed to track soil movement over decadal timescales. Relative stability of SOC was inferred from the ratio of SOC to specific mineral surface area, a proxy for long-term SOC stabilization via organo-mineral complexation. Digital terrain attribute values were important for developing predictive models in both cropland and grassland sites. Profile curvature, and planform curvature were all significant terms in the regression model for both cropland and grassland soils. Additionally, percent slope was also significant in regression 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. We applied the resulting regression models to develop maps of SOC stocks in the uppermost 150 cm under cropland vs. grassland scenarios to illustrate how this approach can be valuable for assessing management impacts on SOC at the landscape scale. When considered in context of erosion history and SOC mass normalized to specific surface area, results from this study showed that soil redistribution acted to mix organic carbon-rich surface soil with subsoils having available mineral surface area providing opportunity for long-term SOC stabilization.