## 3 Results
### Response of Vegetation to Climatic Conditions at Regional Scale  
The linear regression analysis between the NDVI and NPP and the annual precipitation and annual average temperature indicated a highly significant positive correlation between NDVI and annual precipitation and between NPP and annual average temperature in the Sanjiangyuan National Park (Table 4, Figures 9 and 10).  
The correlation coefficient of NDVI and annual precipitation was 0.6729 (\(p=0.0031\)), and the Yangtze River headwater region had the highest correlation coefficient of 0.6849 (\(p=0.0024\)).  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{2}{c}{**NDVI**} & \multicolumn{2}{c}{**NPP**} \\ \cline{2-5}
**Region** & **Annual** & **Annual Average** & **Annual** & **Annual Average** \\  & **Precipitation** & **Temperature** & **Precipitation** & **Temperature** \\ \hline Yellow River & 0.6281 *** & 0.2554 & 0.4828 ** & 0.4610 * \\ Lancang River & 0.5210 ** & 0.1930 & 0.0802 & 0.5137 ** \\ Yangtze River & 0.6849 *** & 0.3569 & 0.3925 & 0.5350 ** \\ Sanjiangyuan & 0.6729 *** & 0.3392 & 0.3526 & 0.5396 ** \\ \hline \hline \end{tabular}  
* *, **, and *** represent 0.05 \(<p\leq\) 0.1, 0.01 \(<p\leq\) 0.05, and \(p\leq\) 0.01, respectively.  
\end{table}
Table 4: NDVI-precipitation, NDVI-temperature, NPP–precipitation, and NPP–temperature correlation coefficients.  
Figure 9: Scatter plot of NDVI–annual precipitation for the Sanjiangyuan National Park (**a**), the Yellow River headwater region (**b**), the Yangtze River headwater region (**c**), and the Lancang River headwater region (**d**).  
The correlation coefficient of NPP and annual average temperature was 0.5396 (\(p=0.0254\)), and the Yangtze River headwater region had the highest correlation coefficient of 0.5350 (\(p=0.0625\)).  
There was no significant correlation between NDVI and annual average temperature in all three parks, and no significant correlation between NPP and annual precipitation in the Yangtze and Lancang Rivers. However, a positive correlation between NPP and annual precipitation was detected in the Yellow River (\(R=0.4828\), \(p=0.05\)).  
The response of vegetation to climatic conditions indicated a highly significant positive correlation between NDVI and annual precipitation among all vegetation types, especially in the meadow and prairie (Table 5). The correlation coefficient of NDVI and annual precipitation was 0.6930 (\(p=0.0020\)) for the meadow and 0.6105 (\(p=0.0092\)) for the prairie. A significant positive correlation between NDVI and annual average temperature was also detected in the prairie, shrub, and alpine types, with correlation coefficients of 0.4671 (\(p=0.0587\)), 0.4417 (\(p=0.0759\)), and 0.4221 (\(p=0.0915\)), respectively. In addition, the unilateral significance test of the influence of the average annual temperature on NDVI passed the 95% confidence level. However, no significant relationships between NDVI and annual average temperature were detected in the meadow and coniferous forest. Furthermore, a highly significant positive correlation between NPP and annual average temperature were also detected among all vegetation types, but there were no significant relationships between NPP and annual precipitation.  
Figure 10: Scatter Plot of NPP–annual average temperature for the Sanjiangyuan National Park (**a**), the Yellow River headwater region (**b**), the Yangtze River headwater region (**c**), and the Lancang River headwater region (**d**).