# The Response of Vegetation Dynamics to Climate in Xinjiang from 1991 to 2018
## 3 Results
### The Response of Vegetation to Climate Change
#### 3.3.2 The Correlation Between Vegetation and Precipitation  
Figure 9 illustrated the correlations between NDVI, LAI, GPP, and precipitation, revealing significant spatial heterogeneity in the relationships between these indices and precipitation. The proportions of positive and negative correlations varied significantly across the different indices. The proportions of positive and negative correlations between NDVI and precipitation were nearly equal, at 50.3% and 49.8%, respectively. However, regions with positive correlations were mainly located in northern Xinjiang, particularly in the southern Altai Mountains, the northwestern Junggar Basin, the Ili River Valley, and parts of northern Tianshan, with correlation coefficients greater than 0.4. In southern Xinjiang, negative correlation areas dominated, mostly located in basins and high-altitude regions of the Kunlun Mountains. Precipitation in high-altitude mountainous areas mainly fell as snow, which was unfavorable for vegetation growth; thus, regions with correlation coefficients below \(-0.4\) were concentrated in the Kunlun Mountains. Positive correlation areas in southern Xinjiang were mainly concentrated around the Tarim Basin and the southern Tianshan, where land types were predominantly cropland and grassland. These regions received ample sunlight, and increased precipitation promoted the growth of crops and herbaceous plants. Compared to NDVI, LAI had a higher proportion of positive correlations with precipitation, reaching 85.5%. Of this, 17.5% of the correlations had a coefficient greater than 0.4. Positive correlation areas were mainly distributed in mountainous regions and around basins, especially in the northwestern Junggar Basin and Ili River Valley, where the correlation coefficient exceeded 0.6. The predominant land type in these regions was grassland. Negative correlation areas were mainly located in regions where precipitation  
Figure 8: Annual characteristics of spatial distribution (**a**) and trend (**b**) of precipitation from 1991 to 2018.  
was decreasing, whereas in most areas with increasing precipitation, the correlation was positive. The areas where correlation between LAI and precipitation exceeded 0.4 were similar to the regions where NDVI presented a positive correlation in northern Xinjiang. However, the proportion for NDVI exceeding 0.4 in this region was only 5.3%. While both indices led to the same conclusion, that precipitation promoted vegetation growth, the specific correlation coefficients and distribution of correlations differed notably. The correlation between GPP and precipitation was also primarily positive, accounting for 74.3%. Among them, 4.2% of the correlations had a coefficient greater than 0.4. Compared to NDVI and LAI, GPP showed a weaker correlation with precipitation, with most regions having correlation coefficients between \(-0.4\) and 0.4, accounting for 95.5%. The spatial distribution of correlations was less distinct for GPP compared to the other two indices, showing an interwoven pattern of positive and negative correlations. There was a negative correlation in areas with high precipitation, which may be due to cloud cover blocking sunlight during rainfall and lowering environmental temperatures at that time, which hindered plants from photosynthesis. However, this should be analyzed in conjunction with temperature variations. Compared to the other two vegetation indices, the impact of precipitation on GPP was smaller than its effect on NDVI and LAI. Using NDVI, LAI, and GPP as reference indices, the vegetation in the study area exhibited significant spatial heterogeneity, with the greening trend in northern Xinjiang being stronger than in southern Xinjiang. This spatial pattern may be attributed to differences in precipitation availability, as northern Xinjiang received more water resources, particularly in mountainous areas like the Tianshan and Altai ranges, which enhanced vegetation productivity.