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1. Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing

Author: Mingjuan Xie, Xiaofei Ma, Yuangang Wang, Chaofan Li, Haiyang Shi, Xiuliang Yuan, Olaf Hellwich, Chunbo Chen, Wenqiang Zhang, Chen Zhang, Qing Ling, Ruixiang Gao, Yu Zhang, Friday Uchenna Ochege, Amaury Frankl, Philippe De Maeyer, Nina Buchmann, Iris Feigenwinter, Jørgen E. Olesen, Radoslaw Juszczak, Adrien Jacotot, Aino Korrensalo, Andrea Pitacco, Andrej Varlagin, Ankit Shekhar, Annalea Lohila, Arnaud Carrara, Aurore Brut, Bart Kruijt, Benjamin Loubet, Bernard Heinesch, Bogdan Chojnicki, Carole Helfter, Caroline Vincke, Changliang Shao, Christian Bernhofer, Christian Brümmer, Christian Wille, Eeva-Stiina Tuittila, Eiko Nemitz, Franco Meggio, Gang Dong, Gary Lanigan, Georg Niedrist, Georg Wohlfahrt, Guoyi Zhou, Ignacio Goded, Thomas Gruenwald, Janusz Olejnik, Joachim Jansen, Johan Neirynck, Juha-Pekka Tuovinen, Junhui Zhang, Katja Klumpp, Kim Pilegaard, Ladislav Šigut, Leif Klemedtsson, Luca Tezza, Lukas Hörtnagl, Marek Urbaniak, Marilyn Roland, Marius Schmidt, Mark A. Sutton, Markus Hehn, Matthew Saunders, Matthias Mauder, Mika Aurela, Mika Korkiakoski, Mingyuan Du, Nadia Vendrame, Natalia Kowalska, Paul G. Leahy, Pavel Alekseychik, Peili Shi, Per Weslien, Shiping Chen, Silvano Fares, Thomas Friborg, Tiphaine Tallec, Tomomichi Kato, Torsten Sachs, Trofim Maximov, Umberto Morra di Cella, Uta Moderow, Yingnian Li, Yongtao He, Yoshiko Kosugi, and Geping Luo
Subjects: Science
Abstract: Abstract Simulating the carbon-water fluxes at more widely distributed meteorological stations based on the sparsely and unevenly distributed eddy covariance flux stations is needed to accurately understand the carbon-water cycle of terrestrial ecosystems. We established a new framework consisting of machine learning, determination coefficient (R2), Euclidean distance, and remote sensing (RS), to simulate the daily net ecosystem carbon dioxide exchange (NEE) and water flux (WF) of the Eurasian meteorological stations using a random forest model or/and RS. The daily NEE and WF datasets with RS-based information (NEE-RS and WF-RS) for 3774 and 4427 meteorological stations during 2002–2020 were produced, respectively. And the daily NEE and WF datasets without RS-based information (NEE-WRS and WF-WRS) for 4667 and 6763 meteorological stations during 1983–2018 were generated, respectively. For each meteorological station, the carbon-water fluxes meet accuracy requirements and have quasi-observational properties. These four carbon-water flux datasets have great potential to improve the assessments of the ecosystem carbon-water dynamics.
Published: 2023
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2. Joint optimization of land carbon uptake and albedo can help achieve moderate instantaneous and long-term cooling effects

Author: Alexander Graf, Georg Wohlfahrt, Sergio Aranda-Barranco, Nicola Arriga, Christian Brümmer, Eric Ceschia, Philippe Ciais, Ankur R. Desai, Sara Di Lonardo, Mana Gharun, Thomas Grünwald, Lukas Hörtnagl, Kuno Kasak, Anne Klosterhalfen, Alexander Knohl, Natalia Kowalska, Michael Leuchner, Anders Lindroth, Matthias Mauder, Mirco Migliavacca, Alexandra C. Morel, Andreas Pfennig, Hendrik Poorter, Christian Poppe Terán, Oliver Reitz, Corinna Rebmann, Arturo Sanchez-Azofeifa, Marius Schmidt, Ladislav Šigut, Enrico Tomelleri, Ke Yu, Andrej Varlagin, and Harry Vereecken
Subjects: Geology, QE1-996.5, Environmental sciences, GE1-350
Abstract: Abstract Both carbon dioxide uptake and albedo of the land surface affect global climate. However, climate change mitigation by increasing carbon uptake can cause a warming trade-off by decreasing albedo, with most research focusing on afforestation and its interaction with snow. Here, we present carbon uptake and albedo observations from 176 globally distributed flux stations. We demonstrate a gradual decline in maximum achievable annual albedo as carbon uptake increases, even within subgroups of non-forest and snow-free ecosystems. Based on a paired-site permutation approach, we quantify the likely impact of land use on carbon uptake and albedo. Shifting to the maximum attainable carbon uptake at each site would likely cause moderate net global warming for the first approximately 20 years, followed by a strong cooling effect. A balanced policy co-optimizing carbon uptake and albedo is possible that avoids warming on any timescale, but results in a weaker long-term cooling effect.
