Developing models to predict soil bulk density in southern Wisconsin using soil chemical properties

There is an emerging need to estimate and verify soil carbon credits attributed to conservation tillage and prairie restoration in the Midwestern U.S. for the developing global carbon market. However, current soil sampling strategies may need to be augmented by empirical modeling to minimize costs while covering larger regions. Models were constructed relating soil bulk density (BD) to soil organic carbon (SOC) and total nitrogen (TN) concentrations using 146 sites in southern Wisconsin under varied land use to determine whether empirical models could reliably predict BD in an effort to support estimates of SOC sequestration for future carbon crediting programs. As expected, a significant exponential relationship resulted between %SOC and BD (R = 0.90; P < 0.0001) across all sites. Exponential models were then constructed after categorizing data into undisturbed ecosystems, prairie restorations, and croplands, and showed that the correlation between observed and predicted BD values, along with model parameters, were quite different. Predicted values were most correlated to observed values for undisturbed sites (R = 0.90), less correlated with prairie restorations (R = 0.49), and the least correlated with croplands (R = 0.25). This suggests that highly intensified crop management practices influence BD in a way that might make using %SOC or %TN as single predictor variables unreliable. It is suggested that models relating BD and soil chemical properties should consider the varied effects of land-use management over many different soil textures, particularly for the determination of carbon credits on agricultural land in temperate