Differential responses of vegetation phenology to climatic elements during extreme events on the Chinese loess plateau.

Extreme, dry events have major impacts on vegetation phenology worldwide. However, the differential responses of vegetation phenology to climatic elements during these extreme events remain unclear. We investigated the response of vegetation phenology to climatic factors during extreme events in arid and semi-arid regions of the Chinese Loess Plateau, using the climate water deficit method, to identify extremely dry and wet events. The results revealed that extremely wet events extended the vegetation growth periods in addition to global warming, whereas extremely dry events did not completely counteract this effect. During different extreme events, phenological changes in vegetation on the Loess Plateau were primarily influenced by the interactive effects of climatic factors. During extremely dry events, a 100 mm increase in precipitation advanced the start of the season by 3.0, 9.2, and 16.7 days in forest, shrubland, and grassland, respectively. During extremely wet events, a 1 °C rise in temperature delayed the end of the season by 1.6, 0.6, and 3.8 days in forest, shrubland, and grassland, respectively. These findings provide crucial guidance for improving predictions of plant phenology changes under extreme climatic events and unraveling biosphere-atmosphere feedback cycles.

Impacts of climate change and human activities on different degraded grassland based on NDVI.

Grassland degradation has emerged as a serious socio-economic and ecological problem, endangering both long-term usage and the regional biogeochemical cycle. Climate change and human activities are the two leading factors leading to grassland degradation. However, it is unclear what the degradation level caused by these two factors is. Using the normalized difference vegetation index (NDVI) and coefficient of variation of NDVI (CVNDVI), the spatial distribution features of grassland degradation or restoration were analyzed in Qilian County in the northeast of the Qinghai-Tibet Plateau. The dominant climate variables affecting NDVI variation were selected through the combination of random forest model and stepwise regression method to improve the residual trend analysis, and on this basis, twelve possible scenarios were established to evaluate the driving factors of different degraded grasslands. Finally, used the Hurst index to forecast the trend of grassland degradation or restoration. The results showed that approximately 55.0% of the grassland had been degraded between 2000 and 2019, and the area of slight degradation (NDVIslope > 0; CVNDVI (slope) > 0; NDVIvalue > 0.2) accounted for 48.6%. These regions were centered in the northwest of Qilian County. Climate and human activities had a joint impact on grassland restoration or degradation. Human activities played a leading role in grassland restoration, while climate change was primarily a driver of grassland degradation. The regions with slight degradation or re-growing (NDVIslope > 0; CVNDVI (slope) > 0), moderate degradation (NDVIslope < 0; CVNDVI (slope) > 0), and severe degradation or desertification (NDVIslope < 0; CVNDVI (slope) < 0) were dominated by the joint effects of climate and anthropogenic activity accounted for 34.3%, 3.3%, and 1.3%, respectively, of the total grassland area. Grasslands in most areas of Qilian County are forecasted to continue to degrade, including the previously degraded areas, with continuous degradation areas accounting for 54.78%. Accurately identifying the driving factors of different degraded grassland and predicting the dynamic change trend of grassland in the future is the key to understand the mechanism of grassland degradation and prevent grassland degradation. The findings offer a reference for accurately identifying the driving forces in grassland degradation, as well as providing a scientific basis for the policy-making of grassland ecological management.

Variations of drought and its trend in the Loess Plateau from 1986 to 2019.

As one of the extreme climatic events, the frequency and intensity of drought have great impacts on regional water resource. Water is a main limiting factor for plant growth in arid and semi-arid regions. Therefore, it is of great scientific significance to explore the spatiotemporal variations and future tendency of drought for the ecological environment in the Loess Plateau. Based on grid data of monthly precipitation and temperature from 1986 to 2019, we calculated standardized precipitation evapotranspiration index (SPEI) and drought frequency. The spatiotemporal patterns and its variations were analyzed at the seasonal and annual scales in the Loess Plateau using the Mann-Kendall test and Sen's slope estimation method. Finally, the future trend of drought was analyzed in the Loess Plateau by the NAR neural network combined with Hurst index. Results showed that the trend of aridification became more significant in the Loess Plateau, and that the frequency of droughts events exhibited great spatial variations at the interannual and seasonal scales during the study period. Specifically, the highest frequency of drought in the interannual, spring and winter was found in the southeast and west of the Loess Plateau, whereas the frequency of drought in summer and autumn was higher in the northwest. The frequency of moderate drought was the highest in summer compared with other seasons while the frequency of slight drought was the highest in interannual and other seasons. The Loess Plateau showed a trend of aridification in spring and summer, but this trend in autumn and winter became weaker in most areas of the study area. The SPEI value in the interannual, spring, and summer exhibited a decline trend in a future period in the Loess Plateau. The aridification would be enhanced. The Hurst index value was the largest and the persis-tence of its change remained stronger in summer. The possibility of continuous drought in summer would be higher than that in other seasons in the future.