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Ice-penetrating radar observation of bed echoes is a core geophysical technique in glaciology. In early and ongoing exploration and mapping surveys, areas with little or no data were often prioritized, leading to few repeated radar sounding profiles. In parallel, advances in radar sounding instruments, platforms and analysis approaches have dramatically opened possibilities for future survey design. Here, we consider the opportunities these advances present for next-generation bed measurements, including both assimilation-optimized mapping and repeat sounding. Based on this analysis, we argue that repeat-pass profiles of bed echo power and englacial layer echo phase should be key priorities for future observations. To that end, we evaluate the detectability of subglacial water bodies, including ocean intrusion in the grounding zone as a target for repeat-pass surveys. We also discuss the distinct implications of our suggested approaches for instrument, platform and survey choices to combine mapping and repeat-pass surveys across the time scales of ice-sheet change. This article is part of the Theo Murphy meeting issue 'Next generation ice-sheet bed measurements'.

Aerosol composition, size, and deposition rate determine the impact these particles have on cryosphere environments. Mineralogical, biological, and geochemical characteristics of aerosols collected over two years from the southwest Greenland Ice Sheet indicate that aerosols delivered via dry deposition and in snow primarily consisted of silicate minerals, with mean particle diameters of 1.01 ± 1.58 μm (2016) and 0.76 ± 0.87 μm (2017) for dry deposition and 2.4 ± 3.2 μm for dust delivered in snow (2017). The rare earth element signature of the delivered dust was typical of nearby Greenlandic lithologies, and combining this with other geochemical results and airmass history modeling indicated that the airborne mineral dust collected on-ice was likely from local emission sources, namely nearby proglacial plains. Dust and snow deposition rates were used to estimate phosphorus delivery to the ice surface at a rate of 1.2 mg·m-2·year-1, which could fuel estimated pigmented glacier ice algal cell abundances of 8.6 × 103 cells·mL-1, a value consistent with glacier ice algal bloom cell densities documented in the region. The eukaryotic communities in air and snow samples were dominated by algae and fungi, respectively, with both sample types also hosting various bacteria. These results suggest that the airborne transfer of glacier ice and snow algae may be a method by which fresh cryosphere surfaces become inoculated with these pigmented organisms. Collectively, these findings highlight the biogeochemical links between aerosols and the ice sheet surface, which have impacts on glacier ice algal growth and the corresponding surface ice albedo and melting.

Cryospheric landforms play a critical role in alpine hydrology and ecosystems. Using historical and contemporary data spanning nearly six decades (1967-2024), we assessed elevation change for glaciers, rock glaciers, and perennial snowfields and the thermal response of streams in the Teton Range, Wyoming, United States. Glaciers and snowfields thinned at -0.84 ± 0.07 meters per year (m year-1) and -0.59 ± 0.04 m year-1 between 2014 and 2022, a ~7-fold increase relative to 1967-2014, driven by warming summer temperatures. In contrast, rock glaciers are near equilibrium (-0.05 ± 0.05 m year-1) and saw no change in rate. Since 2015, snowfield-fed streams have warmed rapidly (+3.4°C), whereas glacier- and rock glacier-fed streams have warmed at lower magnitudes (+0.9° and +0.6°C, respectively). Our results demonstrate the greater resilience of rock glaciers to atmospheric warming, highlighting the critical role that these features will play as glaciers and perennial snowfields are lost.

Reliable real-time measurement of suspended sediment mass concentration (SSC) is essential for effective environmental monitoring and management. It is also important for the operation and maintenance of hydropower schemes, particularly in managing reservoir sedimentation and mitigating turbine abrasion. However, sensor readings are strongly influenced by variable sediment properties, particularly size and shape, hindering reliable monitoring. This study systematically investigates the effects of particle size (median particle diameter d50 and Sauter Mean Diameter SMD) and shape (sphericity Ψ) on the responses of several turbidimeters and acoustic sensors (single- and multi-frequency), and develops methods for practical application. A customized recirculating cylindrical tank with a volume of 246 L and a maximum upward flow velocity of 0.2 ms-1 enabled testing various natural and artificial particles (up to 2 mm) across SSCs from 0.5 to 25 gl-1. We analyzed the specific outputs of the instruments, defined as the outputs divided by SSC, representing the calibration factors for each particle type. We found that for turbidimeters, the specific output scaled with inverse power-law relations of d50 as well as SMD, and decreased nearly linearly with Ψ. SMD and Ψ proved effective for combining size/shape effects and representing shape-related output, offering a basis for generalized field calibration. We developed three generic models to predict sensor output conversion factors for improved real-time SSC monitoring and calibration. The best-performing data-driven model, applied to a natural sediment sample, showed good agreement for turbidimeters but overestimated acoustic sensor response, highlighting refinement needs. The findings advance the understanding of sensor responses and support the feasibility of generic prediction models across diverse sediment types and sensor technologies. This study contributes to better informed sensor selection and calibration, directly enabling more effective and sustainable monitoring and management of water and sediment resources.

