Hideki Kobayashi


2023

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Evaluating photosynthetic activity across Arctic-Boreal land cover types using solar-induced fluorescence
Rui Cheng, Troy S. Magney, Erica L Orcutt, Zoe Pierrat, Philipp Köhler, David R. Bowling, M. Syndonia Bret‐Harte, Eugénie Euskirchen, Martin Jung, Hideki Kobayashi, A. V. Rocha, Oliver Sonnentag, J. Stutz, Sophia Walther, Donatella Zona, Christian Frankenberg
Environmental Research Letters, Volume 17, Issue 11

Abstract Photosynthesis of terrestrial ecosystems in the Arctic-Boreal region is a critical part of the global carbon cycle. Solar-induced chlorophyll Fluorescence (SIF), a promising proxy for photosynthesis with physiological insight, has been used to track gross primary production (GPP) at regional scales. Recent studies have constructed empirical relationships between SIF and eddy covariance-derived GPP as a first step to predicting global GPP. However, high latitudes pose two specific challenges: (a) Unique plant species and land cover types in the Arctic–Boreal region are not included in the generalized SIF-GPP relationship from lower latitudes, and (b) the complex terrain and sub-pixel land cover further complicate the interpretation of the SIF-GPP relationship. In this study, we focused on the Arctic-Boreal vulnerability experiment (ABoVE) domain and evaluated the empirical relationships between SIF for high latitudes from the TROPOspheric Monitoring Instrument (TROPOMI) and a state-of-the-art machine learning GPP product (FluxCom). For the first time, we report the regression slope, linear correlation coefficient, and the goodness of the fit of SIF-GPP relationships for Arctic-Boreal land cover types with extensive spatial coverage. We found several potential issues specific to the Arctic-Boreal region that should be considered: (a) unrealistically high FluxCom GPP due to the presence of snow and water at the subpixel scale; (b) changing biomass distribution and SIF-GPP relationship along elevational gradients, and (c) limited perspective and misrepresentation of heterogeneous land cover across spatial resolutions. Taken together, our results will help improve the estimation of GPP using SIF in terrestrial biosphere models and cope with model-data uncertainties in the Arctic-Boreal region.

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Carbon uptake in Eurasian boreal forests dominates the high‐latitude net ecosystem carbon budget
Jennifer D. Watts, Mary Farina, J. S. Kimball, Luke Schiferl, Zhihua Liu, Kyle A. Arndt, Donatella Zona, Ashley P. Ballantyne, Eugénie Euskirchen, Frans-Jan W. Parmentier, Manuel Helbig, Oliver Sonnentag, Torbern Tagesson, Janne Rinne, Hiroki Ikawa, Masahito Ueyama, Hideki Kobayashi, Torsten Sachs, Daniel F. Nadeau, John Kochendorfer, Marcin Jackowicz-Korczyński, Anna‐Maria Virkkala, Mika Aurela, R. Commane, Brendan Byrne, Leah Birch, Matthew S. Johnson, Nima Madani, Brendan M. Rogers, Jinyang Du, Arthur Endsley, K. E. Savage, B. Poulter, Zhen Zhang, L. Bruhwiler, Charles E. Miller, Scott J. Goetz, Walter C. Oechel
Global Change Biology, Volume 29, Issue 7

Arctic-boreal landscapes are experiencing profound warming, along with changes in ecosystem moisture status and disturbance from fire. This region is of global importance in terms of carbon feedbacks to climate, yet the sign (sink or source) and magnitude of the Arctic-boreal carbon budget within recent years remains highly uncertain. Here, we provide new estimates of recent (2003-2015) vegetation gross primary productivity (GPP), ecosystem respiration (Reco ), net ecosystem CO2 exchange (NEE; Reco - GPP), and terrestrial methane (CH4 ) emissions for the Arctic-boreal zone using a satellite data-driven process-model for northern ecosystems (TCFM-Arctic), calibrated and evaluated using measurements from >60 tower eddy covariance (EC) sites. We used TCFM-Arctic to obtain daily 1-km2 flux estimates and annual carbon budgets for the pan-Arctic-boreal region. Across the domain, the model indicated an overall average NEE sink of -850 Tg CO2 -C year-1 . Eurasian boreal zones, especially those in Siberia, contributed to a majority of the net sink. In contrast, the tundra biome was relatively carbon neutral (ranging from small sink to source). Regional CH4 emissions from tundra and boreal wetlands (not accounting for aquatic CH4 ) were estimated at 35 Tg CH4 -C year-1 . Accounting for additional emissions from open water aquatic bodies and from fire, using available estimates from the literature, reduced the total regional NEE sink by 21% and shifted many far northern tundra landscapes, and some boreal forests, to a net carbon source. This assessment, based on in situ observations and models, improves our understanding of the high-latitude carbon status and also indicates a continued need for integrated site-to-regional assessments to monitor the vulnerability of these ecosystems to climate change.

