Data-Constrained Projections of Methane Fluxes in a Northern Minnesota Peatland in Response to Elevated CO2 and Warming
Abstract
Abstract Large uncertainties exist in predicting responses of wetland methane (CH 4 ) fluxes to future climate change. However, sources of the uncertainty have not been clearly identified despite the fact that methane production and emission processes have been extensively explored. In this study, we took advantage of manual CH 4 flux measurements under ambient environment from 2011 to 2014 at the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site and developed a data‐informed process‐based methane module. The module was incorporated into the Terrestrial ECOsystem (TECO) model before its parameters were constrained with multiple years of methane flux data for forecasting CH 4 emission under five warming and two elevated CO 2 treatments at SPRUCE. We found that 9°C warming treatments significantly increased methane emission by approximately 400%, and elevated CO 2 treatments stimulated methane emission by 10.4%–23.6% in comparison with ambient conditions. The relative contribution of plant‐mediated transport to methane emission decreased from 96% at the control to 92% at the 9°C warming, largely to compensate for an increase in ebullition. The uncertainty in plant‐mediated transportation and ebullition increased with warming and contributed to the overall changes of emissions uncertainties. At the same time, our modeling resultsmore »
- Authors:
-
- Northern Arizona Univ., Flagstaff, AZ (United States)
- Nanjing Forestry Univ., Nanjing (China); Univ. of Oklahoma, Norman, OK (United States)
- Univ. of Oklahoma, Norman, OK (United States); Lab. des Sciences du Climat et de l'Environnement, Gif-sur-Yvette (France)
- Univ. of Oklahoma, Norman, OK (United States)
- Florida State Univ., Tallahassee, FL (United States)
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- U.S. Forest Service, Grand Rapids, MN (United States)
- Northern Arizona Univ., Flagstaff, AZ (United States); Tsinghua Univ., Beijing (China)
- Publication Date:
- Research Org.:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- OSTI Identifier:
- 1415904
- Alternate Identifier(s):
- OSTI ID: 1407820
- Grant/Contract Number:
- AC05-00OR22725; DE‐AC05‐00OR22725
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of Geophysical Research. Biogeosciences
- Additional Journal Information:
- Journal Volume: 122; Journal Issue: 11; Journal ID: ISSN 2169-8953
- Publisher:
- American Geophysical Union
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 58 GEOSCIENCES; data-model fusion; uncertainty; forecasting; methane; wetland; climate change
Citation Formats
Ma, Shuang, Jiang, Jiang, Huang, Yuanyuan, Shi, Zheng, Wilson, Rachel M., Ricciuto, Daniel M., Sebestyen, Stephen D., Hanson, Paul J., and Luo, Yiqi. Data-Constrained Projections of Methane Fluxes in a Northern Minnesota Peatland in Response to Elevated CO2 and Warming. United States: N. p., 2017.
Web. doi:10.1002/2017JG003932.
Ma, Shuang, Jiang, Jiang, Huang, Yuanyuan, Shi, Zheng, Wilson, Rachel M., Ricciuto, Daniel M., Sebestyen, Stephen D., Hanson, Paul J., & Luo, Yiqi. Data-Constrained Projections of Methane Fluxes in a Northern Minnesota Peatland in Response to Elevated CO2 and Warming. United States. https://doi.org/10.1002/2017JG003932
Ma, Shuang, Jiang, Jiang, Huang, Yuanyuan, Shi, Zheng, Wilson, Rachel M., Ricciuto, Daniel M., Sebestyen, Stephen D., Hanson, Paul J., and Luo, Yiqi. Fri .
"Data-Constrained Projections of Methane Fluxes in a Northern Minnesota Peatland in Response to Elevated CO2 and Warming". United States. https://doi.org/10.1002/2017JG003932. https://www.osti.gov/servlets/purl/1415904.
@article{osti_1415904,
title = {Data-Constrained Projections of Methane Fluxes in a Northern Minnesota Peatland in Response to Elevated CO2 and Warming},
author = {Ma, Shuang and Jiang, Jiang and Huang, Yuanyuan and Shi, Zheng and Wilson, Rachel M. and Ricciuto, Daniel M. and Sebestyen, Stephen D. and Hanson, Paul J. and Luo, Yiqi},
abstractNote = {Abstract Large uncertainties exist in predicting responses of wetland methane (CH 4 ) fluxes to future climate change. However, sources of the uncertainty have not been clearly identified despite the fact that methane production and emission processes have been extensively explored. In this study, we took advantage of manual CH 4 flux measurements under ambient environment from 2011 to 2014 at the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site and developed a data‐informed process‐based methane module. The module was incorporated into the Terrestrial ECOsystem (TECO) model before its parameters were constrained with multiple years of methane flux data for forecasting CH 4 emission under five warming and two elevated CO 2 treatments at SPRUCE. We found that 9°C warming treatments significantly increased methane emission by approximately 400%, and elevated CO 2 treatments stimulated methane emission by 10.4%–23.6% in comparison with ambient conditions. The relative contribution of plant‐mediated transport to methane emission decreased from 96% at the control to 92% at the 9°C warming, largely to compensate for an increase in ebullition. The uncertainty in plant‐mediated transportation and ebullition increased with warming and contributed to the overall changes of emissions uncertainties. At the same time, our modeling results indicated a significant increase in the emitted CH 4 :CO 2 ratio. This result, together with the larger warming potential of CH 4 , will lead to a strong positive feedback from terrestrial ecosystems to climate warming. The model‐data fusion approach used in this study enabled parameter estimation and uncertainty quantification for forecasting methane fluxes.},
doi = {10.1002/2017JG003932},
journal = {Journal of Geophysical Research. Biogeosciences},
number = 11,
volume = 122,
place = {United States},
year = {Fri Oct 20 00:00:00 EDT 2017},
month = {Fri Oct 20 00:00:00 EDT 2017}
}
Web of Science
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