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

Author

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

Subjects
geography, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, Eddy covariance, Wetland, 04 agricultural and veterinary sciences, 15. Life on land, Seasonality, Atmospheric sciences, medicine.disease, 01 natural sciences, FluxNet, Boreal, Arctic, 13. Climate action, 040103 agronomy & agriculture, medicine, 0401 agriculture, forestry, and fisheries, General Earth and Planetary Sciences, Environmental science, Ecosystem, Terrestrial ecosystem, 0105 earth and related environmental sciences
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.

Published
2021
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2. The Colorado East River Community Observatory Data Collection

Author

Susan S. Hubbard, Zarine Kakalia, Charuleka Varadharajan, Valerie Hendrix, Erek Alper, Kenneth H. Williams, D. Agarwal, Madison Burrus, Wenming Dong, Douglas Johnson, Rosemary W.H. Carroll, Roelof Versteeg, D. S. Christianson, Matthew L. Henderson, and Eoin L. Brodie

Subjects
Hydrology, Water balance, geography, geography.geographical_feature_category, Watershed, Data collection, Floodplain, Ecohydrology, Drainage basin, Elevation, Environmental science, Vegetation, Water Science and Technology
Abstract

Author(s): Kakalia, Z; Varadharajan, C; Alper, E; Brodie, EL; Burrus, M; Carroll, RWH; Christianson, DS; Dong, W; Hendrix, VC; Henderson, M; Hubbard, SS; Johnson, D; Versteeg, R; Williams, KH; Agarwal, DA | Abstract: The U.S. Department of Energy's (DOE) Colorado East River Community Observatory (ER) in the Upper Colorado River Basin was established in 2015 as a representative mountainous, snow-dominated watershed to study hydrobiogeochemical responses to hydrological perturbations in headwater systems. The ER is characterized by steep elevation, geologic, hydrologic and vegetation gradients along floodplain, montane, subalpine, and alpine life zones, which makes it an ideal location for researchers to understand how different mountain subsystems contribute to overall watershed behaviour. The ER has both long-term and spatially-extensive observations and experimental campaigns carried out by the Watershed Function Scientific Focus Area (SFA), led by Lawrence Berkeley National Laboratory, and researchers from over 30 organizations who conduct cross-disciplinary process-based investigations and modelling of watershed behaviour. The heterogeneous data generated at the ER include hydrological, genomic, biogeochemical, climate, vegetation, geological, and remote sensing data, which combined with model inputs and outputs comprise a collection of datasets and value-added products within a mountainous watershed that span multiple spatiotemporal scales, compartments, and life zones. Within 5 years of collection, these datasets have revealed insights into numerous aspects of watershed function such as factors influencing snow accumulation and melt timing, water balance partitioning, and impacts of floodplain biogeochemistry and hillslope ecohydrology on riverine geochemical exports. Data generated by the SFA are managed and curated through its Data Management Framework. The SFA has an open data policy, and over 70 ER datasets are publicly available through relevant data repositories. A public interactive map of data collection sites run by the SFA is available to inform the broader community about SFA field activities. Here, we describe the ER and the SFA measurement network, present the public data collection generated by the SFA and partner institutions, and highlight the value of collecting multidisciplinary multiscale measurements in representative catchment observatories.

Published
2021
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3. Correction for Vangay et al., 'Microbiome Metadata Standards: Report of the National Microbiome Data Collaborative's Workshop and Follow-On Activities'

Author

Sylvain V. Costes, Jagadish Chandrabose Sundaramurthi, Evangelos Pafilis, Stanton L. Martin, Jonathan M. Galazka, Daniel C. Berrios, Pankaj Jaiswal, Sean M. Gibbons, Anjanette Johnston, John-Marc Chandonia, Jose Pablo Dundore-Arias, Justin P. Shaffer, Nigel J Mouncey, Kristen L. Beck, David Hays, Marcin P. Joachimiak, Luke R. Thompson, J. Damerow, Patrick S. G. Chain, Jie Zheng, Elisha M. Wood-Charlson, Christopher J. Mungall, Pajau Vangay, William D. Duncan, Lorna Richardson, Linda L. Kinkel, W. Judson Hervey, Bonnie L. Hurwitz, Simon Roux, Kayd Miller, Ruth Timme, Josephine Burgin, Lynn M. Schriml, Shane Canon, Lee Ann McCue, Bin Hu, Kjiersten Fagnan, T. B. K. Reddy, D. S. Christianson, Kai Blumberg, Joshua Ladau, and Emiley A. Eloe-Fadrosh

Subjects
Physiology, media_common.quotation_subject, metadata, microbiome, Art, Biochemistry, Microbiology, Computer Science Applications, Modeling and Simulation, Perspective, Genetics, ontology, Author Correction, data standards, Molecular Biology, Humanities, Ecology, Evolution, Behavior and Systematics, media_common
Abstract

Author(s): Vangay, Pajau; Burgin, Josephine; Johnston, Anjanette; Beck, Kristen L; Berrios, Daniel C; Blumberg, Kai; Canon, Shane; Chain, Patrick; Chandonia, John-Marc; Christianson, Danielle; Costes, Sylvain V; Damerow, Joan; Duncan, William D; Dundore-Arias, Jose Pablo; Fagnan, Kjiersten; Galazka, Jonathan M; Gibbons, Sean M; Hays, David; Hervey, Judson; Hu, Bin; Hurwitz, Bonnie L; Jaiswal, Pankaj; Joachimiak, Marcin P; Kinkel, Linda; Ladau, Joshua; Martin, Stanton L; McCue, Lee Ann; Miller, Kayd; Mouncey, Nigel; Mungall, Chris; Pafilis, Evangelos; Reddy, TBK; Richardson, Lorna; Roux, Simon; Schriml, Lynn M; Shaffer, Justin P; Sundaramurthi, Jagadish Chandrabose; Thompson, Luke R; Timme, Ruth E; Zheng, Jie; Wood-Charlson, Elisha M; Eloe-Fadrosh, Emiley A | Abstract: Volume 6, no. 1, e01194-20, 2021, https://doi.org/10.1128/mSystems.01194-20. The article byline and affiliation line should read as given in this correction.

Published
2021

4. Microbiome Metadata Standards: Report of the National Microbiome Data Collaborative's Workshop and Follow-On Activities

Author

Bin Hu, Shane Canon, Simon Roux, D. S. Christianson, Joshua Ladau, Evangelos Pafilis, Bonnie L. Hurwitz, Stanton L. Martin, Kayd Miller, Nigel J Mouncey, Elisha M. Wood-Charlson, Pankaj Jaiswal, Justin P. Shaffer, Josephine Burgin, Marcin P. Joachimiak, W. Judson Hervey, Luke R. Thompson, Jagadish Chandrabose Sundaramurthi, Christopher J. Mungall, Lee Ann McCue, William D. Duncan, J. Damerow, Sylvain V. Costes, Patrick S. G. Chain, Jie Zheng, John-Marc Chandonia, Ruth Timme, Lorna Richardson, T. B. K. Reddy, Pajau Vangay, Emiley A. Eloe-Fadrosh, Kjiersten Fagnan, Kai Blumberg, Linda L. Kinkel, Jose Pablo Dundore-Arias, Kristen L. Beck, David Hays, Sean M. Gibbons, Daniel C. Berrios, Anjanette Johnston, Jonathan M. Galazka, and Bucci, Vanni

Subjects
Physiology, microbiome, Context (language use), Ontology (information science), Biochemistry, Microbiology, 03 medical and health sciences, 0302 clinical medicine, Research community, Genetics, Microbiome, Sociology, ontology, Molecular Biology, Ecology, Evolution, Behavior and Systematics, 030304 developmental biology, 0303 health sciences, Interpretation (philosophy), metadata, Data science, QR1-502, Computer Science Applications, Metadata, Modeling and Simulation, Working group, data standards, 030217 neurology & neurosurgery
Abstract

Microbiome samples are inherently defined by the environment in which they are found. Therefore, data that provide context and enable interpretation of measurements produced from biological samples, often referred to as metadata, are critical. Important contributions have been made in the development of community-driven metadata standards; however, these standards have not been uniformly embraced by the microbiome research community. To understand how these standards are being adopted, or the barriers to adoption, across research domains, institutions, and funding agencies, the National Microbiome Data Collaborative (NMDC) hosted a workshop in October 2019. This report provides a summary of discussions that took place throughout the workshop, as well as outcomes of the working groups initiated at the workshop.

