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1. Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Author

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

Published
2021
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4. CO2 uptake and ecophysiological parameters of the grain crops of midcontinent North America: Estimates from flux tower measurements

Author

Gilmanov, Tagir G., Wylie, Bruce K., Tieszen, Larry L., Meyers, Tilden P., Baron, Vern S., Bernacchi, Carl J., Billesbach, David P., Burba, George G., Fischer, Marc L., Glenn, Aaron J., Hanan, Niall P., Hatfield, Jerry L., Heuer, Mark W., Hollinger, Steven E., Howard, Daniel M., Matamala, Roser, Prueger, John H., Tenuta, Mario, and Young, David G.

Published
2013
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7. FLUXNET-CH4 : a global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands

Author

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

Subjects
1171 Geosciences, Earth sciences, SDG 17 - Partnerships for the Goals, Physical Geography, ddc:550, 114 Physical sciences, 1172 Environmental sciences, Atmospheric Sciences
Abstract

Methane (CH$_{4}$) emissions from natural landscapes constitute roughly half of global CH$_{4}$ 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 CH$_{4}$ flux are ideal for constraining ecosystem-scale CH$_{4}$ emissions due to quasi-continuous and high-temporal-resolution CH$_{4}$ 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-CH$_{4}$ Version 1.0, the first open-source global dataset of CH$_{4}$ 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 CH$_{4}$ 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-CH$_{4}$ representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH$_{4}$ Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH$_{4}$ emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH$_{4}$ 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 CH$_{4}$ emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20° S to 20° N) the spring onset of elevated CH$_{4}$ emissions starts 3 d earlier, and the CH$_{4}$ emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH$_{4}$ emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH$_{4}$ emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH$_{4}$ emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH$_{4}$ emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH$_{4}$ modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH$_{4}$ peak). FLUXNET-CH$_{4}$ is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH$_{4}$ 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 https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH$_{4}$ 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.

Published
2021

10. BOREAS TF-11 SSA-Fen 1996 Water Surface Film Capping Data

Author

Billesbach, David P, Hall, Forrest G, and Knapp, David E

Subjects
Earth Resources And Remote Sensing
Abstract

The BOREAS TF-11 team gathered a variety of data to complement its tower flux measurements collected at the SSA-Fen site. The data described in this document were made by the TF-11 team at the SSA-Fen site to quantify the effect that the films observed to form on open water surfaces had on the transfer of carbon dioxide and methane from the water to the air. Measurements of fluxes of carbon dioxide and methane were made in 1994 and in 1996 using the chamber flux method. A gas chromatograph and a LI-COR LI-6200 were used to measure concentrations and to calculate the fluxes. The data are stored in tabular ASCII files.

Published
2000

11. Much stronger tundra methane emissions during autumn freeze than spring thaw.

Author

Tao Bao, Xiyan Xu, Gensuo Jia, Billesbach, David P., and Sullivan, Ryan C.

Subjects
TUNDRAS, FREEZES (Meteorology), THAWING, FREEZING, SOIL temperature, GROWING season
Abstract

Warming in the Arctic has been more apparent in the non-growing season than in the typical growing season. In this context, methane (CH4) emissions in the non-growing season, particularly in the shoulder seasons, account for a substantial proportion of the annual budget. However, CH4 emissions in spring and autumn shoulders are often underestimated by land models and measurements due to limited data availability and unknown mechanisms. This study investigates CH4 emissions during spring thaw and autumn freeze using eddy covariance CH4 measurements from three Arctic sites with multi-year observations. We find that the shoulder seasons contribute to about a quarter (25.6 ± 2.3%, mean ± SD) of annual total CH4 emissions. Our study highlights the three to four times higher contribution of autumn freeze CH4 emission to total annual emission than that of spring thaw. Autumn freeze exhibits significantly higher CH4 flux (0.88 ± 0.03 mg m-2 hr-1) than spring thaw (0.48 ± 0.04 mg m-2 hr-1). The mean duration of autumn freeze (58.94 ± 26.39 days) is significantly longer than that of spring thaw (20.94 ± 7.79 days), which predominates the much higher cumulative CH4 emission during autumn freeze (1,212.31 ± 280.39 mg m-2 year-1) than that during spring thaw (307.39 ± 46.11 mg m-2 year-1). Near-surface soil temperatures cannot completely reflect the freeze-thaw processes in deeper soil layers and appears to have a hysteresis effect on CH4 emissions from early spring thaw to late autumn freeze. Therefore, it is necessary to consider commonalities and differences in CH4 emissions during spring thaw versus autumn freeze to accurately estimate CH4 source from tundra ecosystems for evaluating carbon-climate feedback in Arctic. [ABSTRACT FROM AUTHOR]

