## 2 Materials and Methods
### Impacts of Variation in SLA on Modeled Gross Primary Productivity  
We first estimated the differences in CLM4.5-modeled gross primary productivity (GPP) at the QYZ, CBS, DHS, and HBG sites between model experiment S2 using the observed SLA values and model experiment S1 with the default SLA values. Figure 5 presented the changes in annual GPP, mean photosynthesis rate (Ac), and mean leaf area index (LAI) at four sites in the experiment S1 compared with those in experiments S2.  
Figure 4: The default SLA values in terrestrial biosphere models and the SLA mean observed values in China for different plant functional types. Box plots show the mean, 25 th percentile, and 75 th percentile of the observed SLA values. Abbreviations: NET, needleleaf evergreen tree; NDT, needleleaf deciduous tree; BET, broadleaf evergreen tree; BDT, broadleaf deciduous tree; BES, broadleaf evergreen shrub; BDS, broadleaf deciduous shrub.  
The mismatch in SLA between default values in CLM4.5 and observations had a larger influence on GPP simulation for temperate NET (QYZ) and temperate BET (CBS) than that for temperate BDT (DHS) and grass (HBG). The overestimation of the default SLA value by 0.003 m\({}^{2}\)/g for temperate NET could result in a lower annual GPP estimation at QYZ by 161 g C m\({}^{-2}\) yr\({}^{-1}\). This weakened productivity was mainly caused by a decrease in the photosynthesis rate in spite of an increase in LAI. Similarly, the higher default SLA value for temperate BDT by 0.008 m\({}^{2}\)/g, induced a lower modeled GPP at CBS by 69 g C m\({}^{-2}\) yr\({}^{-1}\). On the contrary, a 0.002 m\({}^{2}\)/g underestimation of the SLA value for temperate BET in the CLM4.5 caused a decrease in LAI and a slight increase in Ac, which led to a higher annual GPP by 51 g C m\({}^{-2}\) yr\({}^{-1}\). In addition, a large, overvalued SLA in CLM4.5 for C3 grass had a small impact of 5 g C m\({}^{-2}\) yr\({}^{-1}\) on simulated GPP and Ac at HBG, although there was an increase in LAI by 0.3 m\({}^{2}\)/m\({}^{2}\).  
We then quantified the impacts of SLA variation calculated from the observations and models on the modeled GPP at these sites. Table 3 presents the CV of SLA quantified by observed data (Table 2) and default values across seven terrestrial biosphere models (Figure 4), and the corresponding relative changes in modeled GPP, Ac, and LAI with the involvement of these variation in SLA calculated by Equations (7) and (8), respectively. The results showed a larger influence on modeled GPP at QYZ and DHS than that at the CBS and HBG sites due to the variation of the SLA values. The SLA values in temperate NET and temperate BET both changed by 43% at the mean observed level, which caused the modeled GPP at QYZ and DHS to change by 7% and 8%, respectively. The observed SLA variations in temperate BDT and C3 grass had little impact on the GPP simulation at CBT and HBG, although Ac and LAI changed greatly. In particular, the SLA value of C3 grass changed by 57% at the mean observed level and could lead to Ac and LAI changes by 48% and 58%, while GPP at the HBG site only changed by 3%. Moreover, a large SLA variation among models in temperate NET and temperate BET could result in greater impacts on the modeled GPP than the effects from variations in the observation. For example, SLA variation among the models with a CV of 60% in temperate NET caused a GPP change of 19%, resulting from changes in Ac with 31% and LAI with 62% at QYZ.  
Figure 5: The differences in annual gross primary productivity (GPP), mean RuBP-limited photosynthesis rate (Ac), mean leaf area index (LAI) between model experiment S1 (with default SLA values in the CLM4.5 model) and model experiment S2 (with mean SLA observed values). The error bar shows the standard deviation. QYZ site: temperate needleleaf evergreen tree; CBS site: temperate broadleaf deciduous tree; DHS site: broadleaf evergreen tree; HBG site: C3 grass.