Upscaling Wetland Methane Emissions From the FLUXNET–CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison

McNicol, Gavin; Fluet‐Chouinard, Etienne; Ouyang, Zutao; Knox, Sara; Zhang, Zhen; Aalto, Tuula; Bansal, Sheel; Chang, Kuang‐Yu; Chen, Min; Delwiche, Kyle; Feron, Sarah; Goeckede, Mathias; Liu, Jinxun; Malhotra, Avni; Melton, Joe R.; Riley, William; Vargas, Rodrigo; Yuan, Kunxiaojia; Ying, Qing; Zhu, Qing; Alekseychik, Pavel; Aurela, Mika; Billesbach, David P.; Campbell, David I.; Chen, Jiquan; Chu, Housen; Desai, Ankur R.; Euskirchen, Eugenie; Goodrich, Jordan; Griffis, Timothy; Helbig, Manuel; Hirano, Takashi; Iwata, Hiroki; Jurasinski, Gerald; King, John; Koebsch, Franziska; Kolka, Randall; Krauss, Ken; Lohila, Annalea; Mammarella, Ivan; Nilson, Mats; Noormets, Asko; Oechel, Walter; Peichl, Matthias; Sachs, Torsten; Sakabe, Ayaka; Schulze, Christopher; Sonnentag, Oliver; Sullivan, Ryan C.; Tuittila, Eeva‐Stiina; Ueyama, Masahito; Vesala, Timo; Ward, Eric; Wille, Christian; Wong, Guan Xhuan; Zona, Donatella; Windham‐Myers, Lisamarie; Poulter, Benjamin; Jackson, Robert B.

doi:10.1029/2023av000956

Title: Upscaling Wetland Methane Emissions From the FLUXNET–CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison

Journal Article · 06 September 2023 · AGU Advances

DOI: https://doi.org/10.1029/2023av000956 · OSTI ID:1999187

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Stanford University, CA (United States); University of Illinois, Chicago, IL (United States)
Stanford University, CA (United States); ETH Zurich (Switzerland)
Stanford University, CA (United States)
University of British Columbia, Vancouver, BC (Canada)
University of Maryland, College Park, MD (United States)
Finnish Meteorological Institute, Helsinki (Finland)
U.S. Geological Survey, Jamestown, ND (United States)
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
University of Wisconsin‐Madison, WI (United States)
University of California, Berkeley, CA (United States)
University of Groningen (The Netherlands)
Max Planck Institute for Biogeochemistry, Jena (Germany)
U.S. Geological Survey, Moffett Field, CA (United States)
University of Zurich (Switzerland)
Environment and Climate Change Canada, Victoria, BC (Canada)
University of Delaware, Newark, DE (United States)
Natural Resources Institute Finland (LUKE), Helsinki (Finland)
University of Nebraska‐Lincoln, NE (United States)
University of Waikato, Hamilton (New Zealand)
Michigan State University, East Lansing, MI (United States)
University of Alaska, Fairbanks, AK (United States)
University of Minnesota Twin Cities, St. Paul, MN (United States)
Dalhousie University, Halifax, NS (Canada)
Hokkaido University, Sapporo (Japan)
Shinshu University, Matsumoto (Japan)
University of Rostock (Germany); University of Greifswald (Germany)
North Carolina State University, Raleigh, NC (United States)
University of Göttingen (Germany)
USDA Forest Service Northern Research Station, Grand Rapids, MN (United States)
USGS Wetland and Aquatic Research Center, Lafayette, LA (United States)
Finnish Meteorological Institute, Helsinki (Finland); University of Helsinki (Finland)
University of Helsinki (Finland)
Swedish University of Agricultural Sciences, Umeå (Sweden)
Texas A&M University, College Station, TX (United States)
San Diego State University, CA (United States)
GFZ German Research Centre for Geosciences, Potsdam (Germany)
Kyoto University (Japan)
Université de Montréal, QC (Canada)
Argonne National Laboratory (ANL), Argonne, IL (United States)
University of Eastern Finland, Joesnuu (Finland)
Osaka Metropolitan University, Sakai (Japan)
Sarawak Tropical Peat Research Institute, Kota Samarahan (Malaysia)
San Diego State University, CA (United States); University of Sheffield (United Kingdom)
U.S. Geological Survey Water Mission Area, Menlo Park, CA (United States)
NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)

Wetlands are responsible for 20%–31% of global methane (CH₄) emissions and account for a large source of uncertainty in the global CH₄ budget. Data-driven upscaling of CH₄ fluxes from eddy covariance measurements can provide new and independent bottom-up estimates of wetland CH₄ emissions. Here, we develop a six-predictor random forest upscaling model (UpCH4), trained on 119 site-years of eddy covariance CH₄ flux data from 43 freshwater wetland sites in the FLUXNET-CH4 Community Product. Network patterns in site-level annual means and mean seasonal cycles of CH₄ fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash-Sutcliffe Efficiency ~0.52–0.63 and 0.53). UpCH4 estimated annual global wetland CH₄ emissions of 146 ± 43 TgCH₄ y^–1 for 2001–2018 which agrees closely with current bottom-up land surface models (102–181 TgCH₄ y^–1) and overlaps with top-down atmospheric inversion models (155–200 TgCH₄ y^–1). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH₄ fluxes has the potential to produce realistic extra-tropical wetland CH₄ emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid-to-arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). ARM Data Center

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Contributing Organization:: Pacific Northwest National Laboratory (PNNL); Brookhaven National Laboratory (BNL); Argonne National Laboratory (ANL); Oak Ridge National Laboratory (ORNL)

Grant/Contract Number:: AC02-06CH11357

OSTI ID:: 1999187

Journal Information:: AGU Advances, Journal Name: AGU Advances Journal Issue: 5 Vol. 4; ISSN 2576-604X

Publisher:: WileyCopyright Statement

Country of Publication:: United States

Language:: English

References (192)