Published
2021
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12. Productivity and CO2 exchange of the leguminous crops: Estimates from flux-tower measurements

Author

Gilmanov, Tagir G., Baker, John M., Bernacchi, Carl J., Billesbach, David P., Burba, George G., Castro, Saulo, Chen, Jiquan, Eugster, Werner, Fischer, Marc L., Gamon, John A., Gebremedhin, Maheteme, Glenn, Aaron J., Griffis, Timothy J., Hatfield, Jerry L., Heuer, Mark W., Howard, Daniel M., Leclerc, Monique Y., Loescher, Henry W., Marloie, Olivier, Meyers, Tilden P., Olioso, Albert, Phillips, Rebecca L., Prueger, John H., Skinner, R. Howard, Suyker, Andrew E., Tenuta, Mario, Wylie, Bruce K., South Dakota State University (SDSTATE), Soil & water management unit, United States Department of Agriculture, Biological systems engineering department, University of Nebraska System, LI-COR Biosciences, Department of Biological Sciences [Edmonton], University of Alberta, Department of Earth and Atmospheric Sciences [Edmonton], University of Toledo, Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology in Zürich [Zürich] (ETH Zürich), Energy and Environment Technologies Division [LBNL Berkeley], Lawrence Berkeley National Laboratory [Berkeley] (LBNL), Departments of earth & atmospheric sciences and biological sciences, Science and engineering alliance, Science and technolohy branch, Agriculture and Agri-Food [Ottawa] (AAFC), Department soil, water & climate, University of Minnesota [Twin Cities], University of Minnesota System-University of Minnesota System, National laboratory for agriculture and the environment, ARL Atmospheric Turbulence and Diffusion Division (ATD), NOAA Air Resources Laboratory (ARL), National Oceanic and Atmospheric Administration (NOAA)-National Oceanic and Atmospheric Administration (NOAA), Stinger Ghaffarian Technologies (SGT), Laboratory for environmental physics, University of Georgia [USA], National Ecological Observatory Network, Science Office (NEON), Institute of Arctic and Alpine Research (INSTAAR), University of Colorado [Boulder], Unité de Recherches Forestières Méditerranéennes (URFM), Institut National de la Recherche Agronomique (INRA), Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Land care research, National laboratory for agricuture and the environment, School of natural resources, Department of soil science, University of Manitoba [Winnipeg], Center for Earth Resources Observation and Science (EROS), United States Geological Survey [Reston] (USGS), USDOE, Biological and Environmental Research, Terrestrial Carbon Program [DE-FG02-04ER63917, DE-FG02-04ER63911], CarboEuropeIP, Fluxnet-Canada, CFCAS, NSERC, BIOCAP, Environment Canada, NRCan, Canadian Foundation for Innovation, iCORE (Alberta Innovates Technology Futures), USGS Land Change Science Program, USDA-ARS, National Science Foundation (NSF), USDOE, CARBOFRANCE project funded by the European FP7 Program [GOCECT-2003-505572], French Ministry in charge of Environment (GICC programme), USDOE, Office of Science [DE-FCO2-07ER64494], Office of Energy Efficiency and Renewable Energy [DE-ACO5-76RL01830], Energy Efficiency and Renewable Energy [DE-ACO5-76RL01830], NSF LTER Program [DEB 1027253], MSU AgBioResearch, Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), and University of Minnesota [Twin Cities] (UMN)

