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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.…
Author details: | Ingmar NitzeORCiDGND, Guido GrosseORCiDGND, Benjamin M. JonesORCiD, Vladimir E. RomanovskyORCiD, Julia BoikeORCiDGND |
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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): | CC-BY - Namensnennung 4.0 International |
External remark: | Bibliographieeintrag der Originalveröffentlichung/Quelle |