## Discussion
### Variability of the SIFc-GPP Relationship  
Our results show that the linear SIFc-GPP relationship is significantly affected by the spatial and temporal scales (Figure 8). SIFc-GPP shows the strongest linear relationship at the coarsest scales (i.e., biome-multi-yearly). The R\({}^{2}\) value of the linear SIFc-GPP relationship increased with spatial upscaling from site to biome at all temporal scales (i.e., daily, yearly, and multi-yearly). In contrast, the R\({}^{2}\) value did not necessarily increase with temporal upscaling at different spatial scales (i.e., site and biome). This suggests that SIFc (both CSIF and GOSIF) is not effective in capturing temporal variabilities of GPP, particularly the inter-annual variability. Overall, the reconstructed SIFc performs well in tracking long-term biome-wide GPP (Figure 8F), consistent with other studies [9]. The reduced ability of SIFc in capturing the short-term changes of GPP might largely be attributed to the errors in SIFc and GPP products, as well as the footprint mismatch between SIFc and GPP, especially at finer resolutions and during the reconstruction period (from 2001 to 2014) [29; 31]. It should be noticed that, despite moderate to strong R\({}^{2}\) values, there was considerable dispersion in the comparisons of CSIF/GOSIF and GPP at both site and biome levels (Figure 3 and Figure S6). The scattered distribution might be caused by SIFc and flux_GPP data quality as well as the non-universality of the linear GPP-SIFc relationship [44; 45], particularly at CRO and DBF biomes (Figures S3 and S6). For example, SIFc-GPP points scattered around the linear regression lines widely at the DE.Geb site (CRO biome) (Figure S6) while the aggregated annual change of flux_GPP synchronized well with those of SIFc in addition to many scattered points caused by interannual variability (Figure S5), suggesting interannual variability of cropping practices (e.g., rotation of crops, fallow, and fertilization) may contribute substantially to the pronounced scattering of points around the regression lines in Figure S6. On the other hand, there were clearly two clusters at the IT.Noe site (CSH biome), which signifies major difference between CSIF and GOSIF there. Clearly, future efforts are required to investigate the variability in the SIF-GPP relationship systematically to answer a suite of important questions: where/when does a linear SIF-GPP relationship break down? Where/when does it change in slope and why? [PERSON] and [PERSON] [21] reported that C4-dominated grasslands and crops, albeit only two C4 sites, had a significantly higher slope than C3-dominated grasslands and crops (29.42 vs. 20.98, \(p\) < 0.001). Moreover, [PERSON] and [PERSON] [22] found a linear SIF-GPP relationship that is sensitive to crop type (corn vs. soybean) as well. However, our results suggested that there was no significant difference (\(p\) > 0.05) in the slopes between C4 (n = 3) and C3 (n = 8) crops at a site-multi-yearly scale, respectively, for CSIF (C4 vs. C3: 42.71 \(\pm\) 1.33 (mean \(\pm\) SE) vs. 38.87 \(\pm\) 5.38) and for GOSIF (C4 vs. C3: 38.70 \(\pm\) 3.48 vs. 40.32 \(\pm\) 6.11). The difference between our study and [PERSON] and [PERSON] [21] may be due to the limited number of C4 crop sites and the different approaches used for analysis. We compared the difference in the means of the slopes from individual C3 and C4 sites, while [PERSON] and [PERSON] [21] compared the difference in the overall slopes of the C3 and C4 crops after pooling SIF and GPP data from all C3 and C4 sites. Apparently, further research is needed to understand the differences in the SIF-GPP relationships for C3/C4 plants with more C4 sites. The number of EC flux towers is not balanced among the biomes, and some biomes only include one or a few sites. This leads to large uncertainties in the linear GPP/SIFc slopes in some biomes (e.g., CSH, OSH, and WET). For example, the GPP/CSIF slopes of OSH and DNF were lower than other biomes; there are clearly two clusters of data captured within CSH (Figure 3).