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Wildfire activity is increasing in boreal forests as climate warms and dries, increasing risks to rural and urban communities. In black spruce forests of Interior Alaska, fuel reduction treatments are used to create a defensible space for fire suppression and slow fire spread. These treatments introduce novel disturbance characteristics, making longer-term outcomes on ecosystem structure and wildfire risk reduction uncertain. We remeasured a network of sites where fuels were reduced through hand thinning or mechanical shearblading in Interior Alaska to assess how successional trajectories of tree dominance, understory composition, and permafrost change over ∼ 20 years after treatment. We also assessed if these fuel reduction treatments reduce modeled surface rate of fire spread (ROS), flame length, and fireline intensity relative to an untreated black spruce stand, and if surface fire behavior changes over time. In thinned areas, soil organic layer (SOL) disturbance promoted tree seedling recruitment but did not change over time. In shearbladed sites, by contrast, both conifer and broad-leaved deciduous seedling density increased over time and deciduous seedlings were 20 times more abundant than spruce. Thaw depth increased over time in both treatments and was greatest in shearbladed sites with a thin SOL. Understory composition was not altered by thinning but in shearbladed treatments shifted from forbs and horsetail to tall deciduous shrubs and grasses over time. Modeled surface fire behavior was constant in shearbladed sites. This finding is inconsistent with expert opinion, highlighting the need for additional fuels-specific data to capture the changing vegetation structure. Treatment effectiveness at reducing modeled surface ROS, flame length, and fireline intensity depended on the fuel model used for an untreated black spruce stand, pointing to uncertainties about the efficacy of these treatments at mitigating surface fire behavior. Overall, we show that fuel reduction treatments can promote low flammability, deciduous tree dominated successional trajectories, and that shearblading has strong effects on understory composition and permafrost degradation that persist for nearly two decades after disturbance. Such factors need to be considered to enhance the design, management, and predictions of fire behavior in these treatments. 

Abstract. As the northern high latitude permafrost zone experiences accelerated warming, permafrost has become vulnerable to widespread thaw. Simultaneously, wildfire activity across northern boreal forest and Arctic/subarctic tundra regions impact permafrost stability through the combustion of insulating organic matter, vegetation and post-fire changes in albedo. Efforts to synthesise the impacts of wildfire on permafrost are limited and are typically reliant on antecedent pre-fire conditions. To address this, we created the FireALT dataset by soliciting data contributions that included thaw depth measurements, site conditions, and fire event details with paired measurements at environmentally comparable burned and unburned sites. The solicitation resulted in 52,466 thaw depth measurements from 18 contributors across North America and Russia. Because thaw depths were taken at various times throughout the thawing season, we also estimated end of season active layer thickness (ALT) for each measurement using a modified version of the Stefan equation. Here, we describe our methods for collecting and quality checking the data, estimating ALT, the data structure, strengths and limitations, and future research opportunities. The final dataset includes 47,952 ALT estimates (27,747 burned, 20,205 unburned) with 32 attributes. There are 193 unique paired burned/unburned sites spread across 12 ecozones that span Canada, Russia, and the United States. The data span fire events from 1900 to 2022. Time since fire ranges from zero to 114 years. The FireALT dataset addresses a key challenge: the ability to assess impacts of wildfire on ALT when measurements are taken at various times throughout the thaw season depending on the time of field campaigns (typically June through August) by estimating ALT at the end of season maximum. This dataset can be used to address understudied research areas particularly algorithm development, calibration, and validation for evolving process-based models as well as extrapolating across space and time, which could elucidate permafrost-wildfire interactions under accelerated warming across the high northern latitude permafrost zone. The FireALT dataset is available through the Arctic Data Center. 

Abstract. As the northern high-latitude permafrost zone experiences accelerated warming, permafrost has become vulnerable to widespread thaw. Simultaneously, wildfire activity across northern boreal forest and Arctic/subarctic tundra regions impacts permafrost stability through the combustion of insulating organic matter, vegetation, and post-fire changes in albedo. Efforts to synthesis the impacts of wildfire on permafrost are limited and are typically reliant on antecedent pre-fire conditions. To address this, we created the FireALT dataset by soliciting data contributions that included thaw depth measurements, site conditions, and fire event details with paired measurements at environmentally comparable burned and unburned sites. The solicitation resulted in 52 466 thaw depth measurements from 18 contributors across North America and Russia. Because thaw depths were taken at various times throughout the thawing season, we also estimated end-of-season active layer thickness (ALT) for each measurement using a modified version of the Stefan equation. Here, we describe our methods for collecting and quality-checking the data, estimating ALT, the data structure, strengths and limitations, and future research opportunities. The final dataset includes 48 669 ALT estimates with 32 attributes across 9446 plots and 157 burned–unburned pairs spanning Canada, Russia, and the United States. The data span fire events from 1900 to 2022 with measurements collected from 2001 to 2023. The time since fire ranges from 0 to 114 years. The FireALT dataset addresses a key challenge: the ability to assess impacts of wildfire on ALT when measurements are taken at various times throughout the thaw season depending on the time of field campaigns (typically June through August) by estimating ALT at the end-of-season maximum. This dataset can be used to address understudied research areas, particularly algorithm development, calibration, and validation for evolving process-based models as well as extrapolating across space and time, which could elucidate permafrost–wildfire interactions under accelerated warming across the high-northern-latitude permafrost zone. The FireALT dataset is available through the Arctic Data Center (https://doi.org/10.18739/A2RN3092P, Talucci et al., 2024).