AmeriFlux AmeriFlux US-ALQ Allequash Creek Site Olson, Brent AmeriFlux; USGS https://doi.org/10.17190/amf/1480323	dataset	January 2018
AmeriFlux AmeriFlux CA-CF2 Churchill Fen Site 2 Tenuta, Mario AmeriFlux; University of Manitoba https://doi.org/10.17190/amf/1634879	dataset	January 2020
AmeriFlux AmeriFlux PE-QFR Quistococha Forest Reserve Griffis, Timothy; Roman, Tyler AmeriFlux; University of Minnesota; USDA-Forest Service https://doi.org/10.17190/amf/1671889	dataset	January 2020
AmeriFlux AmeriFlux US-MBP Marcell Bog Lake Peatland Roman, Tyler; Kolka, Randy; Griffis, Timothy AmeriFlux; University of Minnesota; USDA- Forest Service https://doi.org/10.17190/amf/1767835	dataset	January 2021
FLUXNET-CH4 BR-Npw Northern Pantanal Wetland Vourlitis, George; Dalmagro, Higo; De S. Nogueira, Jose FluxNet; California State University, San Marcos; Universidade de Cuiabá; Universidade Federal de Mato Grosso; University of British Columbia https://doi.org/10.18140/flx/1669368	dataset	January 2020
FLUXNET-CH4 BW-Gum Guma Helfter, Carole FluxNet; UK Centre for Ecology and Hydrology https://doi.org/10.18140/flx/1669370	dataset	January 2020
FLUXNET-CH4 BW-Nxr Nxaraga Helfter, Carole FluxNet; UK Centre for Ecology and Hydrology https://doi.org/10.18140/flx/1669518	dataset	January 2020
FLUXNET-CH4 CA-SCB Scotty Creek Bog Sonnentag, Oliver; Helbig, Manuel FluxNet; Université de Montréal; Wilfrid Laurier University https://doi.org/10.18140/flx/1669613	dataset	January 2020
FLUXNET-CH4 CA-SCC Scotty Creek Landscape Sonnentag, Oliver; Helbig, Manuel FluxNet; Université de Montréal; Wilfrid Laurier University https://doi.org/10.18140/flx/1669628	dataset	January 2020
FLUXNET-CH4 DE-Hte Huetelmoor Koebsch, Franziska; Jurasinski, Gerald FluxNet; Landscape Ecology, University of Rostock https://doi.org/10.18140/flx/1669634	dataset	January 2020
FLUXNET-CH4 DE-SfN Schechenfilz Nord Schmid, Hans; Klatt, Janina FluxNet; Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research (IMK-IFU) https://doi.org/10.18140/flx/1669635	dataset	January 2020
FLUXNET-CH4 DE-Zrk Zarnekow Sachs, Torsten; Wille, Christian FluxNet; GFZ German Research Centre for Geosciences https://doi.org/10.18140/flx/1669636	dataset	January 2020
FLUXNET-CH4 FI-Lom Lompolojankka Lohila, Annalea; Aurela, Mika; Tuovinen, Juha-Pekka FluxNet; Finnish Meteorological Institute https://doi.org/10.18140/flx/1669638	dataset	January 2020
FLUXNET-CH4 FI-Si2 Siikaneva-2 Bog Vesala, Timo; Tuittila, Eeva-Stiina; Mammarella, Ivan FluxNet; University of Eastern Finland; University of Helsinki https://doi.org/10.18140/flx/1669639	dataset	January 2020
FLUXNET-CH4 FI-Sii Siikaneva Vesala, Timo; Tuittila, Eeva-Stiina; Mammarella, Ivan FluxNet; University of Eastern Finland; University of Helsinki https://doi.org/10.18140/flx/1669640	dataset	January 2020
FLUXNET-CH4 FR-LGt La Guette Jacotot, Adrien; Gogo, Sébastien; Laggoun-Défarge, Fatima FluxNet; Observatoire des Sciences de l'Univers en région Centre https://doi.org/10.18140/flx/1669641	dataset	January 2020
FLUXNET-CH4 ID-Pag Palangkaraya undrained forest Sakabe, Ayaka; Itoh, Masayuki; Hirano, Takashi FluxNet; Hokkaido University; Kyoto University; University of Hyogo; University of Palangkaraya https://doi.org/10.18140/flx/1669643	dataset	January 2020
FLUXNET-CH4 JP-BBY Bibai bog Ueyama, Masahito; Hirano, Takashi; Kominami, Yasuhiro FluxNet; Osaka Prefecture Univeristy https://doi.org/10.18140/flx/1669646	dataset	January 2020
FLUXNET-CH4 MY-MLM Maludam National Park Wong, Guan; Melling, Lulie; Tang, Angela FluxNet; Sarawak Tropical Peat Research Institute https://doi.org/10.18140/flx/1669650	dataset	January 2020
FLUXNET-CH4 NZ-Kop Kopuatai Campbell, David; Goodrich, Jordan FluxNet; University of Waikato https://doi.org/10.18140/flx/1669652	dataset	January 2020
FLUXNET-CH4 RU-Ch2 Chersky reference Goeckede, Mathias FluxNet; Max Planck Institute for Biogeochemistry, Jena, Germany https://doi.org/10.18140/flx/1669654	dataset	January 2020
FLUXNET-CH4 RU-Cok Chokurdakh Dolman, Han; Maximox, Trofim; Parmentier, Frans FluxNet; Vrije Universiteit Amsterdam https://doi.org/10.18140/flx/1669656	dataset	January 2020
FLUXNET-CH4 SE-Deg Degero Nilsson, Mats; Peichl, Matthias FluxNet; Department of Forest Ecology and Management; Swedish University of Agricultural Sciences https://doi.org/10.18140/flx/1669659	dataset	January 2020
FLUXNET-CH4 US-A03 ARM-AMF3-Oliktok Billesbach, Dave; Sullivan, Ryan FluxNet; Argonne National Laboratory https://doi.org/10.18140/flx/1669661	dataset	January 2020
FLUXNET-CH4 US-A10 ARM-NSA-Barrow Billesbach, Dave; Sullivan, Ryan FluxNet; Argonne National Laboratory https://doi.org/10.18140/flx/1669662	dataset	January 2020
FLUXNET-CH4 US-Atq Atqasuk Zona, Donatella; Oechel, Walter FluxNet; San Diego State University https://doi.org/10.18140/flx/1669663	dataset	January 2020
FLUXNET-CH4 US-Beo Barrow Environmental Observatory (BEO) tower Zona, Donatella; Oechel, Walter FluxNet; San Diego State University https://doi.org/10.18140/flx/1669664	dataset	January 2020
FLUXNET-CH4 US-Bes Barrow-Bes (Biocomplexity Experiment South tower) Zona, Donatella; Oechel, Walter FluxNet; San Diego State University https://doi.org/10.18140/flx/1669665	dataset	January 2020
FLUXNET-CH4 US-BZB Bonanza Creek Thermokarst Bog Euskirchen, Eugenie; Edgar, Colin FluxNet https://doi.org/10.18140/flx/1669668	dataset	January 2020
FLUXNET-CH4 US-BZF Bonanza Creek Rich Fen Euskirchen, Eugenie; Edgar, Colin FluxNet https://doi.org/10.18140/flx/1669669	dataset	January 2020
FLUXNET-CH4 US-DPW Disney Wilderness Preserve Wetland Hinkle, Charles; Bracho, Rosvel FluxNet; University of Central Florida; University of Central Florida (UCF) https://doi.org/10.18140/flx/1669672	dataset	January 2020
