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.

Landslides induced by freeze-thaw processes on grasslands are one of the major geohazards, and their scale and frequency are increasing as the global warms. Freeze-thaw induced landslides degrade surface vegetation and soil properties, reduce biodiversity, intensify landscape fragmentation, and lead to losses in economy, human and animal lives. Despite substantial progress in research on landslides, there has been little study focused on how ground freeze-thaw events affect landslides. By critically analyzing previous studies, this paper proposes a conceptual framework for the forms and types, development, dominant factors, monitoring techniques, and impact mechanisms of freeze-thaw induced landslides. Landslides are controlled by soil characteristics and topographic slope, which are major intrinsic determinants. Increased rainfall, rising temperatures, and thickening active layer due to climate change are all direct drivers of freeze-thaw induced landslides. Vegetation conditions, animal behavior interference, and wind erosion all affect the occurrence and development process of landslides by modifying vegetation cover, soil physical and chemical properties, and structure. Currently, landslide monitoring techniques have evolved rapidly with improved efficiency and accuracy, but with only few applications for freeze-thaw induced landslides. There are a variety of prediction models for landslides, but few consider freeze-thaw effects and lack field validation. The new perspective on the occurring types and dominant factors enhances theoretical understanding of the formation mechanisms, which helps further monitor and analysis of freeze-thaw induced landslides. Future studies should concentrate on the coupling mechanism of multiple factors and the development of an accurate prediction system, which will greatly benefit the understanding and early detection of freeze-thaw induced landslides.

Thaw slumps can lead to considerable carbon loss in permafrost regions, while the loss of components from two major origins, i.e., microbial and plant-derived carbon, during this process remains poorly understood. Here, we provide direct evidence that microbial necromass carbon is a major component of lost carbon in a retrogressive permafrost thaw slump by analyzing soil organic carbon (SOC), biomarkers (amino sugars and lignin phenols), and soil environmental variables in a typical permafrost thaw slump in the Tibetan Plateau. The retrogressive thaw slump led to a similar to 61% decrease in SOC and a similar to 25% SOC stock loss. As evident in the levels of amino sugars (average of 55.92 +/- 18.79 mg g-1 of organic carbon, OC) and lignin phenols (average of 15.00 +/- 8.05 mg g-1 OC), microbial-derived carbon (microbial necromass carbon) was the major component of the SOC loss, accounting for similar to 54% of the SOC loss in the permafrost thaw slump. The variation of amino sugars was mainly related to the changes in soil moisture, pH, and plant input, while changes in lignin phenols were mainly related to the changes in soil moisture and soil bulk density.

The decomposition of thawing permafrost organic matter (OM) to the greenhouse gases (GHG) carbon dioxide (CO2) and methane forms a positive feedback to global climate change. Data on in situ GHG fluxes from thawing permafrost OM are scarce and OM degradability is largely unknown, causing high uncertainties in the permafrost-carbon climate feedback. We combined in situ CO2 and methane flux measurements at an abrupt permafrost thaw feature with laboratory incubations and dynamic modeling to quantify annual CO2 release from thawing permafrost OM, estimate its in situ degradability and evaluate the explanatory power of incubation experiments. In July 2016 and 2019, CO2 fluxes ranged between 0.24 and 2.6 g CO2-C m(-2) d(-1). Methane fluxes were low, which coincided with the absence of active methanogens in the Pleistocene permafrost. CO2 fluxes were lower three years after initial thaw after normalizing these fluxes to thawed carbon, indicating the depletion of labile carbon. Higher CO2 fluxes from thawing Pleistocene permafrost than from Holocene permafrost indicate OM preservation for millennia and give evidence that microbial activity in the permafrost was not substantial. Short-term incubations overestimated in situ CO2 fluxes but underestimated methane fluxes. Two independent models simulated median annual CO2 fluxes of 160 and 184 g CO2-C m(-2) from the thaw slump, which include 25%-31% CO2 emissions during winter. Annual CO2 fluxes represent 0.8% of the carbon pool thawed in the surface soil. Our results demonstrate the potential of abrupt thaw processes to transform the tundra from carbon neutral into a substantial GHG source.

Retrogressive thaw slumps (RTSs) are among the most dynamic landforms resulting from the thawing of ice-rich permafrost. However, RTS distribution and evolution are poorly quantified because most of them occur in remote and inaccessible areas. In this study, we propose a method that integrates deep learning, change detection, and medial axis transform, aiming to automatically quantify the RTS development on multi-temporal images in the Beiluhe region on the Tibetan Plateau from 2017 to 2019. The images are taken by the Planet CubeSat constellation with high spatial and temporal resolution. The experiments show that automatic delineation based on deep learning can produce similar results to manual delineation, providing the potential of using these results to quantify the changes of RTS boundaries in different years. Our method reveals that among manuallydelineated 342 RTSs in the Beiluhe region, 83% and 76% of them expanded from 2017 to 2018 and 2018 to 2019, respectively. For the expansion from 2017 to 2018, the average and maximum expanding areas are 0.20 ha and 1.47 ha, while the average and maximum retreat distances are 21.3 m and 91 m, respectively. For 2018 to 2019 the average and maximum expansion areas and retreat distances are 0.22 ha, 2.53 ha, 25.0 m, and 212 m, respectively. The results show that the method can quantify RTS development automatically on multi-temporal images but may miss some small and subtle RTSs. Moreover, this study provides the very first quantitative report on RTS development on the Tibetan Plateau, which helps to advance the understanding of permafrost degradation.

Purpose Thaw slumps are widely distributed in the Qinghai-Tibet Plateau (QTP) due to global warming and engineering constructions. However, an understanding of the effect of thaw slumps on the 3-D soil macropore networks is lacking. In this study, we aimed to quantify the responses of soil macropore structure to thaw slumps in QTP. Materials and methods Three stages were selected according to the intensities of thaw slumping, including the original grassland, collapsing areas, and collapsed areas. Nine undisturbed soil cores (0-30-cm deep) were collected in total with 3 replicates sampled at each stage, and they were scanned by X-ray computed tomography (CT). Results and discussion The results showed that collapsing areas had higher macroporosity, branch density, and node density than the original grassland and collapsed areas. The macropore networks in the collapsing areas had the highest connectivity among the three thaw slump stages. Macropores with volume > 10 mm(3) accounted for more than 50% of the total macropore volume in the original grassland, collapsing areas, and collapsed areas. We speculate that compared with the other two stages, the soil macropore structure in the collapsing areas is more conducive to water infiltration and lateral migration. The connectivity of macropore networks in the collapsed areas was the lowest among the three stages, which may result in water infiltration difficulties after thaw slumps. Conclusions Thaw slumps affected the soil macropore structure remarkably. The effects of thaw slumps on soil macropore network characteristics were more significantly than on the macropore size distribution.