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FLUXNET-CH4 Community Product

FLUXNET-CH4 is an initiative led by the Global Carbon Project, in close partnership with AmeriFlux and EuroFlux, to compile a global database of eddy covariance (EC) methane flux measurements. Data are standardized, post-processed (i.e., partitioned and gap-filled), and released as FLUXNET-CH4 (Delwiche et al. 2021, Knox et al. 2019). FLUXNET-CH4 Version 1.0 includes data from 81 sites, representing freshwater, coastal, upland, natural, and managed ecosystems. The near continuous, high-frequency nature of EC measurements offers significant promise for improving our understanding of ecosystem-scale CH4 flux dynamics. FLUXNET-CH4 exists thanks to the hard work of the site teams who collected these data and their willingness to participate in the FLUXNET-CH4 effort. Please refer to the Data Policy page for data usage and acknowledgement requirements. Funding for the FLUXNET-CH4 initiative was provided by the Gordon and Betty Moore Foundation and the USGS Powell Center.

We now welcome data submissions for FLUXNET-CH4 V2.0

Reference paper

A detailed description of the FLUXNET-CH4 Community Product is available in Delwiche et al. 2021, co-authored by data teams and members of all site teams contributing to FLUXNET-CH4.

Site locations

Figure 1: Global map of FLUXNET-CH4 Version 1.0 site locations colored by site type. The bog and upland site in the Northwest Territories of Canada have been slightly offset from each other to make both visible.
For a more detailed map of FLUXNET-CH4 site locations, please see Delwiche et al. 2021.

Data policies

The FLUXNET-CH4 Community Product is distributed under the two tiers of the FLUXNET2015 Data Policy. Tower teams chose data policy tiers for their site. Data distributed in both tiers can be accessed from the Data Download page for the FLUXNET-CH4 Dataset. To see a list of site-years of data available for each site, please refer to the list of sites and data availability.

IMPORTANT: In case of a synthesis using both CC-By-4.0 (Tier One) and Tier Two data, all data should be treated as Tier Two.

Temporal aggregation resolutions

The FLUXNET-CH4 Community Product provides data in two standard temporal aggregations. Tower teams generate either half-hourly (HH) or hourly (HR) data sets, depending on the conditions in the site. Half-hourly data are the basis of all the processing done for this dataset and are the finest grained temporal resolution provided. FLUXNET-CH4 also contains daily (DD) aggregations.

Metadata descriptions

The FLUXNET-CH4 Community Product includes a file containing select metadata for each site, including site personnel, location, climate and biome classification, among others. Additionally, each site has 6 metadata columns related to site vegetation. The FLUXNET-CH4 sites were assigned vegetation classifications using a 1) presence/absence, designated by Avni Malhotra based on site literature and 2) dominant vegetation based on a questionnaire sent to lead site investigators. For both presence/absence and dominant vegetation, the following plant functional types (PFTs) were considered: brown mosses, Sphagnum mosses, ericaceous shrubs, aerenchymatous plants, and trees. See Delwiche et al. 2021 methods for a detailed description.

