# Climate, CO2, and Anthropogenic Drivers of Accelerated Vegetation Greening in the Haihe River Basin
## 3 Results
### Contribution of CLI, HUM, and CO\({}_{2}\)  
The contributions of the six driving variables to the changes in the annual NDVI were estimated by equation using Equation (4). The actual contributions of CLI, HUM, and CO\({}_{2}\) to variations in NDVI exhibited remarkable spatial heterogeneity (Figure 6A-C). The contribution of CLI ranged from \(-\)20% to 85% and was larger in the surrounding areas of Tianjin. The positive effects of Pre on NDVI trends were displayed in Beijing, the western part of Hebei Province, northern part of Shanxi Province, and the Inner Mongolian province (Figure 6a). The positive contribution of Pre to NDVI trends was largest in the Inner Mongolian province, with a value of \(>\)25%, and the negative contributions were relatively minor, with a value around \(-\)10% in the south-eastern area. Croplands cover a substantial portion of the south-eastern region, which had a negative influence. Because of irrigation activities, the natural response of precipitation-soil moisture is disturbed, and the water stress is mitigated, thus creating a low negative contribution of precipitation to the NDVI. Generally, the contribution of Tem to NDVI trends ranged from \(-\)40% to 65%, with a mean of 9.26% (Figure 6b). Approximately three-quarters (76.12%) of the study area located in the south-eastern area, exhibited a positive contribution, especially in Tianjin, Shijiazhuang in Hebei Province, and Anyang city in Henan Province (>50%). The negative effects of Tem on NDVI trends appeared in most areas of the north-western region, particularly in Baoding and Tangshan in Hebei Province (<\(-\)10%). Additionally, the mean contribution of Rad to the NDVI trends was 3.17% (Figure 6c). Over 60% of the areas showed a positive contribution, with a maximum value of 45.24%. Relatively large negative contributions (<\(-\)5%) were observed in the southern and central parts of the entire region. Figure 4: Interannual linear trends of (**a**) precipitation rate, Pre; (**b**) 2-m air temperature, Tem; (**c**) downward shortwave radiation, Rad; (**d**) area of aforestation (AAF); (**e**) nighttime light (NTL); and (**f**) CO\({}_{2}\) from 2002 to 2018. Significant trends indicate \(p\)-value ¡ 0.05. The histogram in each panel shows the frequency of various trends, and the negative/positive values represent the decreased/increased trends. White color means no data in this county. The contribution of HUM showed a large variability, ranging from \(-55\%\) to \(86\%\). Due to the greater impact of afforestation, HUM was larger in mountainous areas than in plain areas, and it presented a negative effect in plain areas that were primarily controlled by NTL. Afforestation was regarded as a factor, which exerted a greater influence on NDVI in the form of land-use management. In the forested area, the impact of AAF on NDVI presents a positive contribution, with a range of 0-72% (Figure 6d). More than 20% of the counties located in the mountains area had contributions above 40%. The relatively high contributions mainly follow the direction of the mountains, indicating the essential role of vegetation restoration in NDVI changes in the mountainous regions. Moreover, a part of the effect of human activities on NDVI reflected by NTL showed obvious spatial diversity, resulting from the different levels of urbanization and industrialization (Figure 6e). Cangzhou, Hengshui, and Shijiazhuang of Hebei Province as well as Wulan and Chifeng in the Inner Mongolian province had a positive effect that exceeded 50%. Likewise, nearly 40% of the places concentrated on the plain showed negative individual contribution. The largest effect could reach \(-55\%\) in the Shijiazhuang's Yuhua district. The impact of elevated CO\({}_{2}\) concentration on the NDVI was almost positive across the whole region, with an average contribution of 46% (Figure 6C). In mountainous areas, located in the northeast region, the majority of contributions were less than 35%.