Carbon flux simulation of southern poplar plantation based on Biome-BGC model

To accurately simulate carbon fluxes of southern poplar plantations, we applied the PEST parameter optimization method to calibrate the ecophysiological parameters in the Biome-BGC model based on eddy covariance flux tower. We simulated the daily gross primary productivity (GPP) and ecosystem respiration (Re) of the plantation, and identified the sensitive parameters and main meteorological drivers. The results showed that the simulation accuracy of the model for GPP and Re was significantly improved after parameter optimization. The coefficients of determination (R²) for GPP and Re reached 0.74 and 0.63, respectively, which were 27.6% and 31.3% higher than those before optimization. The mean absolute error (MAE) for GPP and Re decreased by 15.6% and 7.5%, and the root mean square error (RMSE) for GPP and Re decreased by 16.9% and 5.9%, respectively. The average GPP and Re simulated by the model over five years were 1.71 and 1.55 kg C·m^-2·a^-1, respectively. Sensitivity analysis showed that leaf carbon-nitrogen ratio and the canopy light extinction coefficient strongly affected carbon flux simulation, and the fraction of leaf nitrogen in Rubisco and the litter carbon-nitrogen ratio were moderately sensitive parameters. Path analysis showed that air temperature and shortwave radiation flux density were the main meteorological factors driving the increase in GPP on the daily scale. Air temperature, precipitation and shortwave radiation flux density significantly promoted the increase in Re, with the effect of air temperature being the strongest. In summary, the PEST parameter calibration substantially improved Biome-BGC performance for carbon flux simulation in southern poplar plantations. The key sensitive parameters affecting the simulation accuracy were leaf carbon-nitrogen ratio and canopy light extinction coefficient. The key meteorological factor that dominated GPP and Re changes was air temperature.