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Ice wedges, which are ubiquitous in permafrost areas, play a significant role in the evolution of permafrost landscapes, influencing the topography and hydrology of these regions. In this paper, we combine a detailed multi-generational, interdisciplinary, and international literature review along with our own field experiences to explore the development of low-centered ice-wedge polygons and their orthogonal networks. Low-centered polygons, a type of ice-wedge polygonal ground characterized by elevated rims and lowered wet central basins, are critical indicators of permafrost conditions. The formation of these features has been subject to numerous inconsistencies and debates since their initial description in the 1800s. The development of elevated rims is attributed to different processes, such as soil bulging due to ice-wedge growth, differential frost heave, and the accumulation of vegetation and peat. The transition of low-centered polygons to flat-centered, driven by processes like peat accumulation, aggradational ice formation, and frost heave in polygon centers, has been generally overlooked. Low-centered polygons occur in deltas, on floodplains, and in drained-lake basins. There, they are often arranged in orthogonal networks that comprise a complex system. The prevailing explanation of their formation does not match with several field studies that practically remain unnoticed or ignored. By analyzing controversial subjects, such as the degradational or aggradational nature of low-centered polygons and the formation of orthogonal ice-wedge networks, this paper aims to clarify misconceptions and present a cohesive overview of lowland terrain ice-wedge dynamics. The findings emphasize the critical role of ice wedges in shaping Arctic permafrost landscapes and their vulnerability to ongoing climatic and landscape changes. 

Abstract The Yukon‐Kuskokwim Delta has the largest intertidal wetland in North America, is a globally critical breeding area for waterbirds, and is home to the largest regional indigenous population in the Arctic. Here, coastal tundra ecosystems, wildlife, and indigenous communities are highly vulnerable to sea‐ice loss in the Bering Sea, sea‐level rise, storm flooding, erosion, and collapsing ground from permafrost thaw caused by climate warming. These drivers interact in non‐linear ways to increase flooding, salinization, and sedimentation, and thus, alter ecosystem trajectories and broader landscape evolution. Rapid changes in these factors over decadal time scales are highly likely to cause transformative shifts in coastal ecosystems across roughly 70% of the outer delta this century. We project saline and brackish ecotypes on the active delta floodplain with frequent sedimentation will maintain dynamic equilibrium with sea‐level rise and flooding, slightly brackish ecotypes on the inactive floodplain with infrequent flooding and low sedimentation rates will be vulnerable to increased flooding and likely transition to more saline and brackish ecotypes, and fresh lacustrine and lowland ecotypes on the abandoned floodplain with permafrost plateaus will be vulnerable to thermokarst, salinization and flooding that will shift them toward brackish ecosystems. This will greatly affect bird nesting and foraging habitats, with both winners and losers. Already, some Yup'ik communities are facing relocation of their low‐lying villages. The societal challenges and consequences of adapting to these changing landscapes are enormous and will require a huge societal effort. 

Abstract In 2007, the Anaktuvuk River fire burned more than 1000 km²of arctic tundra in northern Alaska, ~ 50% of which occurred in an area with ice-rich syngenetic permafrost (Yedoma). By 2014, widespread degradation of ice wedges was apparent in the Yedoma region. In a 50 km²area, thaw subsidence was detected across 15% of the land area in repeat airborne LiDAR data acquired in 2009 and 2014. Updating observations with a 2021 airborne LiDAR dataset show that additional thaw subsidence was detected in < 1% of the study area, indicating stabilization of the thaw-affected permafrost terrain. Ground temperature measurements between 2010 and 2015 indicated that the number of near-surface soil thawing-degree-days at the burn site were 3 × greater than at an unburned control site, but by 2022 the number was reduced to 1.3 × greater. Mean annual ground temperature of the near-surface permafrost increased by 0.33 °C/yr in the burn site up to 7-years post-fire, but then cooled by 0.15 °C/yr in the subsequent eight years, while temperatures at the control site remained relatively stable. Permafrost cores collected from ice-wedge troughs (n = 41) and polygon centers (n = 8) revealed the presence of a thaw unconformity, that in most cases was overlain by a recovered permafrost layer that averaged 14.2 cm and 18.3 cm, respectively. Taken together, our observations highlight that the initial degradation of ice-rich permafrost following the Anaktuvuk River tundra fire has been followed by a period of thaw cessation, permafrost aggradation, and terrain stabilization. 

