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High-Resolution Spatio-Temporal Estimation of Net Ecosystem Exchange in Ice-Wedge Polygon Tundra Using In Situ Sensors and Remote Sensing Data

Author

Listed:
  • Haruko M. Wainwright

    (Earth and Environmental Sciences Area, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA)

  • Rusen Oktem

    (Earth and Environmental Sciences Area, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
    Department of Earth and Planetary Science, University of California, Berkeley, CA 94720, USA)

  • Baptiste Dafflon

    (Earth and Environmental Sciences Area, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA)

  • Sigrid Dengel

    (Earth and Environmental Sciences Area, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA)

  • John B. Curtis

    (Department of Geography, University of Colorado, Boulder, CO 80309, USA)

  • Margaret S. Torn

    (Earth and Environmental Sciences Area, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA)

  • Jessica Cherry

    (Alaska-Pacific River Forecast Center, National Oceanic and Atmospheric Administration, Anchorage, AK 99502, USA)

  • Susan S. Hubbard

    (Earth and Environmental Sciences Area, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA)

Abstract

Land-atmosphere carbon exchange is known to be extremely heterogeneous in arctic ice-wedge polygonal tundra regions. In this study, a Kalman filter-based method was developed to estimate the spatio-temporal dynamics of daytime average net ecosystem exchange (NEEday) at 0.5-m resolution over a 550 m by 700 m study site. We integrated multi-scale, multi-type datasets, including normalized difference vegetation indices (NDVIs) obtained from a novel automated mobile sensor system (or tram system) and a greenness index map obtained from airborne imagery. We took advantage of the significant correlations between NDVI and NEEday identified based on flux chamber measurements. The weighted average of the estimated NEEday within the flux-tower footprint agreed with the flux tower data in term of its seasonal dynamics. We then evaluated the spatial variability of the growing season average NEEday, as a function of polygon geomorphic classes; i.e., the combination of polygon types—which are known to present different degradation stages associated with permafrost thaw—and microtopographic features (i.e., troughs, centers and rims). Our study suggests the importance of considering microtopographic features and their spatial coverage in computing spatially aggregated carbon exchange.

Suggested Citation

  • Haruko M. Wainwright & Rusen Oktem & Baptiste Dafflon & Sigrid Dengel & John B. Curtis & Margaret S. Torn & Jessica Cherry & Susan S. Hubbard, 2021. "High-Resolution Spatio-Temporal Estimation of Net Ecosystem Exchange in Ice-Wedge Polygon Tundra Using In Situ Sensors and Remote Sensing Data," Land, MDPI, vol. 10(7), pages 1-19, July.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:7:p:722-:d:591282
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    References listed on IDEAS

    as
    1. Wikle C. K. & Milliff R. F. & Nychka D. & Berliner L.M., 2001. "Spatiotemporal Hierarchical Bayesian Modeling Tropical Ocean Surface Winds," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 382-397, June.
    2. Edward A. G. Schuur & Jason G. Vogel & Kathryn G. Crummer & Hanna Lee & James O. Sickman & T. E. Osterkamp, 2009. "The effect of permafrost thaw on old carbon release and net carbon exchange from tundra," Nature, Nature, vol. 459(7246), pages 556-559, May.
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