FLUXNET-CH4 US-ICs Imnavait Creek Watershed Wet Sedge Tundra Euskirchen, Eugenie; Bret-Harte, Marion; Edgar, Colin FluxNet; Marine Biological Laboratory; University of Alaska Fairbanks https://doi.org/10.18140/flx/1669678	dataset	January 2020
FLUXNET-CH4 US-Ivo Ivotuk Zona, Donatella; Oechel, Walter FluxNet; San Diego State University https://doi.org/10.18140/flx/1669679	dataset	January 2020
FLUXNET-CH4 US-LA2 Salvador WMA Freshwater Marsh Holm, Guerry; Perez, Brian; McWhorter, David FluxNet; US Geological Survey; USGS-Wetland and Aquatic Research Center https://doi.org/10.18140/flx/1669681	dataset	January 2020
FLUXNET-CH4 US-Los Lost Creek Desai, Ankur FluxNet; University of Wisconsin https://doi.org/10.18140/flx/1669682	dataset	January 2020
FLUXNET-CH4 US-Myb Mayberry Wetland Matthes, Jaclyn; Sturtevant, Cove; Oikawa, Patty FluxNet; University of California, Berkeley https://doi.org/10.18140/flx/1669685	dataset	January 2020
FLUXNET-CH4 US-NC4 NC_AlligatorRiver Noormets, Asko; King, John; Mitra, Bhaskar FluxNet; Texas A&M University https://doi.org/10.18140/flx/1669686	dataset	January 2020
FLUXNET-CH4 US-NGB NGEE Arctic Barrow Torn, Margaret; Dengel, Sigrid FluxNet; Lawrence Berkeley National Laboratory https://doi.org/10.18140/flx/1669687	dataset	January 2020
FLUXNET-CH4 US-NGC NGEE Arctic Council Torn, Margaret; Dengel, Sigrid FluxNet; Berkeley Lab; Lawrence Berkeley National Laboratory https://doi.org/10.18140/flx/1669688	dataset	January 2020
FLUXNET-CH4 US-ORv Olentangy River Wetland Research Park Bohrer, Gil; Morin, Timothy FluxNet; The Ohio State University https://doi.org/10.18140/flx/1669689	dataset	January 2020
FLUXNET-CH4 US-OWC Old Woman Creek Bohrer, Gil; Kerns, Janice; Morin, Timothy FluxNet; Old Woman Creek National Estuarine Research Reserve; The Ohio State University https://doi.org/10.18140/flx/1669690	dataset	January 2020
FLUXNET-CH4 US-Sne Sherman Island Restored Wetland Shortt, Robert; Hemes, Kyle; Szutu, Daphne FluxNet; University of California, Berkeley https://doi.org/10.18140/flx/1669693	dataset	January 2020
FLUXNET-CH4 US-Tw1 Twitchell Wetland West Pond Valach, Alex; Szutu, Daphne; Eichelmann, Elke FluxNet; University of California, Berkeley https://doi.org/10.18140/flx/1669696	dataset	January 2020
FLUXNET-CH4 US-Tw4 Twitchell East End Wetland Eichelmann, Elke; Knox, Sara; Sanchez, Camilo FluxNet; University of California, Berkeley https://doi.org/10.18140/flx/1669698	dataset	January 2020
FLUXNET-CH4 US-Tw5 East Pond Wetland Valach, Alex; Kasak, Kuno; Szutu, Daphne FluxNet; University of California, Berkeley https://doi.org/10.18140/flx/1669699	dataset	January 2020
FLUXNET-CH4 US-Uaf University of Alaska, Fairbanks Iwata, Hiroki; Ueyama, Masahito; Harazono, Yoshinobu FluxNet; Osaka Prefecture University; Shinshu University https://doi.org/10.18140/flx/1669701	dataset	January 2020
FLUXNET-CH4 US-WPT Winous Point North Marsh Chen, Jiquan; Chu, Housen FluxNet; University of Toledo / Michigan State University https://doi.org/10.18140/flx/1669702	dataset	January 2020
Net ecosystem exchange of CO2 and CH4 from two Louisiana coastal marshes Krauss, Ken W.; Raynie, Richard; Killebrew, Charles U.S. Geological Survey https://doi.org/10.5066/f7mg7nsv	dataset	January 2018
MCD15A2H MODIS/Terra+Aqua Leaf Area Index/FPAR 8-day L4 Global 500m SIN Grid V006 Myneni, Ranga; Knyazikhin, Yuri; Park, Taejin NASA EOSDIS Land Processes DAAC https://doi.org/10.5067/modis/mcd15a2h.006	dataset	January 2015
MOD09A1 MODIS/Terra Surface Reflectance 8-Day L3 Global 500m SIN Grid V006 Vermote, Eric NASA EOSDIS Land Processes DAAC https://doi.org/10.5067/modis/mod09a1.006	dataset	January 2015
MODIS/Terra Snow Cover Daily L3 Global 500m SIN Grid Hall, Dorothy K.; Riggs, George A. NASA National Snow and Ice Data Center DAAC https://doi.org/10.5067/modis/mod10a1.006	dataset	January 2015
MOD11A2 MODIS/Terra Land Surface Temperature/Emissivity 8-Day L3 Global 1km SIN Grid V006 Wan, Zhengming; Hook, Simon; Hulley, Glynn NASA EOSDIS Land Processes Distributed Active Archive Center https://doi.org/10.5067/modis/mod11a2.006	dataset	January 2015
Identifying scale-emergent, nonlinear, asynchronous processes of wetland methane exchange: IDENTIFYING METHANE EXCHANGE PROCESSES Sturtevant, Cove; Ruddell, Benjamin L.; Knox, Sara Helen Journal of Geophysical Research: Biogeosciences, Vol. 121, Issue 1 https://doi.org/10.1002/2015jg003054	journal	January 2016
Fluxes all of the time? A primer on the temporal representativeness of FLUXNET: FLUXES ALL OF THE TIME? Chu, Housen; Baldocchi, Dennis D.; John, Ranjeet Journal of Geophysical Research: Biogeosciences, Vol. 122, Issue 2 https://doi.org/10.1002/2016JG003576	journal	February 2017
WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas: NEW CLIMATE SURFACES FOR GLOBAL LAND AREAS Fick, Stephen E.; Hijmans, Robert J. International Journal of Climatology, Vol. 37, Issue 12 https://doi.org/10.1002/joc.5086	journal	May 2017
Potential of Multivariate Quantitative Methods for Delineation and Visualization of Ecoregions Hargrove, William W.; Hoffman, Forrest M. Environmental Management, Vol. 34, Issue S1 https://doi.org/10.1007/s00267-003-1084-0	journal	April 2004
Carbon biogeochemistry of a flooded Pantanal forest over three annual flood cycles Dalmagro, Higo J.; Lathuillière, Michael J.; Hawthorne, Iain Biogeochemistry, Vol. 139, Issue 1 https://doi.org/10.1007/s10533-018-0450-1	journal	May 2018
Partitioning Eddy-Covariance Methane Fluxes from a Shallow Lake into Diffusive and Ebullitive Fluxes Iwata, Hiroki; Hirata, Ryuichi; Takahashi, Yoshiyuki Boundary-Layer Meteorology, Vol. 169, Issue 3 https://doi.org/10.1007/s10546-018-0383-1	journal	August 2018
Representativeness-based sampling network design for the State of Alaska Hoffman, Forrest M.; Kumar, Jitendra; Mills, Richard T. Landscape Ecology, Vol. 28, Issue 8 https://doi.org/10.1007/s10980-013-9902-0	journal	June 2013