Published: 2023
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3. Site Characteristics Mediate the Relationship Between Forest Productivity and Satellite Measured Solar Induced Fluorescence

Author: Theresia Yazbeck, Gil Bohrer, Pierre Gentine, Luping Ye, Nicola Arriga, Christian Bernhofer, Peter D. Blanken, Ankur R. Desai, David Durden, Alexander Knohl, Natalia Kowalska, Stefan Metzger, Meelis Mölder, Asko Noormets, Kim Novick, Russell L. Scott, Ladislav Šigut, Kamel Soudani, Masahito Ueyama, and Andrej Varlagin
Subjects: Gross Primary Production, Solar-Induced Chlorophyll Fluorescence, canopy conductance, canopy structure, photosynthesis, Forestry, SD1-669.5, Environmental sciences, GE1-350
Abstract: Solar-Induced Chlorophyll Fluorescence (SIF) can provide key information about the state of photosynthesis and offers the prospect of defining remote sensing-based estimation of Gross Primary Production (GPP). There is strong theoretical support for the link between SIF and GPP and this relationship has been empirically demonstrated using ground-based, airborne, and satellite-based SIF observations, as well as modeling. However, most evaluations have been based on monthly and annual scales, yet the GPP:SIF relations can be strongly influenced by both vegetation structure and physiology. At the monthly timescales, the structural response often dominates but short-term physiological variations can strongly impact the GPP:SIF relations. Here, we test how well SIF can predict the inter-daily variation of GPP during the growing season and under stress conditions, while taking into account the local effect of sites and abiotic conditions. We compare the accuracy of GPP predictions from SIF at different timescales (half-hourly, daily, and weekly), while evaluating effect of adding environmental variables to the relationship. We utilize observations for years 2018–2019 at 31 mid-latitudes, forested, eddy covariance (EC) flux sites in North America and Europe and use TROPOMI satellite data for SIF. Our results show that SIF is a good predictor of GPP, when accounting for inter-site variation, probably due to differences in canopy structure. Seasonally averaged leaf area index, fraction of absorbed photosynthetically active radiation (fPAR) and canopy conductance provide a predictor to the site-level effect. We show that fPAR is the main factor driving errors in the linear model at high temporal resolution. Adding water stress indicators, namely canopy conductance, to a multi-linear SIF-based GPP model provides the best improvement in the model precision at the three considered timescales, showing the importance of accounting for water stress in GPP predictions, independent of the SIF signal. SIF is a promising predictor for GPP among other remote sensing variables, but more focus should be placed on including canopy structure, and water stress effects in the relationship, especially when considering intra-seasonal, and inter- and intra-daily resolutions.
