## 3 Results
### Model Sensitivity Analysis  
Figure 6 illustrates the effect of changes to key input variables and parameters on annual GPP, TER, NEP and soil CO\({}_{2}\) and N\({}_{2}\)O fluxes simulated using PnET and averaged over 1999-2007 (Table S1a). The simulated annual CO\({}_{2}\) flux components showed rather little sensitivity to changes in soil parameters, but more to changes in temperature and precipitation. Changing the bulk density (BD) input values by 10% produced a disproportionate change in N\({}_{2}\)O fluxes. This value controls the initial organic C (and N) stock in the soil as well as soil porosity. A higher BD (given in g cm\({}^{-3}\)) results in higher organic C content (input to model as a fraction of BD) and lower porosity (input as % of BD), which provides more substrate for microbes and results in more anaerobic conditions during wetting. The hydraulic conductivity of the soil was uncertain, as it was not determined. Although the soil is clay-rich, tree roots promote conduits for water percolation. Values of 10 and 100 times higher than the selected value of 0.0006 mm min\({}^{-1}\) were shown to reduce the simulated gas fluxes by less than 5%. Changing the daily climate variables of minimum, maximum and mean temperature (in a single simulation) or precipitation by \(\pm\) 10% produced changes to gas fluxes of <10%, with a shift from litter layer to mineral soil nitrification due to reduced microbial activity in the litter layer. Changes in N deposition of \(\pm\) 10% changed soil N\({}_{2}\)O fluxes by less than 4%. Increasing N deposition by 100% to 2.46 g N m\({}^{-2}\) year\({}^{-1}\), which is similar to values of 2.0-3.5 g N m\({}^{-2}\) year\({}^{-1}\) recorded for a broadleaved forest at Hoeglwald in central Europe [54], resulted in large, simulated increases in N\({}_{2}\)O fluxes of 17.7%. Thisanalysis therefore showed that simulated soil fluxes were particularly sensitive to initial organic C content (via bulk density) and to factors that control soil moisture and thereby anaerobic conditions, i.e., bulk density and field capacity. It also showed that stand-scale CO\({}_{2}\) fluxes were relatively insensitive to changes in input values, which may explain the low interannual variations simulated. Model sensitivity to selected PnET parameters is shown in Figure 7 (Table S1b). Changes of \(\pm\)10% to GDDFOLEND (daily temperature sum for end of foliage growth; see Table 3) produced >10% change in all simulated soil fluxes; increasing SENESCSTART (leaf death timing) by 30 days decreased simulated GPP, TER and soil CO\({}_{2}\) fluxes by >10%, which indicates the importance of defining the start and end of the growing season to simulated respiration and soil processes. Changing these parameters affects the allocation of carbon at the end of the year and hence the amount available for leaf development the following year, which has a cumulative effect after several years. However, SENESCSTART defines a day of year and therefore is not comparable to % change in outputs, whereas changing GDDFOLEND affects leaf N uptake and therefore the intensity rather than timing of soil emissions. Figure 8 shows model sensitivity to PSIM parameters (Table S1c). No single parameter had a disproportionate effect on the simulated results. Comparison of the PSIM module with and without a vegetation understorey, modelled as different sets of carbon pools (as defined in Table 1), showed that the understorey contributed 20%, 17% and 20% of simulated TER, GPP, and soil CO\({}_{2}\) emissions, respectively, and 14% of simulated soil N\({}_{2}\)O emissions. However, the understorey vegetation characteristics vary substantially across the Inclosure; there are few measurements of understorey parameters to inform the choice of values, and no measurements to evaluate its proportional contribution to fluxes. Therefore, there are considerable uncertainties in the contribution of the understorey to the TER, GPP and soil fluxes of CO\({}_{2}\) and N\({}_{2}\)O in this forest.