Subjects
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, [SDE.MCG]Environmental Sciences/Global Changes
Abstract

Net CO2 exchange data of legume crops at 17 flux tower sites in North America and 3 sites in Europe representing 29 site-years of measurements were partitioned into gross photosynthesis and ecosystem respiration by using nonrectangular hyperbolic light-response function method. The analyses produced net CO2 exchange data and new ecosystem-scale ecophysiological parameter estimates for of legume crops determined at the diurnal and weekly time steps. Dynamics and annual totals of gross photosynthesis, ecosystem respiration, and net ecosystem production were calculated by gap-filling with multivariate nonlinear regression. Comparison with the data from grain crops obtained with the same method demonstrated that CO2 exchange rates and ecophysiological parameters of legumes were lower than for maize, but higher than for wheat crops. Year-round annual legume crops demonstrated a broad range of net ecosystem production, from sinks of +760 g CO2 m-2 yr-1 to sources of –2100 g CO2 m-2 yr-1, with average of –330 g CO2 m-2 yr-1, indicating overall moderate CO2-source activity related to shorter period of photosynthetic uptake and metabolic costs of nitrogen fixation. Perennial legumes (alfalfa) were strong sinks for atmospheric CO2 with average NEP of +980 (range 550 to 1200) g CO2 m-2 yr-1

Published
2014

14. Productivity and Carbon Dioxide Exchange of Leguminous Crops: Estimates from Flux Tower Measurements.

Author

Gilmanov, Tagir G., Baker, John M., Bernacchi, Carl J., Billesbach, David P., Burba, George G., Castro, Saulo, Jiquan Chen, Eugster, Werner, Fischer, Marc L., Gamon, John A., Gebremedhin, Maheteme T., Glenn, Aaron J., Griffis, Timothy J., Hatfield, Jerry L., Heuer, MarkW., Howard, Daniel M., Ledere, Monique Y., Loescher, Henry W., Marloie, Oliver, and Meyers, Tilden P.

Abstract

Net CO2 exchange data of legume crops at 17 flux tower sites in North America and three sites in Europe representing 29 site-years of measurements were partitioned into gross photosynthesis and ecosystem respiration by using the nonrectangular hyperbolic light-response function method. The analyses produced net CO2 exchange data and new ecosystem-scale ecophysiological parameter estimates for legume crops determined at diurnal and weekly time steps. Dynamics and annual totals ofgross photosynthesis, ecosystem respiration, and net ecosystem production were calculated by gap filling with multivariate nonlinear regression. Comparison with the data from grain crops obtained with the same method demonstrated that CO2 exchange rates and ecophysiological parameters of legumes were lowerthan those of maize (ZeamaysL.) but higherthanforwheat (TriticumaestipumL.) crops. Year-round annuallegume crops demonstrated a broad range of net ecosystem production, from sinks of 760 g CO2 m-2 yr-1 to sources of -2100 g CO2 m-2 yr-1, with an average of -330 g CO2 m-2 yr-1, indicating overall moderate CO2-source activity related to a shorter period of photosynthetic uptake and metabolic costs of N2 fixation. Perennial legumes (alfalfa, Medicago sativa L.) were strong sinks for atmospheric CO2, with an average net ecosystem production of 980 (range 550-1200) g CO2 m-2 yr-1. [ABSTRACT FROM AUTHOR]

Published
2014
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16. Spatiotemporal Variations in Growing Season Exchanges of CO2, H2O, and Sensible Heat in Agricultural Fields of the Southern Great Plains.

Author

Fischer, Marc L., Billesbach, David P., Berry, Joseph A., Riley, William J., and Torn, Margaret S.

