## 3 Results
### Stand Characteristics and _NPP\({}_{bm}\)_
#### 3.4.2 _Npp\({}_{bm}\)_  
Most important part of the stand production, at least from the perspective of timber production, comes from the formation of new xylem in tree stems and branches. While it is relatively straightforward to assess the contribution of a given tree species to the part of the _NPP_ that is attributed to aboveground woody growth, the situation is much more complex for non-woody plant components. Therefore, we present only the results of the _NPP\({}_{WBI}\)_ (total woody above- and below-ground) partitioned according to main tree species (Figure 13), while the annual production of leaf litter (_NPP\({}_{L}\)_) and trees' fruits (_NPP\({}_{F}\)_) is given in Table 1.  
The _NPP\({}_{WBI}\)_ ranged from 299 gC m\({}^{-2}\) year\({}^{-1}\) (2017) to 567 gC m\({}^{-2}\) year\({}^{-1}\) (2010), with the mean of 484 gC m\({}^{-2}\) year\({}^{-1}\) during the period 2008-2017. Disaggregation with respect to tree species clearly shows that _Quercus robur_ is the key species (Figure 13) with an average contribution to _NPP\({}_{WBI}\)_ of 66.8%. The average contributions of other important tree species are much smaller; namely, _Alnus glutinosa_ 10.5%, _Carpinus betulus_ 11.8%, _Fraximus angustifolia_ 9.9%. Interestingly, the trend of total productivity of woody biomass with time is significantly negative (\(-\)17.8 gC m\({}^{-2}\) year\({}^{-2}\) or \(-\)3.7% year\({}^{-1}\), \(p\) = 0.030). It is negative for all main species except for _Quercus robur_, for which the trend is also slightly negative but not significant (\(-\)1.8% year\({}^{-1}\), \(p\) = 0.342) (Figure 13). The most  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**DBH \({}^{*}\) (cm)**} & \multicolumn{11}{c}{**Year (at the End of the Season)**} \\ \cline{2-13}  & **2007** & **2008** & **2009** & **2010** & **2011** & **2012** & **2013** & **2014** & **2015** & **2016** & **2017** \\ \hline \multicolumn{13}{c}{Stand age (year)} \\ \cline{2-13}  & 35 & 36 & 37 & 38 & 39 & 40 & 41 & 42 & 43 & 44 & 45 \\ \hline \multicolumn{13}{c}{\({}^{4}\)\({pronounced negative trend was observed in _Frazimus angustifolia_ (\(-11.6\%\) year\({}^{-1}\), \(p<0.001\)), followed by _Alnus glutinosa_ (\(-8.4\%\) year\({}^{-1}\), \(p<0.001\)) and _Carpinus betulus_ (\(-3.9\%\) year\({}^{-1}\), \(p=0.037\)). The year 2017, with unfavourable meteorological conditions, is the last year in the used dataset and it has a strong effect on this trend. Without data from 2017, a statistically significant (95% confidence), negative trend in \(NPP_{WBI}\) is observed only for _Frazimus angustifolia_ (\(-11.1\%\) year\({}^{-1}\), \(p<0.001\)) and _Alnus glutinosa_ (\(-7.5\%\) year\({}^{-1}\), \(p=0.006\)), while other tree species, as well as total \(NPP_{WBI}\), do not display statistically significant trends.  
Seasonal dynamics of \(NPP_{WBI}\) was reconstructed by fitting Equation (10) for each year separately and obtained estimates for the parameters \(NPP_{WBI,annual}\), \(DOY_{max\_WBI}\), and \(k\) are given in Appendix A (Table 10). Recalling Equations (11) and (13), the measured annual \(NPP_{WBI}\) and the existing estimates of \(k\), maximum daily net primary production (\(dNPP_{max}\)) was calculated for each year. The \(dNPP_{max}\) ranged from 6.1 gC m\({}^{-2}\) day\({}^{-1}\) in 2008 to 2.3 gC m\({}^{-2}\) day\({}^{-1}\) in 2017 and it has exhibited a steady downward trend (\(-0.37\) gC m\({}^{-2}\) day\({}^{-1}\) year\({}^{-1}\), \(p<0.001\)) during the period of the research. \(DOY_{max\_WBI}\) ranged from 143 in 2012 to 165 in 2017 with the average of 153 and it has not exhibited a significant trend with time.