Cove Sturtevant


2021

DOI bib
FLUXNET-CH<sub>4</sub>: a global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands
Kyle Delwiche, Sara Knox, Avni Malhotra, Etienne Fluet‐Chouinard, Gavin McNicol, Sarah Féron, Zutao Ouyang, Dario Papale, Carlo Trotta, Eleonora Canfora, You Wei Cheah, Danielle Christianson, Ma. Carmelita R. Alberto, Pavel Alekseychik, Mika Aurela, Dennis Baldocchi, Sheel Bansal, David P. Billesbach, Gil Bohrer, Rosvel Bracho, Nina Buchmann, David I. Campbell, Gerardo Celis, Jiquan Chen, Weinan Chen, Housen Chu, Higo J. Dalmagro, Sigrid Dengel, Ankur R. Desai, Matteo Detto, Han Dolman, Elke Eichelmann, Eugénie Euskirchen, D. Famulari, Kathrin Fuchs, Mathias Goeckede, Sébastien Gogo, Mangaliso J. Gondwe, Jordan P. Goodrich, Pia Gottschalk, Scott L. Graham, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S. Hemes, Takashi Hirano, David Y. Hollinger, Lukas Hörtnagl, Hiroyasu Iwata, Adrien Jacotot, Gerald Jurasinski, Minseok Kang, Kuno Kasak, John S. King, Janina Klatt, Franziska Koebsch, Ken W. Krauss, Derrick Y.F. Lai, Annalea Lohila, Ivan Mammarella, Luca Belelli Marchesini, Giovanni Manca, Jaclyn Hatala Matthes, Trofim C. Maximov, Lutz Merbold, Bhaskar Mitra, Timothy H. Morin, Eiko Nemitz, Mats Nilsson, Shuli Niu, Walter C. Oechel, Patricia Y. Oikawa, Kaori Ono, Matthias Peichl, Olli Peltola, Michele L. Reba, Andrew D. Richardson, William J. Riley, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Camilo Rey‐Sánchez, Edward A. G. Schuur, Karina V. R. Schäfer, Oliver Sonnentag, Jed P. Sparks, Ellen Stuart-Haëntjens, Cove Sturtevant, Ryan C. Sullivan, Daphne Szutu, Jonathan E. Thom, M. S. Torn, Eeva‐Stiina Tuittila, J. Turner, Masahito Ueyama, Alex Valach, Rodrigo Vargas, Andrej Varlagin, Alma Vázquez‐Lule, Joseph Verfaillie, Timo Vesala, George L. Vourlitis, Eric J. Ward, Christian Wille, Georg Wohlfahrt, Guan Xhuan Wong, Zhen Zhang, Donatella Zona, Lisamarie Windham‐Myers, Benjamin Poulter, Robert B. Jackson
Earth System Science Data, Volume 13, Issue 7

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.

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

• We evaluate methane flux gap-filling methods across 17 boreal-to-tropical wetlands • New methods for generating realistic artificial gaps and uncertainties are proposed • Decision tree algorithms perform slightly better than neural networks on average • Soil temperature and generic seasonality are the most important predictors • Open-source code is released for gap-filling steps and uncertainty evaluation Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET).

DOI bib
Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales
Sara Knox, Sheel Bansal, Gavin McNicol, Karina V. R. Schäfer, Cove Sturtevant, Masahito Ueyama, Alex Valach, Dennis Baldocchi, Kyle Delwiche, Ankur R. Desai, Eugénie Euskirchen, Jinxun Liu, Annalea Lohila, Avni Malhotra, Lulie Melling, William J. Riley, Benjamin R. K. Runkle, J. Turner, Rodrigo Vargas, Qing Zhu, Tuula Alto, Etienne Fluet‐Chouinard, Mathias Goeckede, Joe R. Melton, Oliver Sonnentag, Timo Vesala, Eric J. Ward, Zhen Zhang, Sarah Féron, Zutao Ouyang, Pavel Alekseychik, Mika Aurela, Gil Bohrer, David I. Campbell, Jiquan Chen, Housen Chu, Higo J. Dalmagro, Jordan P. Goodrich, Pia Gottschalk, Takashi Hirano, Hiroyasu Iwata, Gerald Jurasinski, Minseok Kang, Franziska Koebsch, Ivan Mammarella, Mats Nilsson, Kaori Ono, Matthias Peichl, Olli Peltola, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Jed P. Sparks, Eeva‐Stiina Tuittila, George L. Vourlitis, Guan Xhuan Wong, Lisamarie Windham‐Myers, B. Poulter, Robert B. Jackson
Global Change Biology, Volume 27, Issue 15

While wetlands are the largest natural source of methane (CH4) to the atmosphere, they represent a large source of uncertainty in the global CH4 budget due to the complex biogeochemical controls on CH4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH4 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 CH4. 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 CH4 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 CH4 emissions.

