Abstract
Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20g g€¯S to 20g g€¯N) the spring onset of elevated CH4 emissions starts 3g€¯d earlier, and the CH4 emission season lasts 4g€¯d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH4 emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH4 modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH4 cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at 10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.
| Original language | English |
|---|---|
| Pages (from-to) | 3607-3689 |
| Number of pages | 83 |
| Journal | Earth System Science Data |
| Volume | 13 |
| Issue number | 7 |
| Early online date | 29 Jul 2021 |
| DOIs | |
| Publication status | Published - Jul 2021 |
Bibliographical note
Publisher Copyright:© Copyright:
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
Funding
Acknowledgements. We acknowledge primary support from the Gordon and Betty Moore Foundation (grant GBMF5439, “Advancing Understanding of the Global Methane Cycle”; Stanford University) and from the John Wesley Powell Center for Analysis and Synthesis of the US Geological Survey (“Wetland FLUXNET Synthesis for Methane” working group). Benjamin R. K. Runkle was supported by the US National Science Foundation CBET CAREER Award 1752083. Ankur R. Desai acknowledges support of the DOE AmeriFlux Network Management Project. Masahito Ueyama was supported by ArCS II (JPMXD1420318865) and JSPS KAKENHI (20K21849). Dario Papale and Nina Buchmann acknowledge the support of the RINGO (GA 730944) H2020 EU project. Nina Buchmann and Kathrin Fuchs acknowledge the SNF project M4P (40FA40_154245/1) and InnoFarm (407340_172433). Nina Buchmann acknowledges support from the SNF for ICOS-CH phases 1 and 2 (20FI21_148992, 20FI20_173691). Carlo Trotta acknowledges the support of the E-SHAPE (GA 820852) H2020 EU project. William J. Riley was supported by the US Department of Energy, BER, RGCM, RUBISCO project under contract no. DEAC02−05CH11231. Jessica Turner acknowledges support from NSF GRFP (DGE−1747503) and NTL LTER (DEB−1440297). Minseok Kang was supported by the National Research Foundation of Korea (NRF−2018 R1C1B6002917). Carole Helfter acknowledges the support of the UK Natural Environment Research Council (the Global Methane Budget project, grant number NE/N015746/1). Rodrigo Vargas acknowledges support from the National Science Foundation (1652594). Dennis Baldocchi acknowledges the California Department of Water Resources for a funding contract from the California Department of Fish and Wildlife and the United States Department of Agriculture (NIFA grant #2011-67003-30371), as well as the US Department of Energy’s Office of Science (AmeriFlux contract #7079856) for funding the AmeriFlux core sites. US-A03 and US-A10 are operated by the Atmospheric Radiation Measurement (ARM) user facility, a US Department of Energy’s Office of Science user facility managed by the Biological and Environmental Research Program. Work at ANL was supported by the US Department of Energy’s Office of Science and Office of Biological and Environmental Research under contract DE-AC02−06CH11357. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US government. The CH-Dav, DE-SfN, FI-Hyy, FI-Lom, FI-Sii, FR-LGt, IT-BCi, SE-Deg, and SE-Sto sites are part of the ICOS European Research Infrastructure. Oliver Sonnentag acknowledges funding by the Canada Research Chairs, Canada Foundation for Innovation Leaders Opportunity Fund, and Natural Sciences and Engineering Research Council Discovery Grant programs for work at CA-SCC and CA-SCB. Benjamin Poulter acknowledges support from the NASA Carbon Cycle and Ecosystems program. Derrick Lai acknowledges the support of the Research Grants Council of the Hong Kong Special Administrative Region, China (project no. CUHK 458913). We thank Nathaniel Goenawan for his help with the representativeness analysis. Financial support. This research has been supported by the Gordon and Betty Moore Foundation (grant no. GBMF5439), the John Wesley Powell Center for Analysis and Synthesis of the US Geological Survey, the National Science Foundation (grant nos. 1752083, DGE−1747503, and 1652594), the ArCS II (grant no. JPMXD1420318865), the JSPS KAKENHI (grant no. 20K21849), the RINGO (grant no. GA 730944), the SNF (grant nos. 40FA40_154245/1, 20FI21_148992, and 20FI20_173691), the InnoFarm (grant no. 407340_172433), the E-SHAPE (grant no. GA 820852), the US Department of Energy (grant nos. DEAC02−05CH11231, 7079856, and DE-AC02−06CH11357), the NTL LTER (grant no. DEB−1440297), the National Research Foundation of Korea (grant no. NRF−2018 R1C1B6002917), the UK Natural Environment Research Council (grant no. NE/N015746/1), the California Department of Fish and Wildlife (grant no. 2011-67003-30371), the Canada Research Chairs, the Canada Foundation for Innovation Leaders Opportunity Fund, the Natural Sciences and Engineering Research Council Discovery Grant programs, and the NASA Carbon Cycle and Ecosystems program.
| Funders | Funder number |
|---|---|
| H2020 EU | |
| Canada Foundation for Innovation Leaders Opportunity Fund | |
| National Aeronautics and Space Administration | |
| Stanford University | |
| U.S. Geological Survey | |
| CA-SCC | |
| California Department of Fish and Wildlife | |
| Natural Sciences and Engineering Research Council of Canada | |
| Canada Research Chairs | |
| CA-SCB | |
| U.S. Department of Agriculture | |
| John Wesley Powell Center | |
| DOE AmeriFlux Network Management Project | |
| Department of Water Resources | |
| U.S. Department of Energy | DEAC02−05CH11231 |
| National Research Foundation of Korea | −2018 R1C1B6002917, NRF−2018 R1C1B6002917 |
| Biological and Environmental Research | DE-AC02−06CH11357 |
| Natural Environment Research Council | NE/P002552/1, NE/N015746/1, NE/R016429/1 |
| National Institute of Food and Agriculture | 2011-67003-30371 |
| Horizon 2020 Framework Programme | 820852, 730944 |
| Research Grants Council, University Grants Committee | CUHK 458913 |
| National Science Foundation | 1440297, 1752083, 1652594, 1747503 |
| Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung | 20FI21_148992, GA 820852, 20FI20_173691, 407340_172433, 40FA40_154245/1 |
| Office of Science | 7079856 |
| NTL LTER | DEB−1440297 |
| UK Research and Innovation | 53706 |
| RGCM | DEAC02−05CH11231 |
| Gordon and Betty Moore Foundation | GBMF5439 |
| ArCS II | JPMXD1420318865 |
| Japan Society for the Promotion of Science | GA 730944, 20K21849 |