Published: 2021
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4. Interannual and spatial variability of net ecosystem production in forests explained by an integrated physiological indicator in summer

Author: Ying Liu, Chaoyang Wu, Lin Liu, Chengyan Gu, T. Andrew Black, Rachhpal S. Jassal, Lukas Hörtnagl, Leonardo Montagnani, Fernando Moyano, Andrej Varlagin, M. Altaf Arain, and Ajit Govind
Subjects: Physiology, Phenology, Forest, Flux, Net ecosystem production, Ecology, QH540-549.5
Abstract: Understanding the feedback of ecosystem carbon uptake on climate change at temporal and spatial scales is crucial for developing ecosystem models. Previous studies have focused on the role of spring and autumn phenology in regulating carbon sequestration in forest stands, but few on the impact of physiological status in summer. However, plant accumulated the most carbon in summer compared with spring and autumn, therefore, it is of great significance to explore the role of summer phenological metrics on the variability of carbon sequestration. Using 514 site-years of flux data obtained at 40 FLUXNET sites including three forest ecosystems (i.e. evergreen needleleaf forest (ENF), deciduous broadleaf forest (DBF) and mixed forest (MF)) in Europe and North America, we compared the potential of physiological and phenological metrics of Gross Primary Production (GPP) and Ecosystem Respiration (RECO) in explaining the interannual and spatial variability (IAV and SV) of forest net ecosystem production (NEP). In view of the better performance of physiological metrics, we developed the maximum carbon uptake index (MCUI), which integrated the physiology metrics of photosynthesis and respiration in summer, and further explored its ability in explaining the IAV and SV of NEP. The results suggest that the MCUI had a better ability than respiration-growth length ratio (RGR) in predicting NEP for all three forest types. The interpretation of MCUI based on meteorological variables illustrated that the controlling meteorological factors of MCUI differed substantially among ecosystems. The summer shortwave radiation had the greatest influence on MCUI at DBF sites, while the soil water content played an important but opposite role at ENF and DBF sites, and no significant meteorological driver was found at MF sites. The higher potential of MCUI in explaining IAV and SV of NEP highlights the importance of summer physiology in controlling the forest carbon sequestration, and further confirms the significant role of peak plant growth in regulating carbon cycle of forest ecosystems. Understanding the drivers of peak plant growth is therefore of a great significance for further improving the precious of ecosystem model in the future.
Published: 2021
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5. Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

Author: Gilberto Pastorello, Carlo Trotta, Eleonora Canfora, Housen Chu, Danielle Christianson, You-Wei Cheah, Cristina Poindexter, Jiquan Chen, Abdelrahman Elbashandy, Marty Humphrey, Peter Isaac, Diego Polidori, Markus Reichstein, Alessio Ribeca, Catharine van Ingen, Nicolas Vuichard, Leiming Zhang, Brian Amiro, Christof Ammann, M. Altaf Arain, Jonas Ardö, Timothy 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, Dave Billesbach, Thomas 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, Benoit Burban, Sean P. Burns, Pauline Buysse, Peter Cale, Mauro 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, Agnes de Grandcourt, Anne De Ligne, Raimundo C. De Oliveira, Nicolas Delpierre, Ankur R. Desai, Carlos Marcelo Di Bella, Paul di Tommasi, Han Dolman, Francisco Domingo, Gang Dong, Sabina Dore, Pierpaolo Duce, Eric Dufrêne, Allison Dunn, Jiří Dušek, Derek Eamus, Uwe Eichelmann, Hatim Abdalla M. ElKhidir, Werner Eugster, Cacilia M. Ewenz, Brent Ewers, Daniela Famulari, Silvano Fares, Iris Feigenwinter, Andrew Feitz, Rasmus Fensholt, Gianluca Filippa, Marc Fischer, John Frank, Marta Galvagno, Mana Gharun, Damiano Gianelle, Bert Gielen, Beniamino Gioli, Anatoly 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 Hutley, Andreas Ibrom, Hiroki Ikawa, Marcin Jackowicz-Korczynski, Dalibor Janouš, Wilma Jans, Rachhpal Jassal, Shicheng Jiang, Tomomichi Kato, Myroslava Khomik, Janina Klatt, Alexander Knohl, Sara Knox, Hideki Kobayashi, Georgia Koerber, Olaf Kolle, Yoshiko Kosugi, Ayumi Kotani, Andrew Kowalski, Bart Kruijt, Julia Kurbatova, Werner L. Kutsch, Hyojung Kwon, Samuli Launiainen, Tuomas Laurila, Bev Law, Ray Leuning, Yingnian Li, Michael Liddell, Jean-Marc Limousin, Marryanna Lion, Adam J. 