Published
2021

5. COSORE: A community database for continuous soil respiration and other soil‐atmosphere greenhouse gas flux data

Author

Dennis D. Baldocchi, Kadmiel Maseyk, Yuji Kominami, Nadine K. Ruehr, Patrick M. Crill, John E. Drake, Mioko Ataka, Anya M. Hopple, Haiming Kan, Samaneh Ashraf, Matthew Saunders, Zhuo Pang, Daphne Szutu, Stephanie C. Pennington, Whendee L. Silver, Scott T. Miller, Cecilio Oyonarte, David A. Lipson, Naishen Liang, Masahito Ueyama, Thomas Wutzler, Michael L. Goulden, Järvi Järveoja, Jiye Zeng, Wu Sun, Debjani Sihi, Takashi Hirano, Nina Buchmann, Amir AghaKouchak, Peter S. Curtis, Ruth K. Varner, Greg Winston, Munemasa Teramoto, Mark G. Tjoelker, Susan E. Trumbore, Kathleen Savage, Omar Gutiérrez del Arroyo, Asko Noormets, Mats Nilsson, Catriona A. Macdonald, Carolyn Monika Görres, M. Altaf Arain, Alexandre A. Renchon, Joseph Verfaillie, James W. Raich, Masahiro Takagi, Jason P. Kaye, Quan Zhang, Hamidreza Norouzi, Ulli Seibt, Melanie A. Mayes, Jinsong Wang, Juan J. Armesto, Marion Schrumpf, Tianshan Zha, Mirco Migliavacca, Chelcy Ford Miniat, Jin-Sheng He, Enrique P. Sánchez-Cañete, Michael Gavazzi, Tarek S. El-Madany, T. A. Black, H. Hughes, Elise Pendall, Christopher M. Gough, Jillian W. Gregg, Guofang Miao, Junliang Zou, Avni Malhotra, Russell L. Scott, D. S. Christianson, Marguerite Mauritz, Steve McNulty, Juying Wu, Jinshi Jian, K. C. Mathes, Tana E. Wood, Rodrigo Vargas, Jennifer Goedhart Nietz, Christoph S. Vogel, Claire L. Phillips, Mariah S. Carbone, Kentaro Takagi, Shih-Chieh Chang, Jorge F. Perez-Quezada, Richard P. Phillips, Hassan Anjileli, Eric A. Davidson, Ankur R. Desai, Christine S. O’Connell, Matthias Peichl, Bruce Osborne, Ben Bond-Lamberty, and Rachhpal S. Jassal

Subjects
0106 biological sciences, 010504 meteorology & atmospheric sciences, Nitrous Oxide, Climate change, open data, computer.software_genre, Greenhouse gas, 010603 evolutionary biology, 01 natural sciences, Database design, soil respiration, Soil respiration, Greenhouse Gases, Soil, 11. Sustainability, greenhouse gases, open science, ddc:550, Environmental Chemistry, Biology, Ecosystem, 0105 earth and related environmental sciences, General Environmental Science, Global and Planetary Change, Database, Ecology, Atmosphere, carbon dioxide, methane, Respiration, Reproducibility of Results, 15. Life on land, Biological Sciences, Climate Action, Earth system science, Ancillary data, Chemistry, Earth sciences, Technical Advance, 13. Climate action, Soil water, Environmental science, Ecosystem respiration, computer, Environmental Sciences
Abstract

Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil‐to‐atmosphere CO2 flux, commonly though imprecisely termed soil respiration (R S), is one of the largest carbon fluxes in the Earth system. An increasing number of high‐frequency R S measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open‐source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long‐term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured R S, the database design accommodates other soil‐atmosphere measurements (e.g. ecosystem respiration, chamber‐measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package., Here we describe the lightweight, open source COSORE (COntinuous SOil REspiration) database and software. COSORE focuses on automated, continuous and long‐term greenhouse gas flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation.

Published
2020

6. The East River Community Observatory Data Collection: Diverse, multiscale data from a mountainous watershed in the East River, Colorado

Author

Erek Alper, Deb Agarwal, D. S. Christianson, Charuleka Varadharajan, Susan S. Hubbard, Madison Burrus, Matthew L. Henderson, Kenneth H. Williams, Roelof Versteeg, Eoin L. Brodie, Valerie Hendrix, Rosemary W.H. Carroll, Zarine Kakalia, and Douglas Johnson

Subjects
geography, geography.geographical_feature_category, Data collection, Watershed, Floodplain, business.industry, Data management, Drainage basin, Vegetation, Water balance, Ecohydrology, Environmental science, Water resource management, business
Abstract

The U.S. Department of Energy’s (DOE) East River community observatory (ER) in the Upper Colorado River Basin was established in 2015 as a representative mountainous, snow-dominated watershed to study hydrobiogeochemical responses to hydrological perturbations in headwater systems. Led by the Watershed Function Science Focus Area (SFA), the ER has both long-term and spatially-extensive observations paired with experimental campaigns. The Watershed Function SFA, led by Berkeley Laboratory, includes researchers from over 30 organizations who conduct cross-disciplinary process-based investigations and mechanistic modeling of watershed behavior in the ER. The data generated at the ER are extremely heterogeneous, and include hydrological, biogeochemical, climate, vegetation, geological, remote sensing, and model data that together comprise an unprecedented collection of data and value-added products within a mountainous watershed, across multiple spatiotemporal scales, compartments, and life zones. Within 5 years of data collection, these datasets have already revealed insights into numerous aspects of watershed function such as factors influencing snow accumulation and melt timing, water balance partitioning, and impacts of floodplain biogeochemistry and hillslope ecohydrology on riverine geochemical exports. Data generated by the SFA are managed and curated through its Data Management Framework. The SFA has an open data policy, and over sixty ER datasets are publicly available through relevant data repositories. A public interactive map of data collection sites run by the SFA is available to inform the broader community about SFA field activities. Here, we describe the ER and the SFA measurement network, present the public data collection generated by the SFA and partner institutions, and highlight the value of collecting multidisciplinary multiscale measurements in representative catchment observatories.

Published
2020
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7. Author Correction

Author

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

Subjects
Data descriptor, Statistics and Probability, Code development, 010504 meteorology & atmospheric sciences, Pipeline (computing), Science, 0207 environmental engineering, Eddy covariance, ComputingMilieux_LEGALASPECTSOFCOMPUTING, 02 engineering and technology, Library and Information Sciences, 01 natural sciences, Education, ddc:550, 020701 environmental engineering, Author Correction, 0105 earth and related environmental sciences, Information retrieval, Published Erratum, Substitution (logic), Statistics, Carbon cycle, Computer Science Applications, Environmental sciences, Earth sciences, Probability and Uncertainty, ddc:500, Statistics, Probability and Uncertainty, Climate sciences, Downscaling, Information Systems
Abstract

The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions. © 2021, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.

Published
2021
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8. A metadata reporting framework (FRAMES) for synthesis of ecohydrological observations

Author

Charuleka Varadharajan, Nate G. McDowell, Bruno O. Gimenez, Jeffrey Q. Chambers, Bradley O. Christoffersen, Thomas L. Powell, Robinson I. Negrón-Juárez, Valerie Hendrix, Lara M. Kueppers, Matteo Detto, Brett T. Wolfe, D. S. Christianson, Megha Sandesh, Gilberto Pastorello, Jeffrey M. Warren, Kolby J. Jardine, Boris Faybishenko, and Deb Agarwal

Subjects
0106 biological sciences, Data element, 010504 meteorology & atmospheric sciences, Ecology, Database, Computer science, Applied Mathematics, Ecological Modeling, computer.software_genre, 01 natural sciences, Data science, Data type, Field (computer science), Computer Science Applications, Variety (cybernetics), Data mapping, Metadata repository, Metadata, Computational Theory and Mathematics, Modeling and Simulation, Data reporting, computer, Ecology, Evolution, Behavior and Systematics, 010606 plant biology & botany, 0105 earth and related environmental sciences
Abstract

Metadata describe the ancillary information needed for data preservation and independent interpretation, comparison across heterogeneous datasets, and quality assessment and quality control (QA/QC). Environmental observations are vastly diverse in type and structure, can be taken across a wide range of spatiotemporal scales in a variety of measurement settings and approaches, and saved in multiple formats. Thus, well-organized, consistent metadata are required to produce usable data products from diverse environmental observations collected across field sites. However, existing metadata reporting protocols do not support the complex data synthesis and model-data integration needs of interdisciplinary earth system research. We developed a metadata reporting framework (FRAMES) to enable management and synthesis of observational data that are essential in advancing a predictive understanding of earth systems. FRAMES utilizes best practices for data and metadata organization enabling consistent data reporting and compatibility with a variety of standardized data protocols. We used an iterative scientist-centered design process to develop FRAMES, resulting in a data reporting format that incorporates existing field practices to maximize data-entry efficiency. Thus, FRAMES has a modular organization that streamlines metadata reporting and can be expanded to incorporate additional data types. With FRAMES's multi-scale measurement position hierarchy, data can be reported at observed spatial resolutions and then easily aggregated and linked across measurement types to support model-data integration. FRAMES is in early use by both data originators (persons generating data) and consumers (persons using data and metadata). In this paper, we describe FRAMES, identify lessons learned, and discuss areas of future development.

