## Materials and Methods
### Data
#### 2.2.2 N Deposition Datasets  
N deposition raster data for the years 2000, 2007, and 2010 [57] were produced with a spatial resolution of 1 km (Appendix A, Figure A1). The N deposition model assimilates land use information from the Swiss Land-Use Statistics point grid, which provides information based on the visual interpretation of aerial photographs at 0.1 km spatial resolution [58]. In order to provide the reader with some background about the Swiss Land-Use Statistics, we include here some details about how the selected MODIS classes relate to this dataset. The Swiss Land-Use Statistics classes considered in the model are arable land (class 221, nomenclature NOLU04), semi-natural grasslands (class 222), alpine meadows (class 241), and alpine pastures (class 242). The class arable land overlapped the MODIS classes croplands by 40.6%, the croplands/natural vegetation mosaic by 35.4%, and the grasslands by 1.35%. The class semi-natural grasslands overlapped the MODIS classes croplands/natural vegetation mosaic by 43.3%, the croplands by 11.7%, and the grasslands by 8.8%. The class alpine meadows overlapped the MODIS classes grasslands by 27.2%, the croplands/natural vegetation mosaic by 12.5%, and the croplands by 9.84%. Finally, the class alpine pastures overlapped the MODIS classes grasslands by 39.9%, the croplands/natural vegetation mosaic by 9.7%, and the croplands by 5.1%. Therefore, arable land and semi-natural grasslands are mostly covered by the MCD12Q1 classes croplands and croplands/natural vegetation mosaic, respectively, and alpine meadows and pastures are mainly covered by the MCD12Q1 class grasslands. In order to avoid possible mismatches between dry deposition and MODIS land cover classes, specific N deposition maps, including only low vegetation (excluding forests), were produced. N deposition maps have been retrieved following a modelling approach based on wet and dry deposition of nitrate and ammonium, as well as gaseous deposition of NH\({}_{3}\), nitrogen dioxide (NO\({}_{2}\)), and nitric acid. Atmospheric N deposition was mapped using a pragmatic approach that combines emission inventories, statistical dispersion models, monitoring data, spatial interpolation methods, and inferential deposition models [59]. Concentrations of the primary gaseous pollutants (NH\({}_{3}\) and NO\({}_{2}\)) are estimated by means of emission maps and statistical dispersion models with a resolution of \(100\times 100\) m\({}^{2}\). As a result, the high spatial variability of these pollutants near emission sources can be reflected in the models. The concentrations of secondary pollutants (aerosols, HNO\({}_{3}\)), as well as the concentrations of N in precipitation, are derived from field monitoring data by applying geo-statistical interpolation methods. Combustion processes and agricultural activities are the main sources of these atmospheric components. In particular, agricultural management practices account for 92% of ammonia (NH\({}_{3}\)) emissions, livestock being the main contributing source. Application and storage of manure (38% and 13.8%, respectively), housing (28.4%), and grazing (2.2%) add up to 82.4% [59]. Therefore, fertilization practices influence NH\({}_{3}\) concentrations directly. Modelled ammonia concentrations were validated with measured concentrations from 48 monitoring sites, R\({}^{2}\) = 0.526 (Root Mean Square Error, RMSE = 43%) [59]. Furthermore, the authors of a recent study concluded that N deposition maps provide reliable estimates for large areas [60].