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Title: Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales

Abstract

Abstract While wetlands are the largest natural source of methane (CH 4 ) to the atmosphere, they represent a large source of uncertainty in the global CH 4 budget due to the complex biogeochemical controls on CH 4 dynamics. Here we present, to our knowledge, the first multi‐site synthesis of how predictors of CH 4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet‐based multi‐resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17 ± 11 days, and lagged air and soil temperature by median values of 8 ± 16 and 5 ± 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat‐dominated sites, with drops in PA coincidingmore » with synchronous releases of CH 4 . At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH 4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1‐ to 4‐h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH 4 emissions.« less

Authors:
ORCiD logo [1];  [2]; ORCiD logo [3];  [4];  [5];  [6];  [7]; ORCiD logo [7];  [3]; ORCiD logo [8];  [9]; ORCiD logo [10]; ORCiD logo [11]; ORCiD logo [3];  [12];  [13]; ORCiD logo [14];  [8]; ORCiD logo [15];  [13] more »;  [16];  [3]; ORCiD logo [17];  [18];  [19];  [20];  [21];  [22];  [23];  [3];  [24];  [16];  [25];  [26]; ORCiD logo [27];  [13];  [28];  [26];  [29];  [30];  [31]; ORCiD logo [32];  [33]; ORCiD logo [32];  [34]; ORCiD logo [35];  [36]; ORCiD logo [35]; ORCiD logo [16];  [37]; ORCiD logo [29];  [38];  [39];  [40]; ORCiD logo [41];  [12];  [42]; ORCiD logo [43];  [3] « less
+ Show Author Affiliations
  1. Univ. of British Columbia, Vancouver, BC (Canada)
  2. US Geological Survey, Jamestown, ND (United States). Northern Prairie Wildlife Research Center
  3. Stanford Univ., CA (United States)
  4. Rutgers Univ. Newark, New Brunswick, NJ (United States)
  5. National Ecological Observatory Network, Battelle, Boulder, CO (United States)
  6. Osaka Prefecture University, Sakai (Japan)
  7. Univ. of California, Berkeley, CA (United States)
  8. Univ. of Wisconsin, Madison, WI (United States)
  9. Univ. of Alaska, Fairbanks, AK (United States)
  10. US Geological Survey, Moffett Field, CA (United States). Western Geographic Science Center
  11. Univ. of Helsinki (Finland); Finnish Meteorological Inst. (FMI), Helsinki (Finland)
  12. Sarawak Tropical Peat Research Institute (Malaysia)
  13. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  14. Univ. of Arkansas, Fayetteville, AR (United States)
  15. Univ. of Delaware, Newark, DE (United States)
  16. Finnish Meteorological Inst. (FMI), Helsinki (Finland)
  17. Max Planck Institute for Biogeochemistry, Jena (Germany)
  18. Environment and Climate Change Canada, Victoria, BC (Canada)
  19. Univ. of Montreal, QC (Canada)
  20. Univ. of Helsinki (Finland); Yugra State University, Khanty-Mansiysk (Russia)
  21. US Geological Survey, Lafayette, LA (United States). Wetland and Aquatic Research Center
  22. Univ. of Maryland, College Park, MD (United States)
  23. Stanford Univ., CA (United States); University of Santiago (Chile)
  24. Natural Resources Institute Finland (LUKE), Helsinki (Finland)
  25. The Ohio State Univ., Columbus, OH (United States)
  26. Univ. of Waikato, Hamilton (New Zealand)
  27. Michigan State Univ., East Lansing, MI (United States)
  28. Universidade de Cuiaba (Brazil)
  29. GFZ German Research Centre for Geosciences, Potsdam (Germany)
  30. Hokkaido University, Sapporo (Japan)
  31. Shinshu Univ., Matsumoto, Nagano (Japan)
  32. Univ. of Rostock (Germany)
  33. National Center for Agro Meteorology, Seoul (South Korea)
  34. Univ. of Helsinki (Finland)
  35. Swedish Univ. of Agricultural Sciences (SLU), Umea (Sweden)
  36. National Agriculture and Food Research Organization, Tsukuba (Japan)
  37. Seoul National Univ. (Korea, Republic of)
  38. Kyoto Univ. (Japan)
  39. Cornell Univ., Ithaca, NY (United States)
  40. Univ. of Eastern Finland, Joesnuu (Finland)
  41. California State University, San Marcos CA (United States)
  42. US Geological Survey, Menlo Park, CA (United States)
  43. NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER); National Science Foundation (NSF); Arctic Challenge for Sustainability II (ArCS II); Japan Society for the Promotion of Science (JSPS); National Research Foundation of Korea (NRF); California Department of Fish and Wildlife; USDA; National Institute of Food and Agriculture (NIFA); Canada Research Chairs Program; Canada Foundation for Innovation (CFI); Natural Sciences and Engineering Research Council of Canada (NSERC); National Aeronautics and Space Administration (NASA); Ohio Department of Natural Resources; Academy of Finland; Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning; Kempe Foundation; German Federal Ministry of Food and Agriculture (BMEL); European Union’s Horizon 2020; USGS; Svenska Forskningsrådet Formas
OSTI Identifier:
1844532
Alternate Identifier(s):
OSTI ID: 1785295
Grant/Contract Number:  
AC02-05CH11231; GBMF5439; N18B 315-11; 1652594; DGE-1747503; 1752083; DEB-1440297; 2011-67003-30371; SC0021067; 296116; 312912; 307331; 287039; 330840; 2016-01289; 696356; NRF-2018 R1C1B6002917; JPMXD1420318865; 20K21849; DE‐SC0021067; DEAC02‐05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Global Change Biology
Additional Journal Information:
Journal Volume: 27; Journal Issue: 15; Journal ID: ISSN 1354-1013
Publisher:
Wiley
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; eddy covariance; generalized additive modeling; lags; methane; mutual information; predictors; random forest; synthesis; time scales; wetlands