Published
2017
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9. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

Author

Eddy Moors, Uwe Eichelmann, Christian Brümmer, Stefano Minerbi, Barbara Marcolla, Gil Bohrer, Leonardo Montagnani, Üllar Rannik, Han Dolman, Janina Klatt, Samuli Launiainen, Elizabeth A. Walter-Shea, Nina Buchmann, Hank A. Margolis, Beniamino Gioli, Peter S. Curtis, Margaret S. Torn, Gabriela Posse, Luca Belelli Marchesini, Gianluca Filippa, Kenneth J. Davis, Leiming Zhang, Alexander Graf, Ray Leuning, Andrew Feitz, Simone Sabbatini, Harry McCaughey, Werner Eugster, Juha Pekka Tuovinen, Timothy J. Arkebauer, N. N. Vygodskaya, Adam J. Liska, Rosvel Bracho, Sebastian Wolf, Marc Aubinet, Jiří Dušek, Eugénie Paul-Limoges, Christof Ammann, Daniel Berveiller, Zoran Nesic, Giacomo Nicolini, Jaclyn Hatala Matthes, Russell L. Scott, David E. Reed, Frans-Jan W. Parmentier, Changliang Shao, Penélope Serrano-Ortiz, Yingnian Li, Jason Beringer, Marc Fischer, Deb Agarwal, Rasmus Fensholt, Russell K. Monson, Agnès de Grandcourt, Stefan K. Arndt, Timo Vesala, Uta Moderow, Joseph Verfaillie, Mika Aurela, Bev Law, Nina Hinko-Najera, Taro Nakai, Richard P. Phillips, Lindsay B. Hutley, Benjamin Loubet, Michele Tomassucci, Ayumi Kotani, Hans Peter Schmid, Raimundo Cosme de Oliveira, Anatoly A. Gitelson, Domenico Vitale, Regine Maier, Caitlin E. Moore, Xiaoqin Dai, Damien Bonal, John M. Frank, Yuelin Li, Christopher M. Gough, Shijie Han, Shirley A. Papuga, Edoardo Cremonese, Shawn Urbanski, Sébastien C. Biraud, Scott D. Miller, Mana Gharun, Annalea Lohila, Ian McHugh, Giovanni Manca, Bert Gielen, Wayne S. Meyer, Pierpaolo Duce, Bruce D. Cook, Carsten Gruening, Hiroki Ikawa, B.R. Reverter, Marian Pavelka, Andrew M. S. McMillan, Gang Dong, Isaac Chini, Kimberly A. Novick, Dalibor Janouš, Anne De Ligne, E. Beamesderfer, Marty Humphrey, Virginie Moreaux, Christian Wille, Markus Hehn, Hideki Kobayashi, Allen H. Goldstein, Walter C. Oechel, Richard Silberstein, Francisco Domingo, Francesco Mazzenga, Elise Pendall, Juha Hatakka, Lutz Merbold, Xingguo Han, Daniela Famulari, Carlo Trotta, Naama Raz-Yaseef, Dario Papale, Jean Marc Ourcival, Benoit Burban, Pavel Sedlák, Diego Polidori, Asko Noormets, Huimin Wang, Birger Ulf Hansen, Thomas Grünwald, Caroline Vincke, Robert M. Stevens, Carole Coursolle, D. P. Billesbach, Karl Schneider, Guoyi Zhou, Marcin Jackowicz-Korczynski, Paul V. Bolstad, Iris Feigenwinter, Shiping Chen, Julia Boike, Ivan Schroder, D. S. Christianson, Junhui Zhang, Pierre Cellier, Catharine van Ingen, Andrej Varlagin, A. Ribeca, Claudia Consalvo, Derek Eamus, Jason Brodeur, Alan G. Barr, Denis Loustau, Andreas Ibrom, Ankur R. Desai, Andrew E. Suyker, Efrén López-Blanco, Peter Cale, Nicola Arriga, William J. Massman, Abdelrahman Elbashandy, Yoshiko Kosugi, Pauline Buysse, Cove Sturtevant, T. A. Black, Housen Chu, David R. Bowling, Sabina Dore, Albin Hammerle, Tilden P. Meyers, M. Altaf Arain, Hatim Abdalla M. ElKhidir, Ignacio Goded, Roberto Zampedri, Alessio Collalti, Torsten Sachs, Tuomas Laurila, Cristina Poindexter, E. Canfora, Alexander Knohl, Donatella Spano, Silvano Fares, Scott R. Saleska, Michiel K. van der Molen, Suzanne M. Prober, Marryanna Lion, Steven C. Wofsy, Michael L. Goulden, Matthew Northwood, Antje Lucas-Moffat, Christine Moureaux, Jean-Marc Limousin, Sara H. Knox, Damiano Gianelle, Olaf Kolle, Jørgen E. Olesen, Mikhail Mastepanov, Bernard Heinesch, Christian Bernhofer, Peter D. Blanken, Hyojung Kwon, Georg Wohlfahrt, Peili Shi, Yann Nouvellon, Allison L. Dunn, Onil Bergeron, Mauro Cavagna, Heiko Prasse, Natalia Restrepo-Coupe, Yanhong Tang, Donatella Zona, Andrew S. Kowalski, Eric Dufrêne, Kim Pilegaard, Serena Marras, Yongtao He, Brent E. Ewers, Siyan Ma, Jean Marc Bonnefond, Jonas Ardö, Ko van Huissteden, Roser Matamala, Robin Weber, Nigel J. Tapper, Humberto Ribeiro da Rocha, Eva van Gorsel, Torbern Tagesson, Frederik Schrader, Frank Tiedemann, Myroslava Khomik, Torben R. Christensen, Jonathan E. Thom, James Cleverly, Víctor Resco de Dios, Ivan Shironya, Jeffrey P. Walker, You Wei Cheah, Ana López-Ballesteros, Georgia R. Koerber, J. William Munger, Shicheng Jiang, Johannes Lüers, Bruno De Cinti, Gilberto Pastorello, David R. Cook, Werner L. Kutsch, Paul Di Tommasi, Nicolas Delpierre, Peter Isaac, Carlos Marcelo Di Bella, Jiquan Chen, Craig Macfarlane, Dennis D. Baldocchi, William Woodgate, Riccardo Valentini, Marilyn Roland, Ladislav Šigut, Tomomichi Kato, Sebastian Westermann, Ivan Mammarella, Bart Kruijt, Marta Galvagno, Marius Schmidt, Serge Rambal, J. Kurbatova, Sean P. Burns, Ettore D'Andrea, Chad Hanson, Vincenzo Magliulo, Anne Griebel, Brian D. Amiro, M. Goeckede, Enrique P. Sánchez-Cañete, Thomas L. Powell, Marcelo D. Nosetto, Cacilia Ewenz, Michael J. Liddell, Satoru Takanashi, Lukas Hörtnagl, Zulia Mayari Sanchez-Mejia, W.W.P. Jans, N. Pirk, Johan Neirynck, Rainer Steinbrecher, Lukas Siebicke, Matthias Peichl, Rachhpal S. Jassal, Costantino Sirca, Earth and Climate, Earth Sciences, Institute for Atmospheric and Earth System Research (INAR), INAR Physics, Micrometeorology and biogeochemical cycles, Viikki Plant Science Centre (ViPS), Ecosystem processes (INAR Forest Sciences), Lawrence Berkeley National Laboratory [Berkeley] (LBNL), Università degli studi della Tuscia [Viterbo], California State University [Sacramento], Michigan State University System, University of Virginia, Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Chinese Academy of Sciences [Beijing] (CAS), University of Manitoba [Winnipeg], Agroscope, McMaster University [Hamilton, Ontario], Lund University [Lund], University of Nebraska–Lincoln, University of Nebraska System, University of Melbourne, University of Antwerp (UA), Université de Liège, Finnish Meteorological Institute (FMI), University of California [Berkeley] (UC Berkeley), University of California (UC), University of Saskatchewan [Saskatoon] (U of S), Peoples Friendship University of Russia [RUDN University] (RUDN), The University of Western Australia (UWA), Technische Universität Dresden = Dresden University of Technology (TU Dresden), Ecologie Systématique et Evolution (ESE), AgroParisTech-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), University of British Columbia (UBC), University of Colorado [Colorado Springs] (UCCS), Ohio State University [Columbus] (OSU), Humboldt University Of Berlin, University of Minnesota System, SILVA (SILVA), AgroParisTech-Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Interactions Sol Plante Atmosphère (UMR ISPA), Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), University of Utah, University of Central Florida [Orlando] (UCF), Thunen Institute of Climate-Smart Agriculture, Department of Environmental Systems Science [ETH Zürich] (D-USYS), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Ecologie des forêts de Guyane (UMR ECOFOG), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Université de Guyane (UG)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Fondazione Edmund Mach - Edmund Mach Foundation [Italie] (FEM), Aarhus University [Aarhus], University of Technology Sydney (UTS), National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), NASA Goddard Space Flight Center (GSFC), Argonne National Laboratory [Lemont] (ANL), Université Laval [Québec] (ULaval), Universidade de São Paulo = University of São Paulo (USP), Pennsylvania State University (Penn State), Penn State System, Ecologie fonctionnelle et biogéochimie des sols et des agro-écosystèmes (UMR Eco&Sols), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), University of Wisconsin-Madison, Vrije Universiteit Amsterdam [Amsterdam] (VU), Centro de Investigaciones Biológicas (CSIC), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Shanxi University (SXU), Worcester State University [Worcester], Czech Academy of Sciences [Prague] (CAS), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), UCL - SST/ELI/ELIE - Environmental Sciences, GILBERTO PASTORELLO, Lawrence Berkeley National Laboratory, THOMAS ANDREW BLACK, University of British Columbia, PETER D. BLANKEN, University of Colorado, GIL BOHRER, Ohio State University, JULIA BOIKE, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research / Humboldt-Universität zu Berlin, PAUL V. BOLSTAD, University of Minnesota, JEAN-MARC BONNEFOND, ISPA Bordeaux Sciences Agro, DAVID R. BOWLING, University of Utah, ROSVEL BRACHO, University of Florida, JASON BRODEUR, McMaster University, CHRISTIAN BRÜMMER, Thünen Institute of Climate-Smart Agriculture, NINA BUCHMANN, ETH Zurich, BENOIT BURBAN, INRAE UMR ECOFOG, AGNES DE GRANDCOURT, UMR Eco&Sols, CIRAD, ANNE DE LIGNE, University of Liege, RAIMUNDO COSME DE OLIVEIRA JUNIOR, CPATU, HAN DOLMAN, Universiteit Amsterdam, FRANCISCO DOMINGO, CSIC, GANG DONG, Shanxi University, SABINA DORE, HydroFocus, PIERPAOLO DUCE, National Research Council of Italy, MARTA GALVAGNO, Environmental Protection Agency of Aosta Valley, MANA GHARUN, ETH Zurich, DAMIANO GIANELLE, Fondazione Edmund Mach, MARCIN JACKOWICZ-KORCZYNSKI, Lund University / Aarhus University, DALIBOR JANOUS, Global Change Research Institute of the Czech Academy of Sciences, WILMA JANS, Wageningen University and Research, RACHHPAL JASSAL, University of British Columbia, SHICHENG JIANG, Northeast Normal University, ANA LÓPEZ-BALLESTEROS, Trinity College Dublin, EFRÉN LÓPEZ-BLANCO, Aarhus University, BENJAMIN LOUBET, Université Paris-Saclay, DENIS LOUSTAU, ISPA - INRA, JOHANNES LÜERS, University of Bayreuth, JOHAN NEIRYNCK, Research Institute for Nature and Forest, ZORAN NESIC, University of British Columbia, GIACOMO NICOLINI, University of Tuscia / CMCC, ASKO NOORMETS, Texas A&M University, MATTHEW NORTHWOOD, Charles Darwin University, KIMBERLY NOVICK, Indiana University Bloomington, MARILYN ROLAND, University of Antwerp, SIMONE SABBATINI, University of Tuscia, TORSTEN SACHS, GFZ German Research Centre for Geosciences, SCOTT R. SALESKA, University of Arizona, ENRIQUE P. SÁNCHEZ-CAÑETE, University of Granada / CEAMA-IISTA, ZULIA M. SANCHEZ-MEJIA, Instituto Tecnológico de Sonora, RAINER STEINBRECHER, Karlsruhe Institute of Technology, ROBERT M. STEVENS, Sentek Pty Ltd, COVE STURTEVANT, National Ecological Observatory Network Program, ANDY SUYKER, University of Nebraska-Lincoln, TORBERN TAGESSON, Lund University / University of Copenhagen, SATORU TAKANASHI, Forestry and Forest Products Research Institute, DOMENICO VITALE, University of Tuscia / CMCC, NATALIA VYGODSKAYA, Russian Academy of Sciences, JEFFREY P. WALKER, Monash University, ELIZABETH WALTER-SHEA, University of Nebraska-Lincoln, HUIMIN WANG, Chinese Academy of Sciences, ROBIN WEBER, University of California Berkeley, SEBASTIAN WESTERMANN, Instituto Nacional de Tecnologia Agropecuaria (INTA), CHRISTIAN WILLE, GFZ German Research Centre for Geosciences, STEVEN WOFSY, Harvard University, GEORG WOHLFAHRT, University of Innsbruck, SEBASTIAN WOLF, ETH Zurich, WILLIAM WOODGATE, CSIRO Land and Water, YUELIN LI, Chinese Academy of Sciences, DONATELLA ZONA, San Diego State University / University of Sheffield, DEB AGARWAL, Lawrence Berkeley National Laboratory, SEBASTIEN BIRAUD, Lawrence Berkeley National Laboratory, MARGARET TORN, Lawrence Berkeley National Laboratory, DARIO PAPALE, University of Tuscia / CMCC., ALLISON DUNN, Worcester State University, JIRÍ DUSEK, Global Change Research Institute of the Czech Academy of Sciences, DEREK EAMUS, University of Technology Sydney, UWE EICHELMANN, Technische Universität Dresden, HOUSEN CHU, Lawrence Berkeley National Laboratory, DANIELLE CHRISTIANSON, Lawrence Berkeley National Laboratory, YOU-WEI CHEAH, Lawrence Berkeley National Laboratory, CRISTINA POINDEXTER, California State University, JIQUAN CHEN, Michigan State University, ABDELRAHMAN ELBASHANDY, Lawrence Berkeley National Laboratory, MARTY HUMPHREY, University of Virginia, PETER ISAAC, TERN Ecosystrem Processes, DIEGO POLIDORI, University of Tuscia / CMCC, ALESSIO RIBECA, University of Tuscia / CMCC, CATHARINE VAN INGEN, Lawrence Berkeley National Laboratory, LEIMINGZ HANG, Chinese Academy of Sciences, BRIAN AMIRO, University of Manitoba, CHRISTOF AMMANN, Agroscope Research Institute, M. ALTAF ARAIN, McMaster University, JONAS ARDÖ, Lund University, TIMOTHY ARKEBAUER, University of Nebraska-Lincoln, STEFAN K. ARNDT, The University of Melbourne, NICOLA ARRIGA, University of Antwerp / Joint Research Centre, MARC AUBINET, University of Liege, MIKA AURELA, Finnish Meteorological Institute, DENNIS BALDOCCHI, University of California Berkeley, ALAN BARR, University of Saskatchewan / Environment and Climate Change Canada, DAMIEN BONAL, Université de Lorraine, SEAN P. BURNS, University of Colorado / National Center for Atmospheric Research, PAULINE BUYSSE, Université Paris-Saclay, PETER CALE, Australian Landscape Trust, MAURO CAVAGNA, Fondazione Edmund Mach, PIERRE CELLIER, Université Paris-Saclay, SHIPING CHEN, Chinese Academy of Sciences, ISAAC CHINI, Fondazione Edmund Mach, TORBEN R . CHRISTENSEN, Aarhus University, JAMES CLEVERLY, University of Technology Sydney, ALESSIO COLLALTI, University of Tuscia / National Research Council of Italy, CLAUDIA CONSALVO, University of Tuscia / National Research Council of Italy, BRUCE D. COOK, NASA Goddard Space Flight Center, DAVID COOK, Argonne National Laboratory, CAROLE COURSOLLE, Natural Resources Canada / Université Laval, EDOARDO CREMONESE, Climate Change Unit, PETER S. CURTIS, Ohio State University, ETTORE DANDREA, National Research Council of Italy, HUMBERTO DA ROCHA, USP, XIAOQIN DAI, Chinese Academy of Sciences, KENNETH J. DAVIS, The Pennsylvania State University, BRUNO DE CINTI, National Research Council of Italy, NICOLAS DELPIERRE, Université Paris-Saclay, ANKUR R . DESAI, University of Wisconsin-Madison, CARLOS MARCELO DI BELLA, Facultad de Agronomía, UBA, Buenos Aires., PAUL DI TOMMASI, National Research Council of Italy, ERIC DUFRÊNE, Université Paris-Saclay, MARIUS SCHMIDT, Agrosphere (IBG3), HATIM ABDALLA M. ELKHIDIR, ElObeid Research Station, WERNER EUGSTER, ETH Zurich, CACILIA M. EWENZ, TERN Ecosystem Processes Central Node, BRENT EWERS, University of Wyoming, DANIELA FAMULARI, National Research Council of Italy, SILVANO FARES, National Research Council of Italy / Research Centre for Forestry and Wood, IRIS FEIGENWINTER, ETH Zurich, ANDREW FEITZ, Geoscience Australia, RASMUS FENSHOLT, University of Copenhagen, GIANLUCA FILIPPA, Environmental Protection Agency of Aosta Valley, MARC FISCHER, Lawrence Berkeley National Laboratory, JOHN FRANK, USDA Forest Service, BERT GIELEN, University of Antwerp, BENIAMINO GIOLI, National Research Council of Italy, ANATOLY GITELSON, University of Nebraska-Lincoln, IGNACIO BALLARIN GODED, Joint Research Centre, MATHIAS GOECKEDE, University of Nebraska-Lincoln, ALLEN H. GOLDSTEIN, University of California Berkeley, CHRISTOPHER M. GOUGH, Virginia Commonwealth University, MICHAEL L. GOULDEN, University of California, ALEXANDER GRAF, Forschungszentrum Jülich, ANNE GRIEBEL, The University of Melbourne, CARSTEN GRUENING, Joint Research Centre, THOMAS GRÜNWALD, Technische Universität Dresden, ALBIN HAMMERLE, University of Innsbruck, SHIJIE HAN, Henan University / Chinese Academy of Sciences, XINGGUO HAN, Chinese Academy of Sciences, BIRGER ULF HANSEN, University of Copenhagen, CHAD HANSON, Oregon State University, JUHA HATAKKA, Finnish Meteorological Institute, YONGTAO HE, Chinese Academy of Sciences / University of Chinese Academy of Sciences, MARKUS HEHN, Technische Universität Dresden, BERNARD HEINESCH, University of Liege, NINA HINKO-NAJERA, The University of Melbourne, LUKAS HÖRTNAGL, ETH Zurich, LINDSAY HUTLEY, Charles Darwin University, ANDREAS IBROM, Technical University of Denmark, HIROKI IKAWA, National Agriculture and Food Research Organization, TOMOMICHI KATO, Hokkaido University, MYROSLAVA KHOMIK, McMaster University / Geography and Environmental Management, JANINA KLATT, Karlsruhe Institute of Technology, ALEXANDER KNOHL, University of Goettingen, SARA KNOX, The University of British Columbia, HIDEKI KOBAYASHI, Institute of Arctic Climate and Environment Research, GEORGIA KOERBER, University of Adelaide, OLAF KOLLE, Max Planck Institute for Biogeochemistry, YOSHIKO KOSUGI, Kyoto University, AYUMI KOTANI, Nagoya University, ANDREW KOWALSKI, University of Granada, BART KRUIJT, Wageningen University, JULIA KURBATOVA, Russian Academy of Sciences, WERNER L. KUTSCH, ICOS ERIC, HYOJUNG KWON, Oregon State University, SAMULI LAUNIAINEN, Natural Resources Institute Finland, TUOMAS LAURILA, Finnish Meteorological Institute, BEV LAW, Oregon State University, RAY LEUNING, In memoriam, YINGNIAN LI, Chinese Academy of Sciences, MICHAEL LIDDELL, James Cook University, JEAN-MARC LIMOUSIN, Univ Montpellier, KARL SCHNEIDER, University of Cologne, MARRYANNA LION, Forest Research Institute Malaysia, ADAM J. LISKA, University of Nebraska-Lincoln, ANNALEA LOHILA, Finnish Meteorological Institute / University of Helsinki, ANTJE LUCAS-MOFFAT, Thünen Institute of Climate-Smart Agriculture / Centre for Agrometeorological Research, SIYAN MA, University of California Berkeley, CRAIG MACFARLANE, CSIRO Land and Water, VINCENZO MAGLIULO, National Research Council of Italy, REGINE MAIER, ETH Zurich, IVAN MAMMARELLA, University of Helsinki, GIOVANNI MANCA, Joint Research Centre, BARBARA MARCOLLA, Fondazione Edmund Mach, HANK A . MARGOLIS, Université Laval, SERENA MARRAS, CMCC / University of Sassari, WILLIAM MASSMAN, USDA Forest Service, MIKHAIL MASTEPANOV, Aarhus University / University of Oulu, ROSER MATAMALA, Argonne National Laboratory, JACLYN HATALA MATTHES, Wellesley College, FRANCESCO MAZZENGA, National Research Council of Italy, HARRY MCCAUGHEY, Queen’s University, IAN MCHUGH, The University of Melbourne, ANDREW M. S. MCMILLAN, Environmental Analytics NZ, LUTZ MERBOLD, International Livestock Research Institute, WAYNE MEYER, University of Adelaide, TILDEN MEYERS, NOAA/OAR/Air Resources Laboratory, SCOTT D. MILLER, State University of New York at Albany, STEFANO MINERBI, Forest Department of South Tyrol, UTA MODEROW, Technische Universität Dresden, RUSSELL K. MONSON, University of Arizona, LEONARDO MONTAGNANI, Forest Department of South Tyrol / Free University of Bolzano, CAITLIN E. MOORE, University of Illinois at Urbana-Champaign, EDDY MOORS, IHE Delft / VU Amsterdam, VIRGINIE MOREAUX, ISPA / University Grenoble Alpes, CHRISTINE MOUREAUX, University of Liege, J. WILLIAM MUNGER, Harvard University, TARO NAKAI, National Taiwan University / University of Alaska Fairbanks, MARCELO NOSETTO, Instituto de Matemática Aplicada San Luis / UNER, YANN NOUVELLON, Univ Montpellier-CIRAD-INRA-IRD-Montpellier SupAgro, WALTER OECHEL, San Diego State University / University of Exeter, JORGEN EIVIND OLESEN, Aarhus University, JEAN-MARC OURCIVAL, Univ Montpellier, SHIRLEY A. PAPUGA, Wayne State University, FRANS-JAN PARMENTIER, Lund University / University of Oslo, EUGENIE PAUL-LIMOGES, University of Zurich, MARIAN PAVELKA, Global Change Research Institute of the Czech Academy of Sciences, MATTHIAS PEICHL, Swedish University of Agricultural Sciences, ELISE PENDALL, Western Sydney University, RICHARD P. PHILLIPS, Indiana University Bloomington, KIM PILEGAARD, Technical University of Denmark, NORBERT PIRK, Lund University / CSIRO Land and Water, GABRIELA POSSE, Instituto Nacional de Tecnologia Agropecuaria (INTA), THOMAS POWELL, Lawrence Berkeley National Laboratory, HEIKO PRASSE, Technische Universität Dresden, SUZANNE M. PROBER, CSIRO Land and Water, SERGE RAMBAL, Univ Montpellier, ÜLLAR RANNIK, University of Helsinki, DAVID REED, Michigan State University, VICTOR RESCO DE DIOS, Western Sydney University / Southwest University of Science and Technology, NATALIA RESTREPO-COUPE, University of Arizona, BORJA R. REVERTER, Universidade Federal da Paraiba, HANS PETER SCHMID, Karlsruhe Institute of Technology, FREDERIK SCHRADER, Federal Research Institute of Rural Areas, IVAN SCHRODER, Geoscience Australia, RUSSELL L. SCOTT, Southwest Watershed Research Center, PAVEL SEDLÁK, Global Change Research Institute of the Czech Academy of Sciences / Institute of Atmospheric Physics of the Czech Academy of Sciences, PENÉLOPE SERRANO-ORTÍZ, CEAMA-IISTA / University of Granada, CHANGLIANG SHAO, Chinese Academy of Agricultural Sciences, PEILI SHI, Chinese Academy of Sciences, IVAN SHIRONYA, Russian Academy of Sciences, LUKAS SIEBICKE, Bioclimatology, University of Goettingen, LADISLAV SIGUT, Global Change Research Institute of the Czech Academy of Sciences, RICHARD SILBERSTEIN, University of Western Australia / Edith Cowan University, COSTANTINO SIRCA, CMCC / University of Sassari, DONATELLA SPANO, CMCC / University of Sassari, YANHONG TANG, Peking University, NIGEL TAPPER, Monash University, JONATHAN THOM, University of Wisconsin-Madison, FRANK TIEDEMANN, University of Goettingen, MICHELE TOMASSUCCI, University of Tuscia / Terrasystem srl, JUHA-PEKKA TUOVINEN, Finnish Meteorological Institute, SHAWN URBANSKI, Rocky Mountain Research Station, RICCARDO VALENTINI, University of Tuscia / CMCC, MICHIEL VAN DER MOLEN, Wageningen University, EVA VAN GORSEL, Australian National University Canberra, KO VAN HUISSTEDEN, Vrije Universiteit Amsterdam, ANDREJ VARLAGIN, Russian Academy of Sciences, JOSEPH VERFAILLIE, University of California Berkeley, TIMO VESALA, University of Helsinki, CAROLINE VINCKE, Chinese Academy of Sciences, ROBERTO ZAMPEDRI, Fondazione Edmund Mach, JUNHUI ZHANG, Chinese Academy of Sciences, GUOYI ZHOU, Nanjing University of Information Science & Technology, NAAMA RAZ-YASEEF, Lawrence Berkeley National Laboratory, ERIC BEAMESDERFER, McMaster University, CARLO TROTTA, University of Tuscia, ELEONORA CANFORA, University of Tuscia / CMCC, LUCA BELELLI MARCHESINI, Fondazione Edmund Mach / RUDN University, ONIL BERGERON, Ministère du Développement durable de l’Environnement et de la Lutte contre les changements climatiques, JASON BERINGER, University of Western Australia, CHRISTIAN BERNHOFER, Technische Universität Dresden, DANIEL BERVEILLER, Université Paris-Saclay, and DAVE BILLESBACH, University of Nebraska-Lincoln

