• Energy Research
• 2016-2025close

Abstract Forest characteristics, structure, and dynamics within the North American boreal region are heavily influenced by wildfire intensity, severity, and frequency. Increasing temperatures are likely to result in drier conditions and longer fire seasons, potentially leading to more intense and frequent fires. However, an increase in deciduous forest cover is also predicted across the region, potentially decreasing flammability. In this study, we use an individual tree-based forest model to test bottom-up (i.e. fuels) vs top-down (i.e. climate) controls on fire activity and project future forest and wildfire dynamics. The University of Virginia Forest Model Enhanced is an individual tree-based forest model that has been successfully updated and validated within the North American boreal zone. We updated the model to better characterize fire ignition and behavior in relation to litter and fire weather conditions, allowing for further interactions between vegetation, soils, fire, and climate. Model output following updates showed good agreement with combustion observations at individual sites within boreal Alaska and western Canada. We then applied the updated model at sites within interior Alaska and the Northwest Territories to simulate wildfire and forest response to climate change under moderate (RCP 4.5) and extreme (RCP 8.5) scenarios. Results suggest that changing climate will act to decrease biomass and increase deciduous fraction in many regions of boreal North America. These changes are accompanied by decreases in fire probability and average fire intensity, despite fuel drying, indicating a negative feedback of fuel loading on wildfire. These simulations demonstrate the importance of dynamic fuels and dynamic vegetation in predicting future forest and wildfire conditions. The vegetation and wildfire changes predicted here have implications for large-scale changes in vegetation composition, biomass, and wildfire severity across boreal North America, potentially resulting in further feedbacks to regional and even global climate and carbon cycling.

AbstractFire is a primary disturbance in boreal forests and generates both positive and negative climate forcings. The influence of fire on surface albedo is a predominantly negative forcing in boreal forests, and one of the strongest overall, due to increased snow exposure in the winter and spring months. Albedo forcings are spatially and temporally heterogeneous and depend on a variety of factors related to soils, topography, climate, land cover/vegetation type, successional dynamics, time since fire, season, and fire severity. However, how these variables interact to influence albedo is not well understood, and quantifying these relationships and predicting postfire albedo becomes increasingly important as the climate changes and management frameworks evolve to consider climate impacts. Here we developed a MODIS‐derived ‘blue sky’ albedo product and a novel machine learning modeling framework to predict fire‐driven changes in albedo under historical and future climate scenarios across boreal North America. Converted to radiative forcing (RF), we estimated that fires generate an annual mean cooling of −1.77 ± 1.35 W/m2 from albedo under historical climate conditions (1971–2000) integrated over 70 years postfire. Increasing postfire albedo along a south–north climatic gradient was offset by a nearly opposite gradient in solar insolation, such that large‐scale spatial patterns in RF were minimal. Our models suggest that climate change will lead to decreases in mean annual postfire albedo, and hence a decreasing strength of the negative RF, a trend dominated by decreased snow cover in spring months. Considering the range of future climate scenarios and model uncertainties, we estimate that for fires burning in the current era (2016) the cooling effect from long‐term postfire albedo will be reduced by 15%–28% due to climate change.

Significance Black spruce is the dominant tree species in boreal North America and has shaped forest flammability, carbon storage, and other landscape processes over the last several thousand years. However, climate warming and increases in wildfire activity may be undermining its ability to maintain dominance, shifting forests toward alternative forested and nonforested states. Using data from across North America, we evaluate whether loss of black spruce resilience is already widespread. Resilience was the most common outcome, but drier climatic conditions and more severe fires consistently undermine resilience, often resulting in complete regeneration failure. Although black spruce forests are currently moderately resilient, ongoing warming and drying may alter this trajectory, with large potential consequences for the functioning of this globally important biome.

Forest fires are usually viewed within the context of a single fire season, in which weather conditions and fuel supply can combine to create conditions favourable for fire ignition-usually by lightning or human activity-and spread1-3. But some fires exhibit 'overwintering' behaviour, in which they smoulder through the non-fire season and flare up in the subsequent spring4,5. In boreal (northern) forests, deep organic soils favourable for smouldering6, along with accelerated climate warming7, may present unusually favourable conditions for overwintering. However, the extent of overwintering in boreal forests and the underlying factors influencing this behaviour remain unclear. Here we show that overwintering fires in boreal forests are associated with hot summers generating large fire years and deep burning into organic soils, conditions that have become more frequent in our study areas in recent decades. Our results are based on an algorithm with which we detect overwintering fires in Alaska, USA, and the Northwest Territories, Canada, using field and remote sensing datasets. Between 2002 and 2018, overwintering fires were responsible for 0.8 per cent of the total burned area; however, in one year this amounted to 38 per cent. The spatiotemporal predictability of overwintering fires could be used by fire management agencies to facilitate early detection, which may result in reduced carbon emissions and firefighting costs.