Metadata descriptions

  • SITE_ID: Site identification code as assigned by regional flux data network
  • SITE_NAME: Site name determined by site personnel
  • SITE_PERSONNEL: Person(s) primarily responsible for data collection of FLUXNET-CH4 V1.0 data (may be different than current site PI information, which can be found under individual site information pages)
  • COUNTRY: Site country
  • LAT: Latitude
  • LON: Longitude
  • SITE_CLASSIFICATION: Site classifications were designated based on literature description of sites and designations were made from the following categories (See Delwiche et al. 2021 for details, designations were made by Kyle B. Delwiche and Gavin McNicol).
    • Marsh
    • Salt marsh
    • Wet tundra
    • Drained (former wetlands that have been artificially drained)
    • Bog
    • Mangrove
    • Rice
    • Fen
    • Lake
    • Swamp
    • Upland
  • UPLAND_CLASS: For upland sites, category of upland type was assigned based on site literature, and categories include:
    • Alpine meadow
    • Crop (crop type)
    • Grassland
    • Mixed forest
    • Needleleaf forest
    • Tundra
    • Urban
  • IGBP: International Geosphere–Biosphere Programme (IGBP) ecosystem surface classification
  • KOPPEN: Koppen climate zone abbreviation
  • ORIGINAL_DATA_SOURCE: Regional network hosting the site methane data that was incorporated into FLUXNET-CH4
  • FLUXNET-CH4_DATA_POLICY: Data policy for site data (CC BY 4.0 or Tier 2)
  • YEAR_START: Year data begins
  • YEAR_END: Year data ends
  • SOIL_TEMP_PROBE_DEPTHS: Installed depth of soil temperature probe (cm, negative values indicate below the surface)
  • MOSS_BROWN: presence or absence (1 or 0) of brown mosses on the site
  • MOSS_SPHAGNUM: presence or absence (1 or 0) of Sphagnum mosses on the site
  • AERENCHYMATOUS: presence or absence (1 or 0) of species that have aerenchyma (mostly Order Poales but includes exceptions)
  • ERI_SHRUB: presence or absence (1 or 0) of ericaceous shrubs on the site
  • TREE: presence or absence (1 or 0) of trees (of any height) on the site
  • DOM_VEG: Dominant plant functional type in the tower footprint. Lead site investigators had to pick one from the following options: moss_brown, moss_sphagnum, aerenchymatous, eri_shrub or tree

Data files

The FLUXNET-CH4 Community Product is distributed in files separated by sites and by temporal aggregation resolutions (e.g., half-hourly or daily). Version information is also assigned to the file to document changes required for a site. The file naming convention below details these options for each file. Multiple files with different temporal aggregation resolution (same site, same data product) are available for download as a single ZIP file archive. Site information metadata are also provided with a data download. Data variable descriptions can be found here.

Template

[PUBLISHER]_[SITEID]_[PROCESSING-PIPELINE]_[RESOLUTION]_[FIRST-LAST-YEARS]_[SITEVERSION-CODEVERSION].[EXT]

Examples

FLX_US-Myb_FLUXNET-CH4_HH_1992-2012_1-1.csv

Field definitions

  • PUBLISHER: 3-character code for publisher. Possible options:
    • FLX: FLUXNET data product
    • other codes can be used by publishers (e.g. regional networks) when distributing data from their databases
  • SITEID: FLUXNET site ID in the format CC-SSS (CC is two-letter country code, SSS is three-character site-level identifier)
  • PROCESSING-PIPELINE: Version of the processing pipeline (e.g., FLUXNET-CH4 is the current version)
  • RESOLUTION: Temporal resolution of data product (NOTE: only applicable to DATA files, not ZIP files). Possible values:
    • HH: Half-Hourly time steps
    • HR: Hourly time steps (NOTE: documentation for HH also applies to HR)
    • DD: Daily time steps
  • FIRST-LAST-YEARS: First and last years of eddy covariance fluxes data in the format YYYY-YYYY
  • SITEVERSION-CODEVERSION: Version string with two integer components separated by a dash (#-#). First integer indicates version of data set for the site within the scope of the release; second integer indicates version of the code of the data processing pipeline within the scope of the release used to process the data set for the site
  • EXT: File extension. Possible values:
    • csv: Comma-separated values in a text file (ASCII)
    • zip: Archive file with all temporal resolutions for same site and data product

Time zone convention

Time is reported in local standard time (i.e., without “Daylight Saving Time”). The timezone information (with respect to UTC time) is reported in the site metadata.

Column ordering

For text file data representations (i.e., CSV formatted), the variable/column order is relevant. The order of columns will NOT be guaranteed to be the same for different files (e.g., different sites), even though they will be similar in many cases. This means that any data processing routines should rely on the variable name (which is always consistent) and not the order of occurrence of that variable in the file. Timestamps are the only exception and will always be the first variable(s)/column(s) of the data file.

Missing data

Missing data values are indicated with -9999 (without decimal points) as a replacement value, independent of the cause for the missing value.

Contact Us

Please send questions, comments, and feedback to [email protected]. We’d love to hear from you!

Please use the Data Downloads page to get access to the FLUXNET-CH4 Community Product.

References

Delwiche et al., 2021. “FLUXNET-CH4: A global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands.” Earth System Science Data Discuss https://doi.org/10.5194/essd-13-3607-2021.

