# Environmental Effects on Normalized Gross Primary Productivity in Beech and Norway Spruce Forests
## 3 Results
### Effect of Meteorological Conditions on GPP
#### 3.2.1 GPP\({}_{\text{norm}}\) Prediction through Stepwise Multi-Linear Regression (SMLR)  
To identify the main environmental variables influencing GPP\({}_{\text{norm}}\) across the beech and both spruce forest sites, an SMLR model was built and evaluated (Figure 4). The accuracy indicators of the SMLR showed a good model quality in predicting significant environmental variables that influenced GPP\({}_{\text{norm}}\) values (Table 2). The model over predicted for low GPP\({}_{\text{norm}}\) values and under predicted for high GPP\({}_{\text{norm}}\) values for all the three forest sites. The Pearson correlation for all forest stations shows strong linear relationship between the predicted and estimated GPP\({}_{\text{norm}}\) values (Table 2). Furthermore, the R\({}^{2}\) of the SMLR model used across each forest ecosystem revealed that approximately 40-49% of the variance in GPP\({}_{\text{norm}}\) was well predicted by the environmental variables used (PAR, CNI, SVWC, VPD, T\({}_{\text{air}}\), and T\({}_{\text{s}}\)). The prediction error RMSE of the interaction model was found to be 0.18, 0.14 and 0.15 for the wet spruce, dry spruce and beech forests, respectively. This shows that model performance was comparable for all sites. At both spruce forest sites, similar statistically significant (\(p<0.01\)) environmental variables affecting GPP\({}_{\text{norm}}\) were PAR, SVWC, VPD, and T\({}_{\text{s}}\) (Tables 3 and 4). In addition to these similar environmental variables, CNI was also found to have secondary effects on GPP\({}_{\text{norm}}\) values at the wet spruce forest site in Blly Kriz (Table 3). At the beech forest site in Stitna, all the environmental variables used in the SMLR analyses were found to be statistically significant (\(p<0.01\)) in influencing GPP\({}_{\text{norm}}\) values, especially for PAR, T\({}_{\text{s}}\), and CNI (Table 5). Moreover, similar quadratic terms such as PAR\({}^{2}\), T\({}_{\text{s}}^{2}\), and CNI\({}^{2}\) with negative coefficients were found to be statistically significant (\(p<0.01\)) across both spruce forest sites, indicating a decrease in GPP\({}_{\text{norm}}\) values (downward sloping) with an increase in PAR, Tand CNI values (Tables A3-A5). Furthermore, at the beech forest site in Stitma, VPD2 and CNI2 proved to be inversely related to GPPnorm and statistically significant (Table A5). However, the positive coefficient value for SVWC2 across all the forest sites showed an increase in GPPnorm values with increasing SVWC values (Tables A3-A5). Figure 2: Annual trend of the daily potential gross primary productivity (red line) using daily sums of gross primary productivity (GPP) for (**a**) the wet spruce forest in Bfly Kräz (CZ-BK1), (**b**) the dry spruce forest in Rájec (CZ-RAJ), and (**c**) the beech forest in Stitma (CZ-Stn) from 2012 to 2016. The vertical lines represent the main growing season period of May–September. Figure 3: Annual variations of estimated Normalized gross primary productivity (GPP\({}_{\rm norm}\)) within (**a**) the wet spruce forest in Blíly Kriz (CZ-BK1), **(b**) the dry spruce forest in Rájec (CZ-RAJ), and (**c**) the beech forest in Stitna (CZ-Stn) from May to September of 2012–2016. The smoothing spline curves was depict the trends in seasonal courses of GPP\({}_{\rm norm}\) during the growing seasons of 2012–2016. The smoothing spline curves (\(\lambda=0.95\)) depict the trends in changes of daily GPP\({}_{\rm norm}\) values over the growing seasons of 2012–2016. For the statistically significant (\(p<0.01\)) interaction terms of SMLR, the VPD:SVWC term was common across all the forest sites showing the interactive effects of VPD and soil water availability on GPPnorm values. At the wet spruce forest site in Bilj Kriz, interactive effects between VPD and other environmental variables such as SVWC, PAR, and Tair were statistically significant. At the dry spruce forest site in Rajec, statistically significant (\(p<0.01\)) interactive terms between SVWC and other environmental variables such as CNI, PAR, and VPD were observed.