AbstractBoreal wildfires are increasing in intensity, extent, and frequency, potentially intensifying carbon emissions and transitioning the region from a globally significant carbon sink to a source. The productive southern boreal forests of central Canada already experience relatively high frequencies of fire, and as such may serve as an analog of future carbon dynamics for more northern forests. Fire–carbon dynamics in southern boreal systems are relatively understudied, with limited investigation into the drivers of pre‐fire carbon stocks or subsequent combustion. As part of NASA's Arctic‐Boreal Vulnerability Experiment, we sampled 79 stands (47 burned, 32 unburned) throughout central Saskatchewan to characterize above‐ and belowground carbon stocks and combustion rates in relation to historical land use, vegetation characteristics, and geophysical attributes. We found southern boreal forests emitted an average of 3.3 ± 1.1 kg C/m2from field sites. The emissions from southern boreal stands varied as a function of stand age, fire weather conditions, ecozone, and soil moisture class. Sites affected by historical timber harvesting had greater combustion rates due to faster carbon stock recovery rates than sites recovering from wildfire events, indicating that different boreal forest land use practices can generate divergent carbon legacy effects. We estimate the 2015 fire season in Saskatchewan emitted a total of 36.3 ± 15.0 Tg C, emphasizing the importance of southern boreal fires for regional carbon budgets. Using the southern boreal as an analog, the northern boreal may undergo fundamental shifts in forest structure and carbon dynamics, becoming dominated by stands <70 years old that hold 2–7 kg C/m2less than current mature northern boreal stands. Our latitudinal approach reinforces previous studies showing that northern boreal stands are at a high risk of holding less carbon under changing disturbance conditions.

Computer code as part of the publication in review: "Climate warming and cooling feedbacks from North American boreal forest fires" Max J. van Gerrevink1, Sander Veraverbeke1,2, Sol Cooperdock3, Stefano Potter3, Qirui Zhong1,4 Michael Moubarak5, Scott J. Goetz6, Michelle C. Mack7, James T. Randerson8, Nick Schutgens1, Merritt R. Turetsky9, Guido R. van der Werf10, and Brendan M. Rogers3 1Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands 2School of Environmental Sciences, University of East Anglia, Norwich, United Kingdom 3Woodwell Climate Research Center, Falmouth, MA, USA 4College of Urban and Environmental Sciences, Peking University, Beijing, China 5Hamilton College, Hamilton, NY, USA 6School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA 7Center for Ecosystem Science and Society and Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA 8Department of Earth System Science, University of California, Irvine, CA, USA 9Renewable and Sustainable Energy Institute, Department of Ecology and Evolutionary Biology, University of Colorado Boulder, Boulder, CO, USA 10Meteorology & Air Quality Group, Wageningen University and Research, Wageningen, The Netherlands Correspondence to: Max J. van Gerrevink (m.j.van.gerrevink@vu.nl) Files contain the computer code used to compute the climate radiative forcing from fire. The computer code is spilt into 7 different scripts: Well-mixed greenhouse gasses, precursors, and aerosol radiative forcing : Radiative_forcing_GHG_precursors_aerosols_boxmodel.py Mapping and uncertainty of Well-mixed greenhouse gasses, precursors, and aerosol radiative forcing : Radiative_forcing_GHG_precursors_aerosols_Mapping_and_uncertainty.py Permafrost greenhouse gas emissions radiative forcing : Radiative_Forcing_Permafrost_GHG.py Changes in surface albedo radiative forcing : Radiative_Forcing_Albedo_change.py Uncertainty in surface albedo radiative forcing : Radiative_Forcing_Albedo_change_uncertainty.py Vegetation recovery radiative forcing : Radiative_Forcing_vegetation_recovery.py Uncertainty in vegetation recovery radiative forcing : Radiative_Forcing_vegetation_recovery_uncertainty.py * The sensitivity analysis for Permafrost greenhouse gas emissions is included in the Radiative_Forcing_Permafrost_GHG.py script. Additionally, input files for atmospheric concentrations and impulse response function data are included as CSV files.