Short-interval fires increasing in the Alaskan boreal forest as fire self-regulation decays across forest types

Buma, Brian; Hayes, Katherine; Weiss, Shelby A.; Lucash, Melissa S.

doi:10.1038/s41598-022-08912-8

Cited by 13 publications

(9 citation statements)

References 43 publications

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“…Our permafrost and SOL module will help process-based modelers produce more accurate projections of how forests in the biome are likely to change over the next century. Better projections will resolve a number of important uncertainties, including (1) where increased burning due to climate change may reduce boreal fuel loads such that fire self-limitation emerges (Héon et al, 2014;Buma et al, 2022); (2) when shifts in postfire successional trajectories will initiate biophysical feedbacks that further alter regional climate; and W. D. Hansen et al: The Permafrost and Organic LayEr module for Forest Models (POLE-FM) 1.0…”

Section: Discussionmentioning

confidence: 99%

The Permafrost and Organic LayEr module for Forest Models (POLE-FM) 1.0

et al. 2023

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Abstract. Climate change and increased fire are eroding the resilience of boreal forests. This is problematic because boreal vegetation and the cold soils underneath store approximately 30 % of all terrestrial carbon. Society urgently needs projections of where, when, and why boreal forests are likely to change. Permafrost (i.e., subsurface material that remains frozen for at least 2 consecutive years) and the thick soil-surface organic layers (SOLs) that insulate permafrost are important controls of boreal forest dynamics and carbon cycling. However, both are rarely included in process-based vegetation models used to simulate future ecosystem trajectories. To address this challenge, we developed a computationally efficient permafrost and SOL module named the Permafrost and Organic LayEr module for Forest Models (POLE-FM) that operates at fine spatial (1 ha) and temporal (daily) resolutions. The module mechanistically simulates daily changes in depth to permafrost, annual SOL accumulation, and their complex effects on boreal forest structure and functions. We coupled the module to an established forest landscape model, iLand, and benchmarked the model in interior Alaska at spatial scales of stands (1 ha) to landscapes (61 000 ha) and over temporal scales of days to centuries. The coupled model generated intra- and inter-annual patterns of snow accumulation and active layer depth (portion of soil column that thaws throughout the year) generally consistent with independent observations in 17 instrumented forest stands. The model also represented the distribution of near-surface permafrost presence in a topographically complex landscape. We simulated 39.3 % of forested area in the landscape as underlain by permafrost, compared to the estimated 33.4 % from the benchmarking product. We further determined that the model could accurately simulate moss biomass, SOL accumulation, fire activity, tree species composition, and stand structure at the landscape scale. Modular and flexible representations of key biophysical processes that underpin 21st-century ecological change are an essential next step in vegetation simulation to reduce uncertainty in future projections and to support innovative environmental decision-making. We show that coupling a new permafrost and SOL module to an existing forest landscape model increases the model's utility for projecting forest futures at high latitudes. Process-based models that represent relevant dynamics will catalyze opportunities to address previously intractable questions about boreal forest resilience, biogeochemical cycling, and feedbacks to regional and global climate.

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Section: Discussionmentioning

confidence: 99%

The Permafrost and Organic LayEr module for Forest Models (POLE-FM) 1.0

et al. 2023

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“…Thinner organic layers tend to be warmer following fire (Harden et al, 2006) and can cause permafrost thaw for decades (Pastick et al, 2017; Yoshikawa et al, 2002) and accelerate decomposition of deep, old organic matter, resulting in substantial CO 2 losses (Estop‐Aragonés et al, 2018; Gibson et al, 2019). Moreover, as fire return intervals shorten (Buma et al, 2022), the threat to deeper soil C pools is much greater in dry sites (Walker et al, 2020) or areas with thinner organic layers (Hoy et al, 2016), even in response to low severity fires, which could result in significant atmospheric CO 2 emissions.…”

Section: Discussionmentioning

confidence: 99%

“…Although our sample size of multiple‐burn plots was relatively small (17 plots), we did not detect a significant difference in soil C ( F = 0.184, p = 0.854) nor live tree C ( F = 0.05, p = 0.961) between plots that had experienced a single fire or multiple fires. However, multiple burns over short intervals (<20 years between fires) may become more frequent in the future (Buma et al, 2022), leading to shifts in species composition (Hayes & Buma, 2021) and reduced ecosystem C (Hoy et al, 2016). Future investigations of multiple burns across the FIA network may elucidate further details of this phenomenon at a broad spatial scale.…”

Section: Discussionmentioning

confidence: 99%

Interactions among wildfire, forest type and landscape position are key determinants of boreal forest carbon stocks