This dataset contains information on cryostratigraphy and ground-ice content of the upper permafrost, which was based on the results of 22 field trips in 2018-2023. Field studies were performed in various regions of Alaska and Canadian Arctic including the following study areas: Utqiagvik (former Barrow), Teshekpuk Lake, Prudhoe Bay Oilfield, Toolik Lake, Jago River, Itkillik River, Anaktuvuk River, Fairbanks, Dalton Highway, Glennallen, Point Lay, Bylot Island (Canada), Inuvik-Tuktoyaktuk (Canada). Cryostratigraphy of the upper permafrost was studied mainly in coastal and riverbank exposures and frozen cores obtained from drilling with the SIPRE corer. Permafrost exposures and cores were described and photographed in the field, and obtained soil samples were delivered to the University of Alaska Fairbanks for additional descriptions and analyses. Ice contents of frozen soils (including gravimetric and volumetric moisture content, excess-ice content) were measured. The dataset includes cryostratigraphic descriptions, gravimetric (GMC) and volumetric (VMC) moisture content, excess-ice content (EIC), electrical conductivity (EC) and photographs of the permafrost exposures and frozen cores obtained from boreholes. 

Permafrost roughly affects half of the boreal region in Alaska and varies greatly in its thermo‐physical properties and genesis. In boreal ecosystems, permafrost formation and degradation respond to complex interactions among climate, topography, hydrology, soils, vegetation, and disturbance. We synthesized data on soil thermal conditions and permafrost characteristics to assess current permafrost conditions in central Alaska, and classified and mapped soil landscapes vulnerable to future thaw and thermokarst development. Permafrost soil properties at 160 sites ranged from rocky soils in hillslope colluvium and glacial till, to silty loess, to thick peats on abandoned floodplains and bogs, across 64 geomorphic units. Ground‐ice contents (% moisture) varied greatly across geomorphic units. Mean annual ground temperatures at ∼1 m depth varied 12.5°C across 77 sites with most permafrost near thawing or actively thawing. To assess the vulnerability of permafrost to climate variability and disturbance, we differentiated permafrost responses in terms of rate of thaw, potential thaw settlement, and thermokarst development. Using a rule‐based model that uses geomorphic units for spatial extrapolation at the landscape scale, we mapped 10 vulnerability classes across three areas in central Alaska ranging from high potential settlement/low thaw rate in extremely ice‐rich loess to low potential settlement/high thaw rate in rocky hillslope colluvium. Permafrost degradation is expected to result in 10 thermokarst landform types. Vulnerability classes corresponded to thermokarst features that developed in response to past climates. Differing patterns in permafrost vulnerability have large implications for ecosystem trajectories, land use, and infrastructure damage from permafrost thaw. 

Abstract Flowpaths of water through catchments influence water quality and flow regimes of streams. Depths of dominant flowpaths respond to variation in climate and catchment characteristics, such as topography, vegetation, and soil type. In high‐latitude regions, the depth and spatial extent of permafrost influences catchment hydrology, and thawing permafrost might change sources and pathways of water supplying solutes and flow to streams. We estimated contributions of precipitation, soil water, and groundwater flowpaths to streams during the open‐water period after snowmelt by applying a Bayesian mixing model to 4–6 years of observed solute concentrations in five catchments of boreal Alaska. The relative contribution of groundwater to streams varied from 12% to 82% across catchments and years and declined as spatial extent of permafrost increased from 25% to 58% across catchments, indicating potential for increased infiltration and drainage as permafrost thaws. Temporal patterns in precipitation also influenced flowpaths. The mean annual contribution of precipitation to streamflow increased in years with more rain. Groundwater contribution increased, on average, in years with few large storms, suggesting deepening flows due to seasonal ground thaw or loss of shallow water to evapotranspiration. In contrast, groundwater contributed less in years when large storms delivered most of the year's rain in late summer or autumn. Overall, spatial and temporal variation in relative flowpath contributions to streams suggest that permafrost thaw will deepen flowpaths, but increasing precipitation expected in high‐latitude regions under warming climate might obscure this effect by routing water via shallow flowpaths following large storms. 

Abstract The permafrost–fire–climate system has been a hotspot in research for decades under a warming climate scenario. Surface vegetation plays a dominant role in protecting permafrost from summer warmth, thus, any alteration of vegetation structure, particularly following severe wildfires, can cause dramatic top–down thaw. A challenge in understanding this is to quantify fire-induced thaw settlement at large scales (>1000 km 2 ). In this study, we explored the potential of using Landsat products for a large-scale estimation of fire-induced thaw settlement across a well-studied area representative of ice-rich lowland permafrost in interior Alaska. Six large fires have affected ∼1250 km 2 of the area since 2000. We first identified the linkage of fires, burn severity, and land cover response, and then developed an object-based machine learning ensemble approach to estimate fire-induced thaw settlement by relating airborne repeat lidar data to Landsat products. The model delineated thaw settlement patterns across the six fire scars and explained ∼65% of the variance in lidar-detected elevation change. Our results indicate a combined application of airborne repeat lidar and Landsat products is a valuable tool for large scale quantification of fire-induced thaw settlement. 