Subjects
Meteorologie en Luchtkwaliteit, Data Descriptor, 010504 meteorology & atmospheric sciences, Settore AGR/05 - ASSESTAMENTO FORESTALE E SELVICOLTURA, dataset provides ecosystem, UNCERTAINTY, Eddy covariance, Observation météorologique, 01 natural sciences, ecosystem-scale data, lcsh:Science, SITES, Energy, Respiration, Statistics, Uncertainty, Carbon cycle, Biological measurements, Terrestrial biome, RESPIRATION, gapfilling, [SDE]Environmental Sciences, Assimilation, Anhídrid carbònic, ddc:500, Net ecosystem exchange, Écosystème, STORAGE, Information Systems, Statistics and Probability, ecosystem approaches [EN], Meteorology and Air Quality, ASSIMILATION, Library and Information Sciences, Education, collection [EN], Donnée climatique, Data collection, Water, 15. Life on land, Earth system science, Climate Resilience, Klimaatbestendigheid, lcsh:Q, processing, Climate sciences, Ecophysiology, Storage, Oceanography, Hydrology, Water Resources, 010501 environmental sciences, CARBON-DIOXIDE, ENERGY-BALANCE CLOSURE, ddc:550, Échange d'énergie, FLUXNET2015, Biosphere, Energy balance closure, fluxnet, Computer Science Applications, Collecte de données, Energia, P01 - Conservation de la nature et ressources foncières, Statistics, Probability and Uncertainty, INTERANNUAL VARIABILITY, Eddy Covariance, SDG 6 - Clean Water and Sanitation, Engineering sciences. Technology, Sensoriamento Remoto, FLUX, 1171 Geosciences, Consistency (database systems), eau, Life Science, Time series, Remote sensing studies, Measurement device, 0105 earth and related environmental sciences, Remote sensing, Ecosystem respiration and photosynthetic, WIMEK, NET ECOSYSTEM EXCHANGE, Pipeline (software), Environmental sciences, Metadata, Earth sciences, Carbon dioxide, 13. Climate action, Environmental science, Probability and Uncertainty, Water Systems and Global Change, Dioxyde de carbone
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-flled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the frst time in this paper. In addition, 206 of these sites are for the frst 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., European Union (EU), United States Department of Energy (DOE)

