The Qinghai-Tibet Plateau (QTP) has the largest amount of permafrost in the low and middle latitudes, making it highly susceptible to the effects of global warming. In particular, the degradation of permafrost can be intensified by anomalous amplified warming. To accurately model the hydrothermal dynamics of permafrost and its future trends, the accumulation of high -precision, long-term data for the soil thermal conductivity (STC) in the active layer is crucial. However, no previous research has systematically investigated the spatio-temporal variation in the STC on the QTP over an extended period. Therefore, this study aims to fill this gap using the XGBoost model to analyze the STC in the permafrost on the QTP from 1980 to 2020. The findings of this study provide some preliminary insights. First, areas with high variation in the STC between the freeze-thaw periods over the 40 years gradually migrated from the western region to the central region. Second, since 2015, STC in more than 90 % of the permafrost region in the thawing period has shown positive growth. While, during the freezing period, the STC also exhibited an increase over most regions of the QTP, though the western region and parts of the northeastern region exhibited a decrease. Third, the spatial center of gravity for the STC during the freezing and thawing periods from 1980 to 2020 shifted. The mean STC was larger in the eastern and northeastern regions during the freezing period and larger in the western region during the thawing period. Fourth, both alpine swamp meadow and alpine meadow exhibited a gradual increase in the STC during the freeze-thaw period from 1980 to 2020. The conclusions and data products from this study are expected to support spatiotemporal modeling of the permafrost on the QTP and assist in the prognosis for its future.

Under the background of climate change, freeze-thaw patterns tend to be turbulent: ecosystem function processes and their mutual feedback mechanisms with microorganisms in sensitive areas around the world are currently a hot topic of research. We studied changes of soil properties in alpine wetlands located in arid areas of Central Asia during the seasonal freeze-thaw period (which included an initial freezing period, a deep freezing period, and a thawing period), and analyzed changes in soil bacterial community diversity, structure, network in different stages with the help of high-throughput sequencing technology. The results showed that the alpha diversity of the soil bacterial community showed a continuous decreasing trend during the seasonal freeze-thaw period. The relative abundance of dominant bacterial groups (Proteobacteria (39.04%-41.28%) and Bacteroidota (14.61%-20.12%)) did not change significantly during the freeze-thaw period. At the genus level, different genera belonging to the same phylum dominated in different stages, or there were clusters of genera belonging to different phylum. For example, g_Ellin6067, g_unclassified_f_Geobacteraceae, g_unclassified_f_Gemmatimonadaceae coexisted in the same cluster, belonging to Proteobacteria, Desulfobacterota and Gemmatimonadota respectively, and their abundance increased significantly during the freezing period. This adaptive freeze-thaw phylogenetic model suggests a heterogeneous stress resistance of bacteria during the freeze-thaw period. In addition, network analysis showed that, although the bacterial network was affected to some extent by environmental changes during the initial freezing period and its recovery in the thawing period lagged behind, the network complexity and stability did not change much as a whole. Our results prove that soil bacterial communities in alpine wetlands are highly resistant and adaptive to seasonal freeze-thaw conditions. As far as we know, compared with short-term freeze-thaw cycles research, this is the first study examining the influence of seasonal freeze-thaw on soil bacterial communities in alpine wetlands. Overall, our findings provide a solid base for further investigations of biogeochemical cycle processes under future climate change.

The Qinghai-Tibet Plateau is an area known to be sensitive to global climate change, and the problems caused by permafrost degradation in the context of climate warming potentially have far-reaching effects on regional hydrogeological processes, ecosystem functions, and engineering safety. Soil thermal conductivity (STC) is a key input parameter for temperature and surface energy simulations of the permafrost active layer. Therefore, understanding the spatial distribution patterns and variation characteristics of STC is important for accurate simulation and future predictions of permafrost on the Qinghai-Tibet Plateau. However, no systematic research has been conducted on this topic. In this study, based on a dataset of 2972 STC measurements, we simulated the spatial distribution patterns and spatiotemporal variation of STC in the shallow layer (5 cm) of the Qinghai-Tibet Plateau and the permafrost area using a machine learning model. The monthly analysis results showed that the STC was high from May to August and low from January to April and from September to December. In addition, the mean STC in the permafrost region of the Qinghai-Tibet Plateau was higher during the thawing period than during the freezing period, while the STC in the eastern and southeastern regions is generally higher than that in the western and northwestern regions. From 2005 to 2018, the difference between the STC in the permafrost region during the thawing and freezing periods gradually decreased, with a slight difference in the western hinterland region and a large difference in the eastern region. In areas with specific landforms such as basins and mountainous areas, the changes in the STC during the thawing and freezing periods were different or even opposite. The STC of alpine meadow was found to be most sensitive to the changes during the thawing and freezing periods within the permafrost zone, while the STC for bare land, alpine desert, and alpine swamp meadow decreased overall between 2005 and 2018. The results of this study provide important baseline data for the subsequent analysis and simulation of the permafrost on the Qinghai-Tibet Plateau.

