# Climate, CO2, and Anthropogenic Drivers of Accelerated Vegetation Greening in the Haihe River Basin
## 4 Discussion  
### Causes of NDVI Change  
Climate is generally identified as an important natural factor that influences vegetation growth [51]. [PERSON] et al. [22] used the SPOT NDVI dataset to investigate the characteristics of variations in vegetation and assess the impacts of climate change (air temperature and precipitation) and human activities (afforestation area and urbanization) on vegetation cover change in the Haile River Basin from 2000 to 2013. However, they did not quantify the contribution of human activities and conjectured that the change in NDVI was primarily attributed to the increase in precipitation. Similarly, [PERSON] et al. [31] applied multiple regression models to predict the NDVI of Beijing-Tianjin-Hebei provinces in China, based on climatic factors, during the growing season from 2000 to 2017, and admitted the dominant position of precipitation and temperature for vegetation growth. However, because climate factors and human activities are highly blended, precipitation and air temperature do not always provide a decisive explanation on NDVI change. In our study, the positive effects of precipitation on NDVI trends were displayed in the north-western area (Figure 6a). The negative contributions in the south-western area covered by croplands were relatively minor. It may be caused by irrigation activities that disturb natural response of precipitation-soil moisture, creating a low negative contribution of precipitation to the NDVI. Therefore, the causes of NDVI changes are complicated [52]. Some studies have shown that socioeconomic activities were important for vegetation greenness. [PERSON] et al. [20] investigated the impacts of climate (temperature and precipitation) and human activities (population, GDP, and forestry investments) on vegetation variations using the geodetector method. They discovered that socioeconomic factors were the dominant driving forces of vegetation change for the typical areas in China. [PERSON] et al. [53]  
Figure 8: Future normalized difference vegetation index (NDVI) simulations from CMIP6 scenarios (SSP126, SSP245 and SSP585). Black solid line after 2020 indicates the mean value of NDVI in different models. The gray shaded area indicates the range of NDVI in the scenario. analyzed vegetation change in China during 2000-2010 under the driving forces of climate and socioeconomic factors using linear regression. The results showed that the most significant elements for vegetation change were socioeconomic factors (human population and economic production). In this study, we found that anthropogenic drivers reflected by NTL have the spatial variation. There was a negative contribution to NDVI in the south-eastern area and a positive contribution in the north-western area. The negative impact was attributed to urban expansion and industrialization, which is consistent with the general understanding. However, the positive impact on rural areas located in the north-western area indicated that some human activities boosted ecosystem functions for those areas. [PERSON] et al. [54] pointed out that urbanization development would be favorable to vegetation growth when the NTL value was lower than 15, which coincided with Figure S1f in our study. We also found that the effect of urbanization on vegetation coverage was positive when the NTL value was higher than 55, such as in the north-west of Beijing and the surroundings of Tianjin in our study. This phenomenon can be explained by [PERSON] et al. [55]: when a city attained a certain development level, people were willing to devote more resources and efforts to improving vegetation coverage and climate for a better living environment [56].