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, William Massman, Mikhail Mastepanov, Roser Matamala, Jaclyn Hatala Matthes, Francesco Mazzenga, Harry McCaughey, Ian McHugh, Andrew M. S. McMillan, Lutz Merbold, Wayne Meyer, Tilden Meyers, Scott D. Miller, Stefano Minerbi, Uta Moderow, Russell K. Monson, Leonardo Montagnani, Caitlin E. Moore, Eddy Moors, Virginie Moreaux, Christine Moureaux, J. William Munger, Taro Nakai, Johan Neirynck, Zoran Nesic, Giacomo Nicolini, Asko Noormets, Matthew Northwood, Marcelo Nosetto, Yann Nouvellon, Kimberly Novick, Walter Oechel, Jørgen Eivind Olesen, Jean-Marc Ourcival, Shirley A. Papuga, Frans-Jan Parmentier, Eugenie Paul-Limoges, Marian Pavelka, Matthias Peichl, Elise Pendall, Richard P. Phillips, Kim Pilegaard, Norbert Pirk, Gabriela Posse, Thomas Powell, Heiko Prasse, Suzanne M. Prober, Serge Rambal, Üllar Rannik, Naama Raz-Yaseef, Corinna Rebmann, David Reed, Victor Resco de Dios, Natalia Restrepo-Coupe, Borja R. Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, Scott R. Saleska, Enrique P. Sánchez-Cañete, Zulia M. Sanchez-Mejia, 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, Rainer Steinbrecher, Robert M. Stevens, Cove Sturtevant, Andy Suyker, Torbern Tagesson, Satoru Takanashi, Yanhong Tang, Nigel Tapper, Jonathan Thom, Michele Tomassucci, Juha-Pekka Tuovinen, Shawn Urbanski, Riccardo Valentini, Michiel van der Molen, Eva van Gorsel, Ko van Huissteden, Andrej Varlagin, Joseph Verfaillie, Timo Vesala, Caroline Vincke, Domenico Vitale, Natalia Vygodskaya, Jeffrey P. Walker, Elizabeth Walter-Shea, Huimin Wang, Robin Weber, Sebastian Westermann, Christian Wille, Steven Wofsy, Georg Wohlfahrt, Sebastian Wolf, William Woodgate, Yuelin Li, Roberto Zampedri, Junhui Zhang, Guoyi Zhou, Donatella Zona, Deb Agarwal, Sebastien Biraud, Margaret Torn, and Dario Papale
Subjects: Science
Abstract: A Correction to this paper has been published: https://doi.org/10.1038/s41597-021-00851-9.
Published: 2021
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6. Direct and indirect effects of climatic variations on the interannual variability in net ecosystem exchange across terrestrial ecosystems

Author: Junjiong Shao, Xuhui Zhou, Yiqi Luo, Bo Li, Mika Aurela, David Billesbach, Peter D. Blanken, Rosvel Bracho, Jiquan Chen, Marc Fischer, Yuling Fu, Lianhong Gu, Shijie Han, Yongtao He, Thomas Kolb, Yingnian Li, Zoltan Nagy, Shuli Niu, Walter C. Oechel, Krisztina Pinter, Peili Shi, Andrew Suyker, Margaret Torn, Andrej Varlagin, Huimin Wang, Junhua Yan, Guirui Yu, and Junhui Zhang
Subjects: net ecosystem exchange, interannual variability, climatic variations, physiological parameters, direct and indirect effects, relative importance, Meteorology. Climatology, QC851-999
Abstract: Climatic variables not only directly affect the interannual variability (IAV) in net ecosystem exchange of CO2 (NEE) but also indirectly drive it by changing the physiological parameters. Identifying these direct and indirect paths can reveal the underlying mechanisms of carbon (C) dynamics. In this study, we applied a path analysis using flux data from 65 sites to quantify the direct and indirect climatic effects on IAV in NEE and to evaluate the potential relationships among the climatic variables and physiological parameters that represent physiology and phenology of ecosystems. We found that the maximum photosynthetic rate was the most important factor for the IAV in gross primary productivity (GPP), which was mainly induced by the variation in vapour pressure deficit. For ecosystem respiration (RE), the most important drivers were GPP and the reference respiratory rate. The biome type regulated the direct and indirect paths, with distinctive differences between forests and non-forests, evergreen needleleaf forests and deciduous broadleaf forests, and between grasslands and croplands. Different paths were also found among wet, moist and dry ecosystems. However, the climatic variables can only partly explain the IAV in physiological parameters, suggesting that the latter may also result from other biotic and disturbance factors. In addition, the climatic variables related to NEE were not necessarily the same as those related to GPP and RE, indicating the emerging difficulty encountered when studying the IAV in NEE. Overall, our results highlight the contribution of certain physiological parameters to the IAV in C fluxes and the importance of biome type and multi-year water conditions, which should receive more attention in future experimental and modelling research.
