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Abstract In the Arctic tundra, warming is anticipated to stimulate nutrient release and potentially alleviate plant nutrient limitations. Typically simulated by fertilization experiments that saturate plant nutrient demand, future increases in soil fertility are thought to favor ectomycorrhizal (EcM) over ericaceous shrubs and have often been identified as a key driver of Arctic shrub expansion. However, the projected increases in fertility will likely vary in their alleviation of nutrient limitations. The resulting responses of shrubs and their mycorrhizae across the gradient of nutrient limitation may be nonlinear and could contradict the current predictions of tundra vegetation shifts. We compared the functional responses of two dominant shrubs, EcM dwarf birch (Betula nana) and ericaceous Labrador tea (Rhododendron tomentosum), across a long‐term nitrogen and phosphorus fertilization gradient experiment in Arctic Alaska. Using linear mixed‐effects modeling, we tested the responses of shrub cover, height, and root enzyme activities to soil fertility. We found thatB. nanacover and height linearly increased with soil fertility. In contrast,R. tomentosumcover initially increased, but decreased after surpassing the intermediate levels of increased soil fertility. Its height did not change. Enzyme activity did not respond to soil fertility on EcM‐colonizedB. nanaroots, but sharply declined onR. tomentosumroots. Overall, the nonlinear responses of shrubs to our fertility gradient demonstrate the importance of experiments grounded in replicated regression design. Our results indicate that under moderate increases in soil fertility, Arctic shrub expansion may not only include deciduous EcM shrubs but also ericaceous shrubs. Regardless of shifts aboveground, changes in root enzyme activity belowground point to some EcM shrub species playing a more influential role in tundra soils; as EcM roots remained steady in their liberation of soil organic nutrients with heightened soil fertility, degradative root enzyme activity on the dominant ericaceous shrub dropped—in some instances with even the slightest increase in fertility. 

The Arctic is warming faster than anywhere else on Earth, placing tundra ecosystems at the forefront of global climate change. Plant biomass is a fundamental ecosystem attribute that is sensitive to changes in climate, closely tied to ecological function, and crucial for constraining ecosystem carbon dynamics. However, the amount, functional composition, and distribution of plant biomass are only coarsely quantified across the Arctic. Therefore, we developed the first moderate resolution (30 m) maps of live aboveground plant biomass (g m− 2) and woody plant dominance (%) for the Arctic tundra biome, including the mountainous Oro Arctic. We modeled biomass for the year 2020 using a new synthesis dataset of field biomass harvest measurements, Landsat satellite seasonal synthetic composites, ancillary geospatial data, and machine learning models. Additionally, we quantified pixel-wise uncertainty in biomass predictions using Monte Carlo simulations and validated the models using a robust, spatially blocked and nested cross-validation procedure. Observed plant and woody plant biomass values ranged from 0 to ~6000 g m− 2 (mean ≈350 g m− 2), while predicted values ranged from 0 to ~4000 g m− 2 (mean ≈275 g m− 2), resulting in model validation root-mean-squared-error (RMSE) ≈400 g m− 2 and R2 ≈ 0.6. Our maps not only capture large-scale patterns of plant biomass and woody plant dominance across the Arctic that are linked to climatic variation (e.g., thawing degree days), but also illustrate how fine-scale patterns are shaped by local surface hydrology, topography, and past disturbance. By providing data on plant biomass across Arctic tundra ecosystems at the highest resolution to date, our maps can significantly advance research and inform decision-making on topics ranging from Arctic vegetation monitoring and wildlife conservation to carbon accounting and land surface modeling 

Abstract In the Arctic, winter soil temperatures exert strong control over mean annual soil temperature and winter CO₂emissions. In tundra ecosystems there is evidence that plant canopy influences on snow accumulation alter winter soil temperatures. By comparison, there has been relatively little research examining the impacts of heterogeneity in boreal forest cover on soil temperatures. Using seven years of data from six sites in northeastern Siberia that vary in stem density we show that snow-depth and forest canopy cover exert equally strong control on cumulative soil freezing degrees days (FDD_soil). Together snow depth and canopy cover explain approximately 75% of the variance in linear models of FDD_soiland freezingn-factors (n_f; calculated as the quotient of FDD_soiland FDD_air), across sites and years. Including variables related to air temperature, or antecedent soil temperatures does not substantially improve models. The observed increase in FDD_soilwith canopy cover suggests that canopy interception of snow or thermal conduction through trees may be important for winter soil temperature dynamics in forested ecosystems underlain by continuous permafrost. Our results imply that changes in Siberian larch forest cover that arise from climate warming or fire regime changes may have important impacts on winter soil temperature dynamics. 

Abstract Deciduous tree cover is expected to increase in North American boreal forests with climate warming and wildfire. This shift in composition has the potential to generate biophysical cooling via increased land surface albedo. Here we use Landsat-derived maps of continuous tree canopy cover and deciduous fractional composition to assess albedo change over recent decades. We find, on average, a small net decrease in deciduous fraction from 2000 to 2015 across boreal North America and from 1992 to 2015 across Canada, despite extensive fire disturbance that locally increased deciduous vegetation. We further find near-neutral net biophysical change in radiative forcing associated with albedo when aggregated across the domain. Thus, while there have been widespread changes in forest composition over the past several decades, the net changes in composition and associated post-fire radiative forcing have not induced systematic negative feedbacks to climate warming over the spatial and temporal scope of our study. 

