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1. Shortened Fire Intervals Stimulate Carbon Losses from Heterotrophic Respiration and Reduce Understorey Plant Productivity in Boreal Forests

   https://doi.org/10.1007/s10021-022-00761-w  

   Shabaga, Jason A. ; Bracho, Rosvel ; Klockow, Paul A. ; Lucash, Melissa S. ; Vogel, Jason G. ( May 2022 , Ecosystems)

   Fire frequency is increasing with climate warming in the boreal regions of interior Alaska, with short fire return intervals (< 50 years) becoming more common. Recent studies suggest these “reburns” will reduce the insulating surface organic layer (SOL) and seedbanks, inhibiting black spruce regeneration and increasing deciduous cover. These changes are projected to amplify soil warming, increasing mineral soil organic carbon (SOC) decomposition rates, and impair re-establishment of understorey vegetation and the SOL. We examined how reburns changed soil temperature, heterotrophic soil respiration (RH), and understorey gross primary production (GPP), and related these to shifts in vegetation composition and SOL depths. Two distinct burn complexes previously covered by spruce were measured; both included areas burned 1x, 2x, and 3x over 60 years and mature (≈ 90 year old) spruce forests underlain by permafrost. A 2.7 °C increase in annual near-surface soil temperatures from 1x to 3x burns was correlated with a decrease in SOL depths and a 1.9 Mg C ha⁻¹increase in annual RH efflux. However, near-surface soil warming accounted for ≤ 23% of higher RH efflux; increases in deciduous overstorey vegetation and root biomass with reburning better correlated with RH than soil temperature. Reburning also warmed deeper soils and reduced the biomass and GPP of understory plants,more »lessening their potential to offset elevated RH and contribute to SOL development. This suggests that reburning led to losses of mineral SOC previously stored in permafrost due to warming soils and changes in vegetation composition, illustrating how burn frequency creates pathways for accelerated regional C loss.

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2. 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)

   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 graduallymore »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.« less
3. Fires on Ice: Emerging Permafrost Peatlands Fire Regimes in Russia’s Subarctic Taiga

   https://doi.org/10.3390/land11030322  

   Kuklina, Vera ; Sizov, Oleg ; Rasputina, Elena ; Bilichenko, Irina ; Krasnoshtanova, Natalia ; Bogdanov, Viktor ; Petrov, Andrey N. ( March 2022 , Land)

   Wildfires in permafrost areas, including smoldering fires (e.g., “zombie fires”), have increasingly become a concern in the Arctic and subarctic. Their detection is difficult and requires ground truthing. Local and Indigenous knowledge are becoming useful sources of information that could guide future research and wildfire management. This paper focuses on permafrost peatland fires in the Siberian subarctic taiga linked to local communities and their infrastructure. It presents the results of field studies in Evenki and old-settler communities of Tokma and Khanda in the Irkutsk region of Russia in conjunction with concurrent remote sensing data analysis. The study areas located in the discontinuous permafrost zone allow examination of the dynamics of wildfires in permafrost peatlands and adjacent forested areas. Interviews revealed an unusual prevalence and witness-observed characteristics of smoldering peatland fires over permafrost, such as longer than expected fire risk periods, impacts on community infrastructure, changes in migration of wild animals, and an increasing number of smoldering wildfires including overwintering “zombie fires” in the last five years. The analysis of concurrent satellite remote sensing data confirmed observations from communities, but demonstrated a limited capacity of satellite imagery to accurately capture changing wildfire activity in permafrost peatlands, which may have significant implicationsmore »for global climate.« less
4. Land Cover Change in the Lower Yenisei River Using Dense Stacking of Landsat Imagery in Google Earth Engine

   https://doi.org/10.3390/rs10081226  

   E. Nyland, Kelsey ; E. Gunn, Grant ; I. Shiklomanov, Nikolay ; N. Engstrom, Ryan ; A. Streletskiy, Dmitry ( August 2018 , Remote Sensing)

   Climate warming is occurring at an unprecedented rate in the Arctic due to regional amplification, potentially accelerating land cover change. Measuring and monitoring land cover change utilizing optical remote sensing in the Arctic has been challenging due to persistent cloud and snow cover issues and the spectrally similar land cover types. Google Earth Engine (GEE) represents a powerful tool to efficiently investigate these changes using a large repository of available optical imagery. This work examines land cover change in the Lower Yenisei River region of arctic central Siberia and exemplifies the application of GEE using the random forest classification algorithm for Landsat dense stacks spanning the 32-year period from 1985 to 2017, referencing 1641 images in total. The semiautomated methodology presented here classifies the study area on a per-pixel basis utilizing the complete Landsat record available for the region by only drawing from minimally cloud- and snow-affected pixels. Climatic changes observed within the study area’s natural environments show a statistically significant steady greening (~21,000 km2 transition from tundra to taiga) and a slight decrease (~700 km2) in the abundance of large lakes, indicative of substantial permafrost degradation. The results of this work provide an effective semiautomated classification strategy for remotemore »sensing in permafrost regions and map products that can be applied to future regional environmental modeling of the Lower Yenisei River region.« less
5. Evaluating Post-Fire Vegetation Recovery in Cajander Larch Forests in Northeastern Siberia Using UAV Derived Vegetation Indices

   https://doi.org/10.3390/rs12182970  

   Talucci, Anna C. ; Forbath, Elena ; Kropp, Heather ; Alexander, Heather D. ; DeMarco, Jennie ; Paulson, Alison K. ; Zimov, Nikita S. ; Zimov, Sergei ; Loranty, Michael M. ( September 2020 , Remote Sensing)

   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 amore »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.« less