Published
2020
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10. Utilizing Interdisciplinary Strategies for Next Generation Ecosystem Experiments Tropics Data Organization

Author

Boris Faybishenko, D. S. Christianson, Gilberto Pastorello, E. Robles, Deb Agarwal, Robinson I. Negrón-Juárez, and Charuleka Varadharajan

Subjects
Metadata, business.industry, Computer science, media_common.quotation_subject, Informatics, Environmental resource management, Tropics, Quality (business), Ecosystem, business, media_common
Abstract

Quality metadata and data are critical to advancing science and preserving data for long-term use. The Next Generation Ecosystem Experiments (NGEE) Tropics project funded by the U.S. Department of ...

Published
2019
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11. Precipitation mediates sap flux sensitivity to evaporative demand in the neotropics

Author

Chonggang Xu, Damien Bonal, Georgianne W. Moore, Lara M. Kueppers, Kolby J. Jardine, Claire Fortunel, Volodymyr Trotsiuk, Nathan G. Swenson, Clarissa G. Fontes, Isaac Borrego, Bradley O. Christoffersen, Liang Wei, Brett T. Wolfe, Nate G. McDowell, Charlotte Grossiord, Jeffrey M. Warren, Robinson I. Negrón-Juárez, D. S. Christianson, L. M. T. Aparecido, Matteo Detto, Benoit Burban, Heidi Asbjornsen, Kristina J. Anderson-Teixeira, Z. Carter Berry, Jeffrey Q. Chambers, Gretchen R. Miller, Boris Faybishenko, Aura M. Alonso-Rodríguez, Clément Stahl, Tana E. Wood, Bruno O. Gimenez, Charu Varadharajan, Christopher Baraloto, Swiss Federal Institute for Forest, Snow and Avalanche Research WSL, School of Geosciences [Edinburgh], University of Edinburgh, Smithsonian Conservation Biology Institute, Ecologie des forêts de Guyane (ECOFOG), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Université des Antilles et de la Guyane (UAG)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), SILVA (SILVA), Institut National de la Recherche Agronomique (INRA)-AgroParisTech-Université de Lorraine (UL), United States Department of Energy, Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud]), Neuroscience, New York State Psychiatric Institute, Czech University of Life Science, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL)-AgroParisTech, Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD [France-Sud]), Los Alamos National Laboratory (LANL), and Pacific Northwest National Laboratory (PNNL)