Abstract Key message Black spruce ( Picea mariana (Mill.) B.S.P.) has historically self-replaced following wildfire, but recent evidence suggests that this is changing. One factor could be negative impacts of intensifying fire activity on black spruce seed rain. We investigated this by measuring black spruce seed rain and seedling establishment. Our results suggest that increases in fire activity could reduce seed rain meaning reductions in black spruce establishment. Context Black spruce is an important conifer in boreal North America that develops a semi-serotinous, aerial seedbank and releases a pulse of seeds after fire. Variation in postfire seed rain has important consequences for black spruce regeneration and stand composition. Aims We explore the possible effects of changes in fire regime on the abundance and viability of black spruce seeds following a very large wildfire season in the Northwest Territories, Canada (NWT). Methods We measured postfire seed rain over 2 years at 25 black spruce-dominated sites and evaluated drivers of stand characteristics and environmental conditions on total black spruce seed rain and viability. Results We found a positive relationship between black spruce basal area and total seed rain. However, at high basal areas, this increasing rate of seed rain was not maintained. Viable seed rain was greater in stands that were older, closer to unburned edges, and where canopy combustion was less severe. Finally, we demonstrated positive relationships between seed rain and seedling establishment, confirming our measures of seed rain were key drivers of postfire forest regeneration. Conclusion These results indicate that projected increases in fire activity will reduce levels of black spruce recruitment following fire. 

Abstract Climate change is driving substantial changes in North American boreal forests, including changes in productivity, mortality, recruitment, and biomass. Despite the importance for carbon budgets and informing management decisions, there is a lack of near‐term (5–30 year) forecasts of expected changes in aboveground biomass (AGB). In this study, we forecast AGB changes across the North American boreal forest using machine learning, repeat measurements from 25,000 forest inventory sites, and gridded geospatial datasets. We find that AGB change can be predicted up to 30 years into the future, and that training on sites across the entire domain allows accurate predictions even in regions with only a small amount of existing field data. While predicting AGB loss is less skillful than gains, using a multi‐model ensemble can improve the accuracy in detecting change direction to >90% for observed increases, and up to 70% for observed losses. Higher stem density, winter temperatures, and the presence of temperate tree species in forest plots were positively associated with AGB change, whereas greater initial biomass, continentality (difference between mean summer and winter temperatures), prevalence of black spruce (Picea mariana), summer precipitation, and early warning metrics from long‐term remote sensing time series were negatively associated with AGB change. Across the domain, we predict nondisturbance‐induced declines in AGB at 23% of sites by 2030. The approach developed here can be used to estimate near‐future forest biomass in boreal North America and inform relevant management decisions. Our study also highlights the power of machine learning multi‐model ensembles when trained on a large volume of forest inventory plots, which could be applied to other regions with adequate plot density and spatial coverage. 

Conifer forests historically have been resilient to wildfires in part due to thick organic soil layers that regulate combustion and post-fire moisture and vegetation change. However, recent shifts in fire activity in western North America may be overwhelming these resilience mechanisms with potential impacts for energy and carbon exchange. Here, we quantify the long-term recovery of the organic soil layer and its carbon pools across 511 forested plots. Our plots span ~ 140,000 km2 across two ecozones of the Northwest Territories, Canada, and allowed us to investigate the impacts of time-after-fire, site moisture class, and dominant canopy type on soil organic layer thickness and associated carbon stocks. Despite thinner soil organic layers in xeric plots immediately after fire, these drier stands supported faster post-fire recovery of the soil organic layer than in mesic plots. Unlike xeric or mesic stands, post-fire soil carbon accumulation rates in hydric plots were negligible despite wetter forested plots having greater soil organic carbon stocks immediately post-fire compared to other stands. While permafrost and high-water tables inhibit combustion and maintain thick organic soils immediately after fire, our results suggest that these wet stands are not recovering their pre-fire carbon stocks on a century timescale. We show that canopy conversion from black spruce to jack pine or deciduous dominance could reduce organic soil carbon stocks by 60–80% depending on stand age. Our two main findings—decreasing organic soil carbon storage with increasing deciduous cover and the lack of post-fire SOL recovery in hydric sites—have implications for the turnover time of carbon stocks in the western boreal forest region and also will impact energy fluxes by controlling albedo and surface soil moisture. 

Vast amounts of organic carbon are stored in Arctic soils. Much of this is in the form of peat, a layer of decomposing plant matter. Arctic wildfires release this carbon to the atmosphere as carbon dioxide (CO 2 ) ( 1 ) and contribute to global warming. This creates a feedback loop in which accelerated Arctic warming ( 2 ) dries peatland soils, which increases the likelihood of bigger, more frequent wildfires in the Arctic and releases more CO 2 , which further contributes to warming. Although this feedback mechanism is qualitatively understood, there remain uncertainties about its details. On page 532 of this issue, Descals et al. ( 3 ) analyze data from the 2019 and 2020 wildfire seasons in the Siberian Arctic and predict the extent of carbon-rich soils likely to burn in the area with future warming. Critically, they suggest that even minor increases in temperature above certain thresholds may promote increasingly larger wildfires. 

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.