## 4 Discussion
### Gross Primary Production and Respiration  
The predictive capability for GPP (\(r^{2}\geq 0.66\)) compares well with other studies using the DNDC forest model [75,121] though LandscapeDNDC results tend to be better-correlated with measurements if site-specific parameters are used (Table 6). In this regard, simulation results are more similar to results obtained with physiologically based models such as the model for Carbon Assimilation and respiration, Transpiration, evaporation and drainage, Allocation and growth in Even Aged forests CASTANEA [13] or the Physiological Simulation Model (PSIM) [41], which are more demanding in terms of parametrization. The use of multi-site parameters resulted in an underestimation of GPP during spring and autumn for evergreen forests, as temperature dependence parameters hamper model processes (_i.e._, GDDFOLSTART, GDDFOLEND). The latter parameters correspond to the minimum and maximum temperature sum for foliage activity onset, and they are applied across a transect. A more comprehensive uncertainty analysis associated with C flux measurements at the former site can be found in [PERSON] _et al._[123].  
In general, only the simulations at the beech site in Denmark (DK-Sor) indicate a systematic underestimation of GPP. A reason for this finding might be the fact that the stand is not a pure beech  
Figure 5: Inter-daily mean for Gross Primary Production (GPP) and Net Ecosystem Exchange (NEE) obtained with site-specific parameters at stands with different model performances (best left site, worst right site). Daily mean values are calculated throughout the evaluation period (see Table 6 for details). PISY: _Pinus sylvestris_, PIAB = _Picea abies_, FASY = _Fagus sylvatica_.  
stand but contains approximately 20% of spruce and larch. Also, the occurrence of ground vegetation and its seasonally specific contribution to GPP might be partly responsible for this result. The importance of phenology for seasonal representation of GPP has been demonstrated in a modeling study which compared 14 different models [124]. In the current investigation we found that the phenology of 9 out of 10 sites was well-represented (see Tables 6 and 7), suggesting that the growing-degree-day approach as implemented in PnET (see appendix) is sufficiently able to describe the forest phenology in Europe. However, the growing-degree-day approach fails in years where vernalization periods are not met, which had been the case in only one occasion here (BE-Bra: 2005). In this single case, the lack of representation of GPP also affects TER because residual respiration rates are calculated as dependent on biomass and temperature with empirically defined parameters.  
It should also be noted that the distinction between GPP and TER in measurements is empirically derived from NEE and thus depends on additional assumptions [125]. For example, [PERSON] _et al._[126] showed that nocturnal EC estimates were poorly correlated with chamber measurements at six coniferous boreal sites, with EC based TER underestimating chamber based soil C losses particularly during the early part of the growing season. Eventually this could be one reason for the deviations between simulated and measured TER which occurred in spring and autumn (e.g., DE-Hoeg).