Subjects
0106 biological sciences, Vapor Pressure, Vapour Pressure Deficit, Humid subtropical climate, Flux, Biology, Forests, Atmospheric sciences, [SDV.BID.SPT]Life Sciences [q-bio]/Biodiversity/Systematics, Phylogenetics and taxonomy, 010603 evolutionary biology, 01 natural sciences, Trees, Transpiration, Vapor pressure deficit, Atmosphere, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, Evapotranspiration, Plant functional traits, Precipitation, Ecology, Evolution, Behavior and Systematics, Ecology, 010604 marine biology & hydrobiology, Water, Plant Transpiration, 15. Life on land, [SDV.BV.BOT]Life Sciences [q-bio]/Vegetal Biology/Botanics, Droughts, 13. Climate action, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Water use
Abstract

International audience; Transpiration in humid tropical forests modulates the global water cycle and is a key driver of climate regulation. Yet, our understanding of how tropical trees regulate sap flux in response to climate variability remains elusive. With a progressively warming climate, atmospheric evaporative demand [i.e., vapor pressure deficit (VPD)] will be increasingly important for plant functioning, becoming the major control of plant water use in the twenty-first century. Using measurements in 34 tree species at seven sites across a precipitation gradient in the neotropics, we determined how the maximum sap flux velocity (vmax) and the VPD threshold at which vmax is reached (VPDmax) vary with precipitation regime [mean annual precipitation (MAP); seasonal drought intensity (PDRY)] and two functional traits related to foliar and wood economics spectra [leaf mass per area (LMA); wood specific gravity (WSG)]. We show that, even though vmax is highly variable within sites, it follows a negative trend in response to increasing MAP and PDRY across sites. LMA and WSG exerted little effect on vmax and VPDmax, suggesting that these widely used functional traits provide limited explanatory power of dynamic plant responses to environmental variation within hyper-diverse forests. This study demonstrates that long-term precipitation plays an important role in the sap flux response of humid tropical forests to VPD. Our findings suggest that under higher evaporative demand, trees growing in wetter environments in humid tropical regions may be subjected to reduced water exchange with the atmosphere relative to trees growing in drier climates.

Published
2019
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12. A reporting format for field measurements of soil respiration

Author

Stephanie C. Pennington, K. C. Mathes, Ben Bond-Lamberty, D. S. Christianson, and Robert Crystal-Ornelas

Subjects
0106 biological sciences, Process (engineering), Computer science, Interoperability, Bioengineering, 010603 evolutionary biology, 01 natural sciences, Field (computer science), Soil gas flux, Information and Computing Sciences, Ecology, Evolution, Behavior and Systematics, Metadata, FAIR data, Data collection, Ecology, business.industry, 010604 marine biology & hydrobiology, Applied Mathematics, Ecological Modeling, Data reporting format, Usability, Subject (documents), Soil respiration, Biological Sciences, Data science, Discoverability, Computer Science Applications, Data standard, Computational Theory and Mathematics, Modeling and Simulation, business
Abstract

Field observations of the soil-to-atmosphere CO2 flux—soil respiration, RS—are a prime example of ‘long tail’ data that historically have had neither centralized databases nor an agreed-upon reporting format. This has hindered scientific transparency, analytical reproducibility, and syntheses with respect to this globally-important component of the carbon cycle. Here we propose a new data and metadata reporting format for RS data, based on engagement with a wide range of researchers in the earth and ecological sciences as well as expert advisory panels. Our goal was a reporting format that would be relevant and useful for synthesis activities, optimizing data discoverability and usability while not placing an undue burden on data contributors. We describe previous RS data collection efforts, lessons learned from related databases and data-oriented networks (e.g., FLUXNET) in earth and ecological sciences, and the process of community consultation. The proposed reporting format focuses on chamber-level data and metadata, specifying measurement conditions and, for a given measurement period defined by beginning and ending timestamps, a mean RS flux (or CO2 concentration) and associated ancillary measurements. With input from the research community, we have also developed research data and metadata templates to support data collection adhering to the reporting format. Fundamentally, this format aims to enable findable, accessible, interoperable, and reusable data, while providing ‘future-proofing’ capabilities to support reanalyses using as yet unknown algorithms or approaches. This proposed RS reporting format is openly available online and is intended to be a dynamic document, subject to further community feedback and/or change.

Published
2021
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13. Balancing the needs of consumers and producers for scientific data collections

Author

Deb Agarwal, J. Damerow, D. S. Christianson, Gilberto Pastorello, Charuleka Varadharajan, Lavanya Ramakrishnan, and You-Wei Cheah

Subjects
0106 biological sciences, Data collection, Ecology, Computer science, 010604 marine biology & hydrobiology, Applied Mathematics, Ecological Modeling, Dynamic data, Information repository, computer.software_genre, 010603 evolutionary biology, 01 natural sciences, Data science, Computer Science Applications, Identifier, Open data, Computational Theory and Mathematics, Multidisciplinary approach, Modeling and Simulation, Citation, GeneralLiterature_REFERENCE(e.g.,dictionaries,encyclopedias,glossaries), computer, Ecology, Evolution, Behavior and Systematics, Data integration
Abstract

Recent emphasis and requirements for open data publication have led to significant increases in data availability in the Earth sciences, which is critical to long-tail data integration. Currently, data are often published in a repository with an identifier and citation, similar to those for papers. Subsequent publications that use the data are expected to provide a citation in the reference section of the paper. However, the format of the data citation is still evolving, particularly with regards to citing dynamic data, subsets, and collections of data. Considering the motivations of both data producers and consumers, the most pressing need is to create user-friendly solutions that provide credit for data producers and enable accurate citation of data, particularly integrated data. Providing easy-to-use data citations is a critical foundation that is required to address the socio-technical challenges around data integration. Studies that integrate data from dozens or hundreds of datasets must often include data citations in supplementary material due to page limits. However, citations in the supplementary material are not indexed, making it difficult to track citations and thus giving credit to the data producer. In this paper, we discuss our experiences and the challenges we have encountered with current citation guidance. We also review the relative merits of the currently available mechanisms designed to enable compact citation of collections of data, such as data collections, data papers, and dynamic data citations. We consider these options for three data producer scenarios: a domain-specific data collection, a data repository, and a large-scale, multidisciplinary project. We posit that a new mechanism is also needed to enable citation of multiple datasets and credit to data producers.

Published
2021
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14. Species-specific shifts in diurnal sap velocity dynamics and hysteretic behavior of ecophysiological variables during the 2015–2016 el niño event in the amazon forest

Author

Jeffrey M. Warren, Clarissa G. Fontes, Nate G. McDowell, Charles D. Koven, Kolby J. Jardine, Israel de Jesus Sampaio-Filho, Jennifer A. Holm, Jeffrey Q. Chambers, Niro Higuchi, Todd E. Dawson, Charuleka Varadharajan, Brent D. Newman, Leticia O. Cobello, Robinson I. Negrón-Juárez, Alessandro Araújo, Gustavo Spanner, Bruno O. Gimenez, and D. S. Christianson

Subjects
0106 biological sciences, Canopy, Stomatal conductance, 010504 meteorology & atmospheric sciences, Vapour Pressure Deficit, Climate change, Plant Biology, sap velocity, Plant Science, lcsh:Plant culture, Atmospheric sciences, 01 natural sciences, Dry season, lcsh:SB1-1110, Water cycle, 0105 earth and related environmental sciences, Morning, Original Research, tropical forests, vapor pressure deficit, Tropics, leaf temperature, direct solar radiation, hysteresis, stomatal conductance, Environmental science, 010606 plant biology & botany
Abstract

