## 3 Results and Discussions
### Impact of Meteorological Factors on Vegetation GPP  
The variation of the vegetation GPP of the forest is the outcome of the coupling influence of various factors including climate change, natural disasters and human disturbance. The changes in surface meteorological factors will inevitably affect the forest to a certain extent; the influence of temperature and precipitation on vegetation GPP is especially more significant. In this study, the impact of temperature and precipitation on vegetation GPP in different parts of the mountain were analyzed by comparing the correlation coefficient, which indicates the strength of relevance between them. Since the annual GPP and growing season GPP showed a similar distribution pattern, as mentioned above, the relationship between the annual average GPP in different parts of the mountain and meteorological factors were examined by using correlation analysis. However, the correlation between two independent variables, temperature and precipitation, was not considered because this was not relevant to our study. Temperature is the determining factor for the growth and development of vegetation. The stronger the impact of temperature on the vegetation GPP, the greater the correlation coefficient between them (Figure 7a). Figure 6: Variation rate of GPP in the Alday Mountains. It can be seen from Figure 7a that vegetation GPP is positively correlated with the annual average temperature, with a mean correlation coefficient of 0.19. The area with positive correlations accounted for 64.85% of the whole, with a mean value of 0.29--this showed a wide distribution but was more intensive in the middle-altitude area of the southern slope of the Altay Mountains. The area with a correlation coefficient of 0-0.2 accounts for 30.23%, the area with a correlation coefficient of 0.2-0.4 accounts for 10.48%. However, in 35.15% of the study area, the correlation coefficient between temperature and the vegetation GPP has a negative value. The area with a correlation coefficient of \(-\)0.2-0 accounts for 13.2%. The areas with a negative correlation coefficient were mainly distributed in the north and southeast parts of the mountain with a lower altitude. Similarly, precipitation also plays an essential role in vegetation GPP. It can be seen from Figure 7b that a GPP of 71.61% of the Altay Mountain area is positively correlated with the annual average precipitation, with a mean correlation coefficient of 0.39. Regarding the distribution of the area, it has a similar distribution pattern to temperature but a relatively wider distribution of the positively correlated areas. The areas with a correlation coefficient of 0-0.2, 0.2-0.4 and 0.4-0.6 account for 16.49%, 16.07% and 13.39%. However, a vegetation GPP of 28.39% of the study area is negatively correlated with the annual average precipitation, of which most were located in the north part of the mountain with a higher altitude. Overall, the result of the correlation analysis indicates a strong linkage between temperature and precipitation with vegetation GPP in the study area. An increase in these variables will likely increase the vegetation productivity. This study's outcome aligns with some previous studies that established a connection between vegetation productivity and meteorological factors. [PERSON] et al. analyzed the influence of temperature and precipitation on forest ecosystems in the vegetation growing season in the Qilian Mountains of northwestern China, and found a significant interaction between temperature and precipitation, contributing up to 30% of total variability in the predicted ecosystem level in the vegetation growing season [46]. Meteorological factors determine the growth and development of vegetation in the Altay Mountains. Conversely, because the forest ecosystem is a huge carbon pool, it acts as a source or sink of CO\({}_{2}\) in the atmosphere, thus, further strengthening or offsetting future climate change. [PERSON] et al.