Published: 2016
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7. The biophysical climate mitigation potential of boreal peatlands during the growing season

Author: Manuel Helbig, James M Waddington, Pavel Alekseychik, Brian Amiro, Mika Aurela, Alan G Barr, T Andrew Black, Sean K Carey, Jiquan Chen, Jinshu Chi, Ankur R Desai, Allison Dunn, Eugenie S Euskirchen, Lawrence B Flanagan, Thomas Friborg, Michelle Garneau, Achim Grelle, Silvie Harder, Michal Heliasz, Elyn R Humphreys, Hiroki Ikawa, Pierre-Erik Isabelle, Hiroki Iwata, Rachhpal Jassal, Mika Korkiakoski, Juliya Kurbatova, Lars Kutzbach, Elena Lapshina, Anders Lindroth, Mikaell Ottosson Löfvenius, Annalea Lohila, Ivan Mammarella, Philip Marsh, Paul A Moore, Trofim Maximov, Daniel F Nadeau, Erin M Nicholls, Mats B Nilsson, Takeshi Ohta, Matthias Peichl, Richard M Petrone, Anatoly Prokushkin, William L Quinton, Nigel Roulet, Benjamin R K Runkle, Oliver Sonnentag, Ian B Strachan, Pierre Taillardat, Eeva-Stiina Tuittila, Juha-Pekka Tuovinen, Jessica Turner, Masahito Ueyama, Andrej Varlagin, Timo Vesala, Martin Wilmking, Vyacheslav Zyrianov, and Christopher Schulze
Subjects: peatlands, boreal forest, climate mitigation, regional climate, energy balance, Environmental technology. Sanitary engineering, TD1-1066, Environmental sciences, GE1-350, Science, Physics, QC1-999
Abstract: Peatlands and forests cover large areas of the boreal biome and are critical for global climate regulation. They also regulate regional climate through heat and water vapour exchange with the atmosphere. Understanding how land-atmosphere interactions in peatlands differ from forests may therefore be crucial for modelling boreal climate system dynamics and for assessing climate benefits of peatland conservation and restoration. To assess the biophysical impacts of peatlands and forests on peak growing season air temperature and humidity, we analysed surface energy fluxes and albedo from 35 peatlands and 37 evergreen needleleaf forests—the dominant boreal forest type—and simulated air temperature and vapour pressure deficit (VPD) over hypothetical homogeneous peatland and forest landscapes. We ran an evapotranspiration model using land surface parameters derived from energy flux observations and coupled an analytical solution for the surface energy balance to an atmospheric boundary layer (ABL) model. We found that peatlands, compared to forests, are characterized by higher growing season albedo, lower aerodynamic conductance, and higher surface conductance for an equivalent VPD. This combination of peatland surface properties results in a ∼20% decrease in afternoon ABL height, a cooling (from 1.7 to 2.5 °C) in afternoon air temperatures, and a decrease in afternoon VPD (from 0.4 to 0.7 kPa) for peatland landscapes compared to forest landscapes. These biophysical climate impacts of peatlands are most pronounced at lower latitudes (∼45°N) and decrease toward the northern limit of the boreal biome (∼70°N). Thus, boreal peatlands have the potential to mitigate the effect of regional climate warming during the growing season. The biophysical climate mitigation potential of peatlands needs to be accounted for when projecting the future climate of the boreal biome, when assessing the climate benefits of conserving pristine boreal peatlands, and when restoring peatlands that have experienced peatland drainage and mining.
