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1. North American boreal forests are a large carbon source due to wildfires from 1986 to 2016

   https://doi.org/10.1038/s41598-021-87343-3  

   Zhao, Bailu ; Zhuang, Qianlai ; Shurpali, Narasinha ; Köster, Kajar ; Berninger, Frank ; Pumpanen, Jukka ( December 2021 , Scientific Reports)

   null (Ed.)

   Abstract Wildfires are a major disturbance to forest carbon (C) balance through both immediate combustion emissions and post-fire ecosystem dynamics. Here we used a process-based biogeochemistry model, the Terrestrial Ecosystem Model (TEM), to simulate C budget in Alaska and Canada during 1986–2016, as impacted by fire disturbances. We extracted the data of difference Normalized Burn Ratio (dNBR) for fires from Landsat TM/ETM imagery and estimated the proportion of vegetation and soil C combustion. We observed that the region was a C source of 2.74 Pg C during the 31-year period. The observed C loss, 57.1 Tg C year −1 , was attributed to fire emissions, overwhelming the net ecosystem production (1.9 Tg C year −1 ) in the region. Our simulated direct emissions for Alaska and Canada are within the range of field measurements and other model estimates. As burn severity increased, combustion emission tended to switch from vegetation origin towards soil origin. When dNBR is below 300, fires increase soil temperature and decrease soil moisture and thus, enhance soil respiration. However, the post-fire soil respiration decreases for moderate or high burn severity. The proportion of post-fire soil emission in total emissions increased with burn severity. Net nitrogen mineralization gradually recovered after fire, enhancing net primary production. Net ecosystem production recovered fast under higher burn severities. The impact of fire disturbance on the C balance of northern ecosystems and the associated uncertainties can be better characterized with long-term, prior-, during- and post-disturbance data across the geospatial spectrum. Our findings suggest that the regional source of carbon to the atmosphere will persist if the observed forest wildfire occurrence and severity continues into the future. 

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2. What is the color when black is burned? Quantifying (re)burn severity using field and satellite remote sensing indices

   https://doi.org/10.1186/s42408-023-00178-3  

   Saberi, Saba J. ; Harvey, Brian J. ( April 2023 , Fire Ecology)

   Trends of increasing area burned in many regions worldwide are leading to more locations experiencing short-interval reburns (i.e., fires occurring two or more times in the same place within 1–3 decades). Field and satellite indices of burn severity are well tested in forests experiencing a single recent fire, but the reliability of these indices in short-interval reburns is poorly understood. We tested how a commonly used field index (the Composite Burn Index, CBI) and satellite index (the Relative differenced Normalized Burn Ratio, RdNBR) compared to eight individual field measures of burn severity in short-interval reburns vs. areas burned in one recent fire, and whether results depended on whether the first fire was stand replacing (fire that is lethal to most dominant trees).

   Correspondence between both CBI and RdNBR with individual burn severity measures differed in short-interval reburns compared to single fires for some metrics of burn severity. Divergence in the relationship between both CBI and RdNBR vs. field measures was greatest when short-interval reburns followed a prior stand-replacing fire, and measures were more comparable to single fires when the first fire was non-stand replacing (i.e., lower severity). When short-interval reburns followed prior stand-replacing fires, CBI and RdNBR underestimated burn severity in the second fire for tree-canopy metrics (e.g., canopy cover loss, tree mortality), as young forests in early developmental stages are more sensitive to a second fire. Conversely, when short-interval reburns followed prior less-than-stand-replacing fires, both CBI and RdNBR overestimated burn severity for forest-floor metrics, as past low severity fires leave behind live fire-resistant trees and can stimulate resprouting understory vegetation. Finally, neither CBI nor RdNBR accurately detected deep wood charring—an important phenomenon that occurs in short-interval reburns.

   Our findings inform interpretability of commonly used indices of burn severity in short-interval reburns by identifying how individual burn severity metrics can be under- or over-estimated, depending on the severity of the fire preceding a reburn. Adjustments to burn severity measurements made in short-interval reburns are particularly critical as reburned areas increase.

    

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3. 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)

   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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4. 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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5. Field-Validated Burn-Severity Mapping in North Patagonian Forests

   https://doi.org/10.3390/rs12020214  

   Franco, María Guadalupe ; Mundo, Ignacio A. ; Veblen, Thomas T. ( January 2020 , Remote Sensing)

   Burn severity, which can be reliably estimated by validated spectral indices, is a key element for understanding ecosystem dynamics and informing management strategies. However, in North Patagonian forests, where wildfires are a major disturbance agent, studies aimed at the field validation of spectral indices of burn severity are scarce. The aim of this work was to develop a field validated methodology for burn-severity mapping by studying two large fires that burned in the summer of 2013–2014 in forests of Araucaria araucana and other tree species. We explored the relation between widely used spectral indices and a field burn-severity index, and we evaluated index performance by examining index sensitivity in discriminating burn-severity classes in different vegetation types. For those indices that proved to be suitable, we adjusted the class thresholds and constructed confusion matrices to assess their accuracy. Burn severity maps of the studied fires were generated using the two most accurate methods and were compared to evaluate their level of agreement. Our results confirm that reliable burn severity estimates can be derived from spectral indices for these forests. Two severity indices, the delta normalized burn ratio (dNBR) and delta normalized difference vegetation index (dNDVI), were highly related to the fire-induced changes observed in the field, but the strength of these associations varied across the five different vegetation types defined by tree heights and tree and tall shrub species regeneration strategies. The thresholds proposed in this study for these indices generated classifications with global accuracies of 82% and Kappa indices of 70%. Both the dNBR and dNDVI classification approaches were more accurate in detecting high severity, but to a lesser degree for detecting low severity burns. Moderate severity was poorly classified, with producer and user errors reaching 50%. These constraints, along with detected differences in separability, need to be considered when interpreting burn severity maps generated using these methods. 

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