Bayesian calibration of the DayCent ecosystem model to simulate soil organic carbon dynamics and reduce model uncertainty

•Bayesian sampling importance resampling was used to parameterize the DayCent model.•Uncertainty was reduced in DayCent Predictions of SOC stocks with Bayesian calibration.•Addressed all sources of uncertainty with 95% prediction intervals for estimates.•May reduce uncertainty by re-applying Bayesian analysis with future model improvements and new measurements.