## 3 Results
### Plant Physiology, Not Phenology, Dominates GPP Variability  
GPPmax is considered the most reliable proxy for peak photosynthetic productivity and is closely related to plant physiology. CUP represents the duration of CO2 absorption by vegetation throughout the year and is closely related to plant phenology. Although the effects of plant phenology and physiology on the interannual variability of GPP are evident, the magnitude of their influence remains uncertain [3]. Previous studies in North America, at both the ecosystem and regional scales, have indicated that the long-term trend and interannual variability of GPP is regulated by GPPmax[4], yet this assertion has not been validated in China. In this study, prior to assessing the impact of plant phenology and physiology on interannual GPP, we conducted a comprehensive analysis of the temporal and spatial variations in GLASS GPPmax at both the 8-day and monthly scales. The standardized values of GPPmax over 8-day and monthly periods exhibited consistent trends, validating  
Figure 7: Interannual changes in the model and remotely sensed GPPmax for China’s terrestrial ecosystems from 1982 to 2018. (**a–c**) Annual GPPmax values of China’s terrestrial ecosystems; (**d**) average slopes of the long-term trends of GPPmax in China’s terrestrial ecosystems. the suitability of the GLASS \(\text{GPP}_{\text{max}}\) dataset for subsequent analyses at an 8-day temporal resolution (Figure 8). Next, we examined the spatial variation characteristics of 8-day \(\text{GPP}_{\text{max}}\) and observed a pronounced increase in China's terrestrial ecosystems' \(\text{GPP}_{\text{max}}\). The average inter-annual variability of \(\text{GPP}_{\text{max}}\) was 0.026 g C m\({}^{-2}\) year\({}^{-1}\), 0.018 g C m\({}^{-2}\) year\({}^{-1}\), and -0.04 g C m\({}^{-2}\) year\({}^{-1}\) for grassland, cropland, and forest, respectively. In particular, the increasing trend was evident in the grassland of the Loess Plateau, the grassland of Tibetan Plateau, and the cropland of North China Plain (Figure 9a), where the \(\text{GPP}_{\text{max}}\) growth rate exceeded 0.1 g C m\({}^{-2}\) year\({}^{-1}\) in most of these regions. This could be attributed to significant vegetation restoration projects on the Loess Plateau, gradual climate warming and humidification on the Tibetan Plateau, and agricultural expansion on the North China Plain, all contributing to a faster increase in \(\text{GPP}_{\text{max}}\) in these regions compared to others [33,34]. Upon comparing \(\text{GPP}_{\text{max}}\) changes over the past four decades, the emergence date of \(\text{GPP}_{\text{max}}\) in Chinese grassland, cropland, and forest has not significantly shifted, except for a slight delay in some Loess Plateau grassland and an earlier emergence in the grassland of Inner Mongolia and the forest of southern China (Figure 9b). In summary, 8-day \(\text{GPP}_{\text{max}}\) served as a reliable indicator of peak ecosystem productivity, allowing for the construction of stable metrics using GLASS \(\text{GPP}_{\text{max}}\) to assess the influence of plant physiology and phenology on interannual GPP in subsequent analyses. Interannual changes of GPP in Chinese grassland were primarily controlled by \(\text{GPP}_{\text{max}}\), with very limited influence (less than 1%) from CUP (Figure 10a). This indicated that the grassland ecosystems rely more on climatic factors such as precipitation and temperature, while their capacity to utilize soil moisture and nutrients remains relatively stable. For cropland, GPP changes were predominantly influenced by \(\text{GPP}_{\text{max}}\), with 8% of interannual GPP changes attributed to CUP, mainly in the North China Plain (Figure 10b).