Mixed Forest Specific Calibration of the 3-Pgmix Model Parameters from Site Observations to Predict Post-Fire Forest Regrowth

Fire disturbance usually breaks the original forest succession trajectory and causes changes in forest composition in the boreal forests region of China. Predicting the process of post-fire mixed tree species regrowth dynamic is critical for understanding the effect of environmental conditions on forest succession. 3-PGmix model proved to be a powerful tool for predicting the growth of mixed forest species. However, using 3-PGmix to simulate the post-fire mixed forest regrowth remains challenging due to the uncertainty for estimation of plenty of model parameters including species-specific and site-specific parameters. Based on the plots with a wide range of environmental conditions, we used the PEST model to conduct the sensitivity analysis and optimization of species-specific parameters for mixed forest stands ( Larix gmelinii and Betula platyphylla ), and developed new methods to accurately estimate the site-specific parameters (e.g., fertility rating, stand density, climate factors). Then the calibrated 3-PGmix model was tested against the independent sites and predicted the characteristic of post-fire forest regrowth. The sensitivity analysis shows that the parameters relate to forest canopy are more sensitive to the objective function of the PEST model. The calibrated 3-PGmix model performed well on independent sites, resulting in agreement with the field-measured diameter at breast height (DBH), the biomass of components, and stand density with a bias of less than 15% on most sites. The model prediction of post-fire forest recovery characteristics found that the highest recovery rate was observed from the moderate burn severity scenarios with a maximum recovery rate of 5.5% per year. Meantime, a higher fertility rating can accelerate the process of post-fire forest successional and shorten the duration time when the species proportion achieves balance. This study suggests that the mixed-forest specific calibration of the 3-PGmix model enables the explicit prediction of post-fire forest succession and possible extension to spatial scale simulation with a wide range of environmental conditions by coupling remote sensing observations is also expected