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1. Permafrost thaw lake methane flux estimates using GPR

   https://doi.org/https://doi.org/10.1190/gpr2020-024.1  

   Rangel, R. ; Parsekian, A.D. ; Engram, M.J. ; Ohara, N. ; Jones, B.M. ; Anthony, K.M.W. ( November 2020 , 18th International Conference on Ground Penetrating Radar)

   This research demonstrates a new measurement and scaling approach to constrain the estimates of methane (CH4) fluxes emitted from permafrost thaw (thermokarst) lakes. Permafrost is estimated to store about 20% of the total terrestrial carbon (C) stock. Permafrost thawing releases C in part as CH4, however, there are large uncertainties in the global CH4 budget that limit the accuracy of climate change projections. Estimating how much C is released from permafrost is critical to overcome this knowledge gap. Lake CH4 fluxes are estimated by combining direct observations, geophysical mapping and satellite remote sensing along with a scaling strategy based on lake expansion rate. This research contributes to advance the understanding of CH4 fluxes from thermokarst lakes and improve atmospheric C models.
2. Rivers across the Siberian Arctic unearth the patterns of carbon release from thawing permafrost

   https://doi.org/10.1073/pnas.1811797116  

   Wild, Birgit ; Andersson, August ; Bröder, Lisa ; Vonk, Jorien ; Hugelius, Gustaf ; McClelland, James W. ; Song, Wenjun ; Raymond, Peter A. ; Gustafsson, Örjan ( May 2019 , Proceedings of the National Academy of Sciences)

   Climate warming is expected to mobilize northern permafrost and peat organic carbon (PP-C), yet magnitudes and system specifics of even current releases are poorly constrained. While part of the PP-C will degrade at point of thaw to CO 2 and CH 4 to directly amplify global warming, another part will enter the fluvial network, potentially providing a window to observe large-scale PP-C remobilization patterns. Here, we employ a decade-long, high-temporal resolution record of 14 C in dissolved and particulate organic carbon (DOC and POC, respectively) to deconvolute PP-C release in the large drainage basins of rivers across Siberia: Ob, Yenisey, Lena, and Kolyma. The 14 C-constrained estimate of export specifically from PP-C corresponds to only 17 ± 8% of total fluvial organic carbon and serves as a benchmark for monitoring changes to fluvial PP-C remobilization in a warming Arctic. Whereas DOC was dominated by recent organic carbon and poorly traced PP-C (12 ± 8%), POC carried a much stronger signature of PP-C (63 ± 10%) and represents the best window to detect spatial and temporal dynamics of PP-C release. Distinct seasonal patterns suggest that while DOC primarily stems from gradual leaching of surface soils, POC reflects abrupt collapse of deepermore »deposits. Higher dissolved PP-C export by Ob and Yenisey aligns with discontinuous permafrost that facilitates leaching, whereas higher particulate PP-C export by Lena and Kolyma likely echoes the thermokarst-induced collapse of Pleistocene deposits. Quantitative 14 C-based fingerprinting of fluvial organic carbon thus provides an opportunity to elucidate large-scale dynamics of PP-C remobilization in response to Arctic warming.« less
3. Recent warming reverses forty-year decline in catastrophic lake drainage and hastens gradual lake drainage across northern Alaska

   https://doi.org/10.1088/1748-9326/ac3602  

   Lara, Mark J. ; Chen, Yaping ; Jones, Benjamin M. ( November 2021 , Environmental Research Letters)

   Lakes represent as much as ∼25% of the total land surface area in lowland permafrost regions. Though decreasing lake area has become a widespread phenomenon in permafrost regions, our ability to forecast future patterns of lake drainage spanning gradients of space and time remain limited. Here, we modeled the drivers of gradual (steady declining lake area) and catastrophic (temporally abrupt decrease in lake area) lake drainage using 45 years of Landsat observations (i.e. 1975–2019) across 32 690 lakes spanning climate and environmental gradients across northern Alaska. We mapped lake area using supervised support vector machine classifiers and object based image analyses using five-year Landsat image composites spanning 388 968 km². Drivers of lake drainage were determined with boosted regression tree models, using both static (e.g. lake morphology, proximity to drainage gradient) and dynamic predictor variables (e.g. temperature, precipitation, wildfire). Over the past 45 years, gradual drainage decreased lake area between 10% and 16%, but rates varied over time as the 1990s recorded the highest rates of gradual lake area losses associated with warm periods. Interestingly, the number of catastrophically drained lakes progressively decreased at a rate of ∼37% decade⁻¹from 1975–1979 (102–273 lakes draining year⁻¹) to 2010–2014 (3–8 lakes drainingmore »year⁻¹). However this 40 year negative trend was reversed during the most recent time-period (2015–2019), with observations of catastrophic drainage among the highest on record (i.e. 100–250 lakes draining year⁻¹), the majority of which occurred in northwestern Alaska. Gradual drainage processes were driven by lake morphology, summer air and lake temperature, snow cover, active layer depth, and the thermokarst lake settlement index (R²_adj= 0.42, CV = 0.35,p< 0.0001), whereas, catastrophic drainage was driven by the thawing season length, total precipitation, permafrost thickness, and lake temperature (R²_adj= 0.75, CV = 0.67,p< 0.0001). Models forecast a continued decline in lake area across northern Alaska by 15%–21% by 2050. However these estimates are conservative, as the anticipated amplitude of future climate change were well-beyond historical variability and thus insufficient to forecast abrupt ‘catastrophic’ drainage processes. Results highlight the urgency to understand the potential ecological responses and feedbacks linked with ongoing Arctic landscape reorganization.

