## Results
### Seasonal and Interannual Variabilities of Modeled and Observed Carbon Dioxide and Water Fluxes
#### 3.2.1 Day-to-Day and Seasonal CO\({}_{2}\) and Water Fluxes Variability
Higher interannual variability was found during the most productive seasons (spring and summer), in which most of the harvest events occurred (on different days each year). GPP is more variable than ER because of the larger direct impact of harvest on photosynthesizing biomass that on total ER. Water limiting conditions and the onset of harvest events (end of April-early May) led to a substantial reduction of GPP and hence of the net ecosystem exchange rate with NEE averaged values during this period as low as wintertime fluxes. Figure 8: Daily carbon and water fluxes averaged for each day of the year over the study period (2006–2010) for the mowed pasture. The blue circles are used for observations, error bars represent one standard deviation around observed means; the red line is used for CenW modeled fluxes; and the yellow shaded areas represent one standard deviation around modeled means. GPP (**a**), ER (**b**), NEE (**c**), and ET (**d**). For the grazed paddock, modeled and observed daily averages (over five years) agree very well for GPP (Figure 9a), as well as their interannual variability (error bars), confirming that the main biotic and abiotic factors controlling the dynamic of GPP were properly incorporated in the CenW ecosystem model. Weaker correlations were found between observed and modeled ER (Figure 9b) and NEE (Figure 9c) during grazing events while outside of grazing periods good agreements were retrieved. These large differences were likely caused by the noncapture of some or all of grazing animals' respiration by the EC system. Overall, model/data agreements are greatly variable and strongly depend of climate conditions and management practices (Figures 8 and 9). Variability of Annual CO2 and Water Fluxes  
Correlations between climate, management practices and CO2 and water fluxes are showed through a matrix plot (Figure 10). The different categories correspond to modeled and observed variables for the mowed and grazed paddocks. All points represent one year of either modeled or  
Figure 9: Daily carbon and water fluxes averaged for each day of the year over the study period (2006–2010) for the grazed pasture. Blue circles are used for observations, error bars represent one standard deviation around observed means; the red line is used for CenW modeled fluxes; and the yellow shaded areas represent one standard deviation around modeled means. GPP (**a**), ER (**b**), NEE (**c**), and ET (**d**). observed variables for the two sites summed/averaged over the summer half-year (15 April to 15 September), corresponding to the most productive time of the year. Lower panels show the scatter plots between the different selected variables and the upper panels give their correlation coefficients. For example, the pink-circled lower panel show the scatter plot of NEE and precipitation and the pink-circled upper panel give the corresponding correlation coefficients for the different categories (MG, MM, OG, and OM) and the overall correlation coefficient (Cor). The blue-circled area of the graph shows the selection of the most important relationships. First, it is striking (Figure 10) that annual CO\({}_{2}\) and H\({}_{2}\)O fluxes were correlated with annual meteorological condition (air temperature and precipitation) and with management practices (C  
Figure 10: Matrix of paired plots showing the interannual variability of summer half-year (15 th April–15 th September) averaged climate drivers (air temperature and precipitation), management practices (N fertilizer application and amounts of C moved/grazed), and observed and modeled CO\({}_{2}\) and H\({}_{2}\)O fluxes for the moved and grazed grassland sites (MG: modeled grazing; MM: modeled moving; OG: observed grazing; OM: observed moving). Variable names are given in the matrix diagonal. Paired scatterplots are in the lower triangle (below the diagonal in gray) with every point being the summer half-year of one year of the study period and colors are related to the different categories listed above.