Subjects
*AGRICULTURE, *CLIMATOLOGY, *CARBON dioxide, *LAND use, *CARBON cycle, *WHEAT, *METEOROLOGICAL precipitation
Abstract

Climate, vegetation cover, and management create finescale heterogeneity in unirrigated agricultural regions, with important but not well-quantified consequences for spatial and temporal variations in surface CO2, water, and heat fluxes. Eddy covariance fluxes were measured in seven agricultural fields—comprising winter wheat, pasture, and sorghum—in the U.S. Southern Great Plains (SGP) during the 2001–03 growing seasons. Land cover was the dominant source of variation in surface fluxes, with 50%–100% differences between fields planted in winter–spring versus fields planted in summer. Interannual variation was driven mainly by precipitation, which varied more than twofold between years. Peak aboveground biomass and growing season net ecosystem exchange (NEE) of CO2 increased in rough proportion to precipitation. Based on a partitioning of gross fluxes with a regression model, ecosystem respiration increased linearly with gross primary production, but with an offset that increased near the time of seed production. Because the regression model was designed for well-watered periods, it successfully retrieved NEE and ecosystem parameters during the peak growing season and identified periods of moisture limitation during the summer. In summary, the effects of crop type, land management, and water limitation on carbon, water, and energy fluxes were large. Capturing the controlling factors in landscape-scale models will be necessary to estimate the ecological feedbacks to climate and other environmental impacts associated with changing human needs for agricultural production of food, fiber, and energy. [ABSTRACT FROM AUTHOR]

Published
2007
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17. Seasonal variation in methane emission from a temperate Phragmites-dominated marsh: effect of growth stage and plant-mediated transport.

Author

Kim, JooN., Verma, Shashi B., and Billesbach, David P.

Subjects
METHANE, MARSHES, PHRAGMITES
Abstract

AbstractThe eddy covariance technique was employed with a tunable diode laser spectrometer to quantify methane flux from a prairie marsh dominated by Phragmites australis in north-central Nebraska, USA. The observations spanned the entire growing season (April to October) and a wide range of weather conditions, allowing a quantitative assessment of the physical and biological controls of methane emission in this ecosystem. Diel patterns in methane emission varied markedly depending on plant growth stage. Prior to plant emergence above water, the rate of methane emission from the marsh was fairly constant throughout the day. After emergence above water, there was a gradual increase in methane emission after sunrise with a peak in late afternoon. Significant changes in diel patterns were observed after tillering. Then, the diel pattern was characterized by a mid- to late-morning peak and a 2-to 4-fold increase in methane emissions from night to daytime. In early stages of plant growth, molecular diffusion through dead/live plants and the standing water column seemed to be the primary transport mechanism. After tillering, a transition occurred in the transport mechanism from a molecular diffusion to a convective throughflow, which is a rapid and active gas transport driven by pressure differences. The role of convective throughflow became less important as the plants senesced. Integrated methane emission over the six-month measurement period (April–October) was about 64 g CH4 m–2. On an annual basis, we estimate the annual methane emission from this ecosystem to be ≈ 80 g CH4 m–2 and that about 80% of the total methane emission occurred between late April and late October. [ABSTRACT FROM AUTHOR]

Published
1999
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20. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

