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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.

 

Climate warming is altering the persistence, timing, and distribution of permafrost and snow cover across the terrestrial northern hemisphere. These cryospheric changes have numerous consequences, not least of which are positive climate feedbacks associated with lowered albedo related to declining snow cover, and greenhouse gas emissions from permafrost thaw. Given the large land areas affected, these feedbacks have the potential to impact climate on a global scale. Understanding the magnitudes and rates of changes in permafrost and snow cover is therefore integral for process understanding and quantification of climate change. However, while permafrost and snow cover are largely controlled by climate, their distributions and climate impacts are influenced by numerous interrelated ecosystem processes that also respond to climate and are highly heterogeneous in space and time. In this perspective we highlight ongoing and emerging changes in ecosystem processes that mediate how permafrost and snow cover interact with climate. We focus on larch forests in northeastern Siberia, which are expansive, ecologically unique, and studied less than other Arctic and subarctic regions. Emerging fire regime changes coupled with high ground ice have the potential to foster rapid regional changes in vegetation and permafrost thaw, with important climate feedback implications. 

Wildfire is an essential disturbance agent that creates burn mosaics, or a patchwork of burned and unburned areas across the landscape. Unburned patches, fire refugia, serve as carbon sinks and seed sources for forest regeneration in burned areas. In the Cajander larch (Larix cajanderiMayr.) forests of north‐eastern Siberia, an unprecedented wildfire season in 2020 and little documentation of landscape patch dynamics have resulted in research gaps about the characteristics of fire refugia in northern latitude forests, which are warming faster than other global forest ecosystems. We aim to characterize the 2010 distribution of fire refugia for these forest ecosystems and evaluate their topographic drivers.

North‐eastern Siberia across the North‐east Siberian Taiga and the Cherskii‐Kolyma Mountain Tundra ecozones.

2001–2020.

Cajander larch.

We used Landsat imagery to define burned and unburned patches, and the Arctic digital elevation model to calculate topographic variables. We characterized the size and density of fire refugia. We sampled individual pixels (n = 80,000) from an image stack that included a binary burned/unburned, elevation, slope, aspect, topographic position index, ruggedness, and tree cover from 2001 to 2020. We evaluated the topographic drivers of fire refugia with boosted regression trees.

We found no substantial difference in fire refugia size and density across the region. The fire refugia size averaged 7.2 ha (0.09–150,439 ha). The majority of interior burned patches exceed the potential wind dispersal distance from fire refugia. Topographic position index and terrain steepness were important predictors of fire refugia.

Unprecedented wildfires in 2020 did not impact fire refugia formation. Fire refugia are strongly controlled by topographic positions such as uplands and lowlands that influence microsite hydrological conditions. Fire refugia contribute to postfire landscape heterogeneity that preserves ecosystem functions, seed sources, habitat, and carbon sinks.

 

The ability to monitor post-fire ecological responses and associated vegetation cover change is crucial to understanding how boreal forests respond to wildfire under changing climate conditions. Uncrewed aerial vehicles (UAVs) offer an affordable means of monitoring post-fire vegetation recovery for boreal ecosystems where field campaigns are spatially limited, and available satellite data are reduced by short growing seasons and frequent cloud cover. UAV data could be particularly useful across data-limited regions like the Cajander larch (Larix cajanderi Mayr.) forests of northeastern Siberia that are susceptible to amplified climate warming. Cajander larch forests require fire for regeneration but are also slow to accumulate biomass post-fire; thus, tall shrubs and other understory vegetation including grasses, mosses, and lichens dominate for several decades post-fire. Here we aim to evaluate the ability of two vegetation indices, one based on the visible spectrum (GCC; Green Chromatic Coordinate) and one using multispectral data (NDVI; Normalized Difference Vegetation Index), to predict field-based vegetation measures collected across post-fire landscapes of high-latitude Cajander larch forests. GCC and NDVI showed stronger linkages with each other at coarser spatial resolutions e.g., pixel aggregated means with 3-m, 5-m and 10-m radii compared to finer resolutions (e.g., 1-m or less). NDVI was a stronger predictor of aboveground carbon biomass and tree basal area than GCC. NDVI showed a stronger decline with increasing distance from the unburned edge into the burned forest. Our results show NDVI tended to be a stronger predictor of some field-based measures and while GCC showed similar relationships with the data, it was generally a weaker predictor of field-based measures for this region. Our findings show distinguishable edge effects and differentiation between burned and unburned forests several decades post-fire, which corresponds to the relatively slow accumulation of biomass for this ecosystem post-fire. These findings show the utility of UAV data for NDVI in this region as a tool for quantifying and monitoring the post-fire vegetation dynamics in Cajander larch forests.