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4. Repeated Permafrost Formation and Degradation in Boreal Peatland Ecosystems in Relation to Climate Extremes, Fire, Ecological Shifts, and a Geomorphic Legacy

   https://doi.org/10.3390/atmos13081170  

   Jorgenson, Mark Torre ; Kanevskiy, Mikhail ; Roland, Carl ; Hill, Kenneth ; Schirokauer, David ; Stehn, Sarah ; Schroeder, Britta ; Shur, Yuri ( August 2022 , Atmosphere)

   Permafrost formation and degradation creates a highly patchy mosaic of boreal peatland ecosystems in Alaska driven by climate, fire, and ecological changes. To assess the biophysical factors affecting permafrost dynamics, we monitored permafrost and ecological conditions in central Alaska from 2005 to 2021 by measuring weather, land cover, topography, thaw depths, hydrology, soil properties, soil thermal regimes, and vegetation cover between burned (1990 fire) and unburned terrain. Climate data show large variations among years with occasional, extremely warm–wet summers and cold–snowless winters that affect permafrost stability. Microtopography and thaw depth surveys revealed both permafrost degradation and aggradation. Thaw depths were deeper in post-fire scrub compared to unburned black spruce and increased moderately during the last year, but analysis of historical imagery (1954–2019) revealed no increase in thermokarst rates due to fire. Recent permafrost formation was observed in older bogs due to an extremely cold–snowless winter in 2007. Soil sampling found peat extended to depths of 1.5–2.8 m with basal radiocarbon dates of ~5–7 ka bp, newly accumulating post-thermokarst peat, and evidence of repeated episodes of permafrost formation and degradation. Soil surface temperatures in post-fire scrub bogs were ~1 °C warmer than in undisturbed black spruce bogs, and thermokarst bogs andmore »lakes were 3–5 °C warmer than black spruce bogs. Vegetation showed modest change after fire and large transformations after thermokarst. We conclude that extreme seasonal weather, ecological succession, fire, and a legacy of earlier geomorphic processes all affect the repeated formation and degradation of permafrost, and thus create a highly patchy mosaic of ecotypes resulting from widely varying ecological trajectories within boreal peatland ecosystems.« less
5. Scaling waterbody carbon dioxide and methane fluxes in the arctic using an integrated terrestrial-aquatic approach

   https://doi.org/10.1088/1748-9326/acd467  

   Ludwig, Sarah M. ; Natali, Susan M. ; Schade, John D. ; Powell, Margaret ; Fiske, Greg ; Schiferl, Luke D. ; Commane, Roisin ( May 2023 , Environmental Research Letters)

   In the Arctic waterbodies are abundant and rapid thaw of permafrost is destabilizing the carbon cycle and changing hydrology. It is particularly important to quantify and accurately scale aquatic carbon emissions in arctic ecosystems. Recently available high-resolution remote sensing datasets capture the physical characteristics of arctic landscapes at unprecedented spatial resolution. We demonstrate how machine learning models can capitalize on these spatial datasets to greatly improve accuracy when scaling waterbody CO₂and CH₄fluxes across the YK Delta of south-west AK. We found that waterbody size and contour were strong predictors for aquatic CO₂emissions, attributing greater than two-thirds of the influence to the scaling model. Small ponds (<0.001 km²) were hotspots of emissions, contributing fluxes several times their relative area, but were less than 5% of the total carbon budget. Small to medium lakes (0.001–0.1 km²) contributed the majority of carbon emissions from waterbodies. Waterbody CH₄emissions were predicted by a combination of wetland landcover and related drivers, as well as watershed hydrology, and waterbody surface reflectance related to chromophoric dissolved organic matter. When compared to our machine learning approach, traditional scaling methods that did not account for relevant landscape characteristics overestimated waterbody CO₂and CH₄emissions by 26%–79% and 8%–53% respectively. This studymore »demonstrates the importance of an integrated terrestrial-aquatic approach to improving estimates and uncertainty when scaling C emissions in the arctic.

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