## 5 Discussion  
This study determined the 3-PG model parameter values for a deciduous broadleaf forest dominated by _B. platyphylla_. The original parameter values were proposed for _Eucalyptus_ forest plantations in Australia [10]. Some authors have directly applied these available parameters to other tree species or indirectly applied tuning methods [12,13,16,24]. The parameter values determined in this study corresponded to mature forest, focusing on biomass production. Data from young forests were not available, so we could not investigate forest growth rate or complete an age-series analysis with the 3-PG model. An allometric analysis was performed to parameterize biomass partitioning between \(W_{S}\) and \(W_{F}\). Our model results were in agreement with empirical data (Figure 6) after parameterization. Even though some default parameter values were used, doing so did not cause significant errors in the output [17]. _pFS2_ and _pFS20_ values were moderately different from previous studies [7,10,11]. Deciduous broadleaf forests have annual leaf cycles, and biomass is typically stored in stems and branches throughout the year. However, DBH growth is small due to the short growing season in cool-temperate forests [25,26]. Even though age-series data were not available, trees with different DBH were present, and were assumed to represent different tree ages; these trees were used to find the relationship between relative annual growth rate and above-ground biomass. The relative annual growth rate of estimated above-ground biomass had a trend similar to the observed one. Foliage biomass was highly responsive to leaf phenology (_i.e._, leaf growth, maturation, senescence, and leaf fall). Litterfall was calculated as a constant fraction of foliage biomass corresponding to leaf growing conditions. In parameterization, growth modifiers are the main factors affecting GPP calculations [8]. Among the growth modifiers, the temperature modifier had the most effect on \(a_{C\!r}\). Because our study site was constrained by temperature, the 3-PG model was run so that GPP = 0 when the temperature was lower than \(T_{n}\) or higher than \(T_{x}\). The temperature at both study sites never reached \(T_{x}\) because it is a cool-temperate area; thus, \(T_{x}\) had no effect on GPP calculations. However, the temperature in the  
Figure 9: Effect of meteorological data on GPP as following **(a)** minimum temperature (open circle and dashed line) and maximum temperature (solid circle and solid line); **(b)** solar radiation The parameter values were changed \(-20\%\), \(-10\%\), \(+10\%\), and \(+20\%\), except for temperature, which was changed in degrees Celsius (\(-2\)\(\mathrm{\SIUnitSymbolC}\), \(-1\)\(\mathrm{\SIUnitSymbolC}\), \(+1\)\(\mathrm{\SIUnitSymbolC}\), and \(+2\)\(\mathrm{\SIUnitSymbolC}\)). winter was always lower than \(T_{n}\), and this affected the number of frost days. Thus, the 3-PG model generated GPP values of 0 at Hitsujigaoka and Takayama during winter. GPP is a function of environmental factors and the interception of radiation for photosynthetic processes. Thus, solar radiation (Figure 9b) increased GPP in relation to leaf area. Soil water may be limited at other forest sites, as found in _Eucalyptus_ forest plantations by [PERSON] _et al._[27]. In that case, increased precipitation resulted in increased stand volume, which is relevant to stem biomass. However, our study sites were not limited by water stress because they were located in an Asian monsoon climate region with high precipitation [28]. Additionally, snow melt increases the amount of soil water in the summer. Therefore, precipitation had no effect on GPP. Biomass production, especially _Ws_ and GPP, was controlled by \(a_{Cx}\) and \(T_{opt}\) (Figure 8). \(a_{Cx}\) can be highly sensitive, relative to other input parameters [16,27], and directly affects the calculation of GPP. Changes in \(a_{Cx}\)result in significant differences in GPP. \(T_{opt}\) had an inverse relationship with GPP, such that lower temperatures resulted in higher GPP.