2022

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The ABCflux database: Arctic–boreal CO<sub>2</sub> flux observations and ancillary information aggregated to monthly time steps across terrestrial ecosystems
Anna-Maria Virkkala, Susan M. Natali, Brendan M. Rogers, Jennifer D. Watts, K. E. Savage, Sara June Connon, Marguerite Mauritz, Edward A. G. Schuur, D. L. Peter, C. Minions, Julia Nojeim, R. Commane, Craig A. Emmerton, Mathias Goeckede, Manuel Helbig, David Holl, Hiroyasu Iwata, Hideki Kobayashi, Pasi Kolari, Efrén López‐Blanco, Maija E. Marushchak, Mikhail Mastepanov, Lutz Merbold, Frans‐Jan W. Parmentier, Matthias Peichl, Torsten Sachs, Oliver Sonnentag, Masahito Ueyama, Carolina Voigt, Mika Aurela, Julia Boike, Gerardo Celis, Namyi Chae, Torben R. Christensen, M. Syndonia Bret‐Harte, Sigrid Dengel, A. J. Dolman, C. Edgar, Bo Elberling, Eugénie Euskirchen, Achim Grelle, Juha Hatakka, Elyn Humphreys, Järvi Järveoja, Ayumi Kotani, Lars Kutzbach, Tuomas Laurila, Annalea Lohila, Ivan Mammarella, Yukiko Matsuura, Gesa Meyer, Mats Nilsson, Steven F. Oberbauer, Sang Jong Park, Roman E. Petrov, А. С. Прокушкин, Christopher Schulze, Vincent L. St. Louis, Eeva‐Stiina Tuittila, Juha‐Pekka Tuovinen, William L. Quinton, Andrej Varlagin, Donatella Zona, Viacheslav I. Zyryanov
Earth System Science Data, Volume 14, Issue 1

Abstract. Past efforts to synthesize and quantify the magnitude and change in carbon dioxide (CO2) fluxes in terrestrial ecosystems across the rapidly warming Arctic–boreal zone (ABZ) have provided valuable information but were limited in their geographical and temporal coverage. Furthermore, these efforts have been based on data aggregated over varying time periods, often with only minimal site ancillary data, thus limiting their potential to be used in large-scale carbon budget assessments. To bridge these gaps, we developed a standardized monthly database of Arctic–boreal CO2 fluxes (ABCflux) that aggregates in situ measurements of terrestrial net ecosystem CO2 exchange and its derived partitioned component fluxes: gross primary productivity and ecosystem respiration. The data span from 1989 to 2020 with over 70 supporting variables that describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. Here, we describe these variables, the spatial and temporal distribution of observations, the main strengths and limitations of the database, and the potential research opportunities it enables. In total, ABCflux includes 244 sites and 6309 monthly observations; 136 sites and 2217 monthly observations represent tundra, and 108 sites and 4092 observations represent the boreal biome. The database includes fluxes estimated with chamber (19 % of the monthly observations), snow diffusion (3 %) and eddy covariance (78 %) techniques. The largest number of observations were collected during the climatological summer (June–August; 32 %), and fewer observations were available for autumn (September–October; 25 %), winter (December–February; 18 %), and spring (March–May; 25 %). ABCflux can be used in a wide array of empirical, remote sensing and modeling studies to improve understanding of the regional and temporal variability in CO2 fluxes and to better estimate the terrestrial ABZ CO2 budget. ABCflux is openly and freely available online (Virkkala et al., 2021b, https://doi.org/10.3334/ORNLDAAC/1934).

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What explains the year-to-year variation in growing season timing of boreal black spruce forests?
Mariam El-Amine, Alexandre Roy, Franziska Koebsch, Jennifer L. Baltzer, Alan Barr, Andrew Black, Hiroki Ikawa, Hiroyasu Iwata, Hideki Kobayashi, Masahito Ueyama, Oliver Sonnentag
Agricultural and Forest Meteorology, Volume 324

