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Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic

  • Local observations indicate that climate change and shifting disturbance regimes are causing permafrost degradation. However, the occurrence and distribution of permafrost region disturbances (PRDs) remain poorly resolved across the Arctic and Subarctic. Here we quantify the abundance and distribution of three primary PRDs using time-series analysis of 30-m resolution Landsat imagery from 1999 to 2014. Our dataset spans four continental-scale transects in North America and Eurasia, covering ~10% of the permafrost region. Lake area loss (−1.45%) dominated the study domain with enhanced losses occurring at the boundary between discontinuous and continuous permafrost regions. Fires were the most extensive PRD across boreal regions (6.59%), but in tundra regions (0.63%) limited to Alaska. Retrogressive thaw slumps were abundant but highly localized (<10−5%). Our analysis synergizes the global-scale importance of PRDs. The findings highlight the need to include PRDs in next-generation land surface models to project the permafrost carbonLocal observations indicate that climate change and shifting disturbance regimes are causing permafrost degradation. However, the occurrence and distribution of permafrost region disturbances (PRDs) remain poorly resolved across the Arctic and Subarctic. Here we quantify the abundance and distribution of three primary PRDs using time-series analysis of 30-m resolution Landsat imagery from 1999 to 2014. Our dataset spans four continental-scale transects in North America and Eurasia, covering ~10% of the permafrost region. Lake area loss (−1.45%) dominated the study domain with enhanced losses occurring at the boundary between discontinuous and continuous permafrost regions. Fires were the most extensive PRD across boreal regions (6.59%), but in tundra regions (0.63%) limited to Alaska. Retrogressive thaw slumps were abundant but highly localized (<10−5%). Our analysis synergizes the global-scale importance of PRDs. The findings highlight the need to include PRDs in next-generation land surface models to project the permafrost carbon feedback.show moreshow less

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Metadaten
Author details:Ingmar NitzeORCiDGND, Guido GrosseORCiDGND, Benjamin M. JonesORCiD, Vladimir E. RomanovskyORCiD, Julia BoikeORCiDGND
URN:urn:nbn:de:kobv:517-opus4-426171
DOI:https://doi.org/10.25932/publishup-42617
ISSN:1866-8372
Title of parent work (English):Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe
Publication series (Volume number):Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe (799)
Publication type:Postprint
Language:English
Date of first publication:2019/12/17
Publication year:2019
Publishing institution:Universität Potsdam
Release date:2019/12/17
Tag:Carbon cycle; Climate change; Cryospheric science; Environmental sciences
Issue:799
Number of pages:11
Source:Nature Communications 10 (2019) Art. 472 DOI: 10.1038/s41467-019-08375-y
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät
DDC classification:5 Naturwissenschaften und Mathematik / 50 Naturwissenschaften / 500 Naturwissenschaften und Mathematik
Peer review:Referiert
Publishing method:Open Access
License (German):License LogoCC-BY - Namensnennung 4.0 International
External remark:Bibliographieeintrag der Originalveröffentlichung/Quelle
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