Global warming has caused the gradual degradation of permafrost, which may affect the vegetation water uptake from different depths. However, the water utilization strategies of different vegetation species during the thawing stages of permafrost regions need further study. To elucidate these differences, we selected the permafrost region in Northeast China as study area. We analyzed the water uptake from different depths of Larix gmelinii, a deciduous coniferous tree, Pinus sylvestris var. mongolica, an evergreen tree, and Betula platyphylla, a deciduous broadleaf tree, using stable isotopes of xylem water, soil water, and precipitation from June to October 2019. The results showed that L. gmelinii primarily used shallow soil water (0-40 cm) with the highest proportion at 64.1%, B. platyphylla generally used middle soil water (40-110 cm) with the highest proportion at 55.7%, and P. sylvestris mainly used middle (40-110cm) and deep soil water (110-150 cm) with the highest proportion at 40.4% and 56.9%. The water sources from different depths exhibited more frequent changes in P. sylvestris, indicating a higher water uptake capacity from different soil depths. L. gmelinii mainly uptakes water from shallow soils, suggesting that the water uptake of this species is sensitive to permafrost degradation. This study revealed the water uptake strategies from different depths of three tree species in a permafrost region, and the results suggested that water uptake capacity of different tree species should be considered in the prediction of vegetation changes in permafrost regions under a warming climate.

Ecosystems at the southern edge of the permafrost distribution are highly sensitive to global warming. Changes in soil freeze-thaw cycles can influence vegetation growth in permafrost regions. Extant studies mainly focused on analyzing the differences of vegetation dynamics in different permafrost regions. However, the intrinsic drivers of permafrost degradation on vegetation growth remain elusive yet. Based on the top temperature of permafrost (TTOP) model, we simulated the spatial distribution of permafrost in Northeast China (NEC) from 2001 to 2020. Using the data of the vegetation Net Primary Productivity (NPP), vegetation phenology, climate and permafrost phenology, and analytical methods including partial correlation, multiple linear regression, and path analysis, we explored the response of vegetation growth and phenology to soil freeze-thaw changes and climate change under different degrees of permafrost degradation. Overall, the start date of the growing season (SOS) was very sensitive to the start date of soil thaw (SOT) changes, and multiple regression analyses showed that SOT was the main factor influencing SOS in 41.8% of the NEC region. Climatic factors remain the main factors affecting vegetation NPP in NEC, and the results of partial correlation analysis showed that only 9.7% of the regional duration of soil thaw (DOT) had a strong correlation with vegetation NPP. Therefore, we determined the mechanism responsible for the soil freeze-thaw changes and vegetation growth relationship using the path analysis. The results indicated that there is a potential inhibitory effect of persistent permafrost degradation on vegetation growth. Our findings would contribute to the improvement of process-based models of forest dynamics in the boreal region, which would help to plan sustainable development and conservation strategies in permafrost areas.

Alpine vegetation plays a crucial role in global carbon cycle. Snow cover is an essential component of alpine land cover and shows high sensitivity to climate change. The Tibetan Plateau (TP) has a typical alpine vegetation ecosystem and is rich of snow resources. With global warming, the snow of the TP has undergone significant changes that will inevitably affect the growth of alpine vegetation, but observed evidence of such interaction is limited. In particular, a comprehensive understanding of the responses of alpine vegetation growth to snow cover variability is still not well characterized on TP region. To investigate this, we calculated three indicators, the start (SOS) and length (LOS) of growing season, and the maximum of normalized difference vegetation index (NOVImax) as proxies of vegetation growth dynamics from the Moderate Resolution Imaging Spectroradiometer (MODIS) data for 2000-2015. Snow cover duration (SCD) and melt (SCM) dates were also extracted during the same time frame from the combination of MODIS and the Interactive Multi-sensor Snow and Ice Mapping System (IMS) data. We found that the snow cover phenology had a strong control on alpine vegetation growth dynamics. Furthermore, the responses of SOS, LOS and NDVImax to snow cover phenology varied among different biomes, eco-geographical zones, and temperature and precipitation gradients. The alpine steppes showed a much stronger negative correlation between SOS and SCD, and also a more evidently positive relationship between LOS and SCD than other types, indicating a longer SCD would lead to an earlier SOS and longer LOS. Most areas showed positive correlation between SOS and SCM, while a contrary response was also found in the warm but drier areas. Both SCD and SCM showed positive correlations with NDVImax, but the relationship became weaker with the increase of precipitation. Our findings provided strong evidence between vegetation growth and snow cover phenology, and changes in snow cover should be also considered when analyzing alpine vegetation growth dynamics in future,