Permafrost degradation in the Western Russian Arctic

Vasiliev, Alexander; Drozdov, Dmitry; Gravis, Andrey; Малкова, Г. В.; Nyland, Kelsey E.; Streletskiy, D. A.

doi:10.1088/1748-9326/ab6f12

Cited by 82 publications

(39 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This study, however, does not preclude in situ permafrost pore water remineralization or extensive thaw. Active layer deepening and degradation of permafrost soils and associated pore water could in fact represent a more dominant form of OC loss given its high bioavailability (Åkerman & Johansson, 2008; Schuur et al., 2015; Vasiliev et al., 2020; Vonk et al., 2015). The end result being permafrost DOC degrades releasing CO 2 from the terrestrial surface to the atmosphere.…”

Section: Discussionmentioning

confidence: 99%

Limited Presence of Permafrost Dissolved Organic Matter in the Kolyma River, Siberia Revealed by Ramped Oxidation

et al. 2021

View full text Add to dashboard Cite

Temperatures in the Arctic are increasing at twice the global average rate of warming (IPCC, 2013). Efforts to quantify the amount and fate of permafrost dissolved organic carbon (DOC) input into major Arctic rivers are increasingly important as the Arctic warms and permafrost thaw rates increase. Permafrost soils in the Arctic hold approximately twice as much carbon as the atmosphere at an estimated 1,330-1,580 Pg within

show abstract

Section: Discussionmentioning

confidence: 99%

Limited Presence of Permafrost Dissolved Organic Matter in the Kolyma River, Siberia Revealed by Ramped Oxidation

et al. 2021

View full text Add to dashboard Cite

show abstract

“…This suggests more active terrestrial C processing in inland waters of permafrost peatlands in European tundra compared to western Siberia. Because the permafrost in BZT is essentially discontinuous to sporadic, and the warming is more pronounced than in the WSL (Vasiliev et al 2020), lakes of BZT could be expected to experience stronger and faster response to warming and permafrost thaw compared to those in western Siberia. Upscaling the average C emissions of European tundra and western Siberia peatlands ([14 AE 5] × 10 −6 Tg km −2 yr −1 ) to the overall area of permafrostaffected peatlands (2,864,000 km 2 ; Smith et al 2007) yields a value of 40 AE 14 Tg yr −1 .…”

Section: Regional Yields and Upscale Of Fluxesmentioning

confidence: 99%

Carbon emission from thermokarst lakes in NE European tundra

Zabelina

Shirokova

Klimov

et al. 2020

Limnology & Oceanography

View full text Add to dashboard Cite

Emission of greenhouse gases (GHGs) from inland waters is recognized as highly important and an understudied part of the terrestrial carbon (C) biogeochemical cycle. These emissions are still poorly quantified in subarctic regions that contain vast amounts of surface C in permafrost peatlands. This is especially true in NE European peatlands, located within sporadic to discontinuous permafrost zones which are highly vulnerable to thaw. Initial measurements of C emissions from lentic waters of the Bolshezemelskaya Tundra (BZT; 200,000 km 2) demonstrated sizable CO 2 and CH 4 concentrations and fluxes to the atmosphere in 98 depressions, thaw ponds, and thermokarst lakes ranging from 0.5 × 10 6 to 5 × 10 6 m 2 in size. CO 2 fluxes decreased by an order of magnitude as waterbody size increased by > 3 orders of magnitude while CH 4 fluxes showed large variability unrelated to lake size. By using a combination of Landsat-8 and GeoEye-1 images, we determined lakes cover 4% of BZT and thus calculated overall C emissions from lentic waters to be 3.8 AE 0.65 Tg C yr −1 (99% C-CO 2 , 1% C-CH 4), which is two times higher than the lateral riverine export. Large lakes dominated GHG emissions whereas small thaw ponds had a minor contribution to overall water surface area and GHG emissions. These data suggest that, if permafrost thaw in NE Europe results in disappearance of large thermokarst lakes and formation of new small thaw ponds and depressions, GHG emissions from lentic waters in this region may decrease.

show abstract

“…The changing climate of the Arctic, with both measured and projected air temperatures and precipitation rapidly increasing [1,2], has a significant impact on permafrost [3][4][5]. As permafrost soils store about twice the amount of carbon as that found in the atmosphere [6,7], permafrost thaw and resulting carbon feedbacks are expected to have a significant impact on the global climate [8].…”

Section: Introductionmentioning

confidence: 99%

Developing and Testing a Deep Learning Approach for Mapping Retrogressive Thaw Slumps

et al. 2021

View full text Add to dashboard Cite

In a warming Arctic, permafrost-related disturbances, such as retrogressive thaw slumps (RTS), are becoming more abundant and dynamic, with serious implications for permafrost stability and bio-geochemical cycles on local to regional scales. Despite recent advances in the field of earth observation, many of these have remained undetected as RTS are highly dynamic, small, and scattered across the remote permafrost region. Here, we assessed the potential strengths and limitations of using deep learning for the automatic segmentation of RTS using PlanetScope satellite imagery, ArcticDEM and auxiliary datasets. We analyzed the transferability and potential for pan-Arctic upscaling and regional cross-validation, with independent training and validation regions, in six different thaw slump-affected regions in Canada and Russia. We further tested state-of-the-art model architectures (UNet, UNet++, DeepLabv3) and encoder networks to find optimal model configurations for potential upscaling to continental scales. The best deep learning models achieved mixed results from good to very good agreement in four of the six regions (maxIoU: 0.39 to 0.58; Lena River, Horton Delta, Herschel Island, Kolguev Island), while they failed in two regions (Banks Island, Tuktoyaktuk). Of the tested architectures, UNet++ performed the best. The large variance in regional performance highlights the requirement for a sufficient quantity, quality and spatial variability in the training data used for segmenting RTS across diverse permafrost landscapes, in varying environmental conditions. With our highly automated and configurable workflow, we see great potential for the transfer to active RTS clusters (e.g., Peel Plateau) and upscaling to much larger regions.

show abstract

Permafrost degradation in the Western Russian Arctic

Cited by 82 publications

References 17 publications

Limited Presence of Permafrost Dissolved Organic Matter in the Kolyma River, Siberia Revealed by Ramped Oxidation

Limited Presence of Permafrost Dissolved Organic Matter in the Kolyma River, Siberia Revealed by Ramped Oxidation

Carbon emission from thermokarst lakes in NE European tundra

Developing and Testing a Deep Learning Approach for Mapping Retrogressive Thaw Slumps

Contact Info

Product

Resources

About