DOI bib
Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data
Gilberto Pastorello, Carlo Trotta, Eleonora Canfora, Housen Chu, Danielle Christianson, You-Wei Cheah, C. Poindexter, Jiquan Chen, Abdelrahman Elbashandy, Marty Humphrey, Peter Isaac, Diego Polidori, Markus Reichstein, Alessio Ribeca, Catharine van Ingen, Nicolas Vuichard, Leiming Zhang, B.D. Amiro, Christof Ammann, M. Altaf Arain, Jonas Ardö, Timothy J. Arkebauer, Stefan K. Arndt, Nicola Arriga, Marc Aubinet, Mika Aurela, Dennis Baldocchi, Alan Barr, Eric Beamesderfer, Luca Belelli Marchesini, Onil Bergeron, Jason Beringer, Christian Bernhofer, Daniel Berveiller, D. P. Billesbach, T. Andrew Black, Peter D. Blanken, Gil Bohrer, Julia Boike, Paul V. Bolstad, Damien Bonal, Jean-Marc Bonnefond, David R. Bowling, Rosvel Bracho, Jason Brodeur, Christian Brümmer, Nina Buchmann, Benoît Burban, Sean P. Burns, Pauline Buysse, Peter Cale, M. Cavagna, Pierre Cellier, Shiping Chen, Isaac Chini, Torben R. Christensen, James Cleverly, Alessio Collalti, Claudia Consalvo, Bruce D. Cook, David Cook, Carole Coursolle, Edoardo Cremonese, Peter S. Curtis, Ettore D’Andrea, Humberto da Rocha, Xiaoqin Dai, Kenneth J. Davis, Bruno De Cinti, A. de Grandcourt, Anne De Ligne, Raimundo Cosme de Oliveira, Nicolas Delpierre, Ankur R. Desai, Carlos Marcelo Di Bella, Paul Di Tommasi, Han Dolman, Francisco Domingo, Gang Dong, Sabina Dore, Pierpaolo Duce, Éric Dufrêne, Allison L. Dunn, J.T. Dusek, Derek Eamus, Uwe Eichelmann, Hatim Abdalla M. ElKhidir, Werner Eugster, Cäcilia Ewenz, B. E. Ewers, D. Famulari, Silvano Fares, Iris Feigenwinter, Andrew Feitz, Rasmus Fensholt, Gianluca Filippa, M. L. Fischer, J. M. Frank, Marta Galvagno, Mana Gharun, Damiano Gianelle, Bert Gielen, Beniamino Gioli, Anatoly A. Gitelson, Ignacio Goded, Mathias Goeckede, Allen H. Goldstein, Christopher M. Gough, Michael L. Goulden, Alexander Graf, Anne Griebel, Carsten Gruening, Thomas Grünwald, Albin Hammerle, Shijie Han, Xingguo Han, Birger Ulf Hansen, Chad Hanson, Juha Hatakka, Yongtao He, Markus Hehn, Bernard Heinesch, Nina Hinko‐Najera, Lukas Hörtnagl, Lindsay B. Hutley, Andreas Ibrom, Hiroki Ikawa, Marcin Jackowicz-Korczyński, Dalibor Janouš, W.W.P. Jans, Rachhpal S. Jassal, Shicheng Jiang, Tomomichi Kato, Myroslava Khomik, Janina Klatt, Alexander Knohl, Sara Knox, Hideki Kobayashi, Georgia R. Koerber, Olaf Kolle, Yukio Kosugi, Ayumi Kotani, Andrew S. Kowalski, Bart Kruijt, Juliya Kurbatova, Werner L. Kutsch, Hyojung Kwon, Samuli Launiainen, Tuomas Laurila, B. E. Law, R. Leuning, Yingnian Li, Michael J. Liddell, Jean‐Marc Limousin, Marryanna Lion, Adam Liska, Annalea Lohila, Ana López‐Ballesteros, Efrèn López‐Blanco, Benjamin Loubet, Denis Loustau, Antje Lucas-Moffat, Johannes Lüers, Siyan Ma, Craig Macfarlane, Vincenzo Magliulo, Regine Maier, Ivan Mammarella, Giovanni Manca, Barbara Marcolla, Hank A. Margolis, Serena Marras, W. J. Massman, Mikhail Mastepanov, Roser Matamala, Jaclyn Hatala Matthes, Francesco Mazzenga, Harry McCaughey, Ian McHugh, Andrew M. S. McMillan, Lutz Merbold, Wayne S. Meyer, Tilden P. Meyers, S. D. Miller, Stefano Minerbi, Uta Moderow, Russell K. Monson, Leonardo Montagnani, Caitlin E. Moore, Eddy Moors, Virginie Moreaux, Christine Moureaux, J. William Munger, T. Nakai, Johan Neirynck, Zoran Nesic, Giacomo Nicolini, Asko Noormets, Matthew Northwood, Marcelo D. Nosetto, Yann Nouvellon, Kimberly A. Novick, W. C. Oechel, Jørgen E. Olesen, Jean‐Marc Ourcival, S. A. Papuga, Frans‐Jan W. Parmentier, Eugénie Paul‐Limoges, Marián Pavelka, Matthias Peichl, Elise Pendall, Richard P. Phillips, Kim Pilegaard, Norbert Pirk, Gabriela Posse, Thomas L. Powell, Heiko Prasse, Suzanne M. Prober, Serge Rambal, Üllar Rannik, Naama Raz‐Yaseef, Corinna Rebmann, David E. Reed, Víctor Resco de Dios, Natalia Restrepo‐Coupe, Borja R. Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, S. R. Saleska, Enrique P. Sánchez-Cañete, Zulia Mayari Sánchez-Mejía, Hans Peter Schmid, Marius Schmidt, Karl Schneider, Frederik Schrader, Ivan Schroder, Russell L. Scott, Pavel Sedlák, Penélope Serrano-Ortíz, Changliang Shao, Peili Shi, Ivan Shironya, Lukas Siebicke, Ladislav Šigut, Richard Silberstein, Costantino Sirca, Donatella Spano, R. Steinbrecher, Robert M. Stevens, Cove Sturtevant, Andy Suyker, Torbern Tagesson, Satoru Takanashi, Yanhong Tang, Nigel Tapper, Jonathan E. Thom, Michele Tomassucci, Juha‐Pekka Tuovinen, S. P. Urbanski, Р. Валентини, M. K. van der Molen, Eva van Gorsel, J. van Huissteden, Andrej Varlagin, Joe Verfaillie, Timo Vesala, Caroline Vincke, Domenico Vitale, N. N. Vygodskaya, Jeffrey P. Walker, Elizabeth A. Walter‐Shea, Huimin Wang, R. J. Weber, Sebastian Westermann, Christian Wille, Steven C. Wofsy, Georg Wohlfahrt, Sebastian Wolf, William Woodgate, Yuelin Li, Roberto Zampedri, Junhui Zhang, Guoyi Zhou, Donatella Zona, D. Agarwal, Sébastien Biraud, M. S. Torn, Dario Papale
Scientific Data, Volume 8, Issue 1