Author

Pastorello, Gilberto Z., Trotta, Carlo, Canfora, Eleonora, Chu, Housen, Christianson, Danielle S., Cheah, Youwei, Poindexter, Cristina M., Chen, Jiquan, Elbashandy, Abdelrahman, Humphrey, Marty, Isaac, Peter, Polidori, Diego, Ribeca, Alessio, van Ingen, Catharine, Zhang, Leiming, Amiro, Brian D., Ammann, Christoph, Arain, Muhammad A., Ardö, Jonas, Arndt, Stefan K., Arriga, Nicola, Aubinet, Marc, Aurela, Mika, Baldocchi, Dennis D., Barr, Alan G., Beamesderfer, Eric R., Marchesini, Luca B., Bergeron, Onil, Beringer, Jason, Bernhofer, Christian, Berveiller, Daniel, Billesbach, David P., Black, Thomas A., Blanken, Peter D., Bohrer, Gil, Boike, Julia, Bolstad, Paul V., Bonal, Damien, Bonnefond, Jean Marc, Bowling, David R., Bracho, Rosvel, Brodeur, Jason J., Brümmer, Christian, Buchmann, Nina, Burban, Benoit, Burns, Sean P., Buysse, Pauline, Cale, Peter, Cavagna, Mauro, Cellier, Pierre, Chen, Shiping, Chini, Isaac, Christensen, Torben R., Cleverly, James, Collalti, Alessio, Consalvo, Claudia, Cook, Bruce D., Cook, David, Cremonese, Edoardo, Curtis, Peter S., D'Andrea, Ettore, da Rocha, Humberto R., Dai, Xiaoqin, Davis, Kenneth J., de Cinti, Bruno, De Grandcourt, Agnès, De Ligne, Anne, de Oliveira Jr., Raimundo C., Delpierre, Nicolas, Desai, Ankur R., Di Bella, Carlos M., Di Tommasi, Paul, Dolman, Han A.J., Domingo, Francisco, Dong, Gang, Dore, Sabina, Duce, Pierpaolo, Dufrêne, Éric, Dunn, Allison, Dušek, Jiří, Eamus, Derek, Eichelmann, Uwe, ElKhidir, Hatim A.M., Eugster, Werner, Ewenz, Cäcilia, Ewers, Brent E., Famulari, Daniela, Fares, Silvano, Feigenwinter, Iris, Feitz, Andrew J., Fensholt, Rasmus, Filippa, Gianluca, Fischer, Marc, Frank, John, Galvagno, Marta, Gharun, Mana, Gianelle, Damiano, Gielen, Bert, Gioli, Beniamino, Gitelson, Anatoly A., Goded, Ignacio, Goeckede, Mathias, Goldstein, Allen H., Gough, Christopher, Hanson, Chad V., Hatakka, Juha, He, Yongtao, Hehn, Markus, Heinesch, Bernhard, Hinko-Najera, Nina, Hörtnagl, Lukas, Hutley, Lindsay B., Ibrom, Andreas, Ikawa, Hiroki, Jackowicz-Korczyński, Marcin, Janous, Dalibor, Jans, Wilma W.P., Jassal, Rachhpal, Jiang, Shicheng, Kato, Tomomichi, Khomik, Myroslava, Klatt, Janina, Goulden, Michael L., Graf, Alexander, Griebel, Anne, Gruening, Carsten, Grünwald, Thomas, Hammerle, Albin, Han, Shijie, Han, Xingguo, Hansen, Birger Ulf, Knohl, Alexander, Knox, Sara H., Kobayashi, Hideki, Koerber, Georgia R., Kolle, Olaf, Kosugi, Yoshiko, Kotani, Ayumi, Kowalski, Andrew S., Kruijt, Bart, Kurbatova, Juliya, Kutsch, Werner