Amplified climate warming in high latitudes is expected to affect growing season timing of the vast boreal biome. It is unclear whether the presence of permafrost (perennially frozen ground) might have an influence on changes in growing season timing. This study examined how different environmental variables explained, either directly or indirectly, the variation in growing season timing of boreal forest stands with and without permafrost. We expected that environmental variables explaining the variation in growing season timing differed or had different explanatory power depending on permafrost presence or absence. The growing season was delineated from daily gross primary productivity (GPP) time series derived from 40 site-year data of net ecosystem carbon dioxide exchange measured with eddy covariance techniques over five black spruce (Picea mariana [Mill.])-dominated boreal forest stands in North America. In permafrost-free forest stands, a combination of start in canopy ‘green-up’ in spring and the timing of air and soil temperature increasing above freezing explained the start-of-season (SOSGPP). Results from commonality analysis and structural equation modeling suggest that canopy ‘green-up’ and air temperature directly affected SOSGPP in permafrost-free forest stands. In addition, soil temperature acted as mediator for an indirect effect of air temperature on SOSGPP. In contrast, none of the environmental variables, or their combination, explained the variation in SOSGPP in forest stands with permafrost. The explanatory power of environmental variables was more consistent regarding the end-of-season (EOSGPP). In both, forest stands with and without permafrost, EOSGPP was directly explained by mean soil water content in the fall and the first day of continuous snowpack formation. A better understanding how environmental variables control SOSGPP and EOSGPP in forest stands with and without permafrost will help to refine parameterizations of the boreal biome in Earth system models.

2021

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Statistical upscaling of ecosystem CO <sub>2</sub> fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties
Anna‐Maria Virkkala, Juha Aalto, Brendan M. Rogers, Torbern Tagesson, Claire C. Treat, Susan M. Natali, Jennifer D. Watts, Stefano Potter, Aleksi Lehtonen, Marguerite Mauritz, Edward A. G. Schuur, John Kochendorfer, Donatella Zona, Walter C. Oechel, Hideki Kobayashi, Elyn Humphreys, Mathias Goeckede, Hiroyasu Iwata, Peter M. Lafleur, Eugénie Euskirchen, Stef Bokhorst, Maija E. Marushchak, Pertti J. Martikainen, Bo Elberling, Carolina Voigt, Christina Biasi, Oliver Sonnentag, Frans‐Jan W. Parmentier, Masahito Ueyama, Gerardo Celis, Vincent L. St. Louis, Craig A. Emmerton, Matthias Peichl, Jinshu Chi, Järvi Järveoja, Mats Nilsson, Steven F. Oberbauer, M. S. Torn, Sang Jong Park, A. J. Dolman, Ivan Mammarella, Namyi Chae, Rafael Poyatos, Efrén López‐Blanco, Torben R. Christensen, Mi Hye Kwon, Torsten Sachs, David Holl, Miska Luoto
Global Change Biology, Volume 27, Issue 17

The regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink-source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high-latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km2) across the high-latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE-focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m−2 yr−1, respectively) compared to tundra (average annual NEE +10 and −2 g C m−2 yr−1). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high-latitude region was on average an annual CO2 sink during 1990–2015, although uncertainty remains high.

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Soil respiration strongly offsets carbon uptake in Alaska and Northwest Canada
Jennifer D. Watts, Susan M. Natali, C. Minions, D. A. Risk, Kyle A. Arndt, Donatella Zona, Eugénie Euskirchen, A. V. Rocha, Oliver Sonnentag, Manuel Helbig, Aram Kalhori, W. C. Oechel, Hiroki Ikawa, Masahito Ueyama, Rikie Suzuki, Hideki Kobayashi, Gerardo Celis, Edward A. G. Schuur, Elyn Humphreys, Yongwon Kim, Bang-Yong Lee, Scott J. Goetz, Nima Madani, Luke Schiferl, R. Commane, J. S. Kimball, Zhihua Liu, M. S. Torn, Stefano Potter, Jonathan Wang, M. Torre Jorgenson, Jingfeng Xiao, Xing Li, C. Edgar
Environmental Research Letters, Volume 16, Issue 8

Abstract Soil respiration (i.e. from soils and roots) provides one of the largest global fluxes of carbon dioxide (CO 2 ) to the atmosphere and is likely to increase with warming, yet the magnitude of soil respiration from rapidly thawing Arctic-boreal regions is not well understood. To address this knowledge gap, we first compiled a new CO 2 flux database for permafrost-affected tundra and boreal ecosystems in Alaska and Northwest Canada. We then used the CO 2 database, multi-sensor satellite imagery, and random forest models to assess the regional magnitude of soil respiration. The flux database includes a new Soil Respiration Station network of chamber-based fluxes, and fluxes from eddy covariance towers. Our site-level data, spanning September 2016 to August 2017, revealed that the largest soil respiration emissions occurred during the summer (June–August) and that summer fluxes were higher in boreal sites (1.87 ± 0.67 g CO 2 –C m −2 d −1 ) relative to tundra (0.94 ± 0.4 g CO 2 –C m −2 d −1 ). We also observed considerable emissions (boreal: 0.24 ± 0.2 g CO 2 –C m −2 d −1 ; tundra: 0.18 ± 0.16 g CO 2 –C m −2 d −1 ) from soils during the winter (November–March) despite frozen surface conditions. Our model estimates indicated an annual region-wide loss from soil respiration of 591 ± 120 Tg CO 2 –C during the 2016–2017 period. Summer months contributed to 58% of the regional soil respiration, winter months contributed to 15%, and the shoulder months contributed to 27%. In total, soil respiration offset 54% of annual gross primary productivity (GPP) across the study domain. We also found that in tundra environments, transitional tundra/boreal ecotones, and in landscapes recently affected by fire, soil respiration often exceeded GPP, resulting in a net annual source of CO 2 to the atmosphere. As this region continues to warm, soil respiration may increasingly offset GPP, further amplifying global climate change.