Citation Formats

Knox, Sara H., Bansal, Sheel, McNicol, Gavin, Schafer, Karina, Sturtevant, Cove, Ueyama, Masahito, Valach, Alex C., Baldocchi, Dennis, Delwiche, Kyle, Desai, Ankur R., Euskirchen, Eugenie, Liu, Jinxun, Lohila, Annalea, Malhotra, Avni, Melling, Lulie, Riley, William, Runkle, Benjamin R. K., Turner, Jessica, Vargas, Rodrigo, Zhu, Qing, Alto, Tuula, Fluet‐Chouinard, Etienne, Goeckede, Mathias, Melton, Joe R., Sonnentag, Oliver, Vesala, Timo, Ward, Eric, Zhang, Zhen, Feron, Sarah, Ouyang, Zutao, Alekseychik, Pavel, Aurela, Mika, Bohrer, Gil, Campbell, David I., Chen, Jiquan, Chu, Housen, Dalmagro, Higo J., Goodrich, Jordan P., Gottschalk, Pia, Hirano, Takashi, Iwata, Hiroki, Jurasinski, Gerald, Kang, Minseok, Koebsch, Franziska, Mammarella, Ivan, Nilsson, Mats B., Ono, Keisuke, Peichl, Matthias, Peltola, Olli, Ryu, Youngryel, Sachs, Torsten, Sakabe, Ayaka, Sparks, Jed P., Tuittila, Eeva‐Stiina, Vourlitis, George L., Wong, Guan X., Windham‐Myers, Lisamarie, Poulter, Benjamin, and Jackson, Robert B. Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales. United States: N. p., 2021. Web. doi:10.1111/gcb.15661.
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Knox, Sara H., Bansal, Sheel, McNicol, Gavin, Schafer, Karina, Sturtevant, Cove, Ueyama, Masahito, Valach, Alex C., Baldocchi, Dennis, Delwiche, Kyle, Desai, Ankur R., Euskirchen, Eugenie, Liu, Jinxun, Lohila, Annalea, Malhotra, Avni, Melling, Lulie, Riley, William, Runkle, Benjamin R. K., Turner, Jessica, Vargas, Rodrigo, Zhu, Qing, Alto, Tuula, Fluet‐Chouinard, Etienne, Goeckede, Mathias, Melton, Joe R., Sonnentag, Oliver, Vesala, Timo, Ward, Eric, Zhang, Zhen, Feron, Sarah, Ouyang, Zutao, Alekseychik, Pavel, Aurela, Mika, Bohrer, Gil, Campbell, David I., Chen, Jiquan, Chu, Housen, Dalmagro, Higo J., Goodrich, Jordan P., Gottschalk, Pia, Hirano, Takashi, Iwata, Hiroki, Jurasinski, Gerald, Kang, Minseok, Koebsch, Franziska, Mammarella, Ivan, Nilsson, Mats B., Ono, Keisuke, Peichl, Matthias, Peltola, Olli, Ryu, Youngryel, Sachs, Torsten, Sakabe, Ayaka, Sparks, Jed P., Tuittila, Eeva‐Stiina, Vourlitis, George L., Wong, Guan X., Windham‐Myers, Lisamarie, Poulter, Benjamin, & Jackson, Robert B. Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales. United States. https://doi.org/10.1111/gcb.15661
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Knox, Sara H., Bansal, Sheel, McNicol, Gavin, Schafer, Karina, Sturtevant, Cove, Ueyama, Masahito, Valach, Alex C., Baldocchi, Dennis, Delwiche, Kyle, Desai, Ankur R., Euskirchen, Eugenie, Liu, Jinxun, Lohila, Annalea, Malhotra, Avni, Melling, Lulie, Riley, William, Runkle, Benjamin R. K., Turner, Jessica, Vargas, Rodrigo, Zhu, Qing, Alto, Tuula, Fluet‐Chouinard, Etienne, Goeckede, Mathias, Melton, Joe R., Sonnentag, Oliver, Vesala, Timo, Ward, Eric, Zhang, Zhen, Feron, Sarah, Ouyang, Zutao, Alekseychik, Pavel, Aurela, Mika, Bohrer, Gil, Campbell, David I., Chen, Jiquan, Chu, Housen, Dalmagro, Higo J., Goodrich, Jordan