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The Qinling Mountains (Qinling Mts.) are characterized as a distinct transition of bioclimatic zones along the north-south geographic boundary in China. Although ongoing global warming may affect the growth of most tree species across elevation gradients, the effect of modern warming on the stable hydrogen isotopes of tree-ring wood is still unknown. In this study, we developed early- and late-wood δ 2H chronologies from 1900 to 2018 CE of lignin methoxy groups (δ 2H LM) at 700-m intervals from 1700 to 3100 m a.s.l. along the elevation gradient in Mount Taibai (Mt. Taibai), the peak of the Qinling Mts. The δ 2H LM values of the earlywood were relatively enriched in 2H compared to the latewood, and an elevation-dependent depleting trend along the altitudinal gradient was observed. Comparing the δ 2H LM values with modelled δ 2H values of precipitation (δ 2H Pre) of the sample sites, similar isotopic patterns can be obtained. The reconstructions of δ 2H Pre values confirm the strong coherence between the isotopic composition of the source water and the methoxy groups in the growing season. The consistency of δ 2H LM chronologies between the early- and late-wood at the higher sites was stronger than that at the lower sites. The additional lagged effect and climate response revealed significant seasonal and altitudinal differences. At the timberline site, δ 2H LM values of earlywood were mainly related to the January and February temperatures, whereas δ 2H LM values of latewood correlated most strongly with temperature from July to September, and both values were controlled by the amount of total precipitation. In addition, the combined new δ 2H LM chronologies, based on the lag-1 autocorrelation and the weighted average of the current year earlywood and previous latewood, could be used to merge the corresponding temperature signals from the middle- and low-elevation sites. Altitudinal correlations of elevation offset between the annual δ 2H LM chronologies and interpolations of precipitation and temperature suggested that the δ 2H LM values at higher elevations better represent regional climatic changes. Therefore, topographic effects such as elevation differences should be considered in large-scale applications of δ 2H LM values in future studies. • Altitude- and seasonal-differences in δ 2H values of both tree-ring wood and precipitation were revealed in Qinling Mountains, China. • Elevational effects of temperature and precipitation resulted in the variations of δ 2H LM of lignin methoxy. • Timberline δ 2H LM recorded the significantly lagged effects and strong hydroclimatic signals. • Altitude specificity of δ 2H LM should be considered in the large-scale investigations. [ABSTRACT FROM AUTHOR]

Temperature and precipitation are considered to be the most important indicators affecting the green-up date. Sensitivity of the green-up date to temperature and precipitation is considered to be one of the key indicators to characterize the response of terrestrial ecosystems to climate change. We selected the main grassland types for analysis, including temperate steppe, temperate meadow steppe, upland meadow, and lowland meadow. This study investigates the variation in key meteorological indicators (daily maximum temperature (Tmax), daily minimum temperature (Tmin), and precipitation) between 2001 and 2018. We then examined the partial correlation and sensitivity of green-up date (GUD) to Tmax, Tmin, and precipitation. Our analysis indicated that the average GUD across the whole area was DOY 113. The mean GUD trend was −3.1 days/decade and the 25% region advanced significantly. Tmax and Tmin mainly showed a decreasing trend in winter (p > 0.05). In spring, Tmax mainly showed an increasing trend (p > 0.05) and Tmin a decreasing trend (p > 0.05). Precipitation showed no significant (p > 0.05) change trend and the trend range was ±10 mm/decade. For temperate steppe, the increase in Tmin in March promotes green-up (27.3%, the proportion of significant pixels), with a sensitivity of −0.17 days/°C. In addition, precipitation in April also promotes green-up (21.7%), with a sensitivity of −0.32 days/mm. The GUDs of temperate meadow steppe (73.9%), lowland meadow (65.9%), and upland meadow (22.1%) were mainly affected by Tmin in March, with sensitivities of −0.15 days/°C, −0.13 days/°C, and −0.14 days/°C, respectively. The results of this study reveal the response of vegetation to climate warming and contribute to improving the prediction of ecological changes as temperatures increase in the future. [ABSTRACT FROM AUTHOR]

Land surface phenology (LSP), as a precise bio-indicator that responds to climate change, has received much attention in fields concerned with climate change and ecology. Yet, the dynamics of LSP changes in the Qinling Mountains (QMs)—A transition zone between warm-temperate and north subtropical climates with complex vegetation structure—under significant climatic environmental evolution are unclear. Here, we analyzed the spatiotemporal dynamics of LSP for different vegetation types in the QMs from 2001 to 2019 and quantified the degree of influence of meteorological factors (temperature, precipitation, and shortwave radiation), and soil (temperature and moisture), and biological factors (maximum of NDVI and middle date during the growing season) on LSP changes using random forest models. The results show that there is an advanced trend (0.15 days/year) for the start of the growing season (SOS), a delayed trend (0.24 days/year) for the end of the growing season (EOS), and an overall extended trend (0.39 days/year) for the length of the growing season (LOS) in the QMs over the past two decades. Advanced SOS and delayed EOS were the dominant patterns leading to a lengthened vegetation growing season, followed by a joint delay of SOS and EOS, and the latter was particularly common in shrub and evergreen broadleaved forests. The growth season length increased significantly in western QMs. Furthermore, we confirmed that meteorological factors are the main factors affecting the interannual variations in SOS and EOS, especially the meteorological factor of preseason mean shortwave radiation (SWP). The grass and crop are most influenced by SWP. The soil condition has, overall, a minor influence the regional LSP. This study highlighted the specificity of different vegetation growth in the QMs under warming, which should be considered in the accurate prediction of vegetation growth in the future. [ABSTRACT FROM AUTHOR]