Alpine timberline is a great place for monitoring climate change. The study of alpine and subalpine timberline in Qinling Mountains has led to early warning that reveals the response and adaptation of terrestrial vegetation ecosystem to climate change. Based on the remote sensing image classification method, the typical timberline area in Qinling Mountains was determined. Temperature and normalized difference vegetation index (NDVI) data were extracted from the typical timberline area based on spatial interpolation and NDVI data. The relationship between NDVI and temperature change and the critical temperature value affecting vegetation response in the timberline area in Qinling Mountains were analyzed. Correlation between NDVI and air temperature in the alpine and subalpine timberline areas of Qinling Mountains exhibited an upward trend, which implied that temperature promotes vegetation activity. A strong correlation between temperature and NDVI in typical timberline areas of Qinling Mountains, and a significant correlation between temperature and NDVI in the early growing season. A phenomenon of NDVI lagging behind air temperature was observed. Temperature response showed synchronization and hysteresis. The correlation between cumulative temperature and vegetation was similar between Taibai Mountain and Niubeiliang timberline, and the correlation between NDVI in April and cumulative temperature in the first 12 months was the strongest. Temperature threshold range of Taibai Mountain timberline played a dominant role in vegetation growth. Our results provide insights and basis for future studies of early warning signs of climate change, specifically between 0.34 and 1.34 °C. The threshold ranges of temperature response of different vegetation types vary. Compared with alpine shrub meadow, the threshold ranges of temperature effect of Coniferous forest and Larix chinensis Beissn. are smaller, implying that these vegetation types are more sensitive to temperature change.

Under the dual influence of climate change and land-use change, different protection policies in Qinling Mountains lead to different hydrological responses. On the basis of land-use and climatic changes in the Qinling Mountains of Shaanxi province, we constructed a response model among land use, climate, and runoff in the Qinling Mountains through the Soil and Water Assessment Tool (SWAT) model. The Patch-generating Land Use Simulation (PLUS) model was used to predict and simulate land-use types of the Qinling Mountains in 2025 and 2030. On the basis of the current ecological protection policy in China, two scenarios of land use were set up to find the best method for forestland protection. The results show the following. The SWAT model is applicable to the Weihe River and Hanjiang River basins of the Qinling Mountains, the simulation results were verified, and the Nash coefficient was above 0.6. Under future climate change and land-use patterns, runoff in the Qinling Mountains watershed shows an upward trend, and the runoff in the Hanjiang River basin increased by more than that in the Weihe River basin, with change rates of 47.471 and 33.356 m³/10a, respectively. According to the future trend of the two different scenarios, the increase degree of runoff in the natural scenario of Weihe River basin was 16.567 m³/10a higher than that in the woodland scenario, and the increase degree of runoff in the Hanjiang River basin was 17.692 m³/10a higher than that in the woodland scenario. Therefore, blindly increasing the forestland area in Qinling Mountains cannot achieve a better hydrological effect.

Due to the fragility of the habitats in mountain nature reserves, the vegetation is extremely sensitive to climate change, and its phenological changes are more specific. Therefore, it is of great significance to study the effects of topography and climate on the vegetation phenology in mountain nature reserves. Based on the vegetation phenology data retrieved from MODIS EVI2 during 2000 to 2017, combined with temperature data, spatial trend analysis and correlation analysis methods were used to study the effects of topographic and climatic factors on vegetation phenology in the Niubeiliang Nature Reserve of the Qinling Mountains. The results showed that the GSS (growing season start) was advanced with a rate of 4.24 days/10a, and the rates in the northern and southern slopes were almost the same; the GSE (growing season end) was delayed with a rate of 3.29 days/10a, and the rate in the northern slope was faster; and the GSL (growing season length) was prolonged. There were seasonal differences and north–south differences in the effects of topography on the phenophase. The phenophase changed regularly with the increase in altitude. The higher the altitude, the more significant the effect. The steeper the slope, the later the GSS, the earlier the GSE, and the more significant its effect on the GSE. The aspect had little effect on GSS but a more significant effect on GSE, which was the latest on the sunny slope and the earliest on the zero slope. Temperature affected both the GSS advance and the GSE delay, and both had a time-lag effect of approximately 2–3 months. Its effect was more significant in the GSE, in the southern slopes, and in the high-altitude areas.