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

• Published in: Nature communications Vol. 9; no. 1; pp. 5423 - 11
• Main Authors: Nitze, I., Grosse, G., Jones, B. M., Romanovsky, V. E., Boike, J.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 21-12-2018; Nature Publishing Group; Nature Portfolio
• Subjects: 704/106/125; 704/106/694; 704/172; 704/47/4113; Abundance; Climate change; Disturbance; Disturbances; Humanities and Social Sciences; Landsat; Landsat satellites; multidisciplinary; Permafrost; Polar environments; Remote sensing; Satellite imagery; Science; Science (multidisciplinary); Time series; Tundra; Arctic region
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-018-07663-3

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 carbon feedback.
The occurrence and distribution of permafrost region disturbances (PRDs) remain poorly resolved across the Arctic and Subarctic. Here, the authors quantify the abundance and distribution of three primary PRDs using a time-series analysis of 30-m resolution Landsat imagery between 1999 and 2014.