U.S. Department of Energy Office of Biological and Environmental Research

BER Research Highlights


A New Entropy-Based Scheme Reveals Dominant Controls on Greenhouse Gas (GHG) Flux Variability in an Arctic Landscape
Published: February 01, 2019
Posted: February 14, 2019

Soil characteristics, vegetation type, changes in vegetation during the growing season and the onset of seasonal thaw were found to be significant controls on GHG flux variability in a polygonal tundra landscape.

The Science
This study was used to develop, apply and assess a novel entropy-based scheme to characterize temporal variability in greenhouse gases (GHG), i.e., CO2 and CH4 fluxes, and identify controls of such variations in a polygonal tundra landscape near Barrow, Alaska.

The Impact
Arctic tundra environments store a vast amount of soil carbon with an acute possibility that these regions will convert from a global carbon sink to a carbon source under warmer conditions. In estimating future changes to global carbon budgets, it is therefore important to identify key controls and understand the mechanistic nature of GHG flux variations especially in carbon-rich environments. Here, we focus on a polygonal tundra environment - a dominant landscape in the Alaskan Arctic Coastal Plain - that demonstrates significant variability in GHG fluxes across space and time. Results from this study indicate that flat-centered polygons may become important sources of CO2 during warm and dry years, while high-centered polygons may become important during cold and wet years. Moreover, the identification of specific geomorphic, soil, vegetation or climatic factors that explain the most variability in GHG fluxes across three successive years (2012-14) - a dataset with significant variability in soil moisture and temperature - provides important insights on which ecosystem properties may be shifted regionally in a future climate.

Summary
Investigating the degree to which environmental factors can impact GHG fluxes in Arctic tundra environments can be especially complex and difficult to interpret because of complex spatial interactions, temporal shifts and strong interdependencies and feedbacks amongst the many primary controls. A research team from LBNL and NGEE-Arctic developed a novel entropy classification scheme that can disentangle these complex relationships and identify dominant controls on GHG flux variability within an Arctic tundra environment. Entropy analysis indicates that temporal variability in CO2 flux was governed by soil temperature variability, vegetation changes during the early and late growing season, and changes in soil moisture at higher topographic locations. Variability in CH4 flux at the site was primarily associated with vegetation changes during the growing season and temporal shifts in relationships between vegetation and environmental factors such as thaw depth. Further, results indicate that recent temperature trends and increasing length of the growing season may act to increase GHG efflux from the site. In this manner, entropy results can be used to identify mechanistic controls on GHG fluxes that may become important under changing climate.

Contacts (BER PM)
Daniel Stover
SC-23.1
Daniel.Stover@science.doe.gov

(PI Contact)
Susan Hubbard
Lawrence Berkeley National Laboratory
SSHubbard@lbl.gov

Funding
This material is based upon work supported as part of the Next-Generation Ecosystem Experiments (NGEE-Arctic) at Lawrence Berkeley National Laboratory funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research under Award Number DE-AC02-05CH11231.

Publications
Arora, B., Wainwright, H.M., Dwivedi, D., Vaughn, L.J., Curtis, J.B., Torn, M.S., Dafflon, B. and Hubbard, S.S. “Evaluating temporal controls on greenhouse gas (GHG) fluxes in an Arctic tundra environment: An entropy-based approach.” Science of the Total Environment, 649, 284-299 (2018). [DOI: 10.1016/j.scitotenv.2018.08.251 ]

Topic Areas:

  • Research Area: Carbon Cycle, Nutrient Cycling
  • Research Area: Next-Generation Ecosystem Experiments (NGEE)

Division: SC-23.1 Climate and Environmental Sciences Division, BER

 

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