Autumn freeze-thaw period significantly influenced the soil temperature, moisture, nutrients, and then affected the structure and diversity of soil microbial community. In this paper, three types of wetlands in the permafrost region of Daxing' an Mountains were selected to investigate the greenhouse gas fluxes during the autumn freeze-thaw period. CO2, CH4 , and N2O fluxes during the autumn freeze-thaw period ranged from 24.76 to 124.06 mg m(-2) h(-1),-249.10 to 968.87 mu g m(-2) h(-1), and - 4.21 to 12.86 mu g m(-2) h(-1). CO2 fluxes were mainly influenced by soil temperature and moisture. CH4 fluxes were mainly influenced by temperature and soil moisture. And N2O fluxes were significantly affected by temperature, soil moisture, ammonia nitrogen, and nitrate nitrogen. Environmental factors could explain 64-73.2%, 51-85.4%, and 60.3-93.3% of temporal variation of CO2, CH4, and N2O fluxes, respectively. Comparing different wetlands, the soil temperature was the significant factor to affect the CH4 flux. The global warming potentials during the autumn freeze-thaw period ranged from 717.83 to 775.57 kg CO2-eq hm(-2).

The Qinghai-Tibet Plateau is an area known to be sensitive to global climate change, and the problems caused by permafrost degradation in the context of climate warming potentially have far-reaching effects on regional hydrogeological processes, ecosystem functions, and engineering safety. Soil thermal conductivity (STC) is a key input parameter for temperature and surface energy simulations of the permafrost active layer. Therefore, understanding the spatial distribution patterns and variation characteristics of STC is important for accurate simulation and future predictions of permafrost on the Qinghai-Tibet Plateau. However, no systematic research has been conducted on this topic. In this study, based on a dataset of 2972 STC measurements, we simulated the spatial distribution patterns and spatiotemporal variation of STC in the shallow layer (5 cm) of the Qinghai-Tibet Plateau and the permafrost area using a machine learning model. The monthly analysis results showed that the STC was high from May to August and low from January to April and from September to December. In addition, the mean STC in the permafrost region of the Qinghai-Tibet Plateau was higher during the thawing period than during the freezing period, while the STC in the eastern and southeastern regions is generally higher than that in the western and northwestern regions. From 2005 to 2018, the difference between the STC in the permafrost region during the thawing and freezing periods gradually decreased, with a slight difference in the western hinterland region and a large difference in the eastern region. In areas with specific landforms such as basins and mountainous areas, the changes in the STC during the thawing and freezing periods were different or even opposite. The STC of alpine meadow was found to be most sensitive to the changes during the thawing and freezing periods within the permafrost zone, while the STC for bare land, alpine desert, and alpine swamp meadow decreased overall between 2005 and 2018. The results of this study provide important baseline data for the subsequent analysis and simulation of the permafrost on the Qinghai-Tibet Plateau.

The Qinghai-Tibet Plateau (QTP) has the largest amount of permafrost in the low and middle latitudes, making it highly susceptible to the effects of global warming. In particular, the degradation of permafrost can be intensified by anomalous amplified warming. To accurately model the hydrothermal dynamics of permafrost and its future trends, the accumulation of high -precision, long-term data for the soil thermal conductivity (STC) in the active layer is crucial. However, no previous research has systematically investigated the spatio-temporal variation in the STC on the QTP over an extended period. Therefore, this study aims to fill this gap using the XGBoost model to analyze the STC in the permafrost on the QTP from 1980 to 2020. The findings of this study provide some preliminary insights. First, areas with high variation in the STC between the freeze-thaw periods over the 40 years gradually migrated from the western region to the central region. Second, since 2015, STC in more than 90 % of the permafrost region in the thawing period has shown positive growth. While, during the freezing period, the STC also exhibited an increase over most regions of the QTP, though the western region and parts of the northeastern region exhibited a decrease. Third, the spatial center of gravity for the STC during the freezing and thawing periods from 1980 to 2020 shifted. The mean STC was larger in the eastern and northeastern regions during the freezing period and larger in the western region during the thawing period. Fourth, both alpine swamp meadow and alpine meadow exhibited a gradual increase in the STC during the freeze-thaw period from 1980 to 2020. The conclusions and data products from this study are expected to support spatiotemporal modeling of the permafrost on the QTP and assist in the prognosis for its future.