## 6 Conclusions  
Our study emphasizes the importance of studying how limiting factors of GPP response relate among them and to GPP to derive conclusions about their explanatory performance. We showed the role of N deposition in explaining GPP variance in soils with low nutrient storage capacity and how these areas present plant N saturation. The most important climatic variable to build all the models was precipitation. Temperature and sunshine were occasionally relevant in specific years. However, temperature was the variable with the second highest correlation with GPP. Therefore, interactions among controlling factors need to be taken into account before drawing conclusions from the final set of explanatory variables selected by a model. This study contributes to characterizing large spatial patterns of GPP in Switzerland and how controlling factors vary in areas with complex topography affected by local climatic conditions and different land management patterns. However, we recommend developing further research lines to disentangle the impact of controlling factors on GPP variance in ecosystems with high intensity of use, mixed management practices, and high species richness as well as the role of precipitation in GPP response in the study area. Finally, we foster accounting for N dynamics and land management practices in conjunction with climatic factors in C budget models to improve our understanding of complex ecosystem processes. Conceptualization: M.G.G., R.d.J., A.K., M.E.S. ; data curation: M.G.G., R.d.J., B.R. ; formal analysis: M.G.G. ; funding acquisition: R.d.J., A.K., M.E.S. ; investigation: M.G.G. ; methodology: M.G.G., R.d.J., M.E.S. ; project administration: A.K., M.E.S. ; resources: A.K., M.E.S. ; software: M.G.G. ; supervision: R.d.J., A.K., M.E.S. ; validation: M.G.G. ; visualizing: M.G.G. ; writing--original draft: M.G.G. ; writing--review and editing: M.G.G., R.d.J., A.K., B.R., M.E.S. This study was a part of the \"Integrated modelling framework to monitor and predict trends of agricultural management and their impact on soil functions at multiple scales\" (iMOSoil) under Project 406840-143062 funded by the Swiss National Science Foundation within the National Resource Program NRP68 \"Sustainable Use of Soil as a Resource\" (www.nfp68.ch). The University of Zurich Research Priority Program on \"Global Change and Biodiversity\" supported the work of [PERSON]; [PERSON] (Meteotest) supplied N deposition datasets adapted to cropland and grassland; the Swiss Federal Office for the Environment (FOEN) is the owner of the N deposition data. The authors declare no conflict of interest. Figure A2: Spatial variability of yearly-accumulated precipitation: (**a–c**) croplands (455–3490 mm/year), croplands/natural vegetation mosaic (469–3472 mm/year), and grasslands (534–3825 mm/year), respectively, for the year 2000; (**d–f**) croplands (530–2919 mm/year), croplands/natural vegetation mosaic (530–2676 mm/year), and grasslands (528–4008 mm/year), respectively, for the year 2007; and (**g–i**) croplands (382–2860 mm/year), croplands/natural vegetation mosaic (386–2793 mm/year), and grasslands (447–3245 mm/year), respectively, for the year 2010. Figure 14: Spatial variability of yearly mean temperature: (**a–c**) croplands (–4–12 \({}^{\circ}\)C), croplands/natural vegetation mosaic (—13 \({}^{\circ}\)C), and grasslands (–9–14 \({}^{\circ}\)C), respectively, for the year 2000; (**d–f**) croplands (–4–13 \({}^{\circ}\)C), croplands/natural vegetation mosaic (–4–13 \({}^{\circ}\)C), and grasslands (–9–15 \({}^{\circ}\)C), respectively, for the year 2007; and (**g–i**) croplands (–6–12 \({}^{\circ}\)C), croplands/natural vegetation mosaic (–5–12 \({}^{\circ}\)C), and grasslands (–10–13 \({}^{\circ}\)C), respectively, for the year 2010. Figure A6: Scatterplot of the standardized residuals and the standardized predicted values using the original values of the class grasslands for the year 2000.