P., Gottschalk, Pia, Hirano, Takashi, Iwata, Hiroki, Jurasinski, Gerald, Kang, Minseok, Koebsch, Franziska, Mammarella, Ivan, Nilsson, Mats B., Ono, Keisuke, Peichl, Matthias, Peltola, Olli, Ryu, Youngryel, Sachs, Torsten, Sakabe, Ayaka, Sparks, Jed P., Tuittila, Eeva‐Stiina, Vourlitis, George L., Wong, Guan X., Windham‐Myers, Lisamarie, Poulter, Benjamin, and Jackson, Robert B. Thu . "Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales". United States. https://doi.org/10.1111/gcb.15661. https://www.osti.gov/servlets/purl/1844532.
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@article{osti_1844532,
title = {Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales},
author = {Knox, Sara H. and Bansal, Sheel and McNicol, Gavin and Schafer, Karina and Sturtevant, Cove and Ueyama, Masahito and Valach, Alex C. and Baldocchi, Dennis and Delwiche, Kyle and Desai, Ankur R. and Euskirchen, Eugenie and Liu, Jinxun and Lohila, Annalea and Malhotra, Avni and Melling, Lulie and Riley, William and Runkle, Benjamin R. K. and Turner, Jessica and Vargas, Rodrigo and Zhu, Qing and Alto, Tuula and Fluet‐Chouinard, Etienne and Goeckede, Mathias and Melton, Joe R. and Sonnentag, Oliver and Vesala, Timo and Ward, Eric and Zhang, Zhen and Feron, Sarah and Ouyang, Zutao and Alekseychik, Pavel and Aurela, Mika and Bohrer, Gil and Campbell, David I. and Chen, Jiquan and Chu, Housen and Dalmagro, Higo J. and Goodrich, Jordan P. and Gottschalk, Pia and Hirano, Takashi and Iwata, Hiroki and Jurasinski, Gerald and Kang, Minseok and Koebsch, Franziska and Mammarella, Ivan and Nilsson, Mats B. and Ono, Keisuke and Peichl, Matthias and Peltola, Olli and Ryu, Youngryel and Sachs, Torsten and Sakabe, Ayaka and Sparks, Jed P. and Tuittila, Eeva‐Stiina and Vourlitis, George L. and Wong, Guan X. and Windham‐Myers, Lisamarie and Poulter, Benjamin and Jackson, Robert B.},
abstractNote = {Abstract While wetlands are the largest natural source of methane (CH 4 ) to the atmosphere, they represent a large source of uncertainty in the global CH 4 budget due to the complex biogeochemical controls on CH 4 dynamics. Here we present, to our knowledge, the first multi‐site synthesis of how predictors of CH 4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet‐based multi‐resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17 ± 11 days, and lagged air and soil temperature by median values of 8 ± 16 and 5 ± 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat‐dominated sites, with drops in PA coinciding with synchronous releases of CH 4 . At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH 4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1‐ to 4‐h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH 4 emissions.},
doi = {10.1111/gcb.15661},
journal = {Global Change Biology},
number = 15,
volume = 27,
place = {United States},
year = {Thu Apr 29 00:00:00 EDT 2021},
month = {Thu Apr 29 00:00:00 EDT 2021}
}
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  • DOI: 10.1016/j.gca.2020.05.013