Correlation and variable importance in random forests Gregorutti, Baptiste; Michel, Bertrand; Saint-Pierre, Philippe Statistics and Computing, Vol. 27, Issue 3 https://doi.org/10.1007/s11222-016-9646-1	journal	March 2016
Overview of the radiometric and biophysical performance of the MODIS vegetation indices Huete, A.; Didan, K.; Miura, T. Remote Sensing of Environment, Vol. 83, Issue 1-2 https://doi.org/10.1016/S0034-4257(02)00096-2	journal	November 2002
NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space Gao, Bo-cai Remote Sensing of Environment, Vol. 58, Issue 3 https://doi.org/10.1016/S0034-4257(96)00067-3	journal	December 1996
Upscaling tower-observed turbulent exchange at fine spatio-temporal resolution using environmental response functions Xu, Ke; Metzger, Stefan; Desai, Ankur R. Agricultural and Forest Meteorology, Vol. 232 https://doi.org/10.1016/j.agrformet.2016.07.019	journal	January 2017
Assessing the carbon and climate benefit of restoring degraded agricultural peat soils to managed wetlands Hemes, Kyle S.; Chamberlain, Samuel D.; Eichelmann, Elke Agricultural and Forest Meteorology, Vol. 268 https://doi.org/10.1016/j.agrformet.2019.01.017	journal	April 2019
Spectral evidence for substrate availability rather than environmental control of methane emissions from a coastal forested wetland Mitra, Bhaskar; Minick, Kevan; Miao, Guofang Agricultural and Forest Meteorology, Vol. 291 https://doi.org/10.1016/j.agrformet.2020.108062	journal	September 2020
Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites Chu, Housen; Luo, Xiangzhong; Ouyang, Zutao Agricultural and Forest Meteorology, Vol. 301-302 https://doi.org/10.1016/j.agrformet.2021.108350	journal	May 2021
Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands Irvin, Jeremy; Zhou, Sharon; McNicol, Gavin Agricultural and Forest Meteorology, Vol. 308-309 https://doi.org/10.1016/j.agrformet.2021.108528	journal	October 2021
Partitioning methane flux by the eddy covariance method in a cool temperate bog based on a Bayesian framework Ueyama, Masahito; Yazaki, Tomotsugu; Hirano, Takashi Agricultural and Forest Meteorology, Vol. 316 https://doi.org/10.1016/j.agrformet.2022.108852	journal	April 2022
Determining total emissions and environmental drivers of methane flux in a Lake Erie estuarine marsh Rey-Sanchez, A. C.; Morin, T. H.; Stefanik, K. C. Ecological Engineering, Vol. 114 https://doi.org/10.1016/j.ecoleng.2017.06.042	journal	April 2018
Importance of spatial predictor variable selection in machine learning applications – Moving from data reproduction to spatial prediction Meyer, Hanna; Reudenbach, Christoph; Wöllauer, Stephan Ecological Modelling, Vol. 411 https://doi.org/10.1016/j.ecolmodel.2019.108815	journal	November 2019
Improving performance of spatio-temporal machine learning models using forward feature selection and target-oriented validation Meyer, Hanna; Reudenbach, Christoph; Hengl, Tomislav Environmental Modelling & Software, Vol. 101 https://doi.org/10.1016/j.envsoft.2017.12.001	journal	March 2018
Google Earth Engine: Planetary-scale geospatial analysis for everyone Gorelick, Noel; Hancher, Matt; Dixon, Mike Remote Sensing of Environment, Vol. 202 https://doi.org/10.1016/j.rse.2017.06.031	journal	December 2017
Evaluating year-to-year anomalies in tropical wetland methane emissions using satellite CH4 observations Parker, Robert J.; Boesch, Hartmut; McNorton, Joe Remote Sensing of Environment, Vol. 211 https://doi.org/10.1016/j.rse.2018.02.011	journal	June 2018
Random Forests Breiman, Leo Machine Learning, Vol. 45, Issue 1, p. 5-32 https://doi.org/10.1023/A:1010933404324	journal	January 2001
An integrated model of soil, hydrology, and vegetation for carbon dynamics in wetland ecosystems: SOIL, HYDROLOGY, VEGETATION INTEGRATED MODEL Zhang, Yu; Li, Changsheng; Trettin, Carl C. Global Biogeochemical Cycles, Vol. 16, Issue 4 https://doi.org/10.1029/2001gb001838	journal	October 2002
Mapping forest canopy height globally with spaceborne lidar Simard, Marc; Pinto, Naiara; Fisher, Joshua B. Journal of Geophysical Research, Vol. 116, Issue G4 https://doi.org/10.1029/2011JG001708	journal	January 2011
Advances in the Eddy Covariance Approach to CH ₄ Monitoring Over Two and a Half Decades Morin, Timothy H. Journal of Geophysical Research: Biogeosciences, Vol. 124, Issue 3 https://doi.org/10.1029/2018JG004796	journal	March 2019
Satellite‐Derived Global Surface Water Extent and Dynamics Over the Last 25 Years (GIEMS‐2) Prigent, C.; Jimenez, C.; Bousquet, P. Journal of Geophysical Research: Atmospheres, Vol. 125, Issue 3 https://doi.org/10.1029/2019jd030711	journal	February 2020
Representativeness of FLUXNET Sites Across Latin America Villarreal, Samuel; Vargas, Rodrigo Journal of Geophysical Research: Biogeosciences, Vol. 126, Issue 3 https://doi.org/10.1029/2020jg006090	journal	March 2021
Satellite Constraints on the Latitudinal Distribution and Temperature Sensitivity of Wetland Methane Emissions Ma, Shuang; Worden, John R.; Bloom, A. Anthony AGU Advances, Vol. 2, Issue 3 https://doi.org/10.1029/2021av000408	journal	September 2021
Tropical Peatland Hydrology Simulated With a Global Land Surface Model Apers, S.; De Lannoy, G. J. M.; Baird, A. J. Journal of Advances in Modeling Earth Systems, Vol. 14, Issue 3 https://doi.org/10.1029/2021ms002784	journal	February 2022
Methane emissions to the troposphere from the Amazon floodplain Devol, Allan H.; Richey, Jeffrey E.; Clark, Wayne A. Journal of Geophysical Research, Vol. 93, Issue D2 https://doi.org/10.1029/JD093iD02p01583	journal	January 1988
Primary production control of methane emission from wetlands Whiting, G. J.; Chanton, J. P. Nature, Vol. 364, Issue 6440 https://doi.org/10.1038/364794a0	journal	August 1993
High-resolution mapping of global surface water and its long-term changes Pekel, Jean-François; Cottam, Andrew; Gorelick, Noel Nature, Vol. 540, Issue 7633 https://doi.org/10.1038/nature20584	journal	December 2016