Knox, Sara H., Robert B. Jackson, Benjamin Poulter, Gavin McNicol, Etienne Fluet-Chouinard, Zhen Zhang, Gustaf Hugelius, et al. 2019. “FLUXNET-CH4 Synthesis Activity: Objectives, Observations, and Future Directions.” Bulletin of the American Meteorological Society 100 (12): 2607–32.

Publications

[1] Peltola, O., T. Vesala, Y. Gao, O. Räty, P. Alekseychik, M. Aurela, B. Chojnicki, A. Desai, A. Dolman, E. Euskirchen, T. Friborg, M. Göckede, M. Helbig, E. Humphreys, R. B. Jackson, G. Jocher, F Joos, J. Klatt, S. H. Knox, L. Kutzbach, S. Lienert, A. Lohila, I. Mammarella, D. F. Nadeau, M. B. Nilsson, W. C. Oechel, M. Peichl, T. Pypker, W. Quinton, J. Rinne, T. Sachs, M. Samson, H. P. Schmid, O. Sonnentag, C. Wille, D. Zona, T. Aalto. 2019. Monthly Gridded Data Product of Northern Wetland Methane Emissions Based on Upscaling Eddy Covariance Observations. Earth System Science Data Discussions. https://doi.org/10.5194/essd-2019-28.

[2] Knox S. H., R. Jackson, B. Poulter, G. McNicol, E. Fluet-Chouinard, Z. Zhang, G. Hugelius, P. Bousquet, J. Canadell J, M. Saunois, D. Papale, H. Chu, T. Keenan, D. Baldocchi, I. Mammarella, M. Aurela, G. Bohrer, D. Campbell, A. Cescatti, S. Chamberlain, J. Chen, S. Dengel, A. Desai, E. Euskirchen, T. Friborg, M. Goeckede, M. Heimann, M. Helbig, M. Kang, J. Klatt, K. Krauss, L. Kutzbach, A. Lohila, B. Mitra, T. Morin, M. Nilsson, S. Niu, A. Noormets, W. Oechel, M. Peichl, O. Peltola, M. Reba, B. Runkle, Y. Ryu, T. Sachs, K. Schäfer, N. Shurpali, O. Sonnentag, A. Tang, T. Vesala, E. Ward, L. Windham-Myers, D. Zona. 2019. FLUXNET-CH4 Synthesis Activity: Objectives, Observations, and Future Directions. Bulletin of the American Meteorological Society, https://doi.org/10.1175/BAMS-D-18-0268.1.

[3] Chang, K., W. J. Riley, S. H. Knox, R. B. Jackson, G. McNicol, B. Poulter, M.a Aurela, D. Baldocchi, S. Bansal, G. Bohrer, D. I. Campbell, A. Cescatti, H. Chu, K. B. Delwiche, A. Desai, E. Euskirchen, T. Friborg, M. Goeckede, M. Kang, T. Keenan, K. W. Krauss, A. Lohila, I. Mammarella, A. Miyata, M. B. Nilsson, A. Noormets, D. Papale, B. R. K. Runkle, Y. Ryu, T. Sachs, K. V. R. Schäfer, H. Peter Schmid, N. Shurpali, O. Sonnentag, A. C. I. Tang, M. S. Torn, C. Trotta, M. Ueyama, R. Vargas, T. Vesala, L. Windham-Myers, Z. Zhang, and D. Zona. 2021. Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions. Nature Communications, 12, 2266, https://doi.org/10.1038/s41467-021-22452-1