Multi-scale temporal variation of methane flux and its controls in a subtropical tidal salt marsh in eastern China
journal, January 2018

Environmental and physical controls on northern terrestrial methane emissions across permafrost zones
journal, November 2012

  • Olefeldt, David; Turetsky, Merritt R.; Crill, Patrick M.
  • Global Change Biology, Vol. 19, Issue 2
  • DOI: 10.1111/gcb.12071

Bias in random forest variable importance measures: Illustrations, sources and a solution
journal, January 2007

  • Strobl, Carolin; Boulesteix, Anne-Laure; Zeileis, Achim
  • BMC Bioinformatics, Vol. 8, Issue 1
  • DOI: 10.1186/1471-2105-8-25

Environmental drivers of methane fluxes from an urban temperate wetland park
journal, November 2014

  • Morin, T. H.; Bohrer, G.; Frasson, R. P. d. M.
  • Journal of Geophysical Research: Biogeosciences, Vol. 119, Issue 11
  • DOI: 10.1002/2014JG002750

Methane emission from tidal freshwater marshes
journal, January 2000

  • Van der Nat, Frans-Jaco; Middelburg, Jack J.
  • Biogeochemistry, Vol. 49, Issue 2, p. 103-121
  • DOI: 10.1023/A:1006333225100

Methane Production Pathway Regulated Proximally by Substrate Availability and Distally by Temperature in a High‐Latitude Mire Complex
journal, October 2019

  • Chang, Kuang‐Yu; Riley, William J.; Brodie, Eoin L.
  • Journal of Geophysical Research: Biogeosciences, Vol. 124, Issue 10
  • DOI: 10.1029/2019JG005355

Causality and Persistence in Ecological Systems: A Nonparametric Spectral Granger Causality Approach
journal, April 2012

  • Detto, Matteo; Molini, Annalisa; Katul, Gabriel
  • The American Naturalist, Vol. 179, Issue 4
  • DOI: 10.1086/664628

The Influence of Water Table Levels on Methane and Carbon Dioxide Emissions from Peatland Soils
journal, February 1989

  • Moore, T. R.; Knowles, R.
  • Canadian Journal of Soil Science, Vol. 69, Issue 1
  • DOI: 10.4141/cjss89-004

Plants, microorganisms, and soil temperatures contribute to a decrease in methane fluxes on a drained Arctic floodplain
journal, November 2016

  • Kwon, Min Jung; Beulig, Felix; Ilie, Iulia
  • Global Change Biology, Vol. 23, Issue 6
  • DOI: 10.1111/gcb.13558

Controls for multi-scale temporal variation in ecosystem methane exchange during the growing season of a permanently inundated fen
journal, May 2015

Variable selection using random forests
journal, October 2010

  • Genuer, Robin; Poggi, Jean-Michel; Tuleau-Malot, Christine
  • Pattern Recognition Letters, Vol. 31, Issue 14
  • DOI: 10.1016/j.patrec.2010.03.014

Methane emission from rice: Stable isotopes, diurnal variations, and CO 2 exchange
journal, March 1997

  • Chanton, J. P.; Whiting, G. J.; Blair, N. E.
  • Global Biogeochemical Cycles, Vol. 11, Issue 1
  • DOI: 10.1029/96GB03761

Effects of soil rewetting and thawing on soil gas fluxes: a review of current literature and suggestions for future research
journal, January 2012

Standardisation of eddy-covariance flux measurements of methane and nitrous oxide
journal, December 2018

  • Nemitz, Eiko; Mammarella, Ivan; Ibrom, Andreas
  • International Agrophysics, Vol. 32, Issue 4
  • DOI: 10.1515/intag-2017-0042

Annual methane emission from Finnish mires estimated from eddy covariance campaign measurements
journal, September 2001

  • Hargreaves, K. J.; Fowler, D.; Pitcairn, C. E. R.
  • Theoretical and Applied Climatology, Vol. 70, Issue 1-4
  • DOI: 10.1007/s007040170015

Cold season emissions dominate the Arctic tundra methane budget
journal, December 2015

  • Zona, Donatella; Gioli, Beniamino; Commane, Róisín
  • Proceedings of the National Academy of Sciences, Vol. 113, Issue 1
  • DOI: 10.1073/pnas.1516017113

Independent coordinates for strange attractors from mutual information
journal, February 1986

Air pressure and methane fluxes
journal, October 1990

  • Mattson, Mark D.; Likens, Gene E.
  • Nature, Vol. 347, Issue 6295
  • DOI: 10.1038/347718b0

