## Discussion
### Potential Caveats and Uncertainties  
Landscape heterogeneity and inconsistency between the flux-tower footprint and SIFc pixel should have contributed to the uncertainty of our results [53]. We acknowledge that the landscape heterogeneity at the EC flux towers is an important obstacle to analyzing the SIF-GPP relationship. Although we have visually checked landscape conditions around all EC-flux tower sites using Google Earth images, and removed four flux towers from our analysis, a more robust approach to address the issue would be using a footprint model to obtain the footprints of all the sites. Our manual examination approach resulted in 208 sites, which was different from that of [PERSON] and [PERSON] [29], who selected only 40 sites using an automated NDVI-based approach. Our results, therefore, might have higher uncertainties than [PERSON] and [PERSON] [29], but at the same time, encompassed more spatial variability of sites globally, which might enhance the representativeness of our results. The results derived from this new paradigm should be better suited to real-world applications than those derived from the conventional approach because of the ubiquity of heterogeneous landscapes [53]. Furthermore, applying the results from conventional analysis that only cover 'homogenous' landscapes to the real world would result in unknown amount of uncertainty. The latter is demonstrated by the good performance of the median-based two-slope scheme at many flux-tower sites and biomes (Figure 9). Retrospectively, our two-slope scheme suggests that the impact of landscape heterogeneity and inconsistency between the flux tower footprint and SIFc pixel might not as severe as we previously thought.  
In addition, for CRO and GRA biomes, the site selection is particularly important, as the flux towers at these biomes are of a height of 2-6 m and the footprint areas are similar when visualized with the SIFc pixel. On top of that, the GPP from these sites very much depend on the crop and management practice (e.g., rotation of crops, fallow, grazing, and fertilization), which can change every few hundred meters, thereby making the satellite-ground comparison challenging.  
Whether the regression method used in this study works well also introduced uncertainty. Just from the mathematical view, one of the fundamental problems of forcing the intercept to zero is getting a much higher R\({}^{2}\) (Figure 8), which will lead to a large portion of bias in the results, especially at a daily scale [2]. Conversely, at the point of vegetation physiology, the zero-intercept logic provides a unique perspective for the SIFc-GPP relationship analysis. [PERSON] and [PERSON] [54] reported that the low daily SIF/GPP measurements are not available in some areas/biomes, such as EBF. In such occasions, the application of our zero-intercept logic makes more sense, which may have greater predictability under unseen conditions (e.g., low SIF/GPP). As this study focused on the comparison of GPP/SIFc slopes across different biomes, we finally applied the zero-intercept method rather than the free intercept. Nevertheless, some free intercept regression model would provide more information about the SIFc-GPP relationship [43].