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.

In the context of global warming, understanding the impact of thaw slump on soil hydrothermal processes and its responses to climate is essential for protecting engineering facilities in cold regions. This study aimed to investigate the effect of thaw slump development on active layer soil. We considered the early thaw slump development in the Tibetan Plateau as research object and conducted long-term monitoring of soil hydrothermal activity in the active layer of various parts of the landslide and the regional meteorology. The results showed that thaw slump development shortened the freezing and thawing time of the active layer, increased the freezing and thawing rates of the shallow soil (10-20 cm), and enhanced the heat exchange between the active layer soil and the atmosphere and the heat transfer between the soils. The heat-exchange efficiency of the active layer, from largest to smallest, was headwall > collapsed area > unaffected area (bottom of the slope) > unaffected area (top of the slope). Furthermore, thaw slump development lowered the water storage of the active layer prof ile and weakened the dynamic response of soil water to precipitation. The events of soil water responses and soil water increments were smaller in the landslide area than in the unaffected area. During a co-precipitation event, the overall soil water storage increment (SWSI) of the profile was significantly smaller in the landslide area than in the unaffected area (P < 0.05), with an SWSI of 2.04 mm in the headwall and 1.77 mm in the collapsed area. In addition, thaw slump development altered the mechanism of soil water transport driven by soil temperature changes, which affected soil water redistribution of profile. The study gives ecohydrology-related research in cold climates a scientific foundation, thereby guiding the construction and maintenance of infrastructure projects.

Permafrost degradation is one of the most significant consequences of climate change in the Arctic. During summers, permafrost degradation is evident with cryospheric hazards like retrogressive thaw slumps (RTSs) and active layer detachment slides (ALDs). In parallel, the Arctic has become a popular tourist destination for nature-based activities, with summer being the peak touristic season. In this context, cryospheric hazards pose potential risks for tourists' presence in Arctic national parks and wilderness in general, like in the Yukon. This essay provides the basis for investigating further periglacial, geomorphological and tourism intersections, highlighting the critical need for future interdisciplinary research on thawing permafrost impacts. More so, this requires moving beyond the predominant focus on permafrost impacts on infrastructure and to also consider the direct threats posed to human physical presence in Arctic tourist destinations affected by permafrost degradation. Such interdisciplinary approach is critical not only to mitigate risks, but also to provide policy- and decision-makers with valuable insights for implementing measures and guidelines.

Influenced by a warm and humid climate, the permafrost on the Qinghai-Tibet Plateau is undergoing significant degradation, leading to the occurrence of extensive thermokarst landforms. Among the most typical landforms in permafrost areas is thaw slump. This study, based on three periods of data from keyhole images of 1968-1970, the fractional images of 2006-2009 and the Gaofen (GF) images of 2018-2019, combined with field surveys for validation, investigates the distribution characteristics and spatiotemporal variation trends of thaw slumps in the Hoh Xil area and evaluates the susceptibility to thaw slumping in this area. The results from 1968 to 2019 indicate a threefold increase in the number and a twofold increase in total area of thaw slumps. Approximately 70% of the thaw slumps had areas less than 2 x 104 m2. When divided into a grid of 3 km x 3 km, about 1.3% (128 grids) of the Hoh Xil region experienced thaw slumping from 1968 to 1970, while 4.4% (420 grids) showed such occurrences from 2018 to 2019. According to the simulation results obtained using the informativeness method, the area classified as very highly susceptible to thaw slumping covers approximately 26% of the Hoh Xil area, while the highly susceptible area covers about 36%. In the Hoh Xil, 61% of the thaw slump areas had an annual warming rate ranging from 0.18 to 0.25 degrees C/10a, with 70% of the thaw slump areas experiencing a precipitation increase rate exceeding 12 mm/10a. Future assessments of thaw slump development suggest a possible minimum of 41 and a maximum of 405 thaw slumps occurrences annually in the Hoh Xil region. Under rapidly changing climatic conditions, apart from environmental risks, there also exist substantial potential risks associated with thaw slumping, such as the triggering of large-scale landslides and debris flows. Therefore, it is imperative to conduct simulated assessments of thaw slumping throughout the entire plateau to address regional risks in the future.

