An anomalous warm weather event in the Antarctic McMurdo Dry Valleys on 18 March 2022 created an opportunity to characterize soil biota communities most sensitive to freeze-thaw stress. This event caused unseasonal melt within Taylor Valley, activating stream water and microbial mats around Canada Stream. Liquid water availability in this polar desert is a driver of soil biota distribution and activity. Because climate change impacts hydrological regimes, we aimed to determine the effect on soil communities. We sampled soils identified from this event that experienced thaw, nearby hyper-arid areas, and wetted areas that did not experience thaw to compare soil bacterial and invertebrate communities. Areas that exhibited evidence of freeze-thaw supported the highest live and dead nematode counts and were composed of soil taxa from hyper-arid landscapes and wetted areas. They received water inputs from snowpacks, hyporheic water, or glacial melt, contributing to community differences associated with organic matter and salinity gradients. Inundated soils had higher organic matter and lower conductivity (p < .02) and hosted the most diverse microbial and invertebrate communities on average. Our findings suggest that as liquid water becomes more available under predicted climate change, soil communities adapted to the hyper-arid landscape will shift toward diverse, wetted soil communities.

Understanding soil organic carbon (SOC) distribution and its environmental controls in permafrost regions is essential for achieving carbon neutrality and mitigating climate change. This study examines the spatial pattern of SOC and its drivers in the Headwater Area of the Yellow River (HAYR), northeastern Qinghai-Xizang Plateau (QXP), a region highly susceptible to permafrost degradation. Field investigations at topsoils of 86 sites over three summers (2021-2023) provided data on SOC, vegetation structure, and soil properties. Moreover, the spatial distribution of key permafrost parameters was simulated: temperature at the top of permafrost (TTOP), active layer thickness (ALT), and maximum seasonal freezing depth (MSFD) using the TTOP model and Stefan Equation. Results reveal a distinct latitudinal SOC gradient (high south, low north), primarily mediated by vegetation structure, soil properties, and permafrost parameters. Vegetation coverage and above-ground biomass showed positive correlation with SOC, while soil bulk density (SBD) exhibited a negative correlation. Climate warming trends resulted in increased ALT and TTOP. Random Forest analysis identified SBD as the most important predictor of SOC variability, which explains 38.20% of the variance, followed by ALT and vegetation coverage. These findings likely enhance the understanding of carbon storage controls in vulnerable alpine permafrost ecosystems and provide insights to mitigate carbon release under climate change.

Frozen soil, covering most of the Tibetan Plateau (TP), critically influences land surface and climate simulations. Although some studies have made advancements in simulations, further investigation into the distinct mechanisms underlying relevant parameterization schemes remains essential. This study compares two frozen soil permeability schemes in Noah-MP (NY06: high-permeability; Koren99: low-permeability) to elucidate their distinct hydrological mechanisms. Although significant disparities exist in the simulation of soil water and ice content between the two schemes in permafrost regions, the simulated soil water content in the shallow layer exhibits similarity. Their underlying physical processes behind this similarity differ fundamentally: Koren99 relies on cross-seasonal ice melt recharge, whereas NY06 depends more on current-season precipitation and snowmelt. With greater soil depth, soil water differences progressively propagate downward, amplifying variations in hydraulic conductivity, and soil memory effects become increasingly dominant. Meanwhile, the Koren99 scheme more effectively impedes bottom-up melting water transport than top-down effect. However, the aforementioned disparities are not apparent in seasonally frozen soil. Notable disparities also exist in simulated evapotranspiration and surface runoff over permafrost regions, particularly during the summer months. This research investigates the differences in water transport within frozen soil over the TP, elucidates the distinct hydrological mechanisms underlying different frozen soil permeability schemes, and highlights that similar soil hydrothermal simulations are associated with different physical processes, leading to varying degrees of effectiveness in soil memory. Furthermore, this research elucidates the dual role of soil ice (permeability restriction and water storage) in hydrological processes, providing a theoretical basis for improving frozen soil parameterization.