[4] Kyle B. Delwiche, Sara Helen Knox, Avni Malhotra, Etienne Fluet-Chouinard, Gavin McNicol, Sarah Feron, Zutao Ouyang, Dario Papale, Carlo Trotta, Eleonora Canfora, You-Wei Cheah, Danielle Christianson, Ma. Carmelita R. Alberto, Pavel Alekseychik, Mika Aurela, Dennis Baldocchi, Sheel Bansal, David P. Billesbach, Gil Bohrer, Rosvel Bracho, Nina Buchmann, David I. Campbell, Gerardo Celis, Jiquan Chen, Weinan Chen, Housen Chu, Higo J. Dalmagro, Sigrid Dengel, Ankur R. Desai, Matteo Detto, Han Dolman, Elke Eichelmann, Eugenie Euskirchen, Daniela Famulari, Kathrin Fuchs, Mathias Goeckede, Sébastien Gogo, Mangaliso J. Gondwe, Jordan P. Goodrich, Pia Gottschalk, Scott L. Graham, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S. Hemes, Takashi Hirano, David Hollinger, Lukas Hörtnagl, Hiroki Iwata, Adrien Jacotot, Gerald Jurasinski, Minseok Kang, Kuno Kasak, John King, Janina Klatt, Franziska Koebsch, Ken W. Krauss, Derrick Y. F. Lai, Annalea Lohila, Ivan Mammarella, Luca Belelli Marchesini, Giovanni Manca, Jaclyn Hatala Matthes, Trofim Maximov, Lutz Merbold, Bhaskar Mitra, Timothy H. Morin, Eiko Nemitz, Mats B. Nilsson, Shuli Niu, Walter C. Oechel, Patricia Y. Oikawa, Keisuke Ono, Matthias Peichl, Olli Peltola, Michele L. Reba, Andrew D. Richardson, William Riley, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Camilo Rey Sanchez, Edward A. Schuur, Karina V. R. Schäfer, Oliver Sonnentag, Jed P. Sparks, Ellen Stuart-Haëntjens, Cove Sturtevant, Ryan C. Sullivan, Daphne J. Szutu, Jonathan E. Thom, Margaret S. Torn, Eeva-Stiina Tuittila, Jessica Turner, Masahito Ueyama, Alex C. Valach, Rodrigo Vargas, Andrej Varlagin, Alma Vazquez-Lule, Joseph G. Verfaillie, Timo Vesala, George L. Vourlitis, Eric J. Ward, Christian Wille, Georg Wohlfahrt, Guan Xhuan Wong, Zhen Zhang, Donatella Zona, Lisamarie Windham-Myers, Benjamin Poulter, and Robert B. Jackson. 2021. FLUXNET-CH4: A global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands. Earth System Science Data Discussions, 1–111, https://doi.org/10.5194/essd-13-3607-2021

[5] Knox, S. H., S. Bansal, G. McNicol, K. Schafer, C.Sturtevant, Ma. Ueyama, A. C. Valach, D. Baldocchi, K. Delwiche, A. R. Desai, E. Euskirchen, J. Liu, A. Lohila, A. Malhotra, L. Melling, W. Riley, B. R. K. Runkle, J. Turner, R. Vargas, Q. Zhu, T. Alto, E. Fluet-Chouinard, M. Goeckede, J. R. Melton, O. Sonnentag, T. Vesala, E. Ward, Z. Zhang, S. Feron, Z. Ouyang, P. Alekseychik, M. Aurela, G. Bohrer, D. I. Campbell, J. Chen, H. Chu, H. J. Dalmagro, J. P. Goodrich, P. Gottschalk, T. Hirano, H. Iwata, G. Jurasinski, M. Kang, F. Koebsch, Ivan Mammarella, M. B. Nilsson, K. Ono, M. Peichl, O. Peltola, Y. Ryu, T. Sachs, A. Sakabe, J. P. Sparks, E.-S. Tuittila, G. L. Vourlitis, G. Xhuan Wong, L. Windham-Myers, B. Poulter, R. B. Jackson. 2021. Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales. Global Change Biology, https://doi.org/10.1111/gcb.15661

