## Materials and Methods
### Eddy Covariance and Meteorological Measurements
#### 2.2.2 EC Data Processing  
Raw EC data were stored in one-hourly binary files (Table 1). Under normal circumstances, every one-hourly binary file has 72,000 records and files having less (or more) records than 72,000 have been discarded. The remaining one-hourly binary files had been further quality checked. For every one-hourly binary file mean value, the standard deviation of CO\({}_{2}\) and a difference (_delta_) between two consecutive CO\({}_{2}\) concentration measurements was calculated. The one-hourly binary file was dismissed from further analysis if the standard deviation was greater than 30 ppm, or the mean value was less than 340 ppm or greater than 600 ppm, or the number of events when _delta_ > 10 ppm was larger than 10. This procedure removed bad data caused by rain and system malfunctions alongside with non-physical shifts, dropouts, and discontinuities described in Vickers and Mahrt [41]. Fluxes were calculated using the free software EdiRe ([[http://www.geos.ed.ac.uk/homes/jbm/micromet/EdiRe](http://www.geos.ed.ac.uk/homes/jbm/micromet/EdiRe)]([http://www.geos.ed.ac.uk/homes/jbm/micromet/EdiRe](http://www.geos.ed.ac.uk/homes/jbm/micromet/EdiRe))) according to the project EUROFLUX methodology [42] and stored as half-hourly values. At first, to avoid the loss of flux due to the physical separation of wind speed and scalar concentration sensors, the time lag was removed. In open-path EC measurement systems gas analyser and three-dimensional (3D) anemometer are usually placed several decimetres (30 cm in our case) apart so the time lag is much smaller than in case of closed path systems. To avoid contamination of vertical wind component w by the other two wind components planar fit method [43] was performed after time lag removal. CO\({}_{2}\) flux was calculated as the average of the product of instantaneous fluctuations of vertical wind velocity (\(w^{\prime}\)) and CO\({}_{2}\) concentration fluctuations (s'):  
\[Fc=\overline{w^{\prime}s^{\prime}} \tag{1}\]  
Calculated flux _Fc_ was first corrected for the imperfect frequency response of the system. After the spectral corrections, the Webb-Pearman-Leuning (WPL) correction was performed to compensate for fluctuations in the density of carbon dioxide resulting from the fluctuations of air temperature and water vapour, which are not representatives of measured flux [42]. Only data that have passed the quality criteria described above were used in the calculation of fluxes. To obtain _NEE_, the CO\({}_{2}\) storage flux (_Sc_) was added to the calculated flux _Fc_. Half-hourly _NEE_ were checked for absolute limits. Values that were outside the range of \(-\)50 umoL m\({}^{-2}\) s\({}^{-1}\) > _NEE_ > 30 umoL m\({}^{-2}\) s\({}^{-1}\) have been removed. High-frequency spikes, i.e., spikes affecting the single instantaneous measurement have been already removed in EdiRe. However, spikes were sometimes still occurring in the final half-hourly fluxes. They were detected and removed by the filtering procedure proposed by [PERSON] et al. [44]. Half-hourly _NEE_ values were categorized into night-time (solar radiation (_Rg_) < 20 Wm\({}^{-2}\)) and day-time _NEE_. The spike detection was based on the double-differenced time series, using the median of absolute deviation around the median (_MAD_):  
\[MAD=\text{median}(|d_{i}-M_{d}|) \tag{2}\]  
where \(M_{d}\) denotes the median of the differences and value \(d_{i}\) was calculated for each half-hourly _NEE_ as:  
\[d_{i}=(NEE_{i}-NEE_{i-1})-(NEE_{i+1}-NEE_{i}) \tag{3}\]  
Half-hourly _NEE_ was flagged as spike and removed from further processing if:  
\[d_{i}<M_{d}-\left(\frac{z\times MAD}{0.6745}\right)\text{OR}\;d_{i}>M_{d}+ \left(\frac{z\times MAD}{0.6745}\right) \tag{4}\]  
where \(z\) is a threshold value. As proposed in [PERSON] et al. [44], the threshold was set to \(z\) = 4 during the night-time and to \(z\) = 5.5 during the day-time to allow for greater variability of daily fluxes.