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Since the launch of the Grain for Green (GFG) program in 1999, the Loess Plateau has undergone significant vegetation changes. However, the driving mechanisms behind these changes in the post-GFG period remain insufficiently understood. This study analyzes the spatiotemporal dynamics of vegetation on the Loess Plateau from 1982 to 2015, based on long-term NDVI time series, and quantitatively identifies the relative contributions of climate variability and human activities using partial correlation and multiple regression residual analysis. The results reveal a significant increase in NDVI after 2000, with the annual variation rate rising from 0.0009 to 0.0028, and the proportion of rapidly greening areas expanding from 13.3% to 62.9%. Spatially, vegetation recovery was more prominent in the eastern and lower-latitude regions. While both climate and anthropogenic factors influenced vegetation changes, the latter became dominant after 2000. The area where human activities significantly enhanced vegetation increased from 1.9% to 60.6%, with the most notable improvements observed in forests, followed by croplands and grasslands. Vegetation in the southern plateau was more sensitive to temperature, while the northern region responded more strongly to precipitation. From 2000 to 2015, the GFG program contributed to increases of 17,059.46 km2 in grasslands and 10,105.78 km2 in forests. These findings improve our understanding of vegetation change drivers on the Loess Plateau and offer a scientific basis for ecological restoration, policy-making, and sustainable development in the Yellow River Basin.

The Qinling Mountains, located at the junction of warm temperate and subtropical zones, serve as the boundary between north and south China. Exploring the sensitivity of the response of vegetation there to hydrothermal dynamics elucidates the dynamics and mechanisms of the main vegetation types in the context of changes in temperature and moisture. Importance should be attached to changes in vegetation in different climate zones. To reveal the sensitivity and areal differentiation of vegetation responses to hydrothermal dynamics, the spatio-temporal variation characteristics of the normalized vegetation index (NDVI) and the standardized precipitation evapotranspiration index (SPEI) on the northern and southern slopes of the Qinling Mountains from 2000 to 2018 are explored using the meteorological data of 32 meteorological stations and the MODIS NDVI datasets. The results show that: 1) The overall vegetation coverage of the Qinling Mountains improved significantly from 2000 to 2018. The NDVI rise rate and area ratio on the southern slope were higher than those on the northern slope, and the vegetation on the southern slope improved more than that on the northern slope. The Qinling Mountains showed an insignificant humidification trend. The humidification rate and humidification area of the northern slope were greater than those on the southern slope. 2) Vegetation on the northern slope of the Qinling Mountains was more sensitive to hydrothermal dynamics than that on the southern slope. Vegetation was most sensitive to hydrothermal dynamics from March to June on the northern slope, and from March to May (spring) on the southern slope. The vegetation on the northern and southern slopes was mainly affected by hydrothermal dynamics on a scale of 3–7 months, responding weakly to responding weakly to hydrothermal dynamics on a scale of 11–12 months. 3) Some 90.34% of NDVI and SPEI was positively correlated in the Qinling Mountains. Spring humidification in most parts of the study area promoted the growth of vegetation all the year round. The sensitivity of vegetation responses to hydrothermal dynamics with increasing altitude increased first and then decreased. Elevations of 800 to 1200 m were the most sensitive range for vegetation response to hydrothermal dynamics. The sensitivity of the vegetation response at elevations of 1200–3000 m decreased with increasing altitude. As regards to vegetation type, grass was most sensitive to hydrothermal dynamics on both the northern and southern slopes of the Qinling Mountains; but most other vegetation types on the northern slope were more sensitive to hydrothermal dynamics than those on the southern slope.

Based on air temperature observation data from 32 meteorological stations, temperature changes in the middle Qinling Mountains from 1959 to 2016 were analysed with respect to the north-south, seasonal and altitude differences. Our research mainly showed the following results. The annual temperature (TA) rose approximately 0.26°C/10a within the past 58 years. This warming trend was stronger on the northern slope than on the southern slope, and a warming trend reversal occurred in 1994 on the northern slope, which was three years earlier than on the southern slope. The temperature changes for the four seasons were not synchronized, and the trend in spring contributed the most to the TA trend, followed by winter, autumn, and summer. The temperature difference between summer and winter (TDSW) decreased significantly over the past 58 years. The temperature change in the middle Qinling Mountains was clearly dependent on altitude. With increases in altitude, the TA increased gradually and became stronger while the TDSW decreased gradually and became weaker. Differences in temperature change between the north and south were mainly observed in low-altitude areas. With increase in altitude, the differences gradually tended to disappear.