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Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data
Gilberto Pastorello, Carlo Trotta, E. 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, A. J. 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, B. 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, Efrén 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, E.J. 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, Z. M. 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, S. 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.

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Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites
Housen Chu, Xiangzhong Luo, Zutao Ouyang, Chan Sc, Sigrid Dengel, S. Biraud, M. S. Torn, Stefan Metzger, Jitendra Kumar, M. Altaf Arain, T. J. Arkebauer, Dennis Baldocchi, Carl J. Bernacchi, D. P. Billesbach, T. Andrew Black, Peter D. Blanken, Gil Bohrer, Rosvel Bracho, Scott Brown, Nathaniel A. Brunsell, Jiquan Chen, Xingyuan Chen, Kenneth L. Clark, Ankur R. Desai, Tomer Duman, David Durden, Silvano Fares, Inke Forbrich, John A. Gamon, Christopher M. Gough, Timothy J. Griffis, Manuel Helbig, David Y. Hollinger, Elyn Humphreys, Hiroki Ikawa, Hiroyasu Iwata, Yang Ju, John F. Knowles, Sara Knox, Hideki Kobayashi, Thomas E. Kolb, Beverly E. Law, Xuhui Lee, M. E. Litvak, Heping Li, J. William Munger, Asko Noormets, Kim Novick, Steven F. Oberbauer, Walter C. Oechel, Patricia Y. Oikawa, S. A. Papuga, Elise Pendall, Prajaya Prajapati, John H. Prueger, William L. Quinton, Andrew D. Richardson, Eric S. Russell, Russell L. Scott, Gregory Starr, R. M. Staebler, Paul C. Stoy, Ellen Stuart-Haëntjens, Oliver Sonnentag, Ryan C. Sullivan, Andy Suyker, Masahito Ueyama, Rodrigo Vargas, J. D. Wood, Donatella Zona
Agricultural and Forest Meteorology, Volume 301-302

• Large-scale eddy-covariance flux datasets need to be used with footprint-awareness • Using a fixed-extent target area across sites can bias model-data integration • Most sites do not represent the dominant land-cover type at a larger spatial extent • A representativeness index provides general guidance for site selection and data use Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 10 3 to 10 7 m 2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applications and to provide general guidance for data use.

2020

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The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data
Gilberto Pastorello, Carlo Trotta, E. 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, A. J. 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, B. 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, Efrén 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, E.J. 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, Z. M. 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, S. 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.

2019

DOI bib
Increased high‐latitude photosynthetic carbon gain offset by respiration carbon loss during an anomalous warm winter to spring transition
Zhi Hua Liu, J. S. Kimball, Nicholas C. Parazoo, Ashley P. Ballantyne, Wen J. Wang, Nima Madani, Caleb G. Pan, Jennifer D. Watts, Rolf H. Reichle, Oliver Sonnentag, Philip Marsh, Miriam Hurkuck, Manuel Helbig, William L. Quinton, Donatella Zona, Masahito Ueyama, Hideki Kobayashi, Eugénie Euskirchen
Global Change Biology, Volume 26, Issue 2

Arctic and boreal ecosystems play an important role in the global carbon (C) budget, and whether they act as a future net C sink or source depends on climate and environmental change. Here, we used complementary in situ measurements, model simulations, and satellite observations to investigate the net carbon dioxide (CO2 ) seasonal cycle and its climatic and environmental controls across Alaska and northwestern Canada during the anomalously warm winter to spring conditions of 2015 and 2016 (relative to 2010-2014). In the warm spring, we found that photosynthesis was enhanced more than respiration, leading to greater CO2 uptake. However, photosynthetic enhancement from spring warming was partially offset by greater ecosystem respiration during the preceding anomalously warm winter, resulting in nearly neutral effects on the annual net CO2 balance. Eddy covariance CO2 flux measurements showed that air temperature has a primary influence on net CO2 exchange in winter and spring, while soil moisture has a primary control on net CO2 exchange in the fall. The net CO2 exchange was generally more moisture limited in the boreal region than in the Arctic tundra. Our analysis indicates complex seasonal interactions of underlying C cycle processes in response to changing climate and hydrology that may not manifest in changes in net annual CO2 exchange. Therefore, a better understanding of the seasonal response of C cycle processes may provide important insights for predicting future carbon-climate feedbacks and their consequences on atmospheric CO2 dynamics in the northern high latitudes.
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