A Correction to this paper has been published: https://doi.org/10.1038/s41597-021-00851-9.

2020

DOI bib
The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data
Gilberto Pastorello, Carlo Trotta, Eleonora Canfora, Housen Chu, Danielle Christianson, You-Wei Cheah, C. Poindexter, Jiquan Chen, Abdelrahman Elbashandy, Marty Humphrey, Peter Isaac, Diego Polidori, Markus Reichstein, Alessio Ribeca, Catharine van Ingen, Nicolas Vuichard, Leiming Zhang, B.D. Amiro, Christof Ammann, M. Altaf Arain, Jonas Ardö, Timothy J. Arkebauer, Stefan K. Arndt, Nicola Arriga, Marc Aubinet, Mika Aurela, Dennis Baldocchi, Alan Barr, Eric Beamesderfer, Luca Belelli Marchesini, Onil Bergeron, Jason Beringer, Christian Bernhofer, Daniel Berveiller, D. P. Billesbach, T. Andrew Black, Peter D. Blanken, Gil Bohrer, Julia Boike, Paul V. Bolstad, Damien Bonal, Jean-Marc Bonnefond, David R. Bowling, Rosvel Bracho, Jason Brodeur, Christian Brümmer, Nina Buchmann, Benoît Burban, Sean P. Burns, Pauline Buysse, Peter Cale, M. Cavagna, Pierre Cellier, Shiping Chen, Isaac Chini, Torben R. Christensen, James Cleverly, Alessio Collalti, Claudia Consalvo, Bruce D. Cook, David Cook, Carole Coursolle, Edoardo Cremonese, Peter S. Curtis, Ettore D’Andrea, Humberto da Rocha, Xiaoqin Dai, Kenneth J. Davis, Bruno De Cinti, A. de Grandcourt, Anne De Ligne, Raimundo Cosme de Oliveira, Nicolas Delpierre, Ankur R. Desai, Carlos Marcelo Di Bella, Paul Di Tommasi, Han Dolman, Francisco Domingo, Gang Dong, Sabina Dore, Pierpaolo Duce, Éric Dufrêne, Allison L. Dunn, J.T. Dusek, Derek Eamus, Uwe Eichelmann, Hatim Abdalla M. ElKhidir, Werner Eugster, Cäcilia Ewenz, B. E. Ewers, D. Famulari, Silvano Fares, Iris Feigenwinter, Andrew Feitz, Rasmus Fensholt, Gianluca Filippa, M. L. Fischer, J. M. Frank, Marta Galvagno, Mana Gharun, Damiano Gianelle, Bert Gielen, Beniamino Gioli, Anatoly A. Gitelson, Ignacio Goded, Mathias Goeckede, Allen H. Goldstein, Christopher M. Gough, Michael L. Goulden, Alexander Graf, Anne Griebel, Carsten Gruening, Thomas Grünwald, Albin Hammerle, Shijie Han, Xingguo Han, Birger Ulf Hansen, Chad Hanson, Juha Hatakka, Yongtao He, Markus Hehn, Bernard Heinesch, Nina Hinko‐Najera, Lukas Hörtnagl, Lindsay B. Hutley, Andreas Ibrom, Hiroki Ikawa, Marcin Jackowicz-Korczyński, Dalibor Janouš, W.W.P. Jans, Rachhpal S. Jassal, Shicheng Jiang, Tomomichi Kato, Myroslava Khomik, Janina Klatt, Alexander Knohl, Sara Knox, Hideki Kobayashi, Georgia R. Koerber, Olaf Kolle, Yukio Kosugi, Ayumi Kotani, Andrew S. Kowalski, Bart Kruijt, Juliya Kurbatova, Werner L. Kutsch, Hyojung Kwon, Samuli Launiainen, Tuomas