2022

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Boreal forest soils contain large stocks of soil carbon (C) that may be sensitive to changes in climate and disturbance. Destablization of boreal forest soil C through changes in C inputs, belowground C pools and/or wildfire could feedback to accelerate rising atmospheric CO2 concentration. Additionally, increasing frequency of severe fires may be changing the dominant forest types and reshaping aboveground C stocks. Although controls on ecosystem C pools have received considerable attention, many studies have been limited to locations near the road system, leading to uncertainty in current and future C stocks across boreal Alaska. Here, we leveraged 545 randomly selected and spatially balanced Forest Inventory and Analysis (FIA) plots across ~13.5 million hectares in interior Alaska to examine the factors governing soil and live tree C pools. Forest type mediated the effects of mean summer air temperature and the probability of near‐surface permafrost on soil C. Meanwhile, forest type, stand age and aspect were the primary drivers of live tree C. Overall, plots with a known history of wildfire during the past 70 years did not have significantly different soil C stocks than plots without a known history of fire, likely due to the historical predominance of low severity fires. Where wildfire likely initiated a transition to deciduous trees (19% of plots), live tree and soil C pools were reduced by 16% and 20%, respectively. Ecosystem C likely recovered over time, as maturing deciduous stands rapidly gained C in live trees. Deciduous stands without a known fire had comparatively very large live tree C stocks, suggesting a significant change in the distribution of ecosystem C following severe fire. Synthesis. Our results highlight the nuanced interactions among wildfire, landscape position and forest type that will play important roles in shaping future boreal ecosystem C stocks.

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“…Our permafrost and SOL module will help process-based modelers produce more accurate projections of how forests in the biome are likely to change over the next century. Better projections will resolve a number of important uncertainties, including 1) where increased burning due to climate change may reduce boreal fuel loads such that fire-self limitation emerges (Héon et al, 2014;Buma et al, 2022); 2) when shifts in postfire successional trajectories will initiate biophysical feedbacks that further alter regional climate; and 3) how climate change, fire, and permafrost thaw will interact to reshape boreal carbon cycling (Schurr et al, 2018;Schuur and Mack, 2018;Mack et al, 2021)…”

Section: Discussionmentioning

confidence: 99%

The Permafrost and Organic LayEr module for Forest Models (POLE-FM) 1.0

Hansen

Foster

Gaglioti

et al. 2022

Preprint

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Abstract. Climate change and increased fire are eroding the resilience of boreal forests. This is problematic because boreal vegetation and the cold soils underneath store approximately 30 % of all terrestrial carbon. Society urgently needs projections of where, when, and why boreal forests are likely to change. Permafrost (i.e., subsurface material that remains frozen for at least two consecutive years) and the thick soil-surface organic layers (SOLs) that insulate permafrost are important controls of boreal forest dynamics and carbon cycling. However, both are rarely included in process-based vegetation models used to simulate future ecosystem trajectories. To address this challenge, we developed a computationally efficient permafrost and SOL module that operates at fine spatial (1 ha) and temporal (daily) resolutions. The module mechanistically simulates daily changes in depth to permafrost, annual SOL accumulation, and their complex effects on boreal forest structure and functions. We coupled the module to an established forest landscape model, iLand, and benchmarked the model in interior Alaska at spatial scales of stands (1 ha) to landscapes (61,000 ha) and over temporal scales of days to centuries. The coupled model could generate intra- and inter-annual patterns of snow accumulation and active layer depth (portion of soil column that thaws throughout the year) consistent with independent observations in 17 instrumented forest stands. The model was also skilled at representing the distribution of near-surface permafrost presence in a topographically complex landscape. We simulated 34.6 % of forested area in the landscape as underlain by permafrost; a close match to the estimated 33.4 % from the benchmarking product. We further determined that the model could accurately simulate moss biomass, SOL accumulation, fire activity, tree-species composition, and stand structure at the landscape scale. Modular and flexible representations of key biophysical processes that underpin 21st-century ecological change are an essential next step in vegetation simulation to reduce uncertainty in future projections and to support innovative environmental decision making. We show that coupling a new permafrost and SOL module to an existing forest landscape model increases the model’s utility for projecting forest futures at high latitudes. Process-based models that represent relevant dynamics will catalyze opportunities to address previously intractable questions about boreal forest resilience, biogeochemical cycling, and feedbacks to regional and global climate.

show abstract

Short-interval fires increasing in the Alaskan boreal forest as fire self-regulation decays across forest types

Cited by 13 publications

References 43 publications

The Permafrost and Organic LayEr module for Forest Models (POLE-FM) 1.0

The Permafrost and Organic LayEr module for Forest Models (POLE-FM) 1.0

Interactions among wildfire, forest type and landscape position are key determinants of boreal forest carbon stocks

The Permafrost and Organic LayEr module for Forest Models (POLE-FM) 1.0

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