[6] Jeremy Irvin, Sharon Zhou, Gavin McNicol, Fred Lu, Vincent Liu, Etienne Fluet-Chouinard, Zutao Ouyang, Sara Helen Knox, Antje Lucas-Moffat, Carlo Trotta, Dario Papale, Domenico Vitale, Ivan Mammarella, Pavel Alekseychik, Mika Aurela, Anand Avati, Dennis Baldocchi, Sheel Bansal, Gil Bohrer, David I Campbell, Jiquan Chen, Housen Chu, Higo J Dalmagro, Kyle B Delwiche, Ankur R Desai, Eugenie Euskirchen, Sarah Feron, Mathias Goeckede, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S Hemes, Takashi Hirano, Hiroki Iwata, Gerald Jurasinski, Aram Kalhori, Andrew Kondrich, Derrick YF Lai, Annalea Lohila, Avni Malhotra, Lutz Merbold, Bhaskar Mitra, Andrew Ng, Mats B Nilsson, Asko Noormets, Matthias Peichl, A. Camilo Rey-Sanchez, Andrew D Richardson, Benjamin RK Runkle, Karina VR Schäfer, Oliver Sonnentag, Ellen Stuart-Haëntjens, Cove Sturtevant, Masahito Ueyama, Alex C Valach, Rodrigo Vargas, George L Vourlitis, Eric J Ward, Guan Xhuan Wong, Donatella Zona, Ma. Carmelita R Alberto, David P Billesbach, Gerardo Celis, Han Dolman, Thomas Friborg, Kathrin Fuchs, Sébastien Gogo, Mangaliso J Gondwe, Jordan P Goodrich, Pia Gottschalk0, Lukas Hörtnagl, Adrien Jacotot, Franziska Koebsch, Kuno Kasak, Regine Maier, Timothy H Morin, Eiko Nemitz, Walter C Oechel, Patricia Y Oikawa, Keisuke Ono, Torsten Sachs, Ayaka Sakabe, Edward A Schuur, Robert Shortt, Ryan C Sullivan, Daphne J Szutu, Eeva-Stiina Tuittila, Andrej Varlagin, Joeseph G Verfaillie, Christian Wille, Lisamarie Windham-Myers, Benjamin Poulter, Robert B Jackson. 2021. Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands. Agriculture and Forest Meteorology 308–309, 108528. https://doi.org/10.1016/J.AGRFORMET.2021.108528

[7] Yuan, K., Q. Zhu, F. Li, W. J. Riley, M. Torn, H. Chu, G. McNicol, M. Chen, S. H. Knox, K. Delwiche, H. Wu, D. Baldocchi, H. Ma, A. R. Desai, J. Chen, T. Sachs, M. Ueyama, O. Sonnentag, M. Helbig, E-S Tuittila, G. Jurasinski, F. Koebsch, D. Campbell, H. Peter Schmid, A. Lohila, M. Goeckede, M. B. Nilsson, T. Friborg, J. Jansen, D. Zona, E. Euskirchen, E. J. Ward, G. Bohrer, Z. Jin, L. Liu, H. Iwata, J. Goodrich, R. Jackson. 2022. Causality guided machine learning model on wetland CH4 emissions across global wetlands. Agricultural and Forest Meteorology, 324, 109115, https://doi.org/10.1016/j.agrformet.2022.109115

[8] Masahito Ueyama, Sara H. Knox, Kyle B. Delwiche, Sheel Bansal, William J. Riley, Dennis Baldocchi, Takashi Hirano, Gavin McNicol, Karina Schafer, Lisamarie Windham-Myers, Benjamin Poulter, Robert B. Jackson, Kuang-Yu Chang, Jiquen Chen, Housen Chu, Ankur R. Desai, Sébastien Gogo, Hiroki Iwata, Minseok Kang, Ivan Mammarella, Matthias Peichl, Oliver Sonnentag, Eeva-Stiina Tuittila, Youngryel Ryu, Eugénie S. Euskirchen, Mathias Göckede, Adrien Jacotot, Mats B. Nilsson, Torsten Sachs. 2023. Modeled production, oxidation and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions. Global Change Biology, 29 (8), 2313-2334, https://doi.org/10.1111/gcb.16594

[9] Zutao Ouyang, Robert B. Jackson, Gavin McNicol, Etienne Fluet-Chouinard Benjamin R.K. Runkle, Dario Papale, Sara H. Knox, Sarah Cooley, Kyle B. Delwiche, Sarah Feron, Jeremy Andrew Irvin, Avni Malhotra, Muhammad Muddasir, Simone Sabbatini, Ma. Carmelita R. Alberto, Alessandro Cescatti, Chi-Ling Chen, Jinwei Dong, Bryant N. Fong, Haiqiang Guo, Lu Hao, Hiroki Iwata, Qingyu Jia, Weimin Ju, Minseok Kang, Hong Li, Joon Kim, Michele L. Reba, Amaresh Kumar Nayak, Debora Regina Roberti, Youngryel Ryu, Chinmaya Kumar Swain, Benjei Tsuang, Xiangming Xiao, Wenping Yuan, Geli Zhang, Yongguang Zhang. 2023. Paddy rice methane emissions across Monsoon Asia. Remote Sensing of Environment, 284, 113335, https://doi.org/10.1016/j.rse.2022.113335