Overriding control of methane flux temporal variability by water table dynamics in a Southern Hemisphere, raised bog: Methane fluxes from a S.H. bog
journal, May 2015

  • Goodrich, J. P.; Campbell, D. I.; Roulet, N. T.
  • Journal of Geophysical Research: Biogeosciences, Vol. 120, Issue 5
  • DOI: 10.1002/2014JG002844

Comparing methane ebullition variability across space and time in a Brazilian reservoir
journal, January 2020

  • Linkhorst, Annika; Hiller, Carolin; DelSontro, Tonya
  • Limnology and Oceanography, Vol. 65, Issue 7
  • DOI: 10.1002/lno.11410

Factors controlling large scale variations in methane emissions from wetlands: METHANE EMISSIONS FROM WETLANDS
journal, April 2003

  • Christensen, Torben R.; Ekberg, Anna; Ström, Lena
  • Geophysical Research Letters, Vol. 30, Issue 7
  • DOI: 10.1029/2002GL016848

ranger : A Fast Implementation of Random Forests for High Dimensional Data in C++ and R
journal, January 2017

  • Wright, Marvin N.; Ziegler, Andreas
  • Journal of Statistical Software, Vol. 77, Issue 1
  • DOI: 10.18637/jss.v077.i01

Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions
journal, April 2021

Methane emissions from wetlands: biogeochemical, microbial, and modeling perspectives from local to global scales
journal, February 2013

  • Bridgham, Scott D.; Cadillo-Quiroz, Hinsby; Keller, Jason K.
  • Global Change Biology, Vol. 19, Issue 5
  • DOI: 10.1111/gcb.12131

Uncertainty in eddy covariance measurements and its application to physiological models
journal, July 2005

Net ecosystem methane and carbon dioxide exchanges in a Lake Erie coastal marsh and a nearby cropland: CH4 and CO2 fluxes in a freshwater marsh
journal, May 2014

  • Chu, Housen; Chen, Jiquan; Gottgens, Johan F.
  • Journal of Geophysical Research: Biogeosciences, Vol. 119, Issue 5
  • DOI: 10.1002/2013JG002520

Effects of seasonality, transport pathway, and spatial structure on greenhouse gas fluxes in a restored wetland
journal, January 2017

  • McNicol, Gavin; Sturtevant, Cove S.; Knox, Sara H.
  • Global Change Biology, Vol. 23, Issue 7
  • DOI: 10.1111/gcb.13580

Carbon dioxide and methane exchange at a cool-temperate freshwater marsh
journal, June 2015

RESPONSE OF CO 2 AND CH 4 EMISSIONS FROM PEATLANDS TO WARMING AND WATER TABLE MANIPULATION
journal, April 2001

Biophysical controls on interannual variability in ecosystem-scale CO 2 and CH 4 exchange in a California rice paddy : INTERANNUAL VARIABILITY RICE CH
journal, March 2016

  • Knox, Sara Helen; Matthes, Jaclyn Hatala; Sturtevant, Cove
  • Journal of Geophysical Research: Biogeosciences, Vol. 121, Issue 3
  • DOI: 10.1002/2015JG003247

Random Forests
journal, January 2001

Conditional variable importance for random forests
journal, July 2008

  • Strobl, Carolin; Boulesteix, Anne-Laure; Kneib, Thomas
  • BMC Bioinformatics, Vol. 9, Issue 1
  • DOI: 10.1186/1471-2105-9-307

Evaluating the Classical Versus an Emerging Conceptual Model of Peatland Methane Dynamics: Peatland Methane Dynamics
journal, September 2017

  • Yang, Wendy H.; McNicol, Gavin; Teh, Yit Arn
  • Global Biogeochemical Cycles, Vol. 31, Issue 9
  • DOI: 10.1002/2017GB005622

FLUXNET-CH4 BR-Npw Northern Pantanal Wetland
dataset, January 2020

  • 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
  • DOI: 10.18140/flx/1669368

FLUXNET-CH4 CA-SCB Scotty Creek Bog
dataset, January 2020

  • Sonnentag, Oliver; Helbig, Manuel
  • FluxNet; Université de Montréal; Wilfrid Laurier University
  • DOI: 10.18140/flx/1669613

FLUXNET-CH4 DE-Hte Huetelmoor
dataset, January 2020

  • Koebsch, Franziska; Jurasinski, Gerald
  • FluxNet; Landscape Ecology, University of Rostock
  • DOI: 10.18140/flx/1669634

