Glacier forelands provide ideal natural laboratories for studying primary vegetation succession. However, understanding of vegetation dynamics on glacier forelands in the Third Pole (TP) region remains limited. In this study, we employed field sampling and aerial photography to investigate key vegetation parameters (species composition, species diversity, and fractional vegetation cover (FVC)) along chronosequences on nine representative glacier forelands of the TP, spanning continental, subcontinental, and maritime glacier types, then analyzed vegetation changes along successional gradients and assessed floristic similarity both within and among the glacier forelands. Our results showed that species diversity and FVC generally exhibited increasing trends, with fluctuations from young to old forelands. These parameters increased more rapidly on maritime glacier forelands. Plant life-forms were similar during the early stages across all forelands but began to diverge as succession progressed, particularly between different glacier types. Furthermore, floristic similarity was observed between glacier forelands, with the highest similarity occurring between forelands of the same glacier type in adjacent geographic locations. Our findings highlight the critical roles of local climate and geographic factors in shaping proglacial ecosystems and flora, providing a scientific basis for understanding the effects of climate change on proglacial ecosystems and guiding biodiversity conservation efforts.

Ambient seismic noise and microseismicity analyses are increasingly applied for the monitoring of landslides and natural hazards. These methodologies can offer a valuable monitoring tool also for glacial and periglacial bodies, to understand the internal processes driven by external modifications in air temperature and rainfall/snowfall regimes and to forecast possible melting-related hazards in the light of climate change adaptation. We applied the methods to an almost continuous year of data recorded by a network of four passive seismic stations deployed in the frontal portion of the Gran Sometta rock glacier (Aosta Valley, NW Italian Alps). The spectral analysis of ambient seismic noise revealed frequency peaks related to stratigraphic resonances inside the rock glacier. Although the resonance frequency related to the bedrock interface was constant over time, a second higher resonance frequency was identified as the effect of variations in the active layer thickness driven by external air temperature modifications at the daily and seasonal scales. Ambient seismic noise cross-correlation highlighted coherent shear wave velocity modifications inside the periglacial body. The microseismicity dataset extracted from the continuous ambient noise recordings was analyzed and clustered to further investigate the ongoing internal processes and gain insight into their source mechanism and location. The first cluster of events was found to be likely related to the basal movements of the rock glacier and to falls and slides of the debris material. The second cluster was possibly related to shallow ice and rock fracturing processes. The validation of the seismic results through simple models of the rock glacier physical and mechanical layering, the internal thermal regime and the surface displacements allowed for a comprehensive understanding of the rock glacier's reaction to the external conditions.

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.

Glaciers playa vital role in providing water resources for drinking, agriculture, and hydro-electricity in many mountainous regions. As global warming progresses, accurately reconstructing long-term glacier mass changes and comprehending their intricate dynamic relationships with environmental variables are imperative for sustaining livelihoods in these regions. This paper presents the use of eXplainable Machine Learning (XML) models with GRACE and GRACE-FO data to reconstruct long-term monthly glacier mass changes in the Upper Yukon Watershed (UYW), Canada. We utilized the H2O-AutoML regression tools to identify the best performing Machine Learning (ML) model for filling missing data and predicting glacier mass changes from hydroclimatic data. The most accurate predictive model in this study, the Gradient Boosting Machine, coupled with explanatory methods based on SHapley Additive eXplanation (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) analyses, led to automated XML models. The XML unveiled and ranked key predictors of glacier mass changes in the UYW, indicating a decrease since 2014. Analysis showed decreases in snow water equivalent, soil moisture storage, and albedo, along with increases in rainfall flux and air temperature were the main drivers of glacier mass loss. A probabilistic analysis hinging on these drivers suggested that the influence of the key hydrological features is more critical than the key meteorological features. Examination of climatic oscillations showed that high positive anomalies in sea surface temperature are correlated with rapid depletion in glacier mass and soil moisture, as identified by XML. Integrating H2OAutoML with SHAP and LIME not only achieved high prediction accuracy but also enhanced the explainability of the underlying hydroclimatic processes of glacier mass change reconstruction from GRACE and GRACE-FO data in the UYW. This automated XML framework is applicable globally, contingent upon sufficient high-quality data for model training and validation.

