## 4 Results and Discussion
### First-step Optimization - PROSAILH-BGC Electrophysiological Parameter Estimates  
The model parameter estimates obtained through model optimization against GPP measured during 2002, their relative standard errors and statistics for the evaluation of model accuracy are listed in Table 2. The optimized parameters (\(\theta_{\mathrm{opt}}\)) showed considerable differences with respect to the original literature-based parameterization (used for Reference Models 1 and 2). In particular, FRC:LC showed  
Figure 4: Relationship between modeled and observed \(\mathrm{PAR}_{\mathrm{t}}\). Red circles represent data modeled with BIOME-BGC while white circles represent data modeled with PROSAIL-BGC. Dashed lines represent the 95% confidence intervals of the linear regression between \(\mathrm{PAR}_{\mathrm{t}}\) modeled (with BIOME-BGC in red and PROSAIL-BGC in black) and observed data. Grey line is the 1:1 line. b[0] is the intercept, b[1] is the slope and \(p\) is the significance of the linear regression analysis.  
a sensible increase (from 0.333 to 1.969). This optimized value is consistent with values published for broadleaved species ([25] (with values from 0.54 to 1.59 found) and for other poplar species ([10] (for which a value of 1.2 was reported). This may therefore indicate that the original ecophysiological parameterization based on the works of [10, 25, 45, 46] was unsuited for the investigated poplar species.  
Linear regression analysis between observed and modeled data showed an increase in both determination coefficient (from 0.88 to 0.93), slope (from 0.68 to 0.83), EF (from 0.78 to 0.88) and a decrease in RMSE (from 2.31 to 1.12 gCm-2 day-1), between the optimized values and the Reference Model 2. Cumulated yearly GPP for 2002 simulated with the optimized model was 1546 gCm-2 year-1, with good agreement with the measured data of 1578 gCm-2 year-1. Conversely, GPP simulated by PROSAILH-BGC with the original parameterization was 1362 gCm-2 year-1, while yearly GPP simulated with the Reference Model 2 (i.e. literature ecophysiological parameterization and phenology derived from site observations) was 1330 gCm-2 year-1, with an underestimation of about 248 gCm-2 year-1.  
As a validation exercise, the accuracy of the optimized model was evaluated using the GPP measurements collected during 2003, achieving a good improvement in GPP estimation with respect to the results obtained by PROSAILH-BGC with the original literature parameterization. Although modeled GPP with the optimized and original parameters explained the same amount of variance of the observed GPP (r2 = 0.78 for both the models), the RMSE decreased from 1.81 gCm-2 day-1 to 1.41 gCm-2 day-1 and EF increased from 0.67 to 0.76 as a consequence of the optimization. This improvement in model accuracy underscores that the main effect introduced by the optimized parameters was the reduction of the bias with a reduction of the systematic underestimation of the model. Conversely, the correlation between observations and modeled data did not improve when using the optimized parameterization because the daily variability of simulated fluxes is mainly driven by meteorological data.