Quantifying Carbon Fluxes at High-Resolution in Ice-Wedge Polygon Tundra Using On-the-Ground Sensors and Remote Sensing Data

Quantifying carbon fluxes at submeter resolutions in the Arctic Tundra.

Graph shows that later in the growing season, both NDVI and NEEday decrease significantly at the high-centered polygons centers and rims, while they continue to be high at the ligh-centered polygons centers and troughs.

NEEday (in micro mol/m2/sec) over the NGEE-Arctic site on DOY 210, 2014.

[Reprinted under a Creative Commons Attribution 4.0 International License (CC BY 4.0) from Wainwright, H.M., et al. “High-Resolution Spatio-Temporal Estimation of Net Ecosystem Exchange in Ice-Wedge Polygon Tundra Using In Situ Sensors and Remote Sensing Data.” Land 10 (7), 722 (2021). DOI: 10.3390/land10070722]

The Science

Land-atmosphere carbon exchange is known to be extremely varied in arctic ice-wedge polygonal tundra regions, which cover much of the high-Arctic. Accurate mapping of net ecosystem exchange (NEE) at the resolution that resolves microtopography is needed to quantify the overall NEE as well as to understand the potential effects of geomorphological changes on NEE associated with permafrost thaw. Although there are many new remote sensing and sensor technologies, a major challenge remains integrating all relevant measurements.

The Impact

This new method enables the estimation of daytime ecosystem carbon exchanges at submeter resolution on any given day. In addition, scientists analyzed NEE-day integrated over the growing season, which suggests the importance of considering microtopographic features and their spatial coverage in computing spatially aggregated carbon exchange.

Summary

Land-atmosphere carbon exchange is known to be extremely heterogeneous in arctic ice-wedge polygonal tundra regions. In this study, scientists developed a Kalman filter-based method to estimate the spatio-temporal dynamics of daytime average net ecosystem exchange (NEE-day) at 0.5-m resolution over a 550 m by 700 m study site. Scientists 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. Scientists 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. Scientists then evaluated the spatial variability of the growing season average NEEday, as a function of polygon geomorphic classes, such as 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). This study suggests the importance of considering microtopographic features and their spatial coverage in computing spatially aggregated carbon exchange.

Principal Investigator

Haruko Wainwright
Lawrence Berkeley National Laboratory
[email protected]

Program Manager

Daniel Stover
U.S. Department of Energy, Biological and Environmental Research (SC-33)
Environmental System Science
[email protected]

Funding

The Next-Generation Ecosystem Experiments (NGEE–Arctic) project is supported by the Office of Biological and Environmental Research (BER), within the Department of Energy’s (DOE) Office of Science. This NGEE–Arctic research is supported through contract number DE-AC0205CH11231 to Lawrence Berkeley National Laboratory.

References

Wainwright, H.M., et al. "High-Resolution Spatio-Temporal Estimation of Net Ecosystem Exchange in Ice-Wedge Polygon Tundra Using In Situ Sensors and Remote Sensing Data." Land 10 (7), 722  (2021). https://doi.org/10.3390/land10070722.