Forests are increasingly impacted by climate change, affecting tree growth and carbon sequestration. Tree-ring width, closely related to tree growth, is a key climate proxy, yet models describing ring width or growth often lack comprehensive environmental data. This study assesses ERA5-Land data for tree-ring width prediction compared to automatic weather station observations, emphasizing the value of extended and global climate data. We analyzed 723 site-averaged and detrended tree-ring chronologies from two broadleaved and two gymnosperm species across Europe, integrating them with ERA5-Land climate data, CO2 concentration, and a drought index (SPEI12). A subset was compared with weather station data. For modelling interannual variations of tree-ring width we used linear models to assess parameter importance. ERA5-Land and weather-station-based models performed similarly, maintaining stable correlations and consistent errors. Models based on meteorological data from weather stations highlighted SPEI12, sunshine duration, and temperature extremes, while ERA5-Land models emphasized SPEI12, dew-point temperature (humidity), and total precipitation. CO2 positively influenced the growth of gymnosperm species. ERA5-Land facilitated broader spatial analysis and incorporated additional factors like evaporation, snow cover, and soil moisture. Monthly assessments revealed the importance of parameters for each species. Our findings confirm that ERA5-Land is a reliable alternative for modeling tree growth, offering new insights into climate-vegetation interactions. The ready availability of underutilized parameters, such as air humidity, soil moisture and temperature, and runoff, enables their inclusion in future growth models. Using ERA5-Land can therefore deepen our understanding of forest responses to diverse environmental drivers on a global scale.

Surface soil moisture (SSM) is a key limiting factor for vegetation growth in alpine meadow on the Qinghai-Tibetan Plateau (QTP). Patches with various sizes and types may cause the redistribution of SSM by changing soil hydrological processes, and then trigger or accelerate alpine grassland degradation. Therefore, it is vital to understand the effects of patchiness on SSM at multi-scales to provide a reference for alpine grassland restoration. However, there is a lack of direct observational evidence concerning the role of the size and type of patches on SSM, and little is known about the effects of patches pattern on SSM at plot scale. Here, we first measured SSM of typical patches with different sizes and types at patch scale and investigated their patterns and SSM spatial distribution through unmanned aerial vehicle (UAV)-mounted multi-type cameras at plot scale. We then analyzed the role of the size and type of patchiness on SSM at both patch and plot scales. Results showed that: (1) in situ measured SSM of typical patches was significantly different (P < 0.01), original vegetation patch (OV) had the highest SSM, followed by isolate vegetation patch (IV), small bare patch (SP), medium bare patch (MP) and large bare patch (LP); (2) the proposed method based on UAV images was able to estimate SSM (0-40 cm) with a satisfactory accuracy (R-2 = 0.89, P < 0.001); (3) all landscape indices of OV, with the exception of patch density, were positively correlated with SSM at plot scale, while most of the landscape indices of LP and IV showed negative correlations (P < 0.05). Our results indicated that patchiness intensified the spatial heterogeneity of SSM and potentially accelerated the alpine meadow degradation. Preventing the development of OV into IV and the expansion of LP is a critical task for alpine meadow management and restoration.

Climate change is transforming the ice-free areas of Antarctica, leading to rapid changes in terrestrial ecosystems. These areas represent <0.5% of the continent and coincide with the most anthropogenically pressured sites, where the human footprint is a source of contamination. Simultaneously, these are the locations where permafrost can be found, not being clear what might be the consequences following its degradation regarding trace element remobilisation. This raises the need for a better understanding of the natural geochemical values of Antarctic soils as well as the extent of human impact in the surroundings of scientific research stations. Permafrost thaw in the Western Antarctic Peninsula region and in the McMurdo Dry Valleys is the most likely to contribute to the remobilisation of toxic trace elements, whether as the result of anthropogenic contamination or due to the degradation of massive buried ice and ice-cemented permafrost. Site-specific locations across Antarctica, with abandoned infrastructure, also deserve attention by continuing to be a source of trace elements that later can be released, posing a threat to the environment. This comprehensive summary of trace element concentrations across the continent's soils enables the geographical systematisation of published results for a better comparison of the literature data. This review also includes the used analytical techniques and methods for trace element dissolution, important factors when reporting low concentrations. A new perspective in environmental monitoring is needed to investigate if trace element remobilisation upon permafrost thaw might be a tangible consequence of climate change.

Light-absorbing impurities (LAIs), such as mineral dust (MD), organic carbon (OC), and black carbon (BC), deposited in snow, can reduce snow albedo and accelerate snowmelt. The Ili Basin, influenced by its unique geography and westerly atmospheric circulation, is a critical region for LAI deposition. However, quantitative assessments on the impact of LAIs on snow in this region remain limited. This study investigated the spatial distribution of LAIs in snow and provided a quantitative evaluation of the effects of MD and BC on snow albedo, radiative forcing, and snowmelt duration through sampling analysis and model simulations. The results revealed that the Kunes River Basin in the eastern Ili Basin exhibited relatively high concentrations of MD. In contrast, the southwestern Tekes River Basin showed relatively high concentrations of OC and BC. Among the impurities, MD plays a dominant role in the reduction of snow albedo and has a greater effect on the absorption of solar radiation by snow than BC, while MD is the most important light-absorbing impurity responsible for the reduction in the number of snow-melting days in the Ili Basin. Under the combined influence of MD and BC, the snowmelt period in the Ili Basin was reduced by 2.19 +/- 1.43 to 7.31 +/- 4.76 days. This study provides an initial understanding of the characteristics of LAIs in snow and their effects on snowmelt within the Ili Basin, offering essential basic data for future research on the influence of LAIs on snowmelt runoff and hydrological processes in this region.