Published: 2020
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8. Inferring CO2 fertilization effect based on global monitoring land-atmosphere exchange with a theoretical model

Author: Masahito Ueyama, Kazuhito Ichii, Hideki Kobayashi, Tomo’omi Kumagai, Jason Beringer, Lutz Merbold, Eugénie S Euskirchen, Takashi Hirano, Luca Belelli Marchesini, Dennis Baldocchi, Taku M Saitoh, Yasuko Mizoguchi, Keisuke Ono, Joon Kim, Andrej Varlagin, Minseok Kang, Takanori Shimizu, Yoshiko Kosugi, M Syndonia Bret-Harte, Takashi Machimura, Yojiro Matsuura, Takeshi Ohta, Kentaro Takagi, Satoru Takanashi, and Yukio Yasuda
Subjects: CO2 fertilization effect, photosynthesis, evapotranspiration, eddy covariance, sun/shade model, Environmental technology. Sanitary engineering, TD1-1066, Environmental sciences, GE1-350, Science, Physics, QC1-999
Abstract: Rising atmospheric CO _2 concentration ([CO _2 ]) enhances photosynthesis and reduces transpiration at the leaf, ecosystem, and global scale via the CO _2 fertilization effect. The CO _2 fertilization effect is among the most important processes for predicting the terrestrial carbon budget and future climate, yet it has been elusive to quantify. For evaluating the CO _2 fertilization effect on land photosynthesis and transpiration, we developed a technique that isolated this effect from other confounding effects, such as changes in climate, using a noisy time series of observed land-atmosphere CO _2 and water vapor exchange. Here, we evaluate the magnitude of this effect from 2000 to 2014 globally based on constraint optimization of gross primary productivity (GPP) and evapotranspiration in a canopy photosynthesis model over 104 global eddy-covariance stations. We found a consistent increase of GPP (0.138 ± 0.007% ppm ^−1 ; percentile per rising ppm of [CO _2 ]) and a concomitant decrease in transpiration (−0.073% ± 0.006% ppm ^−1 ) due to rising [CO _2 ]. Enhanced GPP from CO _2 fertilization after the baseline year 2000 is, on average, 1.2% of global GPP, 12.4 g C m ^−2 yr ^−1 or 1.8 Pg C yr ^−1 at the years from 2001 to 2014. Our result demonstrates that the current increase in [CO _2 ] could potentially explain the recent land CO _2 sink at the global scale.
Published: 2020
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9. Performance of Linear and Nonlinear Two-Leaf Light Use Efficiency Models at Different Temporal Scales

Author: Xiaocui Wu, Weimin Ju, Yanlian Zhou, Mingzhu He, Beverly E. Law, T. Andrew Black, Hank A. Margolis, Alessandro Cescatti, Lianhong Gu, Leonardo Montagnani, Asko Noormets, Timothy J. Griffis, Kim Pilegaard, Andrej Varlagin, Riccardo Valentini, Peter D. Blanken, Shaoqiang Wang, Huimin Wang, Shijie Han, Junhua Yan, Yingnian Li, Bingbing Zhou, and Yibo Liu
Subjects: gross primary productivity (GPP), light use efficiency model, sunlit and shaded leaves, vegetation types, temporal scales, Science
Abstract: The reliable simulation of gross primary productivity (GPP) at various spatial and temporal scales is of significance to quantifying the net exchange of carbon between terrestrial ecosystems and the atmosphere. This study aimed to verify the ability of a nonlinear two-leaf model (TL-LUEn), a linear two-leaf model (TL-LUE), and a big-leaf light use efficiency model (MOD17) to simulate GPP at half-hourly, daily and 8-day scales using GPP derived from 58 eddy-covariance flux sites in Asia, Europe and North America as benchmarks. Model evaluation showed that the overall performance of TL-LUEn was slightly but not significantly better than TL-LUE at half-hourly and daily scale, while the overall performance of both TL-LUEn and TL-LUE were significantly better (p < 0.0001) than MOD17 at the two temporal scales. The improvement of TL-LUEn over TL-LUE was relatively small in comparison with the improvement of TL-LUE over MOD17. However, the differences between TL-LUEn and MOD17, and TL-LUE and MOD17 became less distinct at the 8-day scale. As for different vegetation types, TL-LUEn and TL-LUE performed better than MOD17 for all vegetation types except crops at the half-hourly scale. At the daily and 8-day scales, both TL-LUEn and TL-LUE outperformed MOD17 for forests. However, TL-LUEn had a mixed performance for the three non-forest types while TL-LUE outperformed MOD17 slightly for all these non-forest types at daily and 8-day scales. The better performance of TL-LUEn and TL-LUE for forests was mainly achieved by the correction of the underestimation/overestimation of GPP simulated by