We report the discovery of a previously undocumented subglacial lake beneath the Flade Isblink Ice Cap in North East Greenland. Using satellite Earth Observation data (ICESat-2 elevation data and Sentinel-1 Double Difference InSAR) in the period October 2018 to December 2024 and outputs from a regional climate model, we quantify the lake's role in regional hydrology. The subglacial lake's volume is characterised by an annual cycle of filling during the melt season and drainage in September-October, with the lake storing up to 63 ± 23% of the yearly runoff from its catchment area. In most years, lake drainage causes a 2-3-month lag between peak surface-meltwater production and downstream discharge into the nearby proglacial lake, Romer Sø. Lake drainage occurred in all years of our observation period except 2022, which had the lowest surface melt rates, suggesting that a minimum water-input threshold is required to initiate lake drainage. Additionally, our dataset does not show any evidence of a hydrological connection between the lake and the nearby, well-known subglacial lake on the high plateau of Flade Isblink. Our findings highlight how subglacial conditions may substantially modify the outflow of subglacial water to the ice margin with potential impacts on downstream hydrology and ecosystems. It further demonstrates the potential of integrating remote sensing with hydrological modelling to understand ice-sheet hydrology.

Identifying basal wetness conditions beneath the Antarctic ice sheet is essential for understanding subglacial hydrology, basal traction and long-term ice dynamics. However, conventional reflectivity-wetness analysis methods face significant challenges, such as the reliance on inconsistent reflectivity thresholds and manually labelled training datasets. In this contribution, we propose a signal similarity-informed generative adversarial network (SSIGAN), an unsupervised anomaly detection framework, to predict and analyse the basal wetness conditions using focused radio-echo sounding data. Taking the AGAP region as a case study, the method reformulates the wetness classification as an anomaly detection problem, removing the need for labelled data. It extracts radar waveform similarity features to generate an anomaly score (R1), which is combined with an inverted geometrically corrected and normalized bed return power score (R2) to form a wetness score (R3) that enhances the classification separability. Validations are conducted through spatial comparison with existing inventoried subglacial lakes and consistency analysis at radar intersection zones. The results demonstrate that this method can reliably distinguish the transition between wet and dry basal interfaces, highlighting its potential for continental-wide mapping of basal wetness in Antarctica. This article is part of the Theo Murphy meeting issue 'Next generation ice-sheet bed measurements'.

The Qinghai-Tibet Plateau harbors permafrost ecosystems containing diverse antibiotic resistance genes (ARGs), yet their transcriptional activity and depth-resolved patterns remain poorly understood. Here, we performed meta-transcriptomic profiling of two permafrost cores (40-m and 100-m) from the Tuotuo River Basin. Within each core, permafrost layers exhibited higher relative ARG transcript abundance and diversity than overlying active layers. β-Lactam, multidrug, and puromycin resistance transcripts were enriched in permafrost, whereas aminoglycoside resistance predominated in the active layer. Antibiotic inactivation mechanisms were more prevalent in permafrost, while target modification dominated in the active layer within the analyzed cores. Plasmid-associated ARGs were detected, and mobile genetic elements (MGEs) showed stratified distributions, with integrative and conjugative elements more abundant in active layers and integrons enriched in permafrost strata. ARG transcript levels were associated with microbial community composition, MGEs, metal tolerance genes, and trace metal concentrations. Neutral community modeling suggested that ARG assemblages are largely consistent with stochastic processes, indicating long-term persistence under environmental filtering. As the analysis is limited to two cores, these observations reflect site-specific transcriptional patterns rather than generalizable regional trends. Overall, this study provides evidence of ARG transcripts in permafrost layers, offering a baseline for future investigations of resistome dynamics under thaw conditions.

