## 3 Results
### SIFc-GPP Relationship across Sites, Biones, and Years  
Figure 3 showed the distributions of GPP/SIFc slopes in individual biomes at site-multi-yearly (A and B) and site-yearly (C and D) levels. GPP/SIFc slopes varied greatly across sites and biomes. The CSIF-GPP relationships at the site-multi-yearly scale (Figure 3A) indicated that CSH had the largest inter-site variability with the biggest interquartile ranges (the height of the boxes). In addition, there were significant differences in GPP/CSIF slopes between ENF and several other biomes (i.e., DBF, EBF, GRA and OSH) (\(p<0.001\)), and no significant difference was found among all other biome pairs (\(p>0.05\)). Although the GOSIF-GPP relationships at the site-multi-yearly scale (Figure 3B) look similar to the GOSIF-GPP relationships (Figure 3A), there were substantial differences. First, the GOSIF-GPP inter-site variabilities were smaller than those of GOSIF-GPP in most biomes. Second, with less inter-site variability, the GOSIF-GPP data showed that the number of biomes significantly different from ENF was one more than the CSIF-GPP data (ENF vs. MF) and the significance level (\(p\) value) generally increased as well. In addition to these differences, it is important to notice that there was still no significant difference between any non-ENF biome pairs according to GOSIF-GPP (\(p>0.05\)), consistent with CSIF-GPP. The SIFc-GPP relationships at the site-yearly scale (Figure 3C,D), as expected, showed larger variability than those at the site-multi-yearly scale. The ENF biome showed significant differences with all other biomes (\(p<0.001\)), except for the CSH biome with GPP/CSIF slopes (\(p>0.05\)) (Figure 3C,D). However, there were no significant differences of the SIFc-GPP relationship between OSH and DNF biome with other biomes at site-multi-yearly scale (\(p>0.05\)), although the slopes from OSH and DNF are lower than others (Figure 3A,B). Figure 2: Pearson correlation coefficients (r value) between SIFc (CSIF and GOSIF) and GPP from two partitioning methods (GPP_D and GPP_N) and the mean of them (GPP_M) across (**A**) all 12 biomes (daily data at specific biome of all the years) and (**B**) all 14 years (daily data from whole year) (\(p<0.001\)). Biomes are same as Figure 1. Years are from 2001 to 2014. Temporal variability of site-level GPP/CSIF slopes remained relative stable for most biomes except for a few biomes with very limited number of flux towers (i.e., CSH, OSH, SAV, and WET) (Figure 4). Medians of slopes were more similar than means in different variants. The interannual variability of forest biomes were in general the smallest, followed by grassland and cropland. It is interesting to see that the interannual variability of forest, grassland, and cropland biomes remained relatively stable, not affected by the increase of number of flux towers over time in general. In contrast, other biomes differed as the number of sites were small and the number of towers in normal operation fluctuated across years, which led to large interannual variability in the slopes within each of these biomes. Figure 3: Boxplots and comparison of GPP/SIFc slopes between the 12 biomes are similar to those in Figure 1. (**A,B**) Site-multi-yearly slopes (basis of slopes calculated for whole time); (**C,D**) site-yearly slopes (basis of slopes calculated for each year). Each boxplot represents the distribution of GPP/SIFc slopes in the corresponding biome. The top and bottom of the boxes represent the 75 and 25 percentiles (i.e., Q3 and Q1), respectively; the solid line in the box is the median value of the box; the whole box is the interquartile range (IQR = Q3–Q1); the top and bottom whiskers represent the maximum and minimum values (i.e., Q3–1.5 * IQR, Q1–1.5 * IQR), respectively; the data outside of the maximum and minimum are shown as points beyond the whiskers. Site-yearly and site-multi-yearly slopes were derived from daily SIFc-GPP data obtained in a year and in the whole observation period for each site, respectively, using major axis regression.