View article

Simulation modelling is used to estimate C sequestration associated with agricultural management for purposes of greenhouse gas mitigation. Models are not completely accurate or precise estimators of C pools, however, due to insufficient knowledge and imperfect conceptualizations about ecosystem processes, leading to uncertainty in the results. It can be difficult to quantify the uncertainty using traditional error propagation techniques, such as Monte Carlo Analyses, because of the structural complexity of simulation models. Empirically based methods provide an alternative to the error propagation techniques, and our objective was to apply this alternative approach. Specifically, we developed a linear mixed-effect model to quantify both bias and variance in modeled soil C stocks that were estimated using the Century ecosystem simulation model. The statistical analysis was based on measurements from 47 …