The number and cumulative area of ice-marginal lakes have expanded globally in recent decades, with many lakes residing in glacier-bed overdeepenings, which are subglacial basins formed through preferential glacial erosion. However, current lake expansion rates, key drivers of expansion, and maximum future lake extents are poorly quantified. This is notable because glacial lakes pose hazards, alter hydrologic and ecological systems, and, in some cases, accelerate glacier flow and retreat. Here, we quantify recent ice-marginal lake growth and use existing ice thickness and topographic data to map glacier-bed overdeepenings in Alaska as a predictor of recent and future locations of lake growth. Ice-marginal lakes in the region grew by +156 km2 (26 km2 y-1) between 2018 and 2024, representing a 50% increase relative to the 2009-2018 rate. Eighty percent of lake growth since 2018 occurred in mapped glacier-bed overdeepenings. Approximately 4,250 km2 (2,966 to 5,503 km2 accounting for ± ice thickness uncertainty) of the overdeepened area is connected to an ice-marginal lake, indicating the potential for more than fourfold lake growth of existing lakes as glaciers retreat. An additional 14,500 km2 (12,469 to 17,134 km2) of remaining glacier area resides on glacier-bed overdeepenings not connected to existing lakes, highlighting the potential for substantial new lake development. Velocities from lake-terminating glaciers show clear passive and dynamic endmembers on a continuum of glacier-lake coupling. Glaciers with ice-marginal lakes thinned 23 to 54% more than glaciers of similar area without lakes, underscoring the critical importance of dynamic glacier-lake coupling on the evolution of glaciers in Alaska.

Thwaites Glacier in West Antarctica is losing ice rapidly and is considered especially vulnerable to retreat, but predictions of its future remain limited by uncertainties about its subglacial properties. Here we show results from 344 km of vibroseismic surveys collected along and across the glacier. The data reveal a heterogeneous bed of elevated ridges with steep upstream-facing slopes that form crag-and-tail landforms resisting fast flow. Between these ridges lie basins filled with consolidated sediments. Subglacial water is widespread, occurring in bed depressions and on topographic highs, including an active lake composed of tens of metres of highly porous, water-saturated sediments. Across the glacier, the bed beneath the eastern margin is mostly hard but contains isolated pockets of softer material. These findings demonstrate current models do not capture the full complexity of the bed beneath Thwaites Glacier, where water-bearing sediments and steep basal slopes strongly affect ice flow and retreat.

Subglacial topography and basal conditions form critical controls on ice-sheet dynamics and ice-flow pathways. These controls modulate basal shear stress, affect grounding-line stability and allow the potential for marine ice-sheet instability. Deep troughs and reverse slopes facilitate rapid retreat driven by ocean warming, while topographic ridges and bumps can anchor ice margins. However, substantial data gaps in ice-sheet bed measurements limit the accuracy of sea-level rise projections from numerical ice-sheet models that require such information as inputs. Interpolation techniques often smooth over key features, creating digital elevation models (DEMs) that do not replicate 'real' glacierized systems. This causes uncertainty in simulations of ice-sheet evolution. Advances in physics-informed methods, which use surface velocity and mass conservation to infer bed elevation, have improved reconstructions of bed topography. Nonetheless, important details that characterize glacierized surfaces remain to be resolved in the DEMs and bed topography grids that models rely on. Future priorities to improve these data products involve dense, targeted surveys in key areas such as grounding zones. Machine learning (ML) offers promising tools for optimizing interpolation, prioritizing survey targets and planning future surveys. As ice-sheet model projections extend to 2300 CE and beyond, survey strategies must anticipate migrating grounding lines. Automation and repeat observations, including swath radar and unmanned aerial vehicle (UAV)-based campaigns, will be vital for maintaining up-to-date, high-resolution bed datasets. Ultimately, significant advancements in subglacial mapping are possible within the next 10-20 years, which could greatly improve model accuracy and better inform sea-level rise mitigation and adaptation strategies. This article is part of the Theo Murphy meeting issue 'Next generation ice-sheet bed measurements'.