FLUXNET-CH4 DE-Zrk Zarnekow
dataset, January 2020

  • Sachs, Torsten; Wille, Christian
  • FluxNet; GFZ German Research Centre for Geosciences
  • DOI: 10.18140/flx/1669636

FLUXNET-CH4 FI-Lom Lompolojankka
dataset, January 2020

  • Lohila, Annalea; Aurela, Mika; Tuovinen, Juha-Pekka
  • FluxNet; Finnish Meteorological Institute
  • DOI: 10.18140/flx/1669638

FLUXNET-CH4 FI-Si2 Siikaneva-2 Bog
dataset, January 2020

  • Vesala, Timo; Tuittila, Eeva-Stiina; Mammarella, Ivan
  • FluxNet; University of Eastern Finland; University of Helsinki
  • DOI: 10.18140/flx/1669639

FLUXNET-CH4 FI-Sii Siikaneva
dataset, January 2020

  • Vesala, Timo; Tuittila, Eeva-Stiina; Mammarella, Ivan
  • FluxNet; University of Eastern Finland; University of Helsinki
  • DOI: 10.18140/flx/1669640

FLUXNET-CH4 ID-Pag Palangkaraya undrained forest
dataset, January 2020

  • Sakabe, Ayaka; Itoh, Masayuki; Hirano, Takashi
  • FluxNet; Hokkaido University; Kyoto University; University of Hyogo; University of Palangkaraya
  • DOI: 10.18140/flx/1669643

FLUXNET-CH4 JP-BBY Bibai bog
dataset, January 2020

  • Ueyama, Masahito; Hirano, Takashi; Kominami, Yasuhiro
  • FluxNet; Osaka Prefecture Univeristy
  • DOI: 10.18140/flx/1669646

FLUXNET-CH4 JP-Mse Mase rice paddy field
dataset, January 2020

  • Iwata, Hiroki
  • FluxNet; National Agriculture and Food Research Organization
  • DOI: 10.18140/flx/1669647

FLUXNET-CH4 KR-CRK Cheorwon Rice paddy
dataset, January 2020

  • Ryu, Youngryel; Kang, Minseok; Kim, Jongho
  • FluxNet; National Center for AgroMeteorology; Seoul National University
  • DOI: 10.18140/flx/1669649

FLUXNET-CH4 MY-MLM Maludam National Park
dataset, January 2020

  • Wong, Guan; Melling, Lulie; Tang, Angela
  • FluxNet; Sarawak Tropical Peat Research Institute
  • DOI: 10.18140/flx/1669650

FLUXNET-CH4 NZ-Kop Kopuatai
dataset, January 2020

FLUXNET-CH4 SE-Deg Degero
dataset, January 2020

  • Nilsson, Mats; Peichl, Matthias
  • FluxNet; Department of Forest Ecology and Management; Swedish University of Agricultural Sciences
  • DOI: 10.18140/flx/1669659

FLUXNET-CH4 US-Los Lost Creek
dataset, January 2020

FLUXNET-CH4 US-MAC MacArthur Agro-Ecology
dataset, January 2020

FLUXNET-CH4 US-Myb Mayberry Wetland
dataset, January 2020

  • Matthes, Jaclyn; Sturtevant, Cove; Oikawa, Patty
  • FluxNet; University of California, Berkeley
  • DOI: 10.18140/flx/1669685

FLUXNET-CH4 US-OWC Old Woman Creek
dataset, January 2020

  • Bohrer, Gil; Kerns, Janice; Morin, Timothy
  • FluxNet; Old Woman Creek National Estuarine Research Reserve; The Ohio State University
  • DOI: 10.18140/flx/1669690

FLUXNET-CH4 US-Tw1 Twitchell Wetland West Pond
dataset, January 2020

  • Valach, Alex; Szutu, Daphne; Eichelmann, Elke
  • FluxNet; University of California, Berkeley
  • DOI: 10.18140/flx/1669696

FLUXNET-CH4 US-Twt Twitchell Island
dataset, January 2020

  • Knox, Sara; Matthes, Jaclyn; Verfaillie, Joseph
  • FluxNet; University of California, Berkeley
  • DOI: 10.18140/flx/1669700

FLUXNET-CH4 US-Uaf University of Alaska, Fairbanks
dataset, January 2020

  • Iwata, Hiroki; Ueyama, Masahito; Harazono, Yoshinobu
  • FluxNet; Osaka Prefecture University; Shinshu University
  • DOI: 10.18140/flx/1669701
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