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1. Modeling changes in Siberian forests under climate change, 2020-2024

   https://doi.org/10.18739/A2D50G04B  

   Lucash, Melissa (April 2025, NSF Arctic Data Center)

   Lucash, Melissa S (Ed.)

   Boreal forests are found at high northern latitudes and form the largest terrestrial biome in the world. They comprise 30-50% of the world’s forest carbon stocks (vs. 14% in temperate forests. Temperatures are increasing rapidly in high northern latitudes (IPCC 2021), resulting in modified disturbance regimes and thawing of permafrost, and the socio-economic pressure to harvest timber is growing in currently unharvested areas. Attempts to predict how these changes will affect boreal forests must account for interactions among multiple disturbances (e.g., wind, insects, fire, harvest), seed dispersal, species growth and competition, and changing climate, and therefore uncertainty persists about how these changes will affect composition and function of this biome. Our objectives for this research were to 1) Use LANDIS-II to project forest dynamics under a range of climate and disturbance scenarios across a latitudinal gradient spanning the Siberian taiga from the arctic tundra to steppe ecotones, 2) Quantify the change in albedo and harvesting across bioclimatic zones and climates, 3) Identify the factor(s) that are the strongest drivers of these changes 

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2. Siberian taiga and tundra fire regimes from 2001–2020

   https://doi.org/10.1088/1748-9326/ac3f07  

   Talucci, Anna C.; Loranty, Michael M.; Alexander, Heather D. (January 2022, Environmental Research Letters)

   Abstract Circum-boreal and -tundra systems are crucial carbon pools that are experiencing amplified warming and are at risk of increasing wildfire activity. Changes in wildfire activity have broad implications for vegetation dynamics, underlying permafrost soils, and ultimately, carbon cycling. However, understanding wildfire effects on biophysical processes across eastern Siberian taiga and tundra remains challenging because of the lack of an easily accessible annual fire perimeter database and underestimation of area burned by MODIS satellite imagery. To better understand wildfire dynamics over the last 20 years in this region, we mapped area burned, generated a fire perimeter database, and characterized fire regimes across eight ecozones spanning 7.8 million km²of eastern Siberian taiga and tundra from ∼61–72.5° N and 100° E–176° W using long-term satellite data from Landsat, processed via Google Earth Engine. We generated composite images for the annual growing season (May–September), which allowed mitigation of missing data from snow-cover, cloud-cover, and the Landsat 7 scan line error. We used annual composites to calculate the difference Normalized Burn Ratio (dNBR) for each year. The annual dNBR images were converted to binary burned or unburned imagery that was used to vectorize fire perimeters. We mapped 22 091 fires burning 152 million hectares (Mha) over 20 years. Although 2003 was the largest fire year on record, 2020 was an exceptional fire year for four of the northeastern ecozones resulting in substantial increases in fire activity above the Arctic Circle. Increases in fire extent, severity, and frequency with continued climate warming will impact vegetation and permafrost dynamics with increased likelihood of irreversible permafrost thaw that leads to increased carbon release and/or conversion of forest to shrublands. 

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3. Impacts of pre-fire conifer density and wildfire severity on ecosystem structure and function at the forest-tundra ecotone

   https://doi.org/10.1371/journal.pone.0258558  

   Walker, Xanthe J.; Howard, Brain K.; Jean, Mélanie; Johnstone, Jill F.; Roland, Carl; Rogers, Brendan M.; Schuur, Edward A.; Solvik, Kylen K.; Mack, Michelle C. (October 2021, PLOS ONE)

   Hui, Dafeng (Ed.)