L., Kwon, Hyojung, Launiainen, Samuli, Laurila, Tuomas, Law, Bev, Leuning, Ray, Li, Yingnian, Liddell, Michael, Limousin, Jean M., Lion, Marryanna, Lohila, Annalea, López-Ballesteros, Ana, López-Blanco, Efrén, Loubet, Benjamin, Loustau, Denis, Lucas-Moffat, Antje M., Lüers, Johannes, Ma, Siyan, Macfarlane, Craig, Magliulo, Vincenzo, Maier, Regine, Mammarella, Ivan, Manca, Giovanni, Marcolla, Barbara, Margolis, Hank A., Marras, Serena, Massman, William J., Mastepanov, Mikhail, Matamala, Roser, Matthes, Jaclyn H., Mazzenga, Francesco, McCaughey, Harry, McHugh, Ian, McMillan, Andrew M.S., Merbold, Lutz, Meyer, Wayne S., Meyers, Tilden, Miller, Scott D., Minerbi, Stefano, Moderow, Uta, Monson, Russell K., Montagnani, Leonardo, Moore, Caitlin, Moors, Eddy J., Moreaux, Virginie, Moureaux, Christine, Munger, J. William, Nakai, Taro, Neirynck, Johan, Nesic, Zoran, Nicolini, Giacomo, Noormets, Asko, Northwood, Matthew, Nosetto, Marcelo D., Nouvellon, Yann, Novick, Kimberly A., Oechel, Walter C., Olesen, Jorgen E., Ourcival, Jean-Marc, Papuga, Shirley A., Parmentier, Frans-Jan W., Paul-Limoges, Eugénie, Pavelka, Marián, Peichl, Matthias, Pendall, Elise G., Phillips, Richard P., Pilegaard, Kim, Pirk, Norbert, Posse, Gabriela, Powell, Thomas L., Prasse, Heiko, Prober, Suzanne M., Rambal, Serge, Rannik, Üllar, Raz-Yaseef, Naama, Reed, David E., Resco de Dios, Victor, Restrepo-Coupe, Natalia, Reverter, Borja R., Roland, Marilyn, Sabbatini, Simone, Sachs, Torsten, Saleska, Scott R., Sánchez-Cañete, Enrique P., Sanchez-Mejia, Zulia M., Schmid, Hans P., Schmidt, Marius, Schneider, Karl, Schrader, Frederik, Scott, Russell L., Sedlák, Pavel, Serrano-Ortiz, Penelope, Shao, Changliang, Shi, Peili, Shironya, Ivan I., Siebicke, Lukas, Šigut, Ladislav, Silberstein, Richard, Sirca, Costantino, Spano, Donatella, Steinbrecher, Rainer, Stevens, Robert, Sturtevant, Cove S., Suyker, Andrew E., Tagesson, Torbern, Takanashi, Satoru, Tang, Yanhong, Tapper, Nigel J., Thom, Jonathan, Tiedemann, Frank, Tomassucci, Michele, Tuovinen, Juha-Pekka, Urbanski, Shawn, Valentini, Riccardo, Van Der Molen, Michiel K., van Gorsel, Eva, van Huissteden, Ko J., Varlagin, Andrej, Verfaillie, Joseph, Vesala, Timo, Vincke, Caroline, Vitale, Domenico, Vygodskaya, Natascha N., Walker, Jeffrey, Walter-Shea, Elizabeth A., Wang, Huimin, Weber, Robin, Westermann, Sebastian, Wille, Christian, Wofsy, Steven C., Wohlfahrt, Georg, Wolf, Sebastian, Woodgate, William L., Li, Yuelin, Zampedri, Roberto, Zhang, Junhui, Zhou, Guoyi, Zona, Donatella, Agarwal, Deborah A., Biraud, Sébastien C., Torn, Margaret S., and Papale, Dario

