## 5 Conclusions  
Based on the phenological seasonal scale, we exhibit vegetation dynamics in the upper and middle reaches of the Yellow River basin from 2000 to 2019, as well as immediate and lagged impacts of climate and vegetation growth carryover effects. The following conclusions are drawn: (1) From 2000 to 2019, the spatial distribution of mean NDVI, GPP, and LAI in the growing season exhibited a declining trend from southeast to northwest in the upper and middle reaches of the YRB. The vegetation coverage and productivity experienced a significant increase throughout the study area. (2) Significant positive correlations in the statistical analyses suggest that the vegetation carryover effect dominated the vegetation greening during the three active growing seasons, and this effect increased from early to late growing season. The concurrent season climate factors, especially precipitation, are also important drivers, followed by the climate of the preceding season. Sunshine duration, including its immediate and lagged impacts, always played a negative effect on vegetation growth. (3) As expected, the strongly observed greening trends of the three growing seasons were predominately attributed to the vegetation growth state of the preceding season. In addition, the vegetation growth carryover can be carried over to the subsequent year. This carryover in seasonal vegetation growth is conducive to the next stage of vegetation growth. Although the vegetation growth carryover effect can counteract the negative effects of climate factors, whether this growth carryover effect will still exist under future climate change still needs to be addressed in future research. The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/rs14195011/s1](https://www.mdpi.com/article/10.3390/rs14195011/s1)]([https://www.mdpi.com/article/10.3390/rs14195011/s1](https://www.mdpi.com/article/10.3390/rs14195011/s1)), Figure S1: Spatial distribution (a-c) and interannual variation rates (slope) (d-f) of mean precipitation (PRE), mean temperature (TEM), and mean sunshine duration (SSD) in growing season in the upper and middle reaches of the YRB over a 20-year period (2000-2019); Figure S2: The inter-annual variation rates (slope) of GPP (a) and LAI (b) in the growing season in the middle and upper of the YRB over a 20-year period (2000-2019). Black dots indicate statistically significant correlations at the 95% confidence level. Same below; Figure S3: The inter-annual variation rates (slope) of NDVI in three active seasons in the upper and middle reaches of the YRB over a 20-year period (2000-2019). The slopes patterns are shown for EGS (a), PGS (b) and LGS (c); Figure S4: Partial correlations between vegetation growth and that of its driving factors. This is same as Figure 3, except that vegetation growth is here based on GPP (a) and LAI (b); Figure S5: Spatial distribution of the partial correlations between GPP (a-c) or LAI (d-f) of each season and that of the preceding season. Correlation patterns are shown for EGS (a,d), PGS (b,e), and LGS (c,f); Figure S6: Spatial distribution of the partial correlations between GPP of each season and the concurrent climate factors. Correlation patterns are shown for EGS (a,d,g), PGS (b,e,h) and LGS (c,f,i), and for correlation with concurrent temperature (TEM) (a-c), precipitation (PRE) (d-f) and sunshine duration (SSD) (g-i); Figure S9: Spatial distribution of the partial correlations between LAI of each season and climate factors of the preceding season. Correlation patterns are shown for EGS (a,d,g), PGS (b,e,h) and LGS (c,f,i), and for correlation with preceding season temperature (TEM) (a-c), precipitation (PRE) (d-f) and sunshine duration (SSD) (g-i). Figure S8: Spatial distribution of the partial correlations between LAI of each season and the concurrent climate factors.