## 3 Results
### Time-Variant Response of Vegetation Dynamics to Climate Changes  
Section 3.2 only explores the time-invariant vegetation sensitivity in response to the three climate factors; the temporal variability of the vegetation sensitivity could not be determined. This section focuses on the time-variant vegetation sensitivity with a view to investigating the spatial patterns of its temporal trends (Figure 7), the trend values classified by land-cover types (Figure 8), the impact directions indicated by the signs of regression coefficients (Figure 9), and associated dominant climate factors (Figure 10). Overall, Figure 7 illustrates that the spatial patterns were similar for the trend values of vegetation sensitivity in response to the three climatic factors, as indicated by the LAI, EVI, NDVI, and SIF data. The vegetation sensitivity displayed a significant upward  
Figure 7: Spatial distribution of trend values for vegetation dynamics in response to solar radiation (the first column), temperature (the second column), and water availability (the third column) based on the (**a1–a3**) LAI, (**b1–b3**) EVI, (**c1–c3**) NDVI, and (**d1–d3**) SIF products. trend in response to solar radiation in eastern and parts of southern areas of the QTP, while a significant downward trend in central areas of the QTP was observed. Vegetation sensitivity in response to temperature exhibited a significant downward trend in the central to northeastern QTP. Conversely, pixels with an upward trend were sparsely distributed in other regions and did not yield explicit spatial patterns. Compared with temperature and solar radiation, vegetation exhibited a much lower trend regarding the sensitivity in response to water availability, as most of the associated trend values were in a range from \(-\)0.005 to 0.005. Nevertheless, trend values of water availability were noticeable in the southwestern QTP, as trend values of associated pixels were typically \(>\)0.05 or \(<\)\(-\)0.05. Figure 8: Boxplots of trend values for the vegetation proxies, i.e., SIF (blue), NDVI (orange), EVI (yellow), and LAI (green), in response to (**a**) solar radiation, (**b**) temperature, and (**c**) water availability. The trend values are further classified by BSVs, grasslands, and forests. Associated mean and median values are shown in the right-hand table next to each subfigure. Cases with an opposite performance, i.e., an opposite trend identified by the mean and median values, are highlighted with red coloring in the table. Figure 9: Percentage values of positive and negative regression coefficients derived from LAI, EVI, NDVI, and SIF data for the interannual vegetation sensitivity in response to (**a**) solar radiation, (**b**) temperature, and (**c**) water availability. The boxplots in Figure 8 demonstrate that the trend of vegetation sensitivity in response to the three climatic factors was generally consistent for the four vegetation proxies when considering different land-cover types. As indicated by all four vegetation proxies, vegetation sensitivity in response to temperature gradually decreased over the recent two decades in BSVs, grasslands, and forests, as the associated means and medians of the trend values were <0 (Figure 8b). Such decreasing trends were more pronounced in grasslands than in BSVs and forests. Except for the LAI case, shown in Figure 8a, vegetation sensitivity in response to solar radiation experienced a decreasing trend for BSVs and grasslands. By contrast, an increasing sensitivity was found for forests areas, except for the EVI case. For water availability, as shown in Figure 8c, only the forest cases indicated by SIF data yielded a contrasting trend, i.e., mean and median metrics indicated different trend directions, when compared with the other three proxies. BSVs and forests showed increasing trends, while no obvious trend could be determined for the grasslands, as corresponding mean and median values were typically small and indicated different directions.