Subjects
13. Climate action, 15. Life on land
Abstract

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible., Scientific Data, 7, ISSN:2052-4463

21. FLUXNET-CH4: a global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands

Author

Delwiche, Kyle B., Knox, Sara Helen, Malhotra, Avni, Fluet-Chouinard, Etienne, McNicol, Gavin, Feron, Sarah, Ouyang, Zutao, Papale, Dario, Trotta, Carlo, Canfora, Eleonora, Cheah, You-Wei, Christianson, Danielle, Alberto, Ma. Carmelita R., Alekseychik, Pavel, Aurela, Mika, Baldocchi, Dennis, Bansal, Sheel, Billesbach, David P., Bohrer, Gil, Bracho, Rosvel, Buchmann, Nina, Campbell, David I., Celis, Gerardo, Chen, Jiquan, Chen, Weinan, Chu, Housen, and Hörtnagl, Lukas

Subjects
13. Climate action, 15. Life on land
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 20∘ S to 20∘ N) the spring onset of elevated CH4 emissions starts 3 d earlier, and the CH4 emission season lasts 4 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 https://doi.org/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., Earth System Science Data, 13 (7), ISSN:1866-3516, ISSN:1866-3508

22. FLUXNET-CH$_{4}$: a global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands

Author

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

Subjects
13. Climate action, 15. Life on land, 6. Clean water
Abstract

Methane (CH$_{4}$) emissions from natural landscapes constitute roughly half of global CH$_{4}$ 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 CH$_{4}$ flux are ideal for constraining ecosystem-scale CH$_{4}$ emissions due to quasi-continuous and high-temporal-resolution CH$_{4}$ 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-CH$_{4}$ Version 1.0, the first open-source global dataset of CH$_{4}$ 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 CH$_{4}$ 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-CH$_{4}$ representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH$_{4}$ Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH$_{4}$ emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH$_{4}$ 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 CH$_{4}$ emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20�� S to 20�� N) the spring onset of elevated CH$_{4}$ emissions starts 3 d earlier, and the CH$_{4}$ emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH$_{4}$ emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH$_{4}$ emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH$_{4}$ emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH$_{4}$ emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH$_{4}$ modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH$_{4}$ peak). FLUXNET-CH$_{4}$ is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH$_{4}$ 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 https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH$_{4}$ 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.

23. Dynamics of CO2 and H2O fluxes in Johnson grass in the U.S. Southern Great Plains.

Author

Wagle, Pradeep, Gowda, Prasanna H., Billesbach, David P., Northup, Brian K., Torn, Margaret S., Neel, James P.S., and Biraud, Sébastien C.

Abstract

Johnson grass (Sorghum halepense (L.) Pers.) is rapidly spreading throughout the continental United States (U.S.). Thus, determining magnitudes and seasonal dynamics of carbon dioxide (CO 2) and water vapor (H 2 O) fluxes in Johnson grass is crucial to understand regional changes in hydrology and carbon balance. Using eddy covariance (EC), CO 2 and H 2 O fluxes were measured from June 2017 to October 2019 over a rainfed Johnson grass field in central Oklahoma. Hay was harvested from late May to early July each year, with biomass yield ~7.5 t ha−1. Weekly averaged daily integrated net ecosystem CO 2 exchange (NEE), gross primary production (GPP), and evapotranspiration (ET) reached −8.28 ± 0.76 g C m−2, 20.02 ± 1.62 g C m−2, and 5.42 ± 0.26 mm, respectively. Ecosystem water use efficiency (EWUE) and ecosystem light use efficiency (ELUE) ranged from 3.22 to 3.93 g C mm−1 ET and 0.34 to 0.41 g C mol−1 PAR (photosynthetically active radiation), respectively, during peak growths. Based on aggregated fluxes for each month over the three years (2017–2019), cumulative annual NEE was −434 ± 112 g C m−2, indicating a carbon gain by the Johnson grass field. Cumulative annual ET (858 ± 72 mm) was ~86% of the average annual rainfall (996 ± 100 mm). Results showed Johnson grass could be a carbon sink from May to September in the U.S. Southern Great Plains. Both NEE and ET did not decline up to air temperature (T a) of ~33 °C and vapor pressure deficit (VPD) of ~2 kPa, suggesting optimum T a of ≥33 °C and VPD of ≥2 kPa for the fluxes. Results indicated that Johnson grass might be well suited for dryland production in the region. Additionally, these findings provide initial baseline information on CO 2 fluxes and ET for Johnson grass relative to other forage species in the region. Unlabelled Image • First work to thoroughly study dynamics of CO 2 and H 2 O fluxes in Johnson grass. • Johnson grass harvested for hay showed large carbon uptake potential at annual scales. • Johnson grass could be a carbon sink in the southern plains during May–Sept period. • CO 2 uptake did not decrease up to air temperature of ~33 °C. • Cumulative annual ET (858 ± 72 mm) was ~86% of the average annual rainfall. [ABSTRACT FROM AUTHOR]

Published
2020
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24. CO2 uptake and ecophysiological parameters of the grain crops of midcontinent North America: Estimates from flux tower measurements

Author

Gilmanov, Tagir G., Wylie, Bruce K., Tieszen, Larry L., Meyers, Tilden P., Baron, Vern S., Bernacchi, Carl J., Billesbach, David P., Burba, George G., Fischer, Marc L., Glenn, Aaron J., Hanan, Niall P., Hatfield, Jerry L., Heuer, Mark W., Hollinger, Steven E., Howard, Daniel M., Matamala, Roser, Prueger, John H., Tenuta, Mario, and Young, David G.

