Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions
International audience Wetlands are the largest natural source of methane (CH4) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH4, but interpreting its spatiotemporal variations is challenging due to the co-occurrence of CH4 production, oxida...
Published in: | Global Change Biology |
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Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Other Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
HAL CCSD
2023
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Subjects: | |
Online Access: | https://hal.science/hal-03955531 https://hal.science/hal-03955531/document https://hal.science/hal-03955531/file/GCB-22-2463_Proof_fl.pdf https://doi.org/10.1111/gcb.16594 |
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Open Polar |
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Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) |
op_collection_id |
ftccsdartic |
language |
English |
topic |
Bayesian optimization data-model fusion Eddy covariance methane emissions methane model multi-site synthesis [SDE]Environmental Sciences [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environment |
spellingShingle |
Bayesian optimization data-model fusion Eddy covariance methane emissions methane model multi-site synthesis [SDE]Environmental Sciences [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environment Ueyama, Masahito Knox, Sara, H Delwiche, Kyle, B Bansal, Sheel Riley, William, J Baldocchi, Dennis Hirano, Takashi Mcnicol, Gavin Schafer, Karina Windham‐myers, Lisamarie Poulter, Benjamin Jackson, Robert, B Chang, Kuang‐yu Chen, Jiquen Chu, Housen Desai, Ankur, R Gogo, Sébastien Iwata, Hiroki Kang, Minseok Mammarella, Ivan Peichl, Matthias Sonnentag, Oliver Tuittila, Eeva‐stiina Ryu, Youngryel Euskirchen, Eugénie, S Göckede, Mathias Jacotot, Adrien Nilsson, Mats, B Sachs, Torsten Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions |
topic_facet |
Bayesian optimization data-model fusion Eddy covariance methane emissions methane model multi-site synthesis [SDE]Environmental Sciences [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environment |
description |
International audience Wetlands are the largest natural source of methane (CH4) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH4, but interpreting its spatiotemporal variations is challenging due to the co-occurrence of CH4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data-model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data-constrained model—iPEACE—reasonably reproduced CH4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH4 production appeared to be the most important process, followed by oxidation in explaining inter-site variations in CH4 emissions. Based on a sensitivity analysis, CH4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant-mediated transport appeared to be the major pathway for CH4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH4 production and CH4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH4 production, plant-mediatedtransport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH4 emissions across biomes. These processes and associated parameters for CH4 emissions among and within the wetlands provide useful insights for interpreting observed net CH4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH4 fluxes. |
author2 |
Osaka Metropolitan University University of British Columbia Vancouver Lawrence Berkeley National Laboratory Berkeley (LBNL) Department of Environmental Science, Policy, and Management Berkeley (ESPM) University of California Berkeley (UC Berkeley) University of California (UC)-University of California (UC) US Geological Survey Jamestown United States Geological Survey Reston (USGS) Prairie and Northern Wildlife Research Centre Environment and Climate Change Canada Climate and Ecosystem Sciences Division Research Faculty of Agriculture Hokkaido University Sapporo, Japan University of Illinois Chicago (UIC) University of Illinois System Department of Earth and Environmental Sciences Chicago (EAES) University of Illinois System-University of Illinois System Rutgers University Newark Rutgers University System (Rutgers) Department of Earth and Environmental Science Newark Rutgers University System (Rutgers)-Rutgers University System (Rutgers) US Geological Survey Menlo Park NASA Goddard Space Flight Center (GSFC) Biospheric Sciences Laboratory Department of Earth System Science Stanford (ESS) Stanford EARTH Stanford University-Stanford University Stanford University Michigan State University System University of Wisconsin-Madison Department of Atmospheric and Oceanic Sciences Madison Université de Rennes (UR) Ecosystèmes, biodiversité, évolution Rennes (ECOBIO) Université de Rennes (UR)-Institut Ecologie et Environnement - CNRS Ecologie et Environnement (INEE-CNRS) Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR) Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS) Shinshu University Nagano National Center for Agro-Meteorology Helsingin yliopisto = Helsingfors universitet = University of Helsinki Swedish University of Agricultural Sciences (SLU) Department of Forest Ecology and Management Université de Montréal (UdeM) University of Eastern Finland School of Forest Sciences Seoul National University Seoul (SNU) Department of Landscape Architecture and Rural Systems Engineering Institute of Arctic Biology University of Alaska Fairbanks (UAF) Max Planck Institute for Biogeochemistry (MPI-BGC) Max-Planck-Gesellschaft |
format |
Article in Journal/Newspaper |
author |
Ueyama, Masahito Knox, Sara, H Delwiche, Kyle, B Bansal, Sheel Riley, William, J Baldocchi, Dennis Hirano, Takashi Mcnicol, Gavin Schafer, Karina Windham‐myers, Lisamarie Poulter, Benjamin Jackson, Robert, B Chang, Kuang‐yu Chen, Jiquen Chu, Housen Desai, Ankur, R Gogo, Sébastien Iwata, Hiroki Kang, Minseok Mammarella, Ivan Peichl, Matthias Sonnentag, Oliver Tuittila, Eeva‐stiina Ryu, Youngryel Euskirchen, Eugénie, S Göckede, Mathias Jacotot, Adrien Nilsson, Mats, B Sachs, Torsten |
author_facet |
Ueyama, Masahito Knox, Sara, H Delwiche, Kyle, B Bansal, Sheel Riley, William, J Baldocchi, Dennis Hirano, Takashi Mcnicol, Gavin Schafer, Karina Windham‐myers, Lisamarie Poulter, Benjamin Jackson, Robert, B Chang, Kuang‐yu Chen, Jiquen Chu, Housen Desai, Ankur, R Gogo, Sébastien Iwata, Hiroki Kang, Minseok Mammarella, Ivan Peichl, Matthias Sonnentag, Oliver Tuittila, Eeva‐stiina Ryu, Youngryel Euskirchen, Eugénie, S Göckede, Mathias Jacotot, Adrien Nilsson, Mats, B Sachs, Torsten |
author_sort |
Ueyama, Masahito |
title |
Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions |
title_short |
Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions |
title_full |
Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions |
title_fullStr |
Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions |
title_full_unstemmed |
Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions |
title_sort |
modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and arctic regions |
publisher |
HAL CCSD |
publishDate |
2023 |
url |
https://hal.science/hal-03955531 https://hal.science/hal-03955531/document https://hal.science/hal-03955531/file/GCB-22-2463_Proof_fl.pdf https://doi.org/10.1111/gcb.16594 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
ISSN: 1354-1013 EISSN: 1365-2486 Global Change Biology https://hal.science/hal-03955531 Global Change Biology, 2023, 29 (8), pp.2313-2334. ⟨10.1111/gcb.16594⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1111/gcb.16594 hal-03955531 https://hal.science/hal-03955531 https://hal.science/hal-03955531/document https://hal.science/hal-03955531/file/GCB-22-2463_Proof_fl.pdf doi:10.1111/gcb.16594 WOS: 000918794800001 |
op_rights |
http://creativecommons.org/licenses/by/ info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.1111/gcb.16594 |
container_title |
Global Change Biology |
_version_ |
1792044912308387840 |
spelling |
ftccsdartic:oai:HAL:hal-03955531v1 2024-02-27T08:37:59+00:00 Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions Ueyama, Masahito Knox, Sara, H Delwiche, Kyle, B Bansal, Sheel Riley, William, J Baldocchi, Dennis Hirano, Takashi Mcnicol, Gavin Schafer, Karina Windham‐myers, Lisamarie Poulter, Benjamin Jackson, Robert, B Chang, Kuang‐yu Chen, Jiquen Chu, Housen Desai, Ankur, R Gogo, Sébastien Iwata, Hiroki Kang, Minseok Mammarella, Ivan Peichl, Matthias Sonnentag, Oliver Tuittila, Eeva‐stiina Ryu, Youngryel Euskirchen, Eugénie, S Göckede, Mathias Jacotot, Adrien Nilsson, Mats, B Sachs, Torsten Osaka Metropolitan University University of British Columbia Vancouver Lawrence Berkeley National