The Qinghai-Xizang Plateau of China faces challenges like thaw slumping, threatening slope stability and infrastructure. Understanding the mechanical properties of the roots of the dominant herbaceous plant species in the alpine meadow layer of the permafrost regions on the Qinghai-Xizang Plateau is essential for evaluating their role in enhancing soil shear strength and mitigating slope deformation in these fragile environments. In this study, the roots of four dominant herbaceous plant species-Kobresia pygmaea, Kobresia humilis, Carex moorcroftii, and Leontopodium pusillum-that are widely distributed in the permafrost regions of the Qinghai-Xizang Plateau were explored to determine their mechanical properties and effects in enhancing soil shear strength. Through indoor single root tensile and root group tensile tests, we determined the root diameter, tensile force, tensile strength, tensile ratio, and strength frequency distributions. We also evaluated their contributions to inhibiting slope deformation and failure during the formation and development of thermal thaw slumps in the alpine meadow. The results showed that the distribution of the root diameter of the dominant plant species is mostly normal, while the tensile strength tends to be logarithmically normally distributed. The relationship between the root diameter and root tensile strength conforms to a power function. The theoretical tensile strength of the root group was calculated using the Wu-Waldron Model (WWM) and the Fiber Bundle Model (FBM) under the assumption that the cumulative single tensile strength of the root bundle is identical to the tensile strength of the root group in the WWM. The FBM considers three fracture modes: FBM-D (the tensile force on each single root is proportional to its diameter relative to the total sum of all the root diameters), FBM-S (the cross-sectional stress in the root bundle is uniform), and FBM-N (each tensile strength test of individual roots experiences an equal load). It was found that the model-calculated tensile strength of the root group was 162.60% higher than the test value. The model-derived tensile force of the root group from the FBM-D, FBM-S, and FBM-N was 73.10%, 28.91%, and 13.47% higher than the test values, respectively. The additional cohesion of the soil provided by the roots was calculated to be 25.90-45.06 kPa using the modified WWM, 67.05-38.15 kPa using the FBM-S, and 57.24-32.74 kPa using the FBM-N. These results not only provide a theoretical basis for further quantitative evaluation of the mechanical effects of the root systems of herbaceous plant species in reinforcing the surface soil but also have practical significance for the effective prevention and control of thermal thaw slumping disasters in the permafrost regions containing native alpine meadows on the Qinghai-Xizang Plateau using flexible plant protection measures.

Thermokarst landslide (TL) activity in the Qinghai-Tibet Plateau (QTP) is intensifying due to climate warminginduced permafrost degradation. However, the mechanisms driving landslide formation and evolution remain poorly understood. This study investigates the spatial distribution, annual frequency, and monthly dynamics of TLs along the Qinghai-Tibet engineering corridor (QTEC), in conjunction with in-situ temperature and rainfall observations, to elucidate the interplay between warming, permafrost degradation, and landslide activity. Through the analysis of high-resolution satellite imagery and field surveys, we identified 1298 landslides along the QTEC between 2016 and 2022, with an additional 386 landslides recorded in a typical landslide-prone subarea. In 2016, 621 new active-layer detachments (ALDs) were identified, 1.3 times the total historical record. This surge aligned with unprecedented mean annual and August temperatures. The ALDs emerged primarily between late August and early September, coinciding with maximum thaw depth. From 2016 to 2022, 97.8 % of these ALDs evolved into retrogressive thaw slumps (RTSs), identified as active landslides. Landslides typically occur in alpine meadows at moderate altitudes and on gentle northward slopes. The thick ice layer near the permafrost table serves as the material basis for ALD occurrence. Abnormally high temperature significantly increased the active layer thickness (ALT), resulting in melting of the ice layer and formation of a thawed interlayer, which was the direct causing factor for ALD. By altering the local material, micro-topography, and thermal conditions, ALD activity significantly increases RTS susceptibility. Understanding the mechanisms of ALD formation and evolution into RTS provides a theoretical foundation for infrastructure development and disaster mitigation in extreme environments.

Climate warming can lead to permafrost degradation, potentially resulting in slope failures such as retrogressive thaw slumps (RTSs). The formation of and changes in RTSs could exacerbate the degradation of permafrost and the environment in general. The mechanisms of RTS progression and the potential consequences on the analogous freeze-thaw cycle are not well understood, owing partly to necessitating field work under harsh conditions and with high costs. Here, we used multi-source remote sensing and field surveys to quantify the changes in an RTS on Eboling Mountain in the Qilian Mountain Range in west-central China. Based on optical remote sensing and SBAS-InSAR measurements, we analyzed the RTS evolution and the underlying drivers, combined with meteorological observations. The RTS expanded from 56 m2 in 2015 to 4294 m2 in 2022, growing at a rate of 1300 m2/a to its maximum in 2018 and then decreasing. Changes in temperature and precipitation play a dominant role in the evolution of the RTS, and the extreme weather in 2016 may also be a primary contributor to the accelerated growth, with an average deformation of -8.3 mm during the thawing period, which decreased slope stability. The RTS evolved more actively during the thawing and early freezing process, with earthquakes having potentially contributed further to RTS evolution. We anticipate that the rate of RTS evolution is likely to increase in the coming years.