The degradation of permafrost and the higher number of heavy rainfall events increase geomorphic disturbance (GMD), affecting the vegetation establishment in high-elevation belts. To evaluate the effect of GMDs on vegetation development, it is essential to understand how species or plant groups respond to disturbances. In this study, we investigated vegetation establishment in undisturbed and disturbed plot pairs along elevational transects in the Austrian and Italian Central Alps. Differences in total vegetation cover, species diversity, the cover of different plant groups and the community weighted means of the Landolt indicator values were analysed using the Kruskal-Wallis test for non-parametric data and paired t-test for parametric data. Generalised additive models combined with a principal component analysis were applied to identify the significant environmental variables (e.g., inclination or precipitation) explaining the differences found. To assess species' plasticity, the three most abundant species (five individuals per plot) per undisturbed-disturbed pairs were collected on-site, and functional traits measured in the laboratory. Disturbed sites exhibited lower total vegetation cover, species number, cover of competitive species, dwarf shrubs, herbs and lichens. The cover of stress-tolerant, cryophilic species and herbs was higher in disturbed sites. The observed variations can be mainly explained by climatic, edaphic and topographic variables. The Stream Power Index as a disturbance proxy had a significant negative influence on the total vegetation cover and herb cover and a positive influence on bryophyte, dwarf shrub, and tree cover. Most collected species showed high trait plasticity, with disturbance primarily reducing plant height and specific leaf area. Synthesis: GMD was the key driver in relation to both vegetation cover and species richness. The cover of most functional plant groups as well as species plasticity was primarily affected by climatic factors, soil conditions and the presence of less acidic debris than by GMD.

Melt ponding on Arctic sea ice is a key indicator of the transition from a predominantly perennial to a seasonal sea-ice cover, yet quantitative data on pond depth remain limited. Here, we present the first analysis of melt-pond depth using Ice, Cloud, and land Elevation Satellite-2 (ICESat-2)'s Advanced Topographic Lidar Altimeter System (ATLAS). The Density-Dimension Algorithm for bifurcating sea-ice reflectors (DDA-bifurcate-seaice) automatically detects multiple surface returns in ICESat-2 photon data and estimates corresponding surface heights, enabling melt-pond-depth retrievals under varied noise conditions. Airborne lidar and imagery collected during the NASA ICESat-2 Project Arctic Summer Sea Ice Campaign (July 2022) provide near-coincident observations used to evaluate and optimize the algorithm's melt-pond detection. Evaluation of the melt-pond-depth quantile using Chiroptera data shows that the uniform value used in the ATL07 release 7 data product is near-optimal. We demonstrate DDA-bifurcate-seaice's capability to detect a wide range of melt feature morphologies, including smooth or rough bottoms, ridge-adjacent ponds, partial drainage and seawater intrusion. To further improve depth determination, we propose a depth-quantile function that reduces bias and mean-squared error by a factor of 2.75 and 2.2, respectively. This work improves melt-pond-depth estimation using the DDA-seaice-bifurcate, supporting Arctic- and Antarctic-wide mapping in the ICESat-2/ATLAS experimental sea-ice melt-pond data product on ATL07 (release 7).

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Airborne radio-echo sounding (RES) surveys are currently the primary method of measuring ice sheet thickness to derive subglacial topography, which underpins modelling efforts to improve projections of sea-level rise. However, the scientific impact of these campaigns is hampered by the time required to process the resulting radargrams. Here, we provide an overview of recent advances in machine learning (ML) relevant to ice sheet RES research to show that ML can enhance the value of RES data collected during past campaigns. We highlight two key areas where ML is already being used to enhance RES data analysis: (i) denoising and automated picking of radar returns; (ii) improved spatial interpolation and uncertainty quantification of flightline data. In addition, we suggest two areas where ML may also have a role when planning future surveys. We present examples from Antarctic and Greenland Ice Sheets that demonstrate how ML-driven approaches can outperform traditional methods for interpolation of basal topography and show that advances have been made in ML-based automated extraction of reflecting horizons from radargrams. As numerical ice sheet models become increasingly sophisticated, integrating ML throughout the workflow may help maximize observational value and guide future strategic efforts in the Polar Regions. This article is part of the Theo Murphy meeting issue 'Next generation ice-sheet bed measurements'.

Floods bring pulse and rupture to river ecosystems. In near-natural rivers with high habitat heterogeneity, some habitats buffer harsh conditions during floods and serve as refugia for aquatic organisms, sustaining river resilience. Despite their crucial ecological role, refugia have been poorly studied and barely considered in the restoration of modified rivers with severely reduced habitat heterogeneity. This highly replicated study assessed how flow intensity influences habitat heterogeneity and refugia availability for macrophytes and macroinvertebrates in river reaches with varying levels of human modification. Hydraulic field data was combined with hydrodynamic modelling across three reach morphologies (heavily modified, slightly modified, restored) in ten Swiss rivers. For the 30 reaches investigated, habitat heterogeneity in flow velocity and bed shear stress as well as refugia availability were simulated at mean flow (QM) and six flood intensities (HQ1-HQ100). Habitat heterogeneity in flow velocity and bed shear stress was significantly higher in restored compared to heavily modified reaches across all flow intensities (+17% and +34%, respectively). Across the three reach morphologies, increasing flow intensity significantly reduced habitat heterogeneity in flow velocity (-45%) and in bed shear stress (-43%) averaged from QM to HQ100. Refugia availability for macrophytes declined by 29 percentage points and for macroinvertebrates by 17 percentage points from HQ1 to HQ100. Even at high flood intensities (5-year floods and beyond), refugia were available in restored and slightly modified reaches, e.g., along riverbanks. Refugia availability was positively correlated with habitat heterogeneity. This study highlights the potential of river restoration to foster the resilience of modified river ecosystems by promoting refugia availability through increased habitat heterogeneity. The results suggest that floods of varying intensities should be explicitly considered in restoration planning based on the expectation that disturbances such as floods are likely to increase in the face of climate change.