[10] Chang, K. Y., Riley, W., Collier, N., McNicol, G., Knox, S. H., Jackson, R., Poulter, B., & Saunois, M. 2023. Observational constraints reduce model spread but not uncertainty in global wetland methane emission estimates. Global Change Biology, 29, 4298–4312. https://doi.org/10.1111/gcb.16755

[11] Gavin McNicol, Etienne Fluet-Chouinard, Zutao Ouyang, Sara Knox, Zhen Zhang, Tuula Aalto, Sheel Bansal, Kuang-Yu Chang, Min Chen, Kyle Delwiche, Sarah Feron, Mathias Goeckede, Jinxun Liu, Avni Malhotra, Joe R. Melton, William Riley, Rodrigo Vargas, Kunxiaojia Yuan, Qing Ying, Qing Zhu, Pavel Alekseychik, Mika Aurela, David P. Billesbach, David I. Campbell, Jiquan Chen, Housen Chu, Ankur R. Desai, Eugenie Euskirchen, Jordan Goodrich, Timothy Griffis, Manuel Helbig, Takashi Hirano, Hiroki Iwata, Gerald Jurasinski, John King, Franziska Koebsch, Randall Kolka, Ken Krauss, Annalea Lohila, Ivan Mammarella, Mats Nilson, Asko Noormets, Walter Oechel, Matthias Peichl, Torsten Sachs, Ayaka Sakabe, Christopher Schulze, Oliver Sonnentag, Ryan C. Sullivan, Eeva-Stiina Tuittila, Masahito Ueyama, Timo Vesala, Eric Ward, Christian Wille, Guan Xhuan Wong, Donatella Zona, Lisamarie Windham-Myers, Benjamin Poulter, Robert B. Jackson. 2023. Upscaling wetland methane emissions from the FLUXNET-CH4 eddy covariance network (UpCH4 v1.0): Model development, network Assessment, and Budget Comparison. AGU Advances, 4(5), e2023AV000956. https://doi.org/10.1029/2023AV000956

[12] Zhang Z., S. Bansal, K-Y Chang, E. Fluet-Chouinard, K. Delwiche, M. Goeckede, A. Gustafson, S. H. Knox, A. Leppänen, L. Liu, J. Liu, A. Malhotra, T. Markkanen, G. McNicol, J. R. Melton, P. A. Miller, C. Peng, M. Raivonen, W. J. Riley, O. Sonnentag, A. Tuula, R. Vargas, W. Zhang, Q. Zhu, Q. Zhu, Q. Zhuang, L. Windham-Myers20, R. B. Jackson, B. Poulter. 2023. Characterizing performance of freshwater wetland methane models across time scales at FLUXNET-CH4 sites using wavelet analyses, Journal of Geophysical Research: Biogeosciences, 128 (11), https://doi.org/10.1029/2022JG007259

[13] Feron, S., A. Malhotra, S. Bansal, E. Fluet-Chouinard, G. McNicol, S. H. Knox, K. B. Delwiche, R. R. Cordero, Z. Ouyang, Z. Zhang, B. Poulter, R. B. Jackson. Recent increases in annual, seasonal, and extreme methane fluxes driven by changes in climate and vegetation in boreal and temperate wetland ecosystems. 2024. Global Change Biology, https://doi.org/10.1111/gcb.17131

[14] Yuan, K., Li, F., McNicol, G., Chen, M., Hoyt, A., Knox, S., Riley, W. J., Jackson, R., & Zhu, Q. 2024. Boreal–Arctic wetland methane emissions modulated by warming and vegetation activity. Nature Climate Change 2024 14:3, 14(3), 282–288. https://doi.org/10.1038/s41558-024-01933-3