Current climate change scenarios indicate warmer temperatures and the potential for more extreme droughts in the tropics, such that a mechanistic understanding of the water cycle from individual trees to landscapes is needed to adequately predict future changes in forest structure and function. In this study, we contrasted physiological responses of tropical trees during a normal dry season with the extreme dry season due to the 2015–2016 El Niño-Southern Oscillation (ENSO) event. We quantified high resolution temporal dynamics of sap velocity (Vs), stomatal conductance (gs) and leaf water potential (ΨL) of multiple canopy trees, and their correlations with leaf temperature (Tleaf) and environmental conditions [direct solar radiation, air temperature (Tair) and vapor pressure deficit (VPD)]. The experiment leveraged canopy access towers to measure adjacent trees at the ZF2 and Tapajós tropical forest research (near the cities of Manaus and Santarém). The temporal difference between the peak of gs (late morning) and the peak of VPD (early afternoon) is one of the major regulators of sap velocity hysteresis patterns. Sap velocity displayed species-specific diurnal hysteresis patterns reflected by changes in Tleaf. In the morning, Tleaf and sap velocity displayed a sigmoidal relationship. In the afternoon, stomatal conductance declined as Tleaf approached a daily peak, allowing ΨL to begin recovery, while sap velocity declined with an exponential relationship with Tleaf. In Manaus, hysteresis indices of the variables Tleaf-Tair and ΨL-Tleaf were calculated for different species and a significant difference (p < 0.01, α = 0.05) was observed when the 2015 dry season (ENSO period) was compared with the 2017 dry season (“control scenario”). In some days during the 2015 ENSO event, Tleaf approached 40°C for all studied species and the differences between Tleaf and Tair reached as high at 8°C (average difference: 1.65 ± 1.07°C). Generally, Tleaf was higher than Tair during the middle morning to early afternoon, and lower than Tair during the early morning, late afternoon and night. Our results support the hypothesis that partial stomatal closure allows for a recovery in ΨL during the afternoon period giving an observed counterclockwise hysteresis pattern between ΨL and Tleaf. © 2019 Gimenez, Jardine, Higuchi, Negrón-Juárez, Sampaio-Filho, Cobello, Fontes, Dawson, Varadharajan, Christianson, Spanner, Araújo, Warren, Newman, Holm, Koven, McDowell and Chambers.

Published
2019

15. Challenges in Building an End-to-End System for Acquisition, Management, and Integration of Diverse Data From Sensor Networks in Watersheds: Lessons From a Mountainous Community Observatory in East River, Colorado

Author

Charuleka Varadharajan, Matthew L. Henderson, D. S. Christianson, Dipankar Dwivedi, Chelsea Wilmer, Boris Faybishenko, Yuxin Wu, Madison Burrus, Susan S. Hubbard, Deb Agarwal, Heidi Steltzer, A. Henderson, Wendy Brown, Brian J. Enquist, Rosemary Carroll, Kenneth H. Williams, Valerie Hendrix, Benjamin Potter, Alexander Newman, Zarine Kakalia, Roelof Versteeg, and Baptiste Dafflon

Subjects
geoscience, Technology, 010504 meteorology & atmospheric sciences, General Computer Science, Monitoring, Data management, 0208 environmental biotechnology, 02 engineering and technology, computer.software_genre, sensors, water resources, 01 natural sciences, Data modeling, Engineering, Rivers, Snow, Information and Computing Sciences, General Materials Science, Biology, data integration, 0105 earth and related environmental sciences, watershed, Data processing, Data collection, Temperature measurement, business.industry, Environmental resource management, General Engineering, Data models, 020801 environmental engineering, Water resources, Geological survey, co-design, lcsh:Electrical engineering. Electronics. Nuclear engineering, data management, business, computer, Wireless sensor network, lcsh:TK1-9971, Sensor systems and applications, data processing, Data integration
Abstract

The U.S. Department of Energy's Watershed Function Scientific Focus Area (SFA), centered in the East River, Colorado, generates diverse datasets including hydrological, geological, geochemical, geophysical, ecological, microbiological and remote sensing data. The project has deployed extensive field infrastructure involving hundreds of sensors that measure highly diverse phenomena (e.g. stream and groundwater hydrology, water quality, soil moisture, weather) across the watershed. Data from the sensor network are telemetered and automatically ingested into a queryable database. The data are subsequently quality checked, integrated with the United States Geological Survey's stream monitoring network using a custom data integration broker, and published to a portal with interactive visualizations. The resulting data products are used in a variety of scientific modeling and analytical efforts. This paper describes the SFA's end-to-end infrastructure and services that support the generation of integrated datasets from a watershed sensor network. The development and maintenance of this infrastructure, presents a suite of challenges from practical field logistics to complex data processing, which are addressed through various solutions. In particular, the SFA adopts a holistic view for data collection, assessment and integration, which dramatically improves the products generated, and enables a co-design approach wherein data collection is informed by model results and vice-versa.

Published
2019

16. Hunting Data Rogues at Scale: Data Quality Control for Observational Data in Research Infrastructures

Author

F. O'Brien, Stephen Y. Chan, Gilberto Pastorello, You-Wei Cheah, Abdelrahman Elbashandy, Carlo Trotta, Dario Papale, Dan Gunter, Trevor F. Keenan, Deb Agarwal, Sigrid Dengel, Housen Chu, Norm Beekwilder, Cristina Poindexter, Marty Humphrey, E. Canfora, Boris Faybishenko, and D. S. Christianson

Subjects
010504 meteorology & atmospheric sciences, Computer science, business.industry, media_common.quotation_subject, 01 natural sciences, Data science, Data type, Automation, Ancillary data, Data quality, Scalability, Quality (business), Observational study, business, Implementation, 0105 earth and related environmental sciences, media_common
Abstract

© 2017 IEEE. Data quality control is one of the most time consuming activities within Research Infrastructures (RIs), especially when involving observational data and multiple data providers. In this work we report on our ongoing development of data rogues, a scalable approach to manage data quality issues for observational data within RIs. The motivation for this work started with the creation of the FLUXNET2015 dataset, which includes carbon, water, and energy fluxes plus micrometeorological and ancillary data measured in over 200 sites around the world. To create an uniform dataset, including derived data products, extensive work on data quality control was needed. The unpredictable nature of observational data quality issues makes the automation of data quality control inherently difficult. Developed based on this experience, the data rogues methodology allows for increased automation of quality control activities by systematically identifying, cataloging, and documenting implementations of solutions to data issues. We believe this methodology can be extended and applied to others domains and types of data, making the automation of data quality control a more tractable problem.

Published
2017
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17. Ecosystem Feedbacks to Climate Change in California: Development, Testing, and Analysis Using a Coupled Regional Atmosphere and Land Surface Model (WRF3–CLM3.5)

Author

Margaret S. Torn, D. S. Christianson, Lara M. Kueppers, William J. Riley, Jiming Jin, and Z. M. Subin

Subjects
Atmosphere, Climatology, Weather Research and Forecasting Model, General Earth and Planetary Sciences, Environmental science, Climate change, Climate model, Ecosystem, Vegetation, Atmospheric model, Snow
Abstract

A regional atmosphere model [Weather Research and Forecasting model version 3 (WRF3)] and a land surface model [Community Land Model, version 3.5 (CLM3.5)] were coupled to study the interactions between the atmosphere and possible future California land-cover changes. The impact was evaluated on California’s climate of changes in natural vegetation under climate change and of intentional afforestation. The ability of WRF3 to simulate California’s climate was assessed by comparing simulations by WRF3–CLM3.5 and WRF3–Noah to observations from 1982 to 1991. Using WRF3–CLM3.5, the authors performed six 13-yr experiments using historical and future large-scale climate boundary conditions from the Geophysical Fluid Dynamics Laboratory Climate Model version 2.1 (GFDL CM2.1). The land-cover scenarios included historical and future natural vegetation from the Mapped Atmosphere-Plant-Soil System-Century 1 (MC1) dynamic vegetation model, in addition to a future 8-million-ha California afforestation scenario. Natural vegetation changes alone caused summer daily-mean 2-m air temperature changes of −0.7° to +1°C in regions without persistent snow cover, depending on the location and the type of vegetation change. Vegetation temperature changes were much larger than the 2-m air temperature changes because of the finescale spatial heterogeneity of the imposed vegetation change. Up to 30% of the magnitude of the summer daily-mean 2-m air temperature increase and 70% of the magnitude of the 1600 local time (LT) vegetation temperature increase projected under future climate change were attributable to the climate-driven shift in land cover. The authors projected that afforestation could cause local 0.2°–1.2°C reductions in summer daily-mean 2-m air temperature and 2.0°–3.7°C reductions in 1600 LT vegetation temperature for snow-free regions, primarily because of increased evapotranspiration. Because some of these temperature changes are of comparable magnitude to those projected under climate change this century, projections of climate and vegetation change in this region need to consider these climate–vegetation interactions.

Published
2011
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