|Van Santen, E|
Submitted to: Soil Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/5/2004
Publication Date: 12/1/2004
Citation: Terra, J.A., Shaw, J.N., Reeves, D.W., Raper, R.L., Van Santen, E., Mask, P.L. 2004. Soil carbon relationships with terrain attributes, electrical conductivity surveys and soil map units in a coastal plain landscape. Soil Science. 169:819-831. Interpretive Summary: Researchers and policy-makers need reliable methods to estimate soil carbon in agricultural systems in order to develop management practices that improve soil quality. In addition, methods are needed to monitor carbon storage in soils for use in potential carbon trading programs. ARS scientists at the J. Phil Campbell Sr. Natural Resource Conservation Center, Watkinsville, GA and the Soil Dynamics Research Unit in Auburn, AL, cooperated with Auburn University scientists to determine the relationships between soil carbon, changes in field elevation, soil texture, soil survey mapping, and soil electrical conductivity on a 20 acre field in Alabama. They found that 50% of the variation in soil carbon in the field could be explained by topography (field elevation changes), field slope, silt content, and field-mapped electrical conductivity. The findings suggest that easily measured field topography features and electrical conductivity can be used to better estimate soil carbon distribution in agricultural fields. The information can be used by researchers, action agencies like USDA-NRCS, and policy-makers to better evaluate the effect of soil management practices on carbon storage, and to better estimate carbon storage in agricultural systems for potential monitoring of carbon storage in carbon trading programs.
Technical Abstract: Soil organic carbon (SOC) estimation at the landscape level is critical for assessing impacts of management practices on C sequestration and soil quality. We determined relationships between SOC, terrain attributes, field scale soil electrical conductivity (EC), soil texture and soil survey map units in a 9 ha coastal plain field (Aquic and Typic Paleudults) historically managed by conventional means. The site was composite sampled for SOC (0-30 cm) within 18.3 × 8.5'm grids (n=496), and two data sets were created from the original data. Ordinary kriging, co-kriging, regression kriging and multiple regression were used to develop SOC surfaces that were validated with an independent data set (n= 24) using the mean square error (MSE). Although SOC was relatively low (26.13 Mg ha-1) and only moderately variable (CV= 21%), it showed high spatial dependence. Interpolation techniques produced similar SOC maps but the best predictor was ordinary kriging (MSE= 9.11 Mg2 ha-2) while regression was the worst (MSE= 20.65 Mg2 ha-2). Principal component analysis indicated that the first three components explained 60 % of field variability SOC; compound topographic index (CTI), slope, EC and soil textural fractions dominated these components. Elevation, slope, CTI, silt content and EC explained up to 50% of the SOC variability (P 0.01) suggesting that topography and historical erosion played a significant role in SOC distribution. The study suggests that topography terrain attributes and EC surveys can be especially useful to differentiate zones of variable SOC content, which may be used as bench marks to evaluate field-level impact of management practices on C sequestration.