Large emissions from floodplain trees close the Amazon methane budget Pangala, Sunitha R.; Enrich-Prast, Alex; Basso, Luana S. Nature, Vol. 552, Issue 7684 https://doi.org/10.1038/nature24639	journal	December 2017
Three decades of global methane sources and sinks Kirschke, Stefanie; Bousquet, Philippe; Ciais, Philippe Nature Geoscience, Vol. 6, Issue 10 https://doi.org/10.1038/ngeo1955	journal	September 2013
Methanogenesis in oxygenated soils is a substantial fraction of wetland methane emissions Angle, Jordan C.; Morin, Timothy H.; Solden, Lindsey M. Nature Communications, Vol. 8, Issue 1 https://doi.org/10.1038/s41467-017-01753-4	journal	November 2017
Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions Chang, Kuang-Yu; Riley, William J.; Knox, Sara H. Nature Communications, Vol. 12, Issue 1 https://doi.org/10.1038/s41467-021-22452-1	journal	April 2021
Machine learning-based global maps of ecological variables and the challenge of assessing them Meyer, Hanna; Pebesma, Edzer Nature Communications, Vol. 13, Issue 1 https://doi.org/10.1038/s41467-022-29838-9	journal	April 2022
Recent intensification of wetland methane feedback Zhang, Zhen; Poulter, Benjamin; Feldman, Andrew F. Nature Climate Change, Vol. 13, Issue 5 https://doi.org/10.1038/s41558-023-01629-0	journal	March 2023
Deep learning and process understanding for data-driven Earth system science Reichstein, Markus; Camps-Valls, Gustau; Stevens, Bjorn Nature, Vol. 566, Issue 7743 https://doi.org/10.1038/s41586-019-0912-1	journal	February 2019
The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data Pastorello, Gilberto; Trotta, Carlo; Canfora, Eleonora Scientific Data, Vol. 7, Issue 1 https://doi.org/10.1038/s41597-020-0534-3	journal	July 2020
TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015 Abatzoglou, John T.; Dobrowski, Solomon Z.; Parks, Sean A. Scientific Data, Vol. 5, Issue 1 https://doi.org/10.1038/sdata.2017.191	journal	January 2018
A suite of global, cross-scale topographic variables for environmental and biodiversity modeling Amatulli, Giuseppe; Domisch, Sami; Tuanmu, Mao-Ning Scientific Data, Vol. 5, Issue 1 https://doi.org/10.1038/sdata.2018.40	journal	March 2018
Emerging role of wetland methane emissions in driving 21st century climate change Zhang, Zhen; Zimmermann, Niklaus E.; Stenke, Andrea Proceedings of the National Academy of Sciences, Vol. 114, Issue 36 https://doi.org/10.1073/pnas.1618765114	journal	August 2017
Interpreting contemporary trends in atmospheric methane Turner, Alexander J.; Frankenberg, Christian; Kort, Eric A. Proceedings of the National Academy of Sciences, Vol. 116, Issue 8 https://doi.org/10.1073/pnas.1814297116	journal	February 2019
Observation of flooding and rice transplanting of paddy rice fields at the site to landscape scales in China using VEGETATION sensor data Xiao, X.; Boles, S.; Frolking, S. International Journal of Remote Sensing, Vol. 23, Issue 15 https://doi.org/10.1080/01431160110107734	journal	January 2002
Global, 30-m resolution continuous fields of tree cover: Landsat-based rescaling of MODIS vegetation continuous fields with lidar-based estimates of error Sexton, Joseph O.; Song, Xiao-Peng; Feng, Min International Journal of Digital Earth, Vol. 6, Issue 5 https://doi.org/10.1080/17538947.2013.786146	journal	September 2013
Global wetland contribution to 2000–2012 atmospheric methane growth rate dynamics Poulter, Benjamin; Bousquet, Philippe; Canadell, Josep G. Environmental Research Letters, Vol. 12, Issue 9 https://doi.org/10.1088/1748-9326/aa8391	journal	September 2017
Non-flooded riparian Amazon trees are a regionally significant methane source Gauci, Vincent; Figueiredo, Viviane; Gedney, Nicola Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 380, Issue 2215 https://doi.org/10.1098/rsta.2020.0446	journal	December 2021
Methane removal and the proportional reductions in surface temperature and ozone Abernethy, S.; O'Connor, F. M.; Jones, C. D. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 379, Issue 2210 https://doi.org/10.1098/rsta.2021.0104	journal	September 2021
Rising methane: is there a methane emergency? Nisbet, E. G.; Jones, A. E.; Pyle, J. A. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 380, Issue 2215 https://doi.org/10.1098/rsta.2021.0334	journal	December 2021
Surface Water Microwave Product Series Version 3: A Near-Real Time and 25-Year Historical Global Inundated Area Fraction Time Series From Active and Passive Microwave Remote Sensing Jensen, Katherine; Mcdonald, Kyle IEEE Geoscience and Remote Sensing Letters, Vol. 16, Issue 9 https://doi.org/10.1109/LGRS.2019.2898779	journal	September 2019
Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure Roberts, David R.; Bahn, Volker; Ciuti, Simone Ecography, Vol. 40, Issue 8 https://doi.org/10.1111/ecog.02881	journal	March 2017
Spatial modelling with Euclidean distance fields and machine learning Behrens, T.; Schmidt, K.; Viscarra Rossel, R. A. European Journal of Soil Science, Vol. 69, Issue 5 https://doi.org/10.1111/ejss.12687	journal	July 2018
Methane emissions from wetlands: biogeochemical, microbial, and modeling perspectives from local to global scales Bridgham, Scott D.; Cadillo-Quiroz, Hinsby; Keller, Jason K. Global Change Biology, Vol. 19, Issue 5 https://doi.org/10.1111/gcb.12131	journal	February 2013
A synthesis of methane emissions from 71 northern, temperate, and subtropical wetlands Turetsky, Merritt R.; Kotowska, Agnieszka; Bubier, Jill Global Change Biology, Vol. 20, Issue 7 https://doi.org/10.1111/gcb.12580	journal	April 2014
Measuring fluxes of trace gases and energy between ecosystems and the atmosphere - the state and future of the eddy covariance method Baldocchi, Dennis Global Change Biology, Vol. 20, Issue 12 https://doi.org/10.1111/gcb.12649	journal	June 2014
