Alpine wet meadow (AWM), an important wetland type on the Qinghai-Tibet Plateau (QTP), is sensitive to climate change, which alters the soil hydrothermal regime and impacts ecological and hydrological functions in permafrost regions. The mechanisms underlying extreme AWM degradation in the QTP and hydrothermal factors controlling permafrost degradation remain unclear. In this study, soil hydrothermal processes, soil heat migration, and the permafrost state were measured in AWM and extremely degraded AWM (EDAWM). The results showed that the EDAWM exhibited delayed onset of both soil thawing and freezing, shortened thawing period, and extended freezing period at the lower boundary of the active layer. The lower ground temperatures resulted in a 0.2 m shallower active layer thickness in the EDAWM compared with the AWM. Moreover, the EDAWM altered soil thermal dynamics by redistributing energy, modifying soil moisture, preserving soil organic matter, and adjusting soil thermal properties. As for energy budget, a substantial amount of heat in the EDAWM was consumed by turbulent heat fluxes, particularly latent heat flux, which reduced the amount of heat transferred to the ground. Additionally, the higher soil organic matter content in EDAWM decreased the annual mean soil thermal conductivity from 1.42 W m- 1 K-1 in AWM to 1.26 W m- 1 K-1 in EDAWM, slowing down heat transfer within the active layer and consequently mitigating permafrost degradation. However, with continued climate warming, the soil organic matter content in EDAWM will inevitably decline due to microbial decomposition in the absence of new organic inputs. As the soil organic matter content diminishes, soil heat transfer processes will likely accelerate, and the permafrost warming rate may surpass that in undistributed AWM. These findings enhance our understanding of how alpine ecosystem succession influences regional hydrological cycles and greenhouse gas emissions.

The Arctic experiences rapid climate change, but our ability to predict how this will influence plant communities is hampered by a lack of data on the extent to which different species are associated with particular environmental conditions, how these conditions are interlinked, and how they will change in coming years. Increasing temperatures may negatively affect plants associated with cold areas due to increased competition with warm-adapted species, but less so if local temperature variability is larger than the expected increase. Here we studied the potential drivers of vegetation composition and species richness along coast to inland and altitudinal gradients by the Nuuk fjord in western Greenland using hierarchical modelling of species communities (HMSC) and linear mixed models. Community composition was more strongly associated with random variability at intermediate spatial scales (among plot groups 500 m apart) than with large-scale variability in summer temperature, altitude or soil moisture, and the variation in community composition along the fjord was small. Species richness was related to plant cover, altitude and slope steepness, which explained 42% of the variation, but not to summer temperature. Jointly, this suggests that the direct effect of climate change will be weak, and that many species are associated with microhabitat variability. However, species richness peaked at intermediate cover, suggesting that an increase in plant cover under warming climatic conditions may lead to decreasing plant diversity.

Ongoing and widespread permafrost degradation potentially affects terrestrial ecosystems, whereas the changes in its effects on vegetation under climate change remain unclear. Here, we estimated the relative contribution of progressive active layer thickness (ALT) increases to vegetation gross primary productivity (GPP) in the northern permafrost region during the 21st century. Our results revealed that ALT changes accounted for 40% of the GPP increase in the permafrost region during 2000-2021, with amplified effects observed in late growing season (September-October) (43.2%-45.4%) and was especially notable in tundra ecosystems (51%-52.6%). However, projections indicated that this contribution could decrease considerably in the coming decades. Model simulations suggest that once ALT increments (relative to the 2001-2021 baseline) reach approximately 90 cm between 2035 and 2045, the promoting effect of ALT increase on vegetation growth may disappear. These findings provide crucial insights for accurately modelling and predicting ecosystem carbon dynamics in northern high latitudinal regions.

Periglacial processes and permafrost-related landforms, such as rock glaciers, are particularly vulnerable to climate change because of their reliance on sustained low temperatures to maintain permafrost integrity. Rising temperatures lead to permafrost thawing, increased active layer thickness, and ground instability, which disrupt the structural and ecological stability of these environments. Rock glaciers, which are ubiquitous in high mountain systems, are especially sensitive to these changes and serve as key geo-indicators of current or past alpine permafrost conditions, reflecting the multifaceted impacts of warming on both ecological and abiotic components. In this review, we synthesize current scientific knowledge on the complex and divergent responses of alpine rock glaciers to climate change, highlighting a wide range of methodologies employed to study the complex interactions between climatic drivers and rock glacier dynamics. We first explore ecological impacts, focusing on how climatic changes influence vegetation patterns, species composition, and overall biodiversity associated with rock glaciers. Subsequently, we examine the dynamic behavior of rock glaciers, including their structural integrity, movement patterns, and hydrological roles within high mountain ecosystems. By integrating findings from various disciplines, this review underscores the importance of multidisciplinary approaches and long-term monitoring to advance our understanding of rock glacier ecosystem dynamics and their role in periglacial processes under climate change. Our synthesis identifies critical knowledge gaps, such as the uncertain drivers of divergent rock glacier responses and the limited integration of ecological and abiotic data in existing studies. We highlight research priorities, including the establishment of regional monitoring networks and the development of predictive models that incorporate vegetation and permafrost interactions. These insights provide actionable guidance for adaptive management strategies to mitigate the ecological and geological impacts of climate change on these unique and sensitive environments.

