# Influences of Extreme Weather Conditions on the Carbon Cycles of Bamboo and Tea Ecosystems
## 3 Results and Discussion
### Modeled Plant Growth  
The results of the model that treated bamboo as grass were not reasonable. For example, the modeled leaf area index (LAI) reached as high as 8, but decreased to 0 during the dry August of 2016 (Figure S4a), which was inconsistent with observations at the study site. Therefore, the following modeling results were obtained by considering bamboo as temperate broadleaf evergreen forest.  
The modeled mean LAI values of the bamboo and tea plots during 2015-2017 were 3.3 and 4.5 (Figure S5), respectively. In comparison, the observed LAI for moso bamboo in a subtropical forest (Anji County, northwestern Zhejiang Province, China; 30\({}^{\circ}\)28\({}^{\prime}\) N, 119\({}^{\circ}\)40\({}^{\prime}\) E) located 115 km from the present study site was 3.6 in 2015 [36], similar to the modeled result (3.3) in the present study. The slight decrease in the observed LAI in autumn and winter and increase in spring at the Anji site were also reproduced by the model (Figure S4b). Green tea typically has a very large LAI. For example, [PERSON] [37] observed 36 LAI values for the same type of tea as that examined in the present study in India (Figure 1 in [37]), of which 5 values were within 3.0-4.0 and 30 within 4.0-6.5. High LAI values were observed in the photograph of our study plot (Figure 2b). Therefore, the modeled mean LAI of 4.5 for the tea plot was within a reasonable range.  
The modeled GPP at the two plots was basically consistent with the MODIS GPP product (Figure 6), with the correlation \(R^{2}\) between simulation and MODIS GPP product being 0.39 and 0.38 at the Bamboo  
Figure 5: Observed and modeled soil water content by soil depth at the two study plots.  
and tea plots, respectively. The moderate \(R^{2}\) (0.38-0.39) was caused the noise (e.g., close to zero GPP values during the growing season) in the MODIS product (Figure 6). The picking of the youngest leaves at the tea plot was not considered in the modeling, which could affect the carbon cycle and might contribute to the differences in GPP between modeling results and MODIS product. Both the noise in the MODIS GPP product and the neglect of the youngest leave picking in the modeling contributed to the larger modeled GPP than the MODIS value.  
The modeled C storage in biomass and soil at the tea plot in the present study were consistent with previous studies, supporting the model's accuracy. [PERSON] et al. [36] reported that the average densities of C storage in biomass, litter layer, and soil at tea plantations in China were 50.90, 4.91, and 137.50 Mg C ha\({}^{-1}\), respectively, and no significant differences were found in the density of biomass C among different tea plant varieties and climate conditions. In the present study, the mean biomass C density, including leaf C, fine root C, coarse root C, and stem C, during 2015-2017 was 37.70 Mg C ha\({}^{-1}\), equivalent to 74% of the value reported by [PERSON] et al. [36]. In addition, soil C accounted for the largest proportion of C storage (123.25 Mg C ha\({}^{-1}\)) during 2015-2017 in the present study, equivalent to 90% of the value reported by [PERSON] et al. [36].