   Wildfire frequency and extent is increasing throughout the boreal forest-tundra ecotone as climate warms. Understanding the impacts of wildfire throughout this ecotone is required to make predictions of the rate and magnitude of changes in boreal-tundra landcover, its future flammability, and associated feedbacks to the global carbon (C) cycle and climate. We studied 48 sites spanning a gradient from tundra to low-density spruce stands that were burned in an extensive 2013 wildfire on the north slope of the Alaska Range in Denali National Park and Preserve, central Alaska. We assessed wildfire severity and C emissions, and determined the impacts of severity on understory vegetation composition, conifer tree recruitment, and active layer thickness (ALT). We also assessed conifer seed rain and used a seeding experiment to determine factors controlling post-fire tree regeneration. We found that an average of 2.18 ± 1.13 Kg C m -2 was emitted from this fire, almost 95% of which came from burning of the organic soil. On average, burn depth of the organic soil was 10.6 ± 4.5 cm and both burn depth and total C combusted increased with pre-fire conifer density. Sites with higher pre-fire conifer density were also located at warmer and drier landscape positions and associated with increased ALT post-fire, greater changes in pre- and post-fire understory vegetation communities, and higher post-fire boreal tree recruitment. Our seed rain observations and seeding experiment indicate that the recruitment potential of conifer trees is limited by seed availability in this forest-tundra ecotone. We conclude that the expected climate-induced forest infilling (i.e. increased density) at the forest-tundra ecotone could increase fire severity, but this infilling is unlikely to occur without increases in the availability of viable seed. 

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4. Sublimation measurements of tundra and taiga snowpack in Alaska

   https://doi.org/10.5194/tc-19-1739-2025  

   Stockert, Kelsey A; Euskirchen, Eugénie S; Stuefer, Svetlana L (May 2025, The Cryosphere)

   na (Ed.)

   Abstract. Snow sublimation plays a fundamental role in the winter water balance. To date, few studies have quantified sublimation in tundra and boreal forest snow by direct measurements. Continuous latent heat data collected with eddy covariance (EC) measurements from 2010–2021 were used to calculate snow sublimation at six locations in northern Alaska: three Arctic tundra sites at distinct topographical and vegetation communities in the Imnavait Creek watershed on the North Slope underlain by continuous permafrost, and three lowland boreal forest/taiga sites in discontinuous permafrost in interior Alaska near Fairbanks. Mean surface sublimation rates range from 0.08–0.15 mm d−1 and 15–27 mm yr−1 at the six sites, representing, on average, 21 % of the measured solid precipitation and 8 %–16 % of the cumulative annual water vapor flux to the atmosphere (evaporation plus sublimation). The mean daily sublimation rates of the lowland boreal forest sites are higher than those of the tundra sites, but the longer snow cover period of the tundra sites leads to greater mean annual sublimation rates. We examined the potential controls, drivers, and trends of the sublimation rates by using meteorological data collected in conjunction with EC measurements. This research improves our understanding of how site conditions affect sublimation rates and highlights the fact that sublimation is a substantial component of the winter hydrologic cycle. In addition, the study contributes to the sparse literature on tundra and boreal sublimation measurements, and the measured rates are comparable to sublimation estimates in other northern climates. 

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5. Fire perimeters for eastern Siberia taiga and tundra from 2001-2020

   https://doi.org/10.18739/A2GB1XJ4M  

   Talucci, Anna; Loranty, Michael; Alexander, Heather (January 2021, NSF Arctic Data Center)

   We developed a fire perimeter dataset for eastern Siberian taiga and tundra zones from 2001-2020 based on Landsat imagery. Our study area spanned 7.8 million square kilometers across eight ecozones of eastern Siberian taiga and tundra from approximately 61-72.5°North (N) and 100°East (E)-176°West (W). We used the cloud computing power of Google Earth Engine to access the Landsat archive. We generated composite images for the annual growing season (May - September), which allowed us to mitigate missing data from snow-cover, cloud-cover, and the Landsat 7 scan line error. We used annual composites to calculate the difference Normalized Burn Ratio (dNBR) for each year. Finally, we converted the annual dNBR images to binary burned or unburned imagery that was used to vectorize fire perimeters. We map 22,110 fires burning 150.5 million hectares over 20 years. 

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