Agricultural peatland restoration: effects of land-use change on greenhouse gas (CO ₂ and CH ₄ ) fluxes in the Sacramento-San Joaquin Delta Knox, Sara Helen; Sturtevant, Cove; Matthes, Jaclyn Hatala Global Change Biology, Vol. 21, Issue 2 https://doi.org/10.1111/gcb.12745	journal	October 2014
Nongrowing season methane emissions-a significant component of annual emissions across northern ecosystems Treat, Claire C.; Bloom, A. Anthony; Marushchak, Maija E. Global Change Biology, Vol. 24, Issue 8 https://doi.org/10.1111/gcb.14137	journal	April 2018
Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales Knox, Sara H.; Bansal, Sheel; McNicol, Gavin Global Change Biology, Vol. 27, Issue 15 https://doi.org/10.1111/gcb.15661	journal	May 2021
Spatial biases of information influence global estimates of soil respiration: How can we improve global predictions? Stell, Emma; Warner, Daniel; Jian, Jinshi Global Change Biology, Vol. 27, Issue 16 https://doi.org/10.1111/gcb.15666	journal	May 2021
Regional trends and drivers of the global methane budget Stavert, Ann R.; Saunois, Marielle; Canadell, Josep G. Global Change Biology, Vol. 28, Issue 1 https://doi.org/10.1111/gcb.15901	journal	October 2021
Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions Ueyama, Masahito; Knox, Sara H.; Delwiche, Kyle B. Global Change Biology, Vol. 29, Issue 8 https://doi.org/10.1111/gcb.16594	journal	January 2023
A global 1-km consensus land-cover product for biodiversity and ecosystem modelling: Consensus land cover Tuanmu, Mao-Ning; Jetz, Walter Global Ecology and Biogeography, Vol. 23, Issue 9 https://doi.org/10.1111/geb.12182	journal	April 2014
A global, remote sensing-based characterization of terrestrial habitat heterogeneity for biodiversity and ecosystem modelling: Global habitat heterogeneity Tuanmu, Mao-Ning; Jetz, Walter Global Ecology and Biogeography, Vol. 24, Issue 11 https://doi.org/10.1111/geb.12365	journal	August 2015
Large increases in methane emissions expected from North America’s largest wetland complex Bansal, Sheel; Post van der Burg, Max; Fern, Rachel R. Science Advances, Vol. 9, Issue 9 https://doi.org/10.1126/sciadv.ade1112	journal	March 2023
FLUXNET-CH ₄ Synthesis Activity: Objectives, Observations, and Future Directions Knox, Sara H.; Jackson, Robert B.; Poulter, Benjamin Bulletin of the American Meteorological Society https://doi.org/10.1175/BAMS-D-18-0268.1	journal	July 2019
SoilGrids250m: Global gridded soil information based on machine learning Hengl, Tomislav; Mendes de Jesus, Jorge; Heuvelink, Gerard B. M. PLOS ONE, Vol. 12, Issue 2 https://doi.org/10.1371/journal.pone.0169748	journal	February 2017
AmeriFlux AmeriFlux US-ALQ Allequash Creek Site Olson, Brent AmeriFlux; USGS https://doi.org/10.17190/AMF/1480323	dataset	January 2018
AmeriFlux AmeriFlux CA-CF2 Churchill Fen Site 2 Tenuta, Mario AmeriFlux; University of Manitoba https://doi.org/10.17190/AMF/1634879	dataset	January 2020
AmeriFlux AmeriFlux PE-QFR Quistococha Forest Reserve Griffis, Timothy; Roman, Tyler AmeriFlux; University of Minnesota; USDA-Forest Service https://doi.org/10.17190/AMF/1671889	dataset	January 2020
AmeriFlux AmeriFlux US-MBP Marcell Bog Lake Peatland Roman, Tyler; Kolka, Randy; Griffis, Timothy AmeriFlux; University of Minnesota; USDA- Forest Service https://doi.org/10.17190/AMF/1767835	dataset	January 2021
FLUXNET-CH4 BR-Npw Northern Pantanal Wetland Vourlitis, George; Dalmagro, Higo; De S. Nogueira, Jose FluxNet; California State University, San Marcos; Universidade de Cuiabá; Universidade Federal de Mato Grosso; University of British Columbia https://doi.org/10.18140/FLX/1669368	dataset	January 2020
FLUXNET-CH4 BW-Gum Guma Helfter, Carole FluxNet; UK Centre for Ecology and Hydrology https://doi.org/10.18140/FLX/1669370	dataset	January 2020
FLUXNET-CH4 BW-Nxr Nxaraga Helfter, Carole FluxNet; UK Centre for Ecology and Hydrology https://doi.org/10.18140/FLX/1669518	dataset	January 2020
FLUXNET-CH4 CA-SCB Scotty Creek Bog Sonnentag, Oliver; Helbig, Manuel FluxNet; Université de Montréal; Wilfrid Laurier University https://doi.org/10.18140/FLX/1669613	dataset	January 2020
FLUXNET-CH4 CA-SCC Scotty Creek Landscape Sonnentag, Oliver; Helbig, Manuel FluxNet; Université de Montréal; Wilfrid Laurier University https://doi.org/10.18140/FLX/1669628	dataset	January 2020
FLUXNET-CH4 DE-Hte Huetelmoor Koebsch, Franziska; Jurasinski, Gerald FluxNet; Landscape Ecology, University of Rostock https://doi.org/10.18140/FLX/1669634	dataset	January 2020
FLUXNET-CH4 DE-SfN Schechenfilz Nord Schmid, Hans; Klatt, Janina FluxNet; Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research (IMK-IFU) https://doi.org/10.18140/FLX/1669635	dataset	January 2020
FLUXNET-CH4 DE-Zrk Zarnekow Sachs, Torsten; Wille, Christian FluxNet; GFZ German Research Centre for Geosciences https://doi.org/10.18140/FLX/1669636	dataset	January 2020
FLUXNET-CH4 FI-Lom Lompolojankka Lohila, Annalea; Aurela, Mika; Tuovinen, Juha-Pekka FluxNet; Finnish Meteorological Institute https://doi.org/10.18140/FLX/1669638	dataset	January 2020
FLUXNET-CH4 FI-Si2 Siikaneva-2 Bog Vesala, Timo; Tuittila, Eeva-Stiina; Mammarella, Ivan FluxNet; University of Eastern Finland; University of Helsinki https://doi.org/10.18140/FLX/1669639	dataset	January 2020
FLUXNET-CH4 FI-Sii Siikaneva Vesala, Timo; Tuittila, Eeva-Stiina; Mammarella, Ivan FluxNet; University of Eastern Finland; University of Helsinki https://doi.org/10.18140/FLX/1669640	dataset	January 2020
FLUXNET-CH4 FR-LGt La Guette Jacotot, Adrien; Gogo, Sébastien; Laggoun-Défarge, Fatima FluxNet; Observatoire des Sciences de l'Univers en région Centre https://doi.org/10.18140/FLX/1669641	dataset	January 2020
FLUXNET-CH4 ID-Pag Palangkaraya undrained forest Sakabe, Ayaka; Itoh, Masayuki; Hirano, Takashi FluxNet; Hokkaido University; Kyoto University; University of Hyogo; University of Palangkaraya https://doi.org/10.18140/FLX/1669643	dataset	January 2020