Accurately understanding flood evolution and its attribution is crucial for watershed water resource management as well as disaster prevention and mitigation. The source region of the Yellow River (SRYR) has experienced several severe floods over the past few decades, but the driving factor influencing flood volume variation in the SRYR remains unclear. In this study, the Budyko framework was used to quantify the effects of climate change, vegetation growth, and permafrost degradation on flood volume variation in six basins of the SRYR. The results showed that the flood volume decreased before 2000 and increased after 2000, but the average value after 2000 remained lower than that before 2000. Flood volume is most sensitive to changes in precipitation, followed by changes in landscape in all basins. The decrease in flood volume was primarily influenced by changes in active layer thickness in permafrost-dominated basins, while it was mainly controlled by other landscape changes in non-permafrost-dominated basins. Meanwhile, the contributions of changes in potential evapotranspiration and water storage changes to the reduced flood volume were negative in all basins. Furthermore, the impact of vegetation growth on flood volume variation cannot be neglected due to its regulating role in the hydrological cycle. These findings can provide new insights into the evolution mechanism of floods in cryospheric basins and contribute to the development of strategies for flood control, disaster mitigation, and water resource management under a changing climate.

The Qinghai-Tibetan Plateau (QTP) has undergone significant warming, wetting, and greening (WWG) over decades, alongside substantial alterations in hydrological regimes. These changes present great challenges for safeguarding water resources and ecosystems downstream. However, the lack of field observation and systematic research has obscured our understanding of how hydrological processes respond to the combined influences of climate-permafrost-vegetation. This study focuses on the source regions of the Yangtze River, one of the highest permafrost-covered basins on the QTP, and employs a process-based hydrological model to quantify the effects of WWG on hydrological processes. We show that the increasing precipitation dominates subsurface runoff changes while rising temperature primarily affects surface runoff changes by reducing the frozen duration (-52 days/century) and thickening the active layer (+2.4 cm/year). Greening vegetation primarily affects transpiration and interception evaporation. Warming, wetting, and greening will cause a transition in runoff dynamics from surface runoff dominance to subsurface runoff dominance in permafrost basins, and reduce the risk of both flooding and water shortage indicated by the decreased maximum low flow duration and maximum high flow duration of 11.0 and 5.0 days/year, respectively. Moreover, cold permafrost regions exhibit a greater propensity for generating runoff, as indicated by a higher annual increase in runoff coefficient (0.005/year) and total runoff (4.81 mm/year), compared to warm permafrost regions (with increase of 0.001/year and 1.20 mm/year, respectively). These findings enhance the understanding of hydrological changes due to WWG and provide insights for water resources management in permafrost regions under climate change.

Snow cover variation significantly impacts alpine vegetation dynamics on the Tibetan Plateau (TP), yet this effect under climate change remains underexplored. This study uses a survival analysis model to assess the influence of snow on vegetation green-up dynamics, while controlling for key temperature and water availability factors. This analysis integrates multi-source data, including satellite-derived vegetation green-up dates (GUDs), snow depth, accumulated growing degree days (AGDD), downward shortwave radiation (SRAD), precipitation, and soil moisture. Our survival analysis model effectively simulated GUD on the TP, achieving an R of 0.62 (p < 0.01), a root mean square error (RMSE) of 11.20 days, and a bias of -1.41 days for 2020 GUD predictions. It outperformed both the model excluding snow depth and a linear regression model. By isolating snow's impact, we found it exerts a stronger influence on vegetation GUD than precipitation in snow-covered areas of the TP. Furthermore, snow depth effects varied seasonally: a 1-cm increase in preseason snow depth reduced green-up rates by 8.48% before 156(th) day but increased them by 4.74% afterward. This indicates that deeper preseason snow cover delays GUD before June, but advances it from June onward, rather than having a uniform effect. These findings highlight the critical role of snow and underscore the need to incorporate its distinct effects into vegetation phenology models in alpine regions.