Projections of glacier change typically focus on mass and area loss, yet the disappearance of individual glaciers directly threatens culturally, spiritually and touristically significant landscapes. Here, using three global glacier models, we project a sharp rise in the number of glaciers disappearing worldwide, peaking between 2041 and 2055 with up to ~4,000 glaciers vanishing annually. Regional variability reflects differences in average glacier size, local climate, the magnitude of warming and inventory completeness.

Studies of creep may be traced back for more than 100 years and this extensive experimentation has produced a comprehensive understanding of the various flow mechanisms occurring in the steady-state or secondary stage of creep. These mechanisms range from diffusional creep and Harper-Dorn creep at low stresses to dislocation processes such as glide and climb at higher stresses and to grain boundary sliding where the rate is dependent primarily upon the grain size. This review examines the nature and characteristics of these flow processes and then demonstrates that the theoretical predictions are generally in good agreement with the experimental data. Finally, two examples are presented, in the fields of structural engineering and glaciology, to illustrate the potential for making significant new contributions to the understanding of the creep processes.

This study evaluates global and regional glacier inventories (RGI, GAMDAM, ICIMOD) against the newly generated Kashmir University Glacier Inventory (KUGI) for the Jhelum, Suru, and Chenab basins in the northwestern Himalaya. The KUGI, comprising 2096 glaciers with an area of ~ 3300.0 ± 117.8 km2, was created by manually delineating glacier boundaries from Landsat satellite data, supplemented by a Digital Elevation Model (DEM), Google Earth images, and limited field surveys. The inventory includes 154 glaciers in the Jhelum basin (85.9 ± 11.4 km2), 328 in the Suru basin (487 ± 16.2 km2), and 1614 in the Chenab basin (2727 ± 90.2 km2). While estimates of glacier area, altitude, slope, and aspect of the individual glaciers varied significantly among the four inventories, a broad similarity was found among the evaluated inventories in terms of distribution of the most common glacier size, elevation, and slope classes. Majority of the of glaciers were smaller than 1 km2, while the 1-5 km2 size class accounted for the largest share of the total glacier area. The GAMDAM ( R A B =0.75) and RGI ( R A B =0.73) inventories were relatively consistent with the KUGI; however, significant discrepancies were noted in the debris-covered and shadowed glaciers, particularly in the ICIMOD inventory. Furthermore, the study revealed differential glacier area changes across the three basins from 2000 to 2020. The Jhelum basin experienced the largest area loss (8%), followed by the Suru (4%) and Chenab basins (3%). These area losses are largely explained by the prevailing topographic and morphological settings of the glaciers. The development of a multi-date KUGI with improved attributes and enhanced accuracy in the data-scarce Himalaya offers a reliable database, fostering research in hydrology, glaciology, climate change, glacial hazards, glacier evolution and water resource management.

Recovering ancient DNA from environmental samples is transforming the way we understand historical ecosystems. While high-throughput sequencing of the total DNA in environmental samples (shotgun metagenomic sequencing) reveals the taxonomic contents of these samples, the genetic signals of some taxa (e.g., eukaryotes) can be weak compared to the background levels of DNA from organisms such as bacteria, requiring deep sequencing approaches that are costly. Thus, to increase cost-effectiveness, pre-sequencing enrichment of target DNA can be advantageous. One technique to enrich this target DNA is hybridisation capture, where short RNA or DNA baits are designed to match, bind and isolate specific stretches of DNA. Hybridisation capture has previously been applied to recover DNA from ancient skeletal remains, but it is only beginning to emerge as an approach to characterise organisms from ancient environmental samples. Thus, there is limited information on establishing hybridisation capture workflows for ancient environmental DNA applications, including the limitations and advantages. This mini review focuses on establishing a roadmap for the applications of hybridisation capture to ancient environmental DNA samples.