## 4 Discussion
### Relationship between GPP and SIF  
This research verified that the GOSIF is most correlated with GPP compared with VIs in both spatial and temporal time scales and that the relationship between annual GOSIF and GPP is linear (Figure 4). A similar result was consistent with [PERSON] et al. [22], who reported that the Vegetation Photosynthesis Model (VPM)-based GPP (namely GPP\({}_{\text{VPM}}\)) is compatible with GOME-2 SIF at multiple spatial-temporal scales in China, and the monthly GPP\({}_{\text{VPM}}\) and SIF showed a significant positive linear correlation in most areas. The linear correlation relationship provides a theoretical basis for the subsequent estimation of GPP by SIF at sites or ecosystem levels [52]; however, the correlation between monthly GOSIF and GPP during 2000-2020 presented a polynomial distribution in the MLRYR (Figure 5) and the polynomial fitting R\({}^{2}\) is as high as 0.976. Similar results could be found in Figure 13a. [PERSON] et al. [53] found that SIF was more susceptible to the environmental conditions (e.g., drought and heat stresses, incoming photosynthetic photon flux density, vegetation types, etc.) than GPP; this is worthy of further study, aiming to provide the possibility of reliable estimation of GPP from the perspective of remote sensing observations. [PERSON] et al. [54] studied that SIF cannot track GPP variation well during a short-term heatwave in ENF, further revealing that the nonlinear and complex SIF-GPP relationship exists at different time scales. The research of [PERSON] et al. [55] showed the broken linear SIF-GPP relationship at high-light levels since the GPP tends to saturate while SIF still increases, especially for C3 crops. [PERSON] et al. [56] also reported a strongly nonlinear relationship (hyperbolic regression function) between GPP and SIF in a temperate Evergreen Needleleaf Forest (ENF) at daily and seasonal time scales, which was mainly due to the different physiological mechanisms. In addition, canopy structure and vegetation coverage of diverse communities may be the main influencing factors of spatial heterogeneity of the SIF-GPP relationship [36]. [PERSON] et al. [57] indicated that the tides play an important role in regulating SIF-GPP relationships. Due to the tides, inundation attenuated the role of plant physiology and canopy structure in explaining the relationship between SIF and photosynthesis, thus negatively affecting SIF-based GPP estimates. [PERSON] et al. [58] revealed that the heatwave reversed the photosynthesis-fluorescence relationship at canopy and leaf scales, and the highly non-linear relationship between GPP and SIF is formed by Non-Photochemical Quenching (NPQ), a dissipative mechanism that prevents the adverse effects of high light intensity. To preliminarily investigate the nonlinear relationship between monthly SIF-GPP in this research more clearly, the monthly GPP, SIF, NDVI, EVI, and NIRv variations in 2019 were analyzed, as shown in Figure 15; we see that the monthly variation characteristics of SIF, NDVI, EVI, and NIRv were similar. At the same time, the GPP increased significantly from February to May and decreased considerably from September to December, which was different from that of SIF and VIs. This phenomenon might be responsible for the nonlinear relationship between GPP and SIF. Moreover, we found a polynomial relationship between monthly GPP and SIF in both drought (2019) and non-drought years; however, the findings of [PERSON] et al. [36] claimed a constant SIF-GPP relationship under both drought and non-drought conditions, although the drought stress increased the spatial heterogeneity of the SIF-GPP relationship; therefore, it will be uncertain to explore the influence of environmental stress on the GPP-SIF relationship only from a satellite remote sensing scale. Furthermore, [PERSON] et al.