Subjects
*EFFECT of carbon dioxide on plants, *ECOPHYSIOLOGY, *GRAIN, *NUMERICAL analysis, *BIOTIC communities, *SOIL temperature, *PHOTOSYNTHESIS, *ESTIMATION theory
Abstract

Abstract: We analyzed net CO2 exchange data from 13 flux tower sites with 27 site-years of measurements over maize and wheat fields across midcontinent North America. A numerically robust “light-soil temperature-VPD”-based method was used to partition the data into photosynthetic assimilation and ecosystem respiration components. Year-round ecosystem-scale ecophysiological parameters of apparent quantum yield, photosynthetic capacity, convexity of the light response, respiration rate parameters, ecological light-use efficiency, and the curvature of the VPD-response of photosynthesis for maize and wheat crops were numerically identified and interpolated/extrapolated. This allowed us to gap-fill CO2 exchange components and calculate annual totals and budgets. VPD-limitation of photosynthesis was systematically observed in grain crops of the region (occurring from 20 to 120 days during the growing season, depending on site and year), determined by the VPD regime and the numerical value of the curvature parameter of the photosynthesis-VPD-response, σ VPD. In 78% of the 27 site-years of observations, annual gross photosynthesis in these crops significantly exceeded ecosystem respiration, resulting in a net ecosystem production of up to 2100g CO2 m−2 year−1. The measurement-based photosynthesis, respiration, and net ecosystem production data, as well as the estimates of the ecophysiological parameters, provide an empirical basis for parameterization and validation of mechanistic models of grain crop production in this economically and ecologically important region of North America. [Copyright &y& Elsevier]

Published
2013
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25. Much stronger tundra methane emissions during autumn freeze than spring thaw.

Author

Bao T, Xu X, Jia G, Billesbach DP, and Sullivan RC

Subjects
Arctic Regions, Seasons, Soil, Tundra, Ecosystem, Methane
Abstract

Warming in the Arctic has been more apparent in the non-growing season than in the typical growing season. In this context, methane (CH 4 ) emissions in the non-growing season, particularly in the shoulder seasons, account for a substantial proportion of the annual budget. However, CH 4 emissions in spring and autumn shoulders are often underestimated by land models and measurements due to limited data availability and unknown mechanisms. This study investigates CH 4 emissions during spring thaw and autumn freeze using eddy covariance CH 4 measurements from three Arctic sites with multi-year observations. We find that the shoulder seasons contribute to about a quarter (25.6 ± 2.3%, mean ± SD) of annual total CH 4 emissions. Our study highlights the three to four times higher contribution of autumn freeze CH 4 emission to total annual emission than that of spring thaw. Autumn freeze exhibits significantly higher CH 4 flux (0.88 ± 0.03 mg m -2  hr -1 ) than spring thaw (0.48 ± 0.04 mg m -2  hr -1 ). The mean duration of autumn freeze (58.94 ± 26.39 days) is significantly longer than that of spring thaw (20.94 ± 7.79 days), which predominates the much higher cumulative CH 4 emission during autumn freeze (1,212.31 ± 280.39 mg m -2  year -1 ) than that during spring thaw (307.39 ± 46.11 mg m -2  year -1 ). Near-surface soil temperatures cannot completely reflect the freeze-thaw processes in deeper soil layers and appears to have a hysteresis effect on CH 4 emissions from early spring thaw to late autumn freeze. Therefore, it is necessary to consider commonalities and differences in CH 4 emissions during spring thaw versus autumn freeze to accurately estimate CH 4 source from tundra ecosystems for evaluating carbon-climate feedback in Arctic., (© 2020 John Wiley & Sons Ltd.)

Published
2021
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