Study area: The Binggou and adjacent Yakou catchments in the northeastern Tibetan Plateau. Study focus: Hillslope flow paths were studied using hydrochemical data of various water types in the spring snowmelt and summer rainfall periods based on hydrochemical tracers and endmember mixing analysis. New hydrological insights for the study region: End-member mixing analysis confirmed the dominance of surface and near-surface runoff during the spring snowmelt. Specifically, the spring Binggou stream water had 61 % surface runoff, 22 % shallow groundwater, and 17 % near-surface runoff. The spring Yakou stream water had 64 % snowmelt, 25.5 % near-surface runoff, and 10.5 % riparian saturated soil water at a depth of 20 cm. The application of end-member mixing analysis failed in the summer rainfall period, and shallow subsurface flow contributed the most to the streamflow (similar to 100 %). The average acid-neutralizing capacity of the spring Yakou stream water was 611 mu eq/L, increasing to 841 mu eq/L in the summer, and for the Binggou stream water, the values were 747 mu eq/L and 1084 mu eq/L, respectively, indicating that the thawed soil layers had a significant buffering effect on stream water chemistry. This study revealed seasonal shifts in flow paths and stream sources, with a transition from surface to subsurface flow influenced by meteorological conditions and the active layer thickness. Future climate change may enhance subsurface flow recharge, leading to less diluted streamflow and stronger water-soil interactions.

Permafrost degradation on the Tibetan Plateau (TP) has triggered widespread retrogressive thaw slumps (RTSs), affecting hydrology, carbon sequestration and infrastructure stability. To date, there is still a lack of long-term monitoring of RTSs across the TP, the thaw dynamics and comprehensive driving factors remain unclear. Here, using time-series Landsat imagery and change detection algorithm, we identified RTSs on permafrost regions of the TP from 1986 to 2020. Existing RTSs inventories and high-resolution historical imagery were employed to verify the identified results, the temporal validation of RTSs disturbance pixels demonstrated a high accuracy. In the study area, a total of 3537 RTSs were identified, covering a total area of 5997 ha, representing a 26-fold increase since 1986, and 69.2 % of RTSs formed since 2010. Most RTSs are located on gentle slope (4-12 degrees) at elevations between 4500 m and 5300 m, with a tendency to form in alpine grassland and alpine meadow. Annual variations in RTSs area exhibited a significant positive correlation with minimum air temperature, mean land surface temperature, and annual thawing index, while it showing a significant negative correlation with the decrease in downward shortwave radiation. Spatially, RTSs were more common in areas with higher soil water content and shallower active layer. Landsat imagery captured the vast majority of RTSs on the TP and revealed interannual disturbance details, but the 30 m resolution remains inadequate for delineating the refined boundaries of some micro-scale (< 0.18 ha) RTSs. Detected RTSs disturbances on the TP will aid in hazard management and carbon feedback assessments, and our findings provide novel insights into the impacts of climate change and permafrost environments on RTSs formation.

Ice records provide a qualitative rather than a quantitative indication of the trend of climate change. Using the bulk aerodynamic method and degree day model, this study quantified ice mass loss attributable to sublimation/evaporation (S/E) and meltwater on the basis of integrated observations (1960-2006) of glacier-related and atmospheric variables in the northeastern Tibetan Plateau. During 1961-2005, the average annual mass loss in the ice core was 95.33 +/- 20.56 mm w.e. (minimum: 78.97 mm w.e. in 1967, maximum: 146.67 mm w.e. in 2001), while the average ratio of the revised annual ice accumulation was 21.2 +/- 7.7% (minimum: 11.0% in 1992, maximum 44.8% in 2000). A quantitative formula expressing the relationship between S/E and air temperature at the monthly scale was established, which could be extended to estimation of S/E changes of other glaciers in other regions. The elevation effect on alpine precipitation determined using revised ice accumulation and instrumental data was found remarkable. This work established a method for quantitative assessment of the temporal variation in ice core mass loss, and advanced the reconstruction of long-term precipitation at high elevations. Importantly, the formula established for reconstruction of S/E from temperature time series data could be used in other regions.