Laurila, B. E. Law, R. Leuning, Yingnian Li, Michael J. Liddell, Jean‐Marc Limousin, Marryanna Lion, Adam Liska, Annalea Lohila, Ana López‐Ballesteros, Efrèn López‐Blanco, Benjamin Loubet, Denis Loustau, Antje Maria Moffat, Johannes Lüers, Siyan Ma, Craig Macfarlane, Vincenzo Magliulo, Regine Maier, Ivan Mammarella, Giovanni Manca, Barbara Marcolla, Hank A. Margolis, Serena Marras, W. J. Massman, Mikhail Mastepanov, Roser Matamala, Jaclyn Hatala Matthes, Francesco Mazzenga, Harry McCaughey, Ian McHugh, Andrew M. S. McMillan, Lutz Merbold, Wayne S. Meyer, Tilden P. Meyers, S. D. Miller, Stefano Minerbi, Uta Moderow, Russell K. Monson, Leonardo Montagnani, Caitlin E. Moore, Eddy Moors, Virginie Moreaux, Christine Moureaux, J. William Munger, T. Nakai, Johan Neirynck, Zoran Nesic, Giacomo Nicolini, Asko Noormets, Matthew Northwood, Marcelo D. Nosetto, Yann Nouvellon, Kimberly A. Novick, W. C. Oechel, Jørgen E. Olesen, Jean‐Marc Ourcival, S. A. Papuga, Frans‐Jan W. Parmentier, Eugénie Paul‐Limoges, Marián Pavelka, Matthias Peichl, Elise Pendall, Richard P. Phillips, Kim Pilegaard, Norbert Pirk, Gabriela Posse, Thomas L. Powell, Heiko Prasse, Suzanne M. Prober, Serge Rambal, Üllar Rannik, Naama Raz‐Yaseef, Corinna Rebmann, David E. Reed, Víctor Resco de Dios, Natalia Restrepo‐Coupe, Borja R. Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, S. R. Saleska, Enrique P. Sánchez-Cañete, Zulia Mayari Sánchez-Mejía, Hans Peter Schmid, Marius Schmidt, Karl Schneider, Frederik Schrader, Ivan Schroder, Russell L. Scott, Pavel Sedlák, Penélope Serrano-Ortíz, Changliang Shao, Peili Shi, Ivan Shironya, Lukas Siebicke, Ladislav Šigut, Richard Silberstein, Costantino Sirca, Donatella Spano, R. Steinbrecher, Robert M. Stevens, Cove Sturtevant, Andy Suyker, Torbern Tagesson, Satoru Takanashi, Yanhong Tang, Nigel Tapper, Jonathan E. Thom, Michele Tomassucci, Juha‐Pekka Tuovinen, S. P. Urbanski, Р. Валентини, M. K. van der Molen, Eva van Gorsel, J. van Huissteden, Andrej Varlagin, Joe Verfaillie, Timo Vesala, Caroline Vincke, Domenico Vitale, N. N. Vygodskaya, Jeffrey P. Walker, Elizabeth A. Walter‐Shea, Huimin Wang, R. J. Weber, Sebastian Westermann, Christian Wille, Steven C. Wofsy, Georg Wohlfahrt, Sebastian Wolf, William Woodgate, Yuelin Li, Roberto Zampedri, Junhui Zhang, Guoyi Zhou, Donatella Zona, D. Agarwal, Sébastien Biraud, M. S. Torn, Dario Papale
Scientific Data, Volume 7, Issue 1

Abstract The FLUXNET2015 dataset provides ecosystem-scale data on CO 2 , 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.
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