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

Baptiste Dafflon, Rusen Oktem, John Peterson, Craig Ulrich, Anh Phuong Tran, Vladimir Romanovsky, Susan S. Hubbard

Research output: Contribution to journalArticlepeer-review

45 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)1321-1342
Number of pages22
JournalJournal of Geophysical Research: Biogeosciences
Volume122
Issue number6
DOIs
StatePublished - Jun 1 2017
Externally publishedYes

Funding

The Next-Generation Ecosystem Experiments (NGEE-Arctic) project is supported by the Office of Biological and Environmental Research in the DOE Office of Science. This NGEE-Arctic research is supported through contract number DE-AC02-05CH11231 to Lawrence Berkeley National Laboratory. Logistical support in Barrow was provided by UMIAQ, LLC. The authors thank Bill Cable (University of Alaska at Fairbanks) for helping to install thermistors and providing soil temperature data, Stan Wullschleger (NGEE-Arctic PI, ORNL) for support and field assistance, A. Kemna (University of Bonn) for providing 2-D complex resistivity imaging codes, and C. Tweedie and S. Vargas (University of Texas at El Paso) for providing advice about kite-based aerial imaging. Data sets are available upon request by contacting the corresponding author (Baptiste Dafflon, [email protected]) and from the NGEE-Arctic data repository [Dafflon et al.,] (https://doi.org/10.5440/1355348).

FundersFunder number
UMIAQ
University of Texas
National Science Foundation1304271
Office of ScienceDE-AC02-05CH11231
Biological and Environmental Research
Oak Ridge National Laboratory
University of Alaska Fairbanks
Rheinische Friedrich-Wilhelms-Universität Bonn

    Keywords

    • Arctic
    • aerial imaging
    • codynamics
    • permafrost
    • soil moisture
    • subsurface imaging

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