## 4 Discussion  
### Effects of Vegetation on CUE  
The results of our study are consistent with the observations of [PERSON] and [PERSON] [22], particularly with regard to CUE trends in relation to latitude and longitude. Their study described an initial increase in CUE, followed by a decrease with increasing latitude. There was also a decreasing trend in CUE from west to east over the entire longitude. The results of our study have been corroborated by global studies looking at how CUE varies. It is nevertheless essential to acknowledge that a number of variables are involved in the formation of CUE. These include longitude, latitude, altitude, climatic conditions, the status of vegetation growth, and specific vegetation types, among other factors. The relationship between vegetation CUE and its growth status is of significant consequence. The analysis of key metrics, including GPP, NPP, autotrophic respiration, LAI, and NDVI, provides invaluable insights into the state of vegetation growth. A nuanced understanding of the temporal trajectories and spatial distributions of these ecosystems enhances our comprehension of the carbon dynamics that occur within them. Our research revealed an intriguing pattern, whereby the spatial distribution of LAI is closely aligned with that of autotrophic respiration. This observation indicates the possibility of a correlation between plant autotrophic respiration and LAI. As illustrated in Figure 5, there is a positive correlation between LAI and GPP of vegetation. Nevertheless, the CUE is observed to decline as the LAI increases. This indicated that an increase in leaf area necessitated greater energy input to sustain essential plant life activities. This was particularly the case in alpine regions, where the higher energy demands of vegetation resulted in a reduction in CUE. Previous studies have shown that plant autotrophic respiration is related to biomass. In China, regions situated at high altitudes display a higher mass-specific respiration rate in comparison to other regions. This finding may provide an explanation for the negative correlation between LAI and CUE observed in the Three Rivers Source Region [34]. Figure 9: Contribution of climate change and ecological engineering to CUE. (**a**) A map showing the spatial distribution of human contribution to CUE; (**b**) A map showing the spatial distribution of key factors leading to CUE changes. The diverse characteristics inherent to different vegetation types, including variations in light energy absorption, water utilization efficiency, nutrient uptake, growth cycles, and phenological attributes, contribute to distinct CUE under varying climatic regimes [45; 46; 47]. Our findings highlighted the significant impact of vegetation types on CUE variations. The CUE efficiency was found to decline in the following descending order: alpine vegetation, steppes, meadows, and scrubs. The eastern and southern sectors of the Three Rivers Source region are predominantly characterized by meadows and scrubs, with meadows being notably widespread. A nuanced spatial heterogeneity was observed in the south-eastern Three Rivers Source region, where meadows exhibited negative correlations with temperature, precipitation, and evapotranspiration. In contrast, the data from the north-western regions indicated a positive correlation. The data indicated that shrubs in the northern Three Rivers Source region exhibited positive correlations with temperature, precipitation, and evapotranspiration. In contrast, their southern counterparts demonstrated consistent negative correlations. The steppes, concentrated in the northern expanse of the Three Rivers Source region, exhibited a gradient of correlations. In particular, the correlations between temperature and precipitation exhibited a notable shift from positive in the western regions to negative in the eastern zones. Moreover, the correlation between steppes and precipitation exhibited a shift from a positive association in the northern regions to a negative one in the southern areas.