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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.
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Fusing Regional and Global Datasets to Develop a Composite Land Cover Product Across High Latitudes
Abstract. Rapid warming across the Arctic is the primary driver of widespread permafrost thaw, with far-reaching consequences for local ecosystem resilience, the regional carbon budget, and the global climate system. Because permafrost characteristics and vulnerability are tightly linked to land cover, particularly vegetation type and surface properties, understanding these dynamics requires accurate and detailed land cover information. Spatial variation in vegetation cover influences energy balance, snow insulation, and soil moisture, factors that directly affect permafrost stability. Consequently, high-resolution land cover products are essential for assessing the ecological impacts of permafrost thaw and for improving the representation of permafrost-related processes in predictive models. However, many global land cover datasets fail to capture the spatial heterogeneity and fine-scale ecological features that influence permafrost dynamics, while more detailed regional products often lack coverage across broader, continental extents. This gap presents a challenge for large-scale assessments of permafrost vulnerability under accelerating climate change. To create a spatially cohesive land cover map that accurately represents the distribution of ecosystems across the Arctic-Boreal region, we integrated existing global and regional land cover datasets using a workflow including machine learning techniques. This approach seamlessly combines diverse data sources, enhancing representation and accuracy. The resulting map represents high-latitude land cover types at a 1-km spatial resolution, better capturing the spatial heterogeneity of the landscape compared to coarser resolution land surface products, with a total of 35 land cover classes, including 20 forest types (e.g., Larch, Birch, Mixed forests), 6 shrubland classes, and wetlands subdivided into bog, fen, and marsh. To achieve this, we used a global land cover map, the European Space Agency Climate Change Initiative Land Cover data (ESA CCI-LC), as the base map and integrated regional maps across the circumpolar region with finer-resolution land cover information to capture the diversity of land cover types. This approach ensured consistent classification across geopolitical boundaries while incorporating representative vegetation communities at a region-specific level. We show that regional land cover products can be successfully fused to yield a higher-resolution thematic content at the circumpolar scale in comparison to existing global products. The hybrid land cover product can be freely access via https://doi.org/10.5281/zenodo.15231293 (Briones et al 2025).
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- Award ID(s):
- 2224776
- PAR ID:
- 10665546
- Publisher / Repository:
- Copernicus Publications
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Posted Content:
- https://doi.org/10.5194/essd-2025-226