Permafrost carbon release is potentially the largest terrestrial feedback contributing to climate change. However, the changes in carbon release caused by the abrupt thawing of permafrost and their controlling factors remain largely unknown. Here, we measured soil organic carbon (SOC), total nitrogen (TN) concentrations, and carbon dioxide (CO2) and methane (CH4) emission rates among seven permafrost collapse features over 3 years in the northern Qinghai-Tibetan Plateau (QTP). The results showed soil carbon and nitrogen loss caused by permafrost collapse ranged from - 12% to 28% and - 1% to 38%, respectively. We found there was a nonlinear relationship between soil carbon loss and permafrost collapse chronosequence. Permafrost collapse significantly reduced ecosystem respiration (Reco) and weakened carbon sinks. The net ecosystem exchange (NEE) decreased from 2.59 to - 0.21 & mu;mol CO2 m- 2 s- 1. The Reco and NEE values showed no significant changes over time after the initial permafrost collapse. In contrast, the CH4 fluxes increased over time following permafrost collapse, and the CH4 fluxes significantly increased 2 to 10 times in the exposed area compared with that in the control area. Soil temperature, moisture, and nutrient availability exerted the most controls over the carbon emission during permafrost collapse. This study provides the patterns of carbon loss and emissions in different permafrost collapse landscapes, which will provide deep insights and reliable data for future prediction of the abrupt thawing of permafrost-carbon feedback.

In northern high latitudes, rapid warming is set to amplify carbon-climate feedbacks by enhancing permafrost thaw and biogeochemical transformation of large amounts of soil organic carbon. However, between 30 % and 80 % of permafrost soil organic carbon is considered to be stabilized by geochemical interactions with the soil mineral pool and thus less susceptible to be emitted as greenhouse gases. Quantification of the nature of and controls on mineral-organic carbon interactions is needed to better constrain permafrost-carbon-climate feed-backs, particularly in ice-rich environments resulting in rapid thaw and development of thermokarst landforms. On sloping terrain, mass wasting features called retrogressive thaw slumps are amongst the most dynamic forms of thermokarst. These multi-decadal disturbances grow due to ablation of an ice-rich headwall, and their enlargement due to warming of the Arctic is mobilizing vast stores of previously frozen materials. Here, we investigate headwall profiles of seven retrogressive thaw slumps and sediments displaced from these mass wasting features from the Peel Plateau, western Canadian Arctic. The disturbances varied in their headwall height (2 to 25 m) and affected land surface area ( 30 ha). We present total and water extractable mineral element concentrations, mineralogy, and mineral-organic carbon interactions in the headwall layers (active layer, permafrost materials above an early Holocene thaw unconformity, and Pleistocene-aged permafrost tills) and in displaced material (suspended sediments in runoff and material accumulated on the debris tongue). Our data show that the main mechanism of organic carbon stabilization through mineral-organic carbon interactions within the headwall is the complexation with metals (mainly iron), which stabilizes 30 +/- 15 % of the total organic carbon pool with higher concentrations in near-surface layers compared to deep permafrost. In the displaced material, this proportion drops to 18 +/- 5 %. In addition, we estimate that up to 12 +/- 5 % of the total organic carbon is stabilized by associations to poorly crystalline iron oxides, with no significant difference be-tween near-surface layers, deep permafrost and displaced material. Our findings suggest that the organic carbon interacting with the sediment mineral pool in slump headwalls is preserved in the material mobilized by slumping and displaced as debris. Overall, up to 32 +/- 6 % of the total organic carbon displaced by retrogressive thaw slumps is stabilized by organo-mineral interactions in this region. This indicates that organo-mineral in-teractions play a significant role in the preservation of organic carbon in the material displaced from retro-gressive thaw slumps over years to decades after their development resulting in decadal to centennial scale sequestration of this retrogressive thaw slump-mobilized organic carbon interacting with the soil mineral pool.

The thawing of permafrost on the Qinghai-Tibet Plateau (QTP) leads to more frequent occurrences of thaw slump (TS), which have significant impacts on local ecosystems, carbon cycles, and infrastructure development. Ac-curate recognition of TS would help in understanding its occurrence and evolution. Machine learning capabilities for TS recognition are still not fully exploited. We systematically evaluate the performance of machine learning models for TS recognition from unmanned aerial vehicle (UAV) and propose an ensemble learning object-based model for TS recognition (EOTSR). The EOTSR has the following advantages: 1) pioneering the introduction of spatial information to assist in recognition; 2) the misclassification of recognition models is improved by object -based technology; and 3) attempting to integrate the strengths of different machine learning models to obtain a recognition accuracy no less than that of commonly used deep learning models. The results show that object -based technology is more suitable for TS recognition than pixel-based technology. Recursive feature elimina-tion (RFE)-based feature selection proves that texture and geometry are effective complements to TS recognition. Among the improved object-based machine learning models, support vector machine (SVM) has the highest recognition accuracy, with an overall accuracy of 93.06 %. McNemar's test proves that EOTSR significantly improves TS recognition compared to a single model and achieves an overall accuracy of 97.32 %. The EOTSR model provides an effective recognition method for the increasingly frequent TS events in the permafrost regions of the QTP, and can produce label data for deep learning models based on satellite imagery.