Dynamic Variation of Vegetation NPP and Its Driving Forces in the Yellow River Basin, China

The productivity of vegetation is influenced by both climate change and human activities. Understanding the specific contributions of these influencing factors is crucial for ecological conservation and regional sustainability. This study utilized a combination of multi-source data to examine the spatiotemporal patterns of Net Primary Productivity(NPP) in the Yellow River Basin(YRB), China from 1982 to 2020. Additionally, a scenario-based approach was employed to compare Potential NPP(PNPP) with Actual NPP(ANPP)to determine the relative roles of climatic and human factors in NPP changes. The PNPP was estimated using the Lund-Potsdam-Jena General Ecosystem Simulator(LPJ-GUESS) model, while ANPP was evaluated by the Carnegie-Ames-Stanford Approach(CASA)model using different NDVI data sources. Both model simulations revealed that significant greening occurring in the YRB, with a gradual decrease observed from southeast to northwest. According to the LPJ＿GUESS model simulations, areas experiencing an increasing trend in NPP accounted for 86.82% of the YRB. When using GIMMS and MODIS NDVI data with CASA model simulations, areas showing an increasing trend in NPP accounted for 71.42% and 97.02%, respectively. Furthermore, both climatic conditions and human factors had positive effects on vegetation restoration; approximated 41.15% of restored vegetation areas were influenced by both climate variation and human activities, while around 31.93% were solely affected by climate variation. However, it was found that human activities served as the principal driving force of vegetation degradation within the YRB, impacting 26.35% of degraded areas solely due to human activities. Therefore, effective management strategies encompassing both human activities and climate change adaptation are imperative for facilitating vegetation restoration within this region. These findings will valuable for enhancing our understanding in NPP changes and its underlying factors, thereby contributing to improved ecological management and the pursuit of regional carbon neutrality in China.