Coincident aboveground and belowground autonomous monitoring to quantify covariability in permafrost, soil, and vegetation properties in Arctic tundra

©2017. American Geophysical Union. All Rights Reserved. Coincident monitoring of the spatiotemporal distribution of and interactions between land, soil, and permafrost properties is important for advancing our understanding of ecosystem dynamics. In this study, a novel monitoring strategy was develo...

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Published in:Journal of Geophysical Research: Biogeosciences
Main Authors: Dafflon, B, Oktem, R, Peterson, J, Ulrich, C, Tran, AP, Romanovsky, V, Hubbard, SS
Format: Article in Journal/Newspaper
Language:English
Published: eScholarship, University of California 2017
Subjects:
Online Access:http://www.escholarship.org/uc/item/0pt5x6bq
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spelling ftcdlib:qt0pt5x6bq 2023-05-15T14:26:40+02:00 Coincident aboveground and belowground autonomous monitoring to quantify covariability in permafrost, soil, and vegetation properties in Arctic tundra Dafflon, B Oktem, R Peterson, J Ulrich, C Tran, AP Romanovsky, V Hubbard, SS 1321 - 1342 2017-06-01 application/pdf http://www.escholarship.org/uc/item/0pt5x6bq english eng eScholarship, University of California qt0pt5x6bq http://www.escholarship.org/uc/item/0pt5x6bq public Dafflon, B; Oktem, R; Peterson, J; Ulrich, C; Tran, AP; Romanovsky, V; et al.(2017). Coincident aboveground and belowground autonomous monitoring to quantify covariability in permafrost, soil, and vegetation properties in Arctic tundra. Journal of Geophysical Research: Biogeosciences, 122(6), 1321 - 1342. doi:10.1002/2016JG003724. Lawrence Berkeley National Laboratory: Retrieved from: http://www.escholarship.org/uc/item/0pt5x6bq article 2017 ftcdlib https://doi.org/10.1002/2016JG003724 2018-09-28T22:52:42Z ©2017. American Geophysical Union. All Rights Reserved. Coincident monitoring of the spatiotemporal distribution of and interactions between land, soil, and permafrost properties is important for advancing our understanding of ecosystem dynamics. In this study, a novel monitoring strategy was developed to quantify complex Arctic ecosystem responses to the seasonal freeze-thaw-growing season conditions. The strategy exploited autonomous measurements obtained through electrical resistivity tomography to monitor soil properties, pole-mounted optical cameras to monitor vegetation dynamics, point probes to measure soil temperature, and periodic manual measurements of thaw layer thickness, snow thickness, and soil dielectric permittivity. The spatially and temporally dense monitoring data sets revealed several insights about tundra system behavior at a site located near Barrow, AK. In the active layer, the soil electrical conductivity (a proxy for soil water content) indicated an increasing positive correlation with the green chromatic coordinate (a proxy for vegetation vigor) over the growing season, with the strongest correlation (R = 0.89) near the typical peak of the growing season. Soil conductivity and green chromatic coordinate also showed significant positive correlations with thaw depth, which is influenced by soil and surface properties. In the permafrost, soil electrical conductivity revealed annual variations in solute concentration and unfrozen water content, even at temperatures well below 0°C in saline permafrost. These conditions may contribute to an acceleration of long-term thaw in Coastal permafrost regions. Demonstration of this first aboveground and belowground geophysical monitoring approach within an Arctic ecosystem illustrates its significant potential to remotely “visualize” permafrost, soil, and vegetation ecosystem codynamics in high resolution over field relevant scales. Article in Journal/Newspaper Arctic Arctic permafrost Tundra University of California: eScholarship Arctic Journal of Geophysical Research: Biogeosciences 122 6 1321 1342
institution Open Polar
collection University of California: eScholarship
op_collection_id ftcdlib
language English
