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Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic
摘要： 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.
关键词： permafrost,disturbances,Subarctic,fires,remote sensing,lakes,retrogressive thaw slumps,Arctic
更新于2025-09-23 15:23:52
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Soil organic carbon predictions in Subarctic Greenland by visible–near infrared spectroscopy
摘要： Release of carbon from high-latitude soils to the atmosphere may have significant effects on Earth’s climate. In this contribution, we evaluate visible–near-infrared spectroscopy (vis-NIRS) as a time- and cost-efficient tool for assessing soil organic carbon (SOC) concentrations in South Greenland. Soil samples were collected at two sites and analyzed with vis-NIRS. We used partial least square regression (PLS-R) modeling to predict SOC from vis-NIRS spectra referenced against in situ dry combustion measurements. The ability of our approach was validated in three setups: (1) calibration and validation data sets from the same location, (2) calibration and validation data sets from different locations, and (3) the same setup as in (2) with the calibration model enlarged with few samples from the opposite target area. Vis-NIRS predictions were successful in setup 1 (R2 = 0.95, root mean square error of prediction [RMSEP] = 1.80 percent and R2 = 0.82, RMSEP = 0.64 percent). Predictions in setup 2 had higher errors (R2 = 0.90, RMSEP = 7.13 percent and R2 = 0.78, RMSEP = 2.82 percent). In setup 3, the results were again improved (R2 = 0.95, RMSEP = 2.03 percent and R2 = 0.77, RMSEP = 2.14 percent). We conclude that vis-NIRS can obtain good results predicting SOC concentrations across two subarctic ecosystems, when the calibration models are augmented with few samples from the target site. Future efforts should be made toward determination of SOC stocks to constrain soil–atmosphere carbon exchange.
关键词： visible–near-infrared spectroscopy,subarctic,Soil organic carbon,Greenland
更新于2025-09-12 10:27:22