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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.

 

Permafrost warming and degradation is well documented across the Arctic. However, observation‐ and model‐based studies typically consider thaw to occur at 0°C, neglecting the widespread occurrence of saline permafrost in coastal plain regions. In this study, we document rapid saline permafrost thaw below a shallow arctic lake. Over the 15‐year period, the lakebed subsided by 0.6 m as ice‐rich, saline permafrost thawed. Repeat transient electromagnetic measurements show that near‐surface bulk sediment electrical conductivity increased by 198% between 2016 and 2022. Analysis of wintertime Synthetic Aperture Radar satellite imagery indicates a transition from a bedfast to a floating ice lake with brackish water due to saline permafrost thaw. The regime shift likely contributed to the 65% increase in thermokarst lake lateral expansion rates. Our results indicate that thawing saline permafrost may be contributing to an increase in landscape change rates in the Arctic faster than anticipated.

 

Beavers have established themselves as a key component of low arctic ecosystems over the past several decades. Beavers are widely recognized as ecosystem engineers, but their effects on permafrost-dominated landscapes in the Arctic remain unclear. In this study, we document the occurrence, reconstruct the timing, and highlight the effects of beaver activity on a small creek valley confined by ice-rich permafrost on the Seward Peninsula, Alaska using multi-dimensional remote sensing analysis of satellite (Landsat-8, Sentinel-2, Planet CubeSat, and DigitalGlobe Inc./MAXAR) and unmanned aircraft systems (UAS) imagery. Beaver activity along the study reach of Swan Lake Creek appeared between 2006 and 2011 with the construction of three dams. Between 2011 and 2017, beaver dam numbers increased, with the peak occurring in 2017 (n = 9). Between 2017 and 2019, the number of dams decreased (n = 6), while the average length of the dams increased from 20 to 33 m. Between 4 and 20 August 2019, following a nine-day period of record rainfall (>125 mm), the well-established dam system failed, triggering the formation of a beaver-induced permafrost degradation feature. During the decade of beaver occupation between 2011 and 2021, the creek valley widened from 33 to 180 m (~450% increase) and the length of the stream channel network increased from ~0.6 km to more than 1.9 km (220% increase) as a result of beaver engineering and beaver-induced permafrost degradation. Comparing vegetation (NDVI) and snow (NDSI) derived indices from Sentinel-2 time-series data acquired between 2017 and 2021 for the beaver-induced permafrost degradation feature and a nearby unaffected control site, showed that peak growing season NDVI was lowered by 23% and that it extended the length of the snow-cover period by 19 days following the permafrost disturbance. Our analysis of multi-dimensional remote sensing data highlights several unique aspects of beaver engineering impacts on ice-rich permafrost landscapes. Our detailed reconstruction of the beaver-induced permafrost degradation event may also prove useful for identifying degradation of ice-rich permafrost in optical time-series datasets across regional scales. Future field- and remote sensing-based observations of this site, and others like it, will provide valuable information for the NSF-funded Arctic Beaver Observation Network (A-BON) and the third phase of the NASA Arctic-Boreal Vulnerability Experiment (ABoVE) Field Campaign. 

Very high spatial resolution commercial satellite imagery can inform observation, mapping, and documentation of micro-topographic transitions across large tundra regions. The bridging of fine-scale field studies with pan-Arctic system assessments has until now been constrained by a lack of overlap in spatial resolution and geographical coverage. This likely introduced biases in climate impacts on, and feedback from the Arctic region to the global climate system. The central objective of this exploratory study is to develop an object-based image analysis workflow to automatically extract ice-wedge polygon troughs from very high spatial resolution commercial satellite imagery. We employed a systematic experiment to understand the degree of interoperability of knowledge-based workflows across distinct tundra vegetation units—sedge tundra and tussock tundra—focusing on the same semantic class. In our multi-scale trough modelling workflow, we coupled mathematical morphological filtering with a segmentation process to enhance the quality of image object candidates and classification accuracies. Employment of the master ruleset on sedge tundra reported classification accuracies of correctness of 0.99, completeness of 0.87, and F1 score of 0.92. When the master ruleset was applied to tussock tundra without any adaptations, classification accuracies remained promising while reporting correctness of 0.87, completeness of 0.77, and an F1 score of 0.81. Overall, results suggest that the object-based image analysis-based trough modelling workflow exhibits substantial interoperability across the terrain while producing promising classification accuracies. From an Arctic earth science perspective, the mapped troughs combined with the ArcticDEM can allow hydrological assessments of lateral connectivity of the rapidly changing Arctic tundra landscape, and repeated mapping can allow us to track fine-scale changes across large regions and that has potentially major implications on larger riverine systems.