This study provides an improved understanding of the microbial mechanisms contributing to peat decomposition that reduces uncertainty around C cycling in these systems, however, results also suggest the potential for uncoupling of the N and C cycles as these environments evolve over time.
There are large uncertainties about the fate of carbon stored in deep peat deposits under our changing environment. Understanding how microorganisms affect the decomposition of these deposits under varying conditions should help reduce this uncertainty.
Scientists from Oak Ridge National Laboratory hypothesized that the more stable recalcitrant subsurface environment would contain a smaller less diverse microbial enzyme pool, that is better adapted to a narrow temperature range. Potential enzyme activity decreased with peat depth as expected and corresponded with changes in peat composition and microbial biomass. Enzyme activation energy decreased with depth as predicted, however leucine amino peptidase activation energy was much lower than other enzymes, suggesting a limited ability for these N acquiring enzymes to increase activity with increased temperatures. Stable temperatures at depth in the peat appear to result in a microbial community containing enzymes that have lower sensitivity or responsiveness to temperature increases.
Daniel Stover (BER PM)
Christopher W. Schadt (PI)
Senior Staff Scientist, Oak Ridge National Laboratory
Supported by the US Department of Energy, Office of Science, Office of Biological and Environmental Research, Terrestrial Ecosystem Science (TES) Program as part of the ORNL SPRUCE project under the TES SFA, and a university led project of The Georgia Institute of Technology (grant number # DE-SC0012088).
Steinweg, J.M., J.E. Kostka, P.J. Hanson and C.W. Schadt, “Temperature sensitivity of extracellular enzymes differs with peat depth but not with season in an ombrotrophic bog.” Soil Biology and Biochemistry 125, 244-250 (2018). [DOI:10.1016/j.soilbio.2018.07.001]
BER supports basic research and scientific user facilities to advance DOE missions in energy and environment. More about BER
May 10, 2019
Quantifying Decision Uncertainty in Water Management via a Coupled Agent-Based Model
Considering risk perception can improve the representation of human decision-making processes in age [more...]
May 09, 2019
Projecting Global Urban Area Growth Through 2100 Based on Historical Time Series Data and Future Scenarios
Study provides country-specific urban area growth models and the first dataset on country-level urba [more...]
May 05, 2019
Calibrating Building Energy Demand Models to Refine Long-Term Energy Planning
A new, flexible calibration approach improved model accuracy in capturing year-to-year changes in bu [more...]
May 03, 2019
Calibration and Uncertainty Analysis of Demeter for Better Downscaling of Global Land Use and Land Cover Projections
Researchers improved the Demeter model’s performance by calibrating key parameters and establi [more...]
Apr 22, 2019
Representation of U.S. Warm Temperature Extremes in Global Climate Model Ensembles
Representation of warm temperature events varies considerably among global climate models, which has [more...]
List all highlights (possible long download time)