青藏高原地区水能资源丰富，开展气候变化背景下不同重现期洪水量级计算可为当地水利工程建设提供科学支撑。以帕隆藏布江流域为研究区，将分布式水文模型VIC-Glacier与可解释机器学习方法相结合，基于第六次国际耦合模式比较计划（CMIP6）以及冰川未来变化预估结果，推求未来近期（2027—2040年）、中期（2047—2060年）、远期（2087—2100年）在中等强迫（SSP2-4.5）和高强迫（SSP5-8.5）情景下不同重现期的洪水量级。结果表明：帕隆藏布江流域洪水量级及其变化具有显著的空间异质特征；未来气候情景下，冰川覆盖面积减少、降水量增加导致径流组分发生改变；对于有冰川覆盖流域，不同重现期洪水量级未来整体呈现减少趋势，减少幅度为6.46%～32.27%；对于无冰川覆盖流域，不同重现期洪水量级未来整体呈现增加趋势，增加幅度为2.87%～15.52%。

青藏高原地区水能资源丰富，开展气候变化背景下不同重现期洪水量级计算可为当地水利工程建设提供科学支撑。以帕隆藏布江流域为研究区，将分布式水文模型VIC-Glacier与可解释机器学习方法相结合，基于第六次国际耦合模式比较计划（CMIP6）以及冰川未来变化预估结果，推求未来近期（2027—2040年）、中期（2047—2060年）、远期（2087—2100年）在中等强迫（SSP2-4.5）和高强迫（SSP5-8.5）情景下不同重现期的洪水量级。结果表明：帕隆藏布江流域洪水量级及其变化具有显著的空间异质特征；未来气候情景下，冰川覆盖面积减少、降水量增加导致径流组分发生改变；对于有冰川覆盖流域，不同重现期洪水量级未来整体呈现减少趋势，减少幅度为6.46%～32.27%；对于无冰川覆盖流域，不同重现期洪水量级未来整体呈现增加趋势，增加幅度为2.87%～15.52%。

青藏高原地区水能资源丰富，开展气候变化背景下不同重现期洪水量级计算可为当地水利工程建设提供科学支撑。以帕隆藏布江流域为研究区，将分布式水文模型VIC-Glacier与可解释机器学习方法相结合，基于第六次国际耦合模式比较计划（CMIP6）以及冰川未来变化预估结果，推求未来近期（2027—2040年）、中期（2047—2060年）、远期（2087—2100年）在中等强迫（SSP2-4.5）和高强迫（SSP5-8.5）情景下不同重现期的洪水量级。结果表明：帕隆藏布江流域洪水量级及其变化具有显著的空间异质特征；未来气候情景下，冰川覆盖面积减少、降水量增加导致径流组分发生改变；对于有冰川覆盖流域，不同重现期洪水量级未来整体呈现减少趋势，减少幅度为6.46%～32.27%；对于无冰川覆盖流域，不同重现期洪水量级未来整体呈现增加趋势，增加幅度为2.87%～15.52%。

Study area: Urumqi Glacier No.1 Catchment in central Asia. Study focus: Chemical weathering at the basin scale is important process for understanding the feedback mechanism of the carbon cycle and climate change. This study mainly used the actual sampling data in 2013, 2014, and 2016, and the first collection from the literature in same catchment to analyze the seasonal and interannual characteristics of meltwater runoff, as well as cation denudation rate (CDR). New hydrological insights for the study region: The dominant ions of meltwater runoff are Ca2 +, HCO3- , and SO42-, which are mainly derived from calcite dissolution, feldspar weathering and sulfide oxidation. Meltwater runoff at Urumqi Glacier No.1 has higher concentrations of Ca2+ and lower concentrations of HCO3- than that from glaciers in Asia. Compared to 2006 and 2007, cation concentrations increased in 2013 and 2014, while SO42- concentration decreased. The daily ion concentration has seasonality and exhibits a negative relationship with discharge. Daily CDR is positively related to discharge and temperature. Annual CDR values range from 12.34 to 19.04 t/ km2/yr in 2013, 2014, and 2016, which are 1-1.7 times higher than those in 2006 and 2007 and higher than some glaciers in Asia. These results indicate that chemical weathering rate in the Urumqi Glacier No.1 catchment has increased with climate warming, and it is stronger than that of some glaciers in the Tibetan Plateau and surroundings.

Glaciers provide multiple ecosystem services (ES) to human society. Due to the continued global warming, the valuation of glacier ES is of urgent importance because this knowledge can support the protection of glaciers. However, a systematic valuation of glacier ES is still lacking, particularly from the perspective of ES contributors. In this study, we introduce the concept of emergy to establish a methodological framework for accounting glacier ES values, and take the Tibetan Plateau (TP) as a case study to comprehensively evaluate the spatiotemporal characteristics of glacier ES during the early 21st century. The results show that the total glacier ES values on the TP increased from 2.36E+24 sej/yr in the 2000s to 2.40E+24 sej/yr in the 2010s, with an overall growth rate of 1.6%. The values of the various services in the 2010s are ranked in descending order: climate regulation (1.59E+24 sej/yr, 66.1%), runoff regulation (4.40E+23 sej/yr, 18.4%), hydropower generation (1.88E+23 sej/ yr, 7.8%). Significantly higher glacier ES values were recorded in the marginal TP than in the endorheic area. With the exception of climate regulation and carbon sequestration, all other service values increased during the study period, partially cultural services, which have experienced rapid growth in tandem with social development. The results of this study will help establish the methodological basis for the assessment of regional and global glacier ES, as well as a scientific basis for the regional protection of glacier resources.