description ©2017. American Geophysical Union. All Rights Reserved. Coincident monitoring of the spatiotemporal distribution of and interactions between land, soil, and permafrost properties is important for advancing our understanding of ecosystem dynamics. In this study, a novel monitoring strategy was developed to quantify complex Arctic ecosystem responses to the seasonal freeze-thaw-growing season conditions. The strategy exploited autonomous measurements obtained through electrical resistivity tomography to monitor soil properties, pole-mounted optical cameras to monitor vegetation dynamics, point probes to measure soil temperature, and periodic manual measurements of thaw layer thickness, snow thickness, and soil dielectric permittivity. The spatially and temporally dense monitoring data sets revealed several insights about tundra system behavior at a site located near Barrow, AK. In the active layer, the soil electrical conductivity (a proxy for soil water content) indicated an increasing positive correlation with the green chromatic coordinate (a proxy for vegetation vigor) over the growing season, with the strongest correlation (R = 0.89) near the typical peak of the growing season. Soil conductivity and green chromatic coordinate also showed significant positive correlations with thaw depth, which is influenced by soil and surface properties. In the permafrost, soil electrical conductivity revealed annual variations in solute concentration and unfrozen water content, even at temperatures well below 0°C in saline permafrost. These conditions may contribute to an acceleration of long-term thaw in Coastal permafrost regions. Demonstration of this first aboveground and belowground geophysical monitoring approach within an Arctic ecosystem illustrates its significant potential to remotely “visualize” permafrost, soil, and vegetation ecosystem codynamics in high resolution over field relevant scales.
format Article in Journal/Newspaper
author Dafflon, B
Oktem, R
Peterson, J
Ulrich, C
Tran, AP
Romanovsky, V
Hubbard, SS
spellingShingle Dafflon, B
Oktem, R
Peterson, J
Ulrich, C
Tran, AP
Romanovsky, V
Hubbard, SS
Coincident aboveground and belowground autonomous monitoring to quantify covariability in permafrost, soil, and vegetation properties in Arctic tundra
author_facet Dafflon, B
Oktem, R
Peterson, J
Ulrich, C
Tran, AP
Romanovsky, V
Hubbard, SS
author_sort Dafflon, B
title Coincident aboveground and belowground autonomous monitoring to quantify covariability in permafrost, soil, and vegetation properties in Arctic tundra
title_short Coincident aboveground and belowground autonomous monitoring to quantify covariability in permafrost, soil, and vegetation properties in Arctic tundra
title_full Coincident aboveground and belowground autonomous monitoring to quantify covariability in permafrost, soil, and vegetation properties in Arctic tundra
title_fullStr Coincident aboveground and belowground autonomous monitoring to quantify covariability in permafrost, soil, and vegetation properties in Arctic tundra
title_full_unstemmed Coincident aboveground and belowground autonomous monitoring to quantify covariability in permafrost, soil, and vegetation properties in Arctic tundra
title_sort coincident aboveground and belowground autonomous monitoring to quantify covariability in permafrost, soil, and vegetation properties in arctic tundra
publisher eScholarship, University of California
publishDate 2017
url http://www.escholarship.org/uc/item/0pt5x6bq
op_coverage 1321 - 1342
geographic Arctic
geographic_facet Arctic
genre Arctic
Arctic
permafrost
Tundra
genre_facet Arctic
Arctic
permafrost
Tundra
op_source Dafflon, B; Oktem, R; Peterson, J; Ulrich, C; Tran, AP; Romanovsky, V; et al.(2017). Coincident aboveground and belowground autonomous monitoring to quantify covariability in permafrost, soil, and vegetation properties in Arctic tundra. Journal of Geophysical Research: Biogeosciences, 122(6), 1321 - 1342. doi:10.1002/2016JG003724. Lawrence Berkeley National Laboratory: Retrieved from: http://www.escholarship.org/uc/item/0pt5x6bq
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op_doi https://doi.org/10.1002/2016JG003724
container_title Journal of Geophysical Research: Biogeosciences
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