# Decoupling the Impacts of Climate Change and Human Activities on Terrestrial Vegetation Carbon Sink
## 3 Results
### Relative Contributions of CC and HA to NEP Dynamics  
As shown in Figure 8, about 66.02% of the study area showed that the combined effects of CC and HA were the driving factor for the increase in NEP, which is widely distributed within the study area; about 4.28% of the area showed an increase in NEP due to CC alone, which was mainly in the southern part of the Beijing-Tianjin-Hebei region; and about 5.31% of the area showed an increase in NEP due to HA alone, which was mainly distributed in the immediate periphery of the core areas of major cities in the northern provinces. In addition, about 12.82% of the area showed that CC and HA were both reasons for the decrease in NEP, which was mainly concentrated in distribution in Shanghai and the provinces south of Zhejiang, while about 2.82% and 8.76% of the area exhibited a decrease in NEP due to CC and HA, respectively, and the distribution was relatively dispersed. In general, CC and HA are the main reasons for the changes in NEP in CCZ over the past 21 years. As shown in Table 3, the dominant driver types of NEP among the provinces in CCZ similarly exhibit an obvious north-south difference. NEP changes in provinces north of Zhejiang are mainly characterized by a double-driven improvement. On the contrary, one-factor-induced degradation of NEP is mainly observed in provinces south of Zhejiang. Specifically, the human-driven degradation of NEP mainly occurred in Fujian, Shanghai,  
Figure 7: Partial correlation coefficients of NEP and meteorological factors: (**a**) NEP-Temperature; (**b**) NET-Precipitation. and Hong Kong. NEP in Taiwan is mainly characterized by climate-induced degradation, and NEP in Hainan mainly exhibited a double-driven degradation change. To distinguish differences in the contributions of CC and HA to the changes in NEP, we analyzed the variation trend of NEP predictions and NEP residual values. The results showed that the area where CC positively affected NEP accounted for 78.13% of the total area. In comparison, only 21.87% of the area was adversely affected. NEP was positively affected by HA in 72.28% of the total area. In the remaining 26.72% of the areas, HA harmed NEP. As shown in Figure 9, the average contribution rate of CC is 35.76%, which is less than that of HA (64.24%). The contribution rate of CC less than 40% occupied about 63% of the total area, in which the contribution rate within the ranges of 0-20% and 20-40% \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Province**} & \multicolumn{4}{c}{**Mean Slope**} & \multicolumn{2}{c}{**Dominant Driver Type**} \\ \cline{2-6}  & **NEP\({}_{\text{obs}}\)** & **NEP\({}_{\text{CC}}\)** & **NEP\({}_{\text{HA}}\)** & \\ \hline Beijing & 7.33 & 3.05 & 4.28 & double-driven improvement \\ \hline Hebei & 5.57 & 2.39 & 3.18 & double-driven improvement \\ \hline Shandong & 4.38 & 1.45 & 2.93 & double-driven improvement \\ \hline Tianjin & 4.06 & 2.65 & 1.41 & double-driven improvement \\ \hline Jiangsu & 2.59 & 0.9 & 1.69 & double-driven improvement \\ \hline Guangxi & 2.57 & 0.77 & 1.8 & double-driven improvement \\ \hline Liaoning & 2.53 & 1.05 & 1.48 & double-driven improvement \\ \hline Zhejiang & 1.69 & 0.79 & 0.9 & double-driven improvement \\ \hline Guangdong & 1.01 & 0.67 & 0.34 & double-driven improvement \\ \hline Fujian & \(-\)0.19 & 0.86 & \(-\)1.06 & human-driven degradation \\ \hline Shanghai & \(-\)0.23 & 0.36 & \(-\)0.59 & human-driven degradation \\ \hline Taiwan & \(-\)0.43 & \(-\)0.76 & 0.32 & climate-driven degradation \\ \hline Hong Kong & \(-\)0.53 & 0.34 & \(-\)0.9 & human-driven degradation \\ \hline Hainan & \(-\)0.88 & \(-\)0.22 & \(-\)0.65 & double-driven degradation \\ \hline \hline \end{tabular} \(\text{NEP}_{\text{obs}}\): NEP observations; NEP\({}_{\text{CC}}\): NEP predictions; NEP\({}_{\text{HA}}\): NEP residual values.  
\end{table} 
Table 3: Average trend and dominant drivers of NEP changes in main provincial-level regions. Figure 8: Spatial distribution of NEP driver types and their area proportion. occupied about 31% of the total area.