Laboratory Berkeley (LBNL) Department of Environmental Science, Policy, and Management Berkeley (ESPM) University of California Berkeley (UC Berkeley) University of California (UC)-University of California (UC) US Geological Survey Jamestown United States Geological Survey Reston (USGS) Prairie and Northern Wildlife Research Centre Environment and Climate Change Canada Climate and Ecosystem Sciences Division Research Faculty of Agriculture Hokkaido University Sapporo, Japan University of Illinois Chicago (UIC) University of Illinois System Department of Earth and Environmental Sciences Chicago (EAES) University of Illinois System-University of Illinois System Rutgers University Newark Rutgers University System (Rutgers) Department of Earth and Environmental Science Newark Rutgers University System (Rutgers)-Rutgers University System (Rutgers) US Geological Survey Menlo Park NASA Goddard Space Flight Center (GSFC) Biospheric Sciences Laboratory Department of Earth System Science Stanford (ESS) Stanford EARTH Stanford University-Stanford University Stanford University Michigan State University System University of Wisconsin-Madison Department of Atmospheric and Oceanic Sciences Madison Université de Rennes (UR) Ecosystèmes, biodiversité, évolution Rennes (ECOBIO) Université de Rennes (UR)-Institut Ecologie et Environnement - CNRS Ecologie et Environnement (INEE-CNRS) Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR) Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS) Shinshu University Nagano National Center for Agro-Meteorology Helsingin yliopisto = Helsingfors universitet = University of Helsinki Swedish University of Agricultural Sciences (SLU) Department of Forest Ecology and Management Université de Montréal (UdeM) University of Eastern Finland School of Forest Sciences Seoul National University Seoul (SNU) Department of Landscape Architecture and Rural Systems Engineering Institute of Arctic Biology University of Alaska Fairbanks (UAF) Max Planck Institute for Biogeochemistry (MPI-BGC) Max-Planck-Gesellschaft 2023 https://hal.science/hal-03955531 https://hal.science/hal-03955531/document https://hal.science/hal-03955531/file/GCB-22-2463_Proof_fl.pdf https://doi.org/10.1111/gcb.16594 en eng HAL CCSD Wiley info:eu-repo/semantics/altIdentifier/doi/10.1111/gcb.16594 hal-03955531 https://hal.science/hal-03955531 https://hal.science/hal-03955531/document https://hal.science/hal-03955531/file/GCB-22-2463_Proof_fl.pdf doi:10.1111/gcb.16594 WOS: 000918794800001 http://creativecommons.org/licenses/by/ info:eu-repo/semantics/OpenAccess ISSN: 1354-1013 EISSN: 1365-2486 Global Change Biology https://hal.science/hal-03955531 Global Change Biology, 2023, 29 (8), pp.2313-2334. ⟨10.1111/gcb.16594⟩ Bayesian optimization data-model fusion Eddy covariance methane emissions methane model multi-site synthesis [SDE]Environmental Sciences [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environment info:eu-repo/semantics/article Journal articles 2023 ftccsdartic https://doi.org/10.1111/gcb.16594 2024-01-28T00:58:02Z International audience Wetlands are the largest natural source of methane (CH4) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH4, but interpreting its spatiotemporal variations is challenging due to the co-occurrence of CH4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data-model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data-constrained model—iPEACE—reasonably reproduced CH4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH4 production appeared to be the most important process, followed by oxidation in explaining inter-site variations in CH4 emissions. Based on a sensitivity analysis, CH4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant-mediated transport appeared to be the major pathway for CH4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH4 production and CH4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH4 production, plant-mediatedtransport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH4 emissions across biomes. These processes and associated parameters for CH4 emissions among and within the wetlands provide useful insights for interpreting observed net CH4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH4 fluxes. Article in Journal/Newspaper Arctic Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) Arctic Global Change Biology |