## Materials and Methods
### Data  
#### 2.2.1 MODIS Datasets  
MODIS GPP datasets were available from the year 2000 to present (data: [[http://files.ntsg.umt.edu/data/NTSG_Products/](http://files.ntsg.umt.edu/data/NTSG_Products/)]([http://files.ntsg.umt.edu/data/NTSG_Products/](http://files.ntsg.umt.edu/data/NTSG_Products/))). Total annual values per pixel of 8-day GPP composite products (MOD17A2 version 5.5) for the years 2000, 2007, and 2010 were used in this study [51]. These years were selected to allow a comparison with the available N deposition datasets at the time of the study. Flagged data were filtered out.  
The MOD17A2 algorithm estimates GPP based on a radiation conversion efficiency approach with attenuation scalars for low temperature and water stress across biomes, using the MODIS land cover product (MOD12) (1). These parameters are specific for each biome and are available through a biome-property-look-up-table [52]. Scalars are estimated from coarse spatial resolution climate datasets. While the use of daily climate data at higher spatial resolutions can improve the quantification of GPP [53], MODIS products are still useful for characterizing how climate influences annual GPP response at regional scales [54; 55]. We considered MODIS GPP as a good compromise between observational data available at a spatial resolution of 1 km and data quality:  
\[GPP=\ \varepsilon_{max}*TMIN_{scalar}*VPD_{scalar}*SWRad*0.45*FPAR \tag{1}\]  
where \(\varepsilon_{max}\) is the maximum light use efficiency (kg C MJ\({}^{-1}\)), \(TMIN_{scalar}\) and \(VPD_{scalar}\) are scalars between 0 and 1 that attenuate light use efficiency values based on daily minimum temperature, the vapour pressure deficit, SWrad * 0.45, corresponds to the amount of incident shortwave radiation for photosynthesis, and is the fraction of absorbed photosynthetic active radiation (PAR).  
The land cover classes used in this study were obtained from the MODIS product MCD12Q1 [35], which is also used as an input to the algorithm that retrieves GPP. Therefore, we stratified the analysis, according to MODIS land cover classes, for consistency. We selected: Grasslands, croplands, and croplands/natural vegetation mosaic. The land cover classes croplands and croplands/natural vegetation mosaic are mostly found in the Midlands (or Swiss Plateau) and the Jura mountains, and the class grasslands is mainly located in the Alps. According to the Digital Height Model [56], the land cover classes selected can be found from a minimum altitude of ca. 200 m to a maximum altitude of 2634 m a.s.l. in croplands, 3033 m a.s.l. in croplands/natural vegetation mosaic, and 3570 m a.s.l. in grasslands.  
The GPP algorithm is based on the UMD classification scheme proposed by the University of Maryland (UMD). However, we used the International Geosphere and Biosphere Programme (IGBP) legend, in which the UMD class croplands is divided in two classes: Croplands and croplands/natural vegetation mosaic. [PERSON], et al. [35] reported an overall accuracy of 74.8% for the MCD12Q1 product using the IGBP legend with 16 classes. The classes 10, 12, and 14 were selected i.e., grasslands, croplands, and croplands/natural vegetation mosaic, respectively. All datasets were used at a spatial resolution of 1 km.