Environmental changes, such as climate warming and higher herbivory pressure, are altering the carbon balance of Arctic ecosystems; yet, how these drivers modify the carbon balance among different habitats remains uncertain. This hampers our ability to predict changes in the carbon sink strength of tundra ecosystems. We investigated how spring goose grubbing and summer warming-two key environmental-change drivers in the Arctic-alter CO2 fluxes in three tundra habitats varying in soil moisture and plant-community composition. In a full-factorial experiment in high-Arctic Svalbard, we simulated grubbing and warming over two years and determined summer net ecosystem exchange (NEE) alongside its components: gross ecosystem productivity (GEP) and ecosystem respiration (ER). After two years, we found net CO2 uptake to be suppressed by both drivers depending on habitat. CO2 uptake was reduced by warming in mesic habitats, by warming and grubbing in moist habitats, and by grubbing in wet habitats. In mesic habitats, warming stimulated ER (+75%) more than GEP (+30%), leading to a 7.5-fold increase in their CO2 source strength. In moist habitats, grubbing decreased GEP and ER by similar to 55%, while warming increased them by similar to 35%, with no changes in summer-long NEE. Nevertheless, grubbing offset peak summer CO2 uptake and warming led to a twofold increase in late summer CO2 source strength. In wet habitats, grubbing reduced GEP (-40%) more than ER (-30%), weakening their CO2 sink strength by 70%. One-year CO2-flux responses were similar to two-year responses, and the effect of simulated grubbing was consistent with that of natural grubbing. CO2-flux rates were positively related to aboveground net primary productivity and temperature. Net ecosystem CO2 uptake started occurring above similar to 70% soil moisture content, primarily due to a decline in ER. Herein, we reveal that key environmental-change drivers-goose grubbing by decreasing GEP more than ER and warming by enhancing ER more than GEP-consistently suppress net tundra CO2 uptake, although their relative strength differs among habitats. By identifying how and where grubbing and higher temperatures alter CO2 fluxes across the heterogeneous Arctic landscape, our results have implications for predicting the tundra carbon balance under increasing numbers of geese in a warmer Arctic.

Estimating the landscape and soil freeze-thaw (FT) dynamics in the Northern Hemisphere (NH) is crucial for understanding permafrost response to global warming and changes in regional and global carbon budgets. A new framework for surface FT-cycle retrievals using L-band microwave radiometry based on a deep convolutional autoencoder neural network is presented. This framework defines the landscape FT-cycle retrieval as a time-series anomaly detection problem, considering the frozen states as normal and the thawed states as anomalies. The autoencoder retrieves the FT-cycle probabilistically through supervised reconstruction of the brightness temperature (TB) time series using a contrastive loss function that minimizes (maximizes) the reconstruction error for the peak winter (summer). Using the data provided by the Soil Moisture Active Passive (SMAP) satellite, it is demonstrated that the framework learns to isolate the landscape FT states over different land surface types with varying complexities related to the radiometric characteristics of snow cover, lake-ice phenology, and vegetation canopy. The consistency of the retrievals is assessed over Alaska using in situ observations, demonstrating an 11% improvement in accuracy and reduced uncertainties compared to traditional methods that rely on thresholding the normalized polarization ratio (NPR).

The Arctic has warmed nearly four times faster than the global average since 1979, resulting in rapid glacier retreat and exposing new glacier forelands. These forelands offer unique experimental settings to explore how global warming impacts ecosystems, particularly for highly climate-sensitive arthropods. Understanding these impacts can help anticipate future biodiversity and ecosystem changes under ongoing warming scenarios. In this study, we integrate data on arthropod diversity from DNA gut content analysis-offering insight into predator diets-with quantitative measures of arthropod activity-density at a Greenland glacier foreland using Structural Equation Modelling (SEM). Our SEM analysis reveals both bottom-up and top-down controlled food chains. Bottom-up control, linked to sit-and-wait predator behavior, was prominent for spider and harvestman populations, while top-down control, associated with active search behavior, was key for ground beetle populations. Bottom-up controlled dynamics predominated during the early stages of vegetation succession, while top-down mechanisms dominated in later successional stages further from the glacier, driven largely by increasing temperatures. In advanced successional stages, top-down cascades intensify intraguild predation (IGP) among arthropod predators. This is especially evident in the linyphiid spider Collinsia holmgreni, whose diet included other linyphiid and lycosid spiders, reflecting high IGP. The IGP ratio in C. holmgreni negatively correlated with the activity-density of ground-dwelling prey, likely contributing to the local decline and possible extinction of this cold-adapted species in warmer, late-succession habitats where lycosid spiders dominate. These findings suggest that sustained warming and associated shifts in food web dynamics could lead to the loss of cold-adapted species, while brief warm events may temporarily impact populations without lasting extinction effects.