## 4 Discussion  
This study was conducted to investigate how the relationships of coupling and sensitivity between NDVI and GPP vary along the aridity gradients and PFTs of China's terrestrial ecosystems during the growing season from 1982 to 2018. Previous research has reported that canopy structure can explain the decoupling relationship between greenness and productivity in a short period of time [27; 50]. Building upon these findings, our study observed a decadal-scale decoupling of greenness and productivity across China. This decoupling was also evident within PFTs (see Figure 4). Specifically, we found that the relationship of R\({}^{2}\) values between NDVI and GPP decreases with increasing AI (becoming more humid), suggesting that wetter conditions weaken this relationship (Figure 4a). Concurrently, the sensitivity of GPP to NDVI also declined with increasing AI (Figure 7). In arid regions (AI ranging from 0 to 0.65), the strength of NDVI-GPP coupling is characterized by an R\({}^{2}\) value of 0.21, with slopes ranging from 0.12 to 0.06. In contrast, in humid areas (AI greater than 0.65), the NDVI-GPP relationship showed an R\({}^{2}\) of 0.11, with slopes ranging from 0.04 to 0.01 (Figures 4a and 7). These findings suggest a significant decoupling and insensitivity between canopy greenness (NDVI) and productivity (GPP) in more humid areas. The result is consistent with [PERSON] et al. (2022), who observed that aridity increased the strength of the coupling between LAI and GPP [26]. This implies that changes in greenness are a crucial strategy for ecosystems in arid environments to manage climate fluctuations. It is worth noting that different types of trees (ENF, EBF, DNF, DBF, and MF) and grasses exhibit significant variability in the NDVI-GPP relationships. Overall, inter-annual GPP and NDVI were highly coupled (i.e., high R\({}^{2}\)) in grasslands, with a value of 0.20. However, weaker NDVI-GPP relationships (greenness-productivity decoupling) were found in forest ecosystems (i.e., ENF (0.04), EBF (0.09), DNF (0.07), DBF (0.11), and MF (0.07)), especially ENF (see Figure 4b). Previous studies have reported that environmental factors (water availability, heat stress, and temperature), as well as canopy structure and vegetation types, influence the NDVI-GPP relationships [51; 52; 53; 54]. In grasslands, a previous study illustrated that the correlation between greenness and multi-year average GPP during the length of greening was the strongest (R\({}^{2}\) is 0.49) [55], indicating high NDVI-GPP coupling in grassland [56]. For forest ecosystems, particularly in tropical forests, previous studies have also identified a decoupling between vegetation structure and productivity [26; 56]. This phenomenon may be attributed to vegetation greenness changes slower than plant productivity over the season in forests, which limits the effectiveness of VIs in tracking photosynthetic activity. Additionally, as trees grow, the slight increase in greenness may cause the discrepancy between inter-annual variations in greenness and GPP (Figure 5b). Furthermore, forest ecosystems often have varying light conditions within the canopy, affecting photosynthetic rates differently in the upper and lower canopy layers. The greenness-productivity decoupling of forest ecosystems is likely driven by global and local factors, such as elevated CO\({}_{2}\) and changes in fire regime. Although decoupling relationships between greenness and productivity were evident in forests, the study by [PERSON] et al. (2022) demonstrated that this relationship was weaker in EBF rather than ENF [26]. This finding implies that relying solely on green products to assess changes in ecosystem carbon uptake in response to climatic variables can lead to uncertain evaluations, particularly in more hydric ecosystems. Compared with traditional enhanced vegetation index (EVI) and NDVI, solar-induced fluorescence (SIF) is more sensitive to drought-induced variations in canopy photosynthesis [57; 58].