• Energy Research

We investigate the spatiotemporal patterns and environmental controls of the end of the vegetation growing season (EOS) in autumn across the alpine and temperate grasslands of China from 2001 through 2020, focusing on whether the EOS is likely a "dryness effect" due to drought or a "coolness effect" caused by cold temperature in autumn. The results show that the EOS date is earlier (∼6 days earlier on average) in alpine grasslands than in temperate grasslands. During 2001-2020, a slight non-significant delay of 1.0 day/decade is observed for the regional averaged EOS, which is mostly induced by the delayed EOS in 64.4 % of the study region. Preseason temperature (1-2 months before the EOS) exerts a positive control on the EOS in most of the alpine grasslands and some regions of the eastern part of the temperate grasslands, while drought with a mean length of 3.2 months before the EOS exerts positive effects on the EOS in the central, southwestern, and western parts of the temperate grasslands and in the northeastern part of the alpine grasslands. The positive effects of temperature and drought are very likely phenomena reflecting that the EOS is the "coolness effect" associated with lower temperatures in autumn and the "dryness effect" due to drought, especially meteorological drought without consideration of soil moisture, in late summer and/or early autumn, respectively. Our findings are supported by an analysis of the spatial patterns of the cold degree days (CDD) and EOS sensitivity to the CDD. However, the negative effects of drought are also found in eastern temperate grasslands, likely caused by decreased temperature accompanied by increased moisture. The results presented here highlight the importance of incorporating the impacts of droughts on EOS variability, as well as their interactive effects with temperature, into current vegetation autumn phenology models for grasslands.

Global warming and intense human activity are altering the net primary productivity (NPP) of vegetation in arid and semi-arid regions where vegetation ecosystems are sensitive to climate change, including the Mongolian Plateau (MP). To deepen the understanding of the dynamics of vegetation and its driving factors on the MP, the actual NPP (ANPP) of the MP from 2000 to 2019 was estimated based on a modified Carnegie–Ames–Stanford Approach (CASA) model. The Thornthwaite Memorial and Guangsheng Zhou models were applied concurrently to estimate the potential NPP of the vegetation, and different scenarios were constructed to evaluate quantitatively the impact of climate change and human activity on the vegetation productivity of our study area. The results showed that the carbon sequestration capacities of various vegetation types in the MP differ, with forest > cropland > grassland > wetland. The NPP increased significantly during 2000–2019. Most areas showed a continuous and stable change in vegetation ANPP, with the current trend in variation mainly reflected in the continuous improvement of vegetation. In general, restoration of vegetation was prominent in the MP, and human activities affected more than 30% of vegetation restoration. The ANPP was positively correlated with temperature and precipitation, the latter of which had a more significant effect. Desertification management, restoration of cropland to forest and grassland, afforestation and reasonable grazing activities were the main human activities performed to restore vegetation. This study is expected to advance the theoretical understanding of ecological protection and sustainable development in the MP.

As a measure of the accumulated heat deficit during the growing season transition, cooling degree days (CDDs) play a crucial role in regulating vegetation phenology and ecosystem dynamics. However, systematic analyses of CDD trends and their driving mechanisms remain limited, particularly in high-altitude regions where climate variability is pronounced. This study investigated the spatiotemporal variability in CDDs from 1982 to 2022 in alpine grasslands on the Qinghai–Tibetan Plateau (TP) and quantified the contributions of key climatic factors. The results indicate that lower CDD values (<350 °C-days) were predominantly found in warm, arid regions, whereas higher CDD values (>600 °C-days) were concentrated in colder, wetter areas. Temporally, area-averaged CDDs exhibited a significant decline, decreasing from 490.9 °C-days in 1982 to 495.8 °C-days in 2022 at a rate of 3.8 °C-days per year. Elevation plays a critical role in shaping CDD patterns, displaying a nonlinear relationship: CDDs decrease as elevation increases up to 4300 m, beyond which they increase, suggesting a transition from global climate-driven warming at lower elevations to local environmental controls at higher elevations, where snow–albedo feedback, topographic effects, and atmospheric circulation patterns regulate temperature dynamics. Tmax was identified as the dominant climatic driver of CDD variation, particularly above 4300 m, while radiation showed a consistent positive influence across elevations. In contrast, precipitation had a limited and spatially inconsistent effect. These findings emphasize the complex interactions between elevation, temperature, radiation, and precipitation in regulating CDD trends. By providing a long-term perspective on CDD variations and their climatic drivers, this study enhances our understanding of vegetation–climate interactions in alpine ecosystems. The results offer a scientific basis for modeling late-season phenological changes, ecosystem resilience, and land-use planning under ongoing climate change.