Understanding the key mechanisms that control northern treelines is important to accurately predict biome shifts and terrestrial feedbacks to climate. At a global scale, it has long been observed that elevational and latitudinal treelines occur at similar mean growing season air temperature (GSAT) isotherms, inspiring the growth limitation hypothesis (GLH) that cold GSAT limits aboveground growth of treeline trees, with mean treeline GSAT ~6-7 degrees celsius (°C). Treelines with mean GSAT warmer than 6-7 °C may indicate other limiting factors. Many treelines globally are not advancing despite warming, and other climate variables are rarely considered at broad scales. Our goals were to test whether current boreal treelines in northern Alaska correspond with the GLH isotherm, determine which environmental factors are most predictive of treeline presence, and to identify areas beyond the current treeline where advance is most likely. We digitized ~12,400 kilometers (km) of treelines (greater than 26K points) and computed seasonal climate variables across northern Alaska. We then built a generalized additive model predicting treeline presence to identify key factors determining treeline. Two metrics of mean GSAT at Alaska’s northern treelines were consistently warmer than the 6-7 °C isotherm (means of 8.5 °C and 9.3 °C), indicating that direct physiological limitation from low GSAT is unlikely to explain the position of treelines in northern Alaska. Our final model included cumulative growing degree-days, near-surface (≤ 1 meters (m)) permafrost probability, and growing season total precipitation, which together may represent the importance of soil temperature. Our results indicate that mean GSAT may not be the primary driver of treeline in northern Alaska or that its effect is mediated by other more proximate, and possibly non-climatic, controls. Our model predicts treeline potential in several areas beyond current treelines, pointing to possible routes of treeline advance if unconstrained by non-climatic factors. 

Understanding the key mechanisms that control northern treelines is important to accurately predict biome shifts and terrestrial feedbacks to climate. At a global scale, it has long been observed that elevational and latitudinal treelines occur at similar mean growing season air temperature (GSAT) isotherms, inspiring the growth limitation hypothesis (GLH) that cold GSAT limits aboveground growth of treeline trees, with mean treeline GSAT ~6-7 degrees celsius (°C). Treelines with mean GSAT warmer than 6-7 °C may indicate other limiting factors. Many treelines globally are not advancing despite warming, and other climate variables are rarely considered at broad scales. Our goals were to test whether current boreal treelines in northern Alaska correspond with the GLH isotherm, determine which environmental factors are most predictive of treeline presence, and to identify areas beyond the current treeline where advance is most likely. We digitized ~12,400 kilometers (km) of treelines (greater than 26K (26,000) points) and computed seasonal climate variables across northern Alaska. We then built a generalized additive model predicting treeline presence to identify key factors determining treeline. Two metrics of mean GSAT at Alaska’s northern treelines were consistently warmer than the 6-7 °C isotherm (means of 8.5 °C and 9.3 °C), indicating that direct physiological limitation from low GSAT is unlikely to explain the position of treelines in northern Alaska. Our final model included cumulative growing degree-days, near-surface (≤ 1 meters (m)) permafrost probability, and growing season total precipitation, which together may represent the importance of soil temperature. Our results indicate that mean GSAT may not be the primary driver of treeline in northern Alaska or that its effect is mediated by other more proximate, and possibly non-climatic, controls. Our model predicts treeline potential in several areas beyond current treelines, pointing to possible routes of treeline advance if unconstrained by non-climatic factors. 

Abstract Alaska has diverse boreal ecosystems across heterogeneous landscapes driven by a wide range of biological and geomorphic processes associated with disturbance and successional patterns under a changing climate. To assess historical patterns and rates of change, we quantified the areal extent of ecotypes and the biophysical factors driving change through photo-interpretation of 2200 points on a time-series (∼1949, ∼1978, ∼2007, ∼2017) of geo-rectified imagery for 22 grids across central Alaska. Overall, 68.6% of the area had changes in ecotypes over ∼68 years. Most of the change resulted from increases in upland and lowland forest types, with an accompanying decrease in upland and lowland scrub types, as post-fire succession led to mid- and late-successional stages. Of 17 drivers of landscape change, fire was by far the largest, affecting 46.5% of the region overall from 1949 to 2017. Fire was notably more extensive in the early 1900s. Thermokarst nearly doubled from 3.9% in 1949 to 6.3% in 2017. Riverine ecotypes covered 7.8% area and showed dynamic changes related to channel migration and succession. Using past rates of ecotype transitions, we developed four state-transition models to project future ecotype extent based on historical rates, increasing temperatures, and driver associations. Ecotype changes from 2017 to 2100, nearly tripled for the driver-adjusted RCP6.0 temperature model (30.6%) compared to the historical rate model (11.5%), and the RCP4.5 (12.4%) and RCP8.0 (14.7%) temperature models. The historical-rate model projected 38 ecotypes will gain area and 24 will lose area by 2100. Overall, disturbance and recovery associated with a wide range of drivers across the patchy mosaic of differing aged ecotypes led to a fairly stable overall composition of most ecotypes over long intervals, although fire caused large temporal fluctuations for many ecotypes. Thermokarst, however, is accelerating and projected to have increasingly transformative effects on future ecotype distributions.