Sources: Haruko Wainwright, Susan Hubbard, Dan Hawkes
By taking advantage of the broad range of scientific skills within their interdisciplinary team, investigators for the Next Generation Ecosystem Experiment-Arctic have in recent years led a comprehensive aboveground/belowground characterization of the Arctic tundra ecosystem (near Barrow, Alaska), to explore the spatial distribution of ecosystem properties—relevant to soil carbon decomposition and climate change—in the Barrow landscape. In the most recent of these studies (published in late April 2015 in Journal of Geophysical Research—Biogeosciences), a multidisciplinary team of researchers (led by ESD’s Haruko Wainwright and including ESD’s Baptiste Dafflon, Yuxin Wu, Craig Ulrich, John Peterson, Margaret Torn, and Susan Hubbard) sought to develop an approach to characterize the spatial variability of properties within the Arctic landscape that influence soil respiration of greenhouse gases—to identify ecosystem “functional zones.”
The Arctic tundra currently stores a significant amount of carbon locked in permafrost. The Arctic, however, has experienced the Earth’s greatest regional warming in recent decades, and is projected to warm twice as much as the rest of the globe by the end of the 2lst century. There is great concern that currently stored carbon may be released into the atmosphere as CO2 and CH4, as permafrost degrades.
Large portions of the tundra are covered by ice-wedge polygons, which are a unique, fascinating ground pattern formed by freeze-thaw cycles. Ecosystem properties in ice-wedge polygonal tundra are known to be extremely heterogeneous (e.g., varying in soil temperature, vegetation, soil moisture, biogeochemistry, carbon fluxes), which hinders efforts to understand and predict carbon fluxes and climate feedback. Working along a single transect, the covariation of above- and belowground properties was documented at the NGEE-Site by Hubbard et al. (2013).
In the aforementioned more recent study (Wainwright et al., 2015), investigators used multiscale datasets, including in situ measurements, core analysis, geophysics, and remote sensing data, to characterize the ice-wedge polygonal geomorphology and associated above- and belowground properties at the landscape scale. The team first delineated each polygon, then used a data-mining approach to discover polygon types that have distinct distributions of ecosystem properties—termed ecosystem functional zones—using geophysical and kite-based landscape-imaging datasets. Then they extrapolated those data-discovered zones over the study site, using a digital elevation map derived from LiDARremote sensing. Based on point measurements, they characterized the distribution of vegetation, hydrological, thermal, and geochemical properties, as well as carbon fluxes within each polygon type. Statistical analysis results showed that identified zones could explain the variability of those ecosystem properties over a large-scale landscape.
The significance of the identified functional zones was further validated by detailed biogeochemical analyses. Newman et al. (2015), for example, reported that surface-water and pore-water chemistry showed significant differences among the functional zones, especially for redox sensitive species and nutrients such as dissolved oxygen, nitrate, phosphate, and sulfate. In Tas et al. (2013), 16S rRNA gene sequencing revealed a significant variation in microbial community structures among the functional zones. They also found that the functional zones have distinct metabolic potentials for CH4 production and oxidation.
These studies reveal multiple lines of evidence, suggesting the strong interactions of above- and belowground properties, their influence on the Arctic tundra functioning, and the value of the functional-zone approach for characterizing a range of processes and properties—in sufficient detail and over scales useful for climate modeling. This zonation approach is expected to be useful for improved system understanding, site characterization, and parameterization of numerical models aimed at predicting ecosystem feedbacks to the climate.
The NGEE Arctic project is supported by the Office of Biological and Environmental Research in the DOE Office of Science. Partners include Oak Ridge, Brookhaven, Los Alamos, and Lawrence Berkeley National Laboratory, and the University of Alaska Fairbanks.
To read the most recent NGEE paper (Wainwright et al.), go to: http://onlinelibrary.wiley.com/doi/10.1002/2014JG002799/full
Citations:
Hubbard, S. S., Gangodagamage, C., Dafflon, B., Wainwright, H., Peterson, J. E., Gusmeroli, A., Ulrich, C., Wu, Y., Wilson, C., Rowland, J., Tweedie, C., and S.D. Wullschleger, 2013, Quantifying and relating land-surface and subsurface variability in permafrost environments using LiDAR and surface geophysical datasets, Hydrogeology, doi: 10.1007/s10040-012-0939-y
Wainwright, H.M., B. Dafflon, L.J. Smith, M.S. Hahn, J.B. Curtis, Y. Wu, C. Ulrich, J.E. Peterson, M.S. Torn, and S.S. Hubbard (2015), Identifying multiscale zonation and assessing the relative importance of polygon geomorphology on carbon fluxes in an Arctic Tundra Ecosystem. Journal of Geophysical Research—Biogeosciences, DOI: 10.1002/2014JG002799.
Newman, B.D., H.M. Throckmorton, D.E. Graham, B. Gu, S.S. Hubbard, L. Liang, Y. Wu, J.M. Heikoop, E.M. Herndon, T.J. Phelps, C.J. Wilson, and S.D. Wullschleger (2015), Microtopographic and depth controls on active layer chemistry in Arctic polygonal ground. Geophysical Research Letters, DOI: 10.1002/2014GL062804.
Tas, N., Y. Wu, L.J. Smith, C. Ulrich, T.J Kneafsey, M.S. Torn, S.S. Hubbard, S.D. Wullschleger, and J. Jansson (2013), Integrated metagenomics and field measurements of polygon features at the NGEE-Arctic Barrow site, AGU Fall Meeting Abstracts (Vol. 1, p. 563).