FLUXNET-CH4 JP-BBY Bibai bog Ueyama, Masahito; Hirano, Takashi; Kominami, Yasuhiro FluxNet; Osaka Prefecture Univeristy https://doi.org/10.18140/FLX/1669646	dataset	January 2020
FLUXNET-CH4 MY-MLM Maludam National Park Wong, Guan; Melling, Lulie; Tang, Angela FluxNet; Sarawak Tropical Peat Research Institute https://doi.org/10.18140/FLX/1669650	dataset	January 2020
FLUXNET-CH4 NZ-Kop Kopuatai Campbell, David; Goodrich, Jordan FluxNet; University of Waikato https://doi.org/10.18140/FLX/1669652	dataset	January 2020
FLUXNET-CH4 RU-Ch2 Chersky reference Goeckede, Mathias FluxNet; Max Planck Institute for Biogeochemistry, Jena, Germany https://doi.org/10.18140/FLX/1669654	dataset	January 2020
FLUXNET-CH4 RU-Cok Chokurdakh Dolman, Han; Maximox, Trofim; Parmentier, Frans FluxNet; Vrije Universiteit Amsterdam https://doi.org/10.18140/FLX/1669656	dataset	January 2020
FLUXNET-CH4 SE-Deg Degero Nilsson, Mats; Peichl, Matthias FluxNet; Department of Forest Ecology and Management; Swedish University of Agricultural Sciences https://doi.org/10.18140/FLX/1669659	dataset	January 2020
FLUXNET-CH4 US-A03 ARM-AMF3-Oliktok Billesbach, Dave; Sullivan, Ryan FluxNet; Argonne National Laboratory https://doi.org/10.18140/FLX/1669661	dataset	January 2020
FLUXNET-CH4 US-A10 ARM-NSA-Barrow Billesbach, Dave; Sullivan, Ryan FluxNet; Argonne National Laboratory https://doi.org/10.18140/FLX/1669662	dataset	January 2020
FLUXNET-CH4 US-Atq Atqasuk Zona, Donatella; Oechel, Walter FluxNet; San Diego State University https://doi.org/10.18140/FLX/1669663	dataset	January 2020
FLUXNET-CH4 US-Beo Barrow Environmental Observatory (BEO) tower Zona, Donatella; Oechel, Walter FluxNet; San Diego State University https://doi.org/10.18140/FLX/1669664	dataset	January 2020
FLUXNET-CH4 US-Bes Barrow-Bes (Biocomplexity Experiment South tower) Zona, Donatella; Oechel, Walter FluxNet; San Diego State University https://doi.org/10.18140/FLX/1669665	dataset	January 2020
FLUXNET-CH4 US-BZB Bonanza Creek Thermokarst Bog Euskirchen, Eugenie; Edgar, Colin FluxNet https://doi.org/10.18140/FLX/1669668	dataset	January 2020
FLUXNET-CH4 US-BZF Bonanza Creek Rich Fen Euskirchen, Eugenie; Edgar, Colin FluxNet https://doi.org/10.18140/FLX/1669669	dataset	January 2020
FLUXNET-CH4 US-DPW Disney Wilderness Preserve Wetland Hinkle, Charles; Bracho, Rosvel FluxNet; University of Central Florida; University of Central Florida (UCF) https://doi.org/10.18140/FLX/1669672	dataset	January 2020
FLUXNET-CH4 US-ICs Imnavait Creek Watershed Wet Sedge Tundra Euskirchen, Eugenie; Bret-Harte, Marion; Edgar, Colin FluxNet; Marine Biological Laboratory; University of Alaska Fairbanks https://doi.org/10.18140/FLX/1669678	dataset	January 2020
FLUXNET-CH4 US-Ivo Ivotuk Zona, Donatella; Oechel, Walter FluxNet; San Diego State University https://doi.org/10.18140/FLX/1669679	dataset	January 2020
FLUXNET-CH4 US-LA2 Salvador WMA Freshwater Marsh Holm, Guerry; Perez, Brian; McWhorter, David FluxNet; US Geological Survey; USGS-Wetland and Aquatic Research Center https://doi.org/10.18140/FLX/1669681	dataset	January 2020
FLUXNET-CH4 US-Los Lost Creek Desai, Ankur FluxNet; University of Wisconsin https://doi.org/10.18140/FLX/1669682	dataset	January 2020
FLUXNET-CH4 US-Myb Mayberry Wetland Matthes, Jaclyn; Sturtevant, Cove; Oikawa, Patty FluxNet; University of California, Berkeley https://doi.org/10.18140/FLX/1669685	dataset	January 2020
FLUXNET-CH4 US-NC4 NC_AlligatorRiver Noormets, Asko; King, John; Mitra, Bhaskar FluxNet; Texas A&M University https://doi.org/10.18140/FLX/1669686	dataset	January 2020
FLUXNET-CH4 US-NGB NGEE Arctic Barrow Torn, Margaret; Dengel, Sigrid FluxNet; Lawrence Berkeley National Laboratory https://doi.org/10.18140/FLX/1669687	dataset	January 2020
FLUXNET-CH4 US-NGC NGEE Arctic Council Torn, Margaret; Dengel, Sigrid FluxNet; Berkeley Lab; Lawrence Berkeley National Laboratory https://doi.org/10.18140/FLX/1669688	dataset	January 2020
FLUXNET-CH4 US-ORv Olentangy River Wetland Research Park Bohrer, Gil; Morin, Timothy FluxNet; The Ohio State University https://doi.org/10.18140/FLX/1669689	dataset	January 2020
FLUXNET-CH4 US-OWC Old Woman Creek Bohrer, Gil; Kerns, Janice; Morin, Timothy FluxNet; Old Woman Creek National Estuarine Research Reserve; The Ohio State University https://doi.org/10.18140/FLX/1669690	dataset	January 2020
FLUXNET-CH4 US-Sne Sherman Island Restored Wetland Shortt, Robert; Hemes, Kyle; Szutu, Daphne FluxNet; University of California, Berkeley https://doi.org/10.18140/FLX/1669693	dataset	January 2020
FLUXNET-CH4 US-Tw1 Twitchell Wetland West Pond Valach, Alex; Szutu, Daphne; Eichelmann, Elke FluxNet; University of California, Berkeley https://doi.org/10.18140/FLX/1669696	dataset	January 2020
FLUXNET-CH4 US-Tw4 Twitchell East End Wetland Eichelmann, Elke; Knox, Sara; Sanchez, Camilo FluxNet; University of California, Berkeley https://doi.org/10.18140/FLX/1669698	dataset	January 2020
FLUXNET-CH4 US-Tw5 East Pond Wetland Valach, Alex; Kasak, Kuno; Szutu, Daphne FluxNet; University of California, Berkeley https://doi.org/10.18140/FLX/1669699	dataset	January 2020
FLUXNET-CH4 US-Uaf University of Alaska, Fairbanks Iwata, Hiroki; Ueyama, Masahito; Harazono, Yoshinobu FluxNet; Osaka Prefecture University; Shinshu University https://doi.org/10.18140/FLX/1669701	dataset	January 2020
FLUXNET-CH4 US-WPT Winous Point North Marsh Chen, Jiquan; Chu, Housen FluxNet; University of Toledo / Michigan State University https://doi.org/10.18140/FLX/1669702	dataset	January 2020
ranger : A Fast Implementation of Random Forests for High Dimensional Data in C++ and R Wright, Marvin N.; Ziegler, Andreas Journal of Statistical Software, Vol. 77, Issue 1 https://doi.org/10.18637/jss.v077.i01	journal	January 2017
Development and Evaluation of a Multi-Year Fractional Surface Water Data Set Derived from Active/Passive Microwave Remote Sensing Data Schroeder, Ronny; McDonald, Kyle; Chapman, Bruce Remote Sensing, Vol. 7, Issue 12 https://doi.org/10.3390/rs71215843	journal	December 2015
Net ecosystem exchange of CO2 and CH4 from two Louisiana coastal marshes Krauss, Ken W.; Raynie, Richard; Killebrew, Charles U.S. Geological Survey https://doi.org/10.5066/F7MG7NSV	dataset	January 2018
MCD15A2H MODIS/Terra+Aqua Leaf Area Index/FPAR 8-day L4 Global 500m SIN Grid V006 Myneni, Ranga; Knyazikhin, Yuri; Park, Taejin NASA EOSDIS Land Processes DAAC https://doi.org/10.5067/MODIS/MCD15A2H.006	dataset	January 2015
MOD09A1 MODIS/Terra Surface Reflectance 8-Day L3 Global 500m SIN Grid V006 Vermote, Eric NASA EOSDIS Land Processes DAAC https://doi.org/10.5067/MODIS/MOD09A1.006	dataset	January 2015
MODIS/Terra Snow Cover Daily L3 Global 500m SIN Grid Hall, Dorothy K.; Riggs, George A. NASA National Snow and Ice Data Center DAAC https://doi.org/10.5067/MODIS/MOD10A1.006	dataset	January 2015
MOD11A2 MODIS/Terra Land Surface Temperature/Emissivity 8-Day L3 Global 1km SIN Grid V006 Wan, Zhengming; Hook, Simon; Hulley, Glynn NASA EOSDIS Land Processes Distributed Active Archive Center https://doi.org/10.5067/MODIS/MOD11A2.006	dataset	January 2015
Multi-model mean nitrogen and sulfur deposition from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): evaluation of historical and projected future changes Lamarque, J. -F.; Dentener, F.; McConnell, J. Atmospheric Chemistry and Physics, Vol. 13, Issue 16 https://doi.org/10.5194/acp-13-7997-2013	journal	January 2013
CarbonTracker-CH ₄ : an assimilation system for estimating emissions of atmospheric methane Bruhwiler, L.; Dlugokencky, E.; Masarie, K. Atmospheric Chemistry and Physics, Vol. 14, Issue 16 https://doi.org/10.5194/acp-14-8269-2014	journal	January 2014
Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane Jacob, Daniel J.; Varon, Daniel J.; Cusworth, Daniel H. Atmospheric Chemistry and Physics, Vol. 22, Issue 14 https://doi.org/10.5194/acp-22-9617-2022	journal	July 2022
Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP) Melton, J. R.; Wania, R.; Hodson, E. L. Biogeosciences, Vol. 10, Issue 2 https://doi.org/10.5194/bg-10-753-2013	journal	January 2013
Testing the applicability of neural networks as a gap-filling method using CH ₄ flux data from high latitude wetlands Dengel, S.; Zona, D.; Sachs, T. Biogeosciences, Vol. 10, Issue 12 https://doi.org/10.5194/bg-10-8185-2013	journal	January 2013
Model estimates of climate controls on pan-Arctic wetland methane emissions Chen, X.; Bohn, T. J.; Lettenmaier, D. P. Biogeosciences, Vol. 12, Issue 21 https://doi.org/10.5194/bg-12-6259-2015	journal	January 2015
Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms Tramontana, Gianluca; Jung, Martin; Schwalm, Christopher R. Biogeosciences, Vol. 13, Issue 14 https://doi.org/10.5194/bg-13-4291-2016	journal	January 2016
Scaling carbon fluxes from eddy covariance sites to globe: synthesis and evaluation of the FLUXCOM approach Jung, Martin; Schwalm, Christopher; Migliavacca, Mirco Biogeosciences, Vol. 17, Issue 5 https://doi.org/10.5194/bg-17-1343-2020	journal	January 2020
Gaps in network infrastructure limit our understanding of biogenic methane emissions for the United States Malone, Sparkle L.; Oh, Youmi; Arndt, Kyle A. Biogeosciences, Vol. 19, Issue 9 https://doi.org/10.5194/bg-19-2507-2022	journal	May 2022
Constraining global methane emissions and uptake by ecosystems Spahni, R.; Wania, R.; Neef, L. Biogeosciences, Vol. 8, Issue 6 https://doi.org/10.5194/bg-8-1643-2011	journal	January 2011
Barriers to predicting changes in global terrestrial methane fluxes: analyses using CLM4Me, a methane biogeochemistry model integrated in CESM Riley, W. J.; Subin, Z. M.; Lawrence, D. M. Biogeosciences, Vol. 8, Issue 7 https://doi.org/10.5194/bg-8-1925-2011	journal	January 2011
Upscaled diurnal cycles of land–atmosphere fluxes: a new global half-hourly data product Bodesheim, Paul; Jung, Martin; Gans, Fabian Earth System Science Data, Vol. 10, Issue 3 https://doi.org/10.5194/essd-10-1327-2018	journal	January 2018
Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations Peltola, Olli; Vesala, Timo; Gao, Yao Earth System Science Data, Vol. 11, Issue 3 https://doi.org/10.5194/essd-11-1263-2019	journal	January 2019
The Global Methane Budget 2000–2017 Saunois, Marielle; Stavert, Ann R.; Poulter, Ben Earth System Science Data, Vol. 12, Issue 3 https://doi.org/10.5194/essd-12-1561-2020	journal	January 2020
Development of the global dataset of Wetland Area and Dynamics for Methane Modeling (WAD2M) Zhang, Zhen; Fluet-Chouinard, Etienne; Jensen, Katherine Earth System Science Data, Vol. 13, Issue 5 https://doi.org/10.5194/essd-13-2001-2021	journal	January 2021
FLUXNET-CH₄: a global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands Delwiche, Kyle B.; Knox, Sara Helen; Malhotra, Avni Earth System Science Data, Vol. 13, Issue 7 https://doi.org/10.5194/essd-13-3607-2021	journal	January 2021
BAWLD-CH₄: a comprehensive dataset of methane fluxes from boreal and arctic ecosystems Kuhn, McKenzie A.; Varner, Ruth K.; Bastviken, David Earth System Science Data, Vol. 13, Issue 11 https://doi.org/10.5194/essd-13-5151-2021	journal	January 2021
A global wetland methane emissions and uncertainty dataset for atmospheric chemical transport models (WetCHARTs version 1.0) Bloom, A. Anthony; Bowman, Kevin W.; Lee, Meemong Geoscientific Model Development, Vol. 10, Issue 6 https://doi.org/10.5194/gmd-10-2141-2017	journal	January 2017
WETMETH 1.0: a new wetland methane model for implementation in Earth system models Nzotungicimpaye, Claude-Michel; Zickfeld, Kirsten; MacDougall, Andrew H. Geoscientific Model Development, Vol. 14, Issue 10 https://doi.org/10.5194/gmd-14-6215-2021	journal	October 2021

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