Tracking the influence of controlled traffic regimes on field scale soil variability and geospatial modeling techniques

The employment of controlled traffic farming (CTF) can yield improvements to soil quality attributes through the confinement of equipment traffic to tramlines with the field. There is a need to identify how soil property variability and spatial modeling techniques are influenced by the inclusion of controlled traffic regimes at the field scale. Soil properties such as available nitrogen (AN), soil pH, soil total nitrogen (STN), soil organic carbon (SOC), bulk density, macro pore volume, soil quality S-Index, plant available water capacity (PAWC) and unsaturated hydraulic conductivity (Km) were analyzed and compared among different positions within the traffic regime across two annual cropland sites actively employing CTF. The inclusion of tramlines displayed significant worse soil physical conditions when compared to un-trafficked soils while subsequently displaying minimal changes in soil nutrient properties. Furthermore, we contrasted regression models with ordinary geostatistical methods, such as ordinary kriging (OK) as well as the hybrid method of covariate kriging (COK) and regression kriging (ROK) to predict if the spatial distribution of soil properties in the field scale was altered from the traffic regime. The alteration of field scale bulk density, macro pore volume, S-Index and PAWC within the tramline soil caused consistent homogeneity within the area and direction of equipment traffic; however, these linear features were unable to be displayed through our ordinary geostatistical modeling methods and only somewhat captured using the ROK method. Alternately, AN, pH, STN, SOC and Km observed to vary primarily as a function of landscape. This resulted in the addition of light detection and ranging derived terrain covariates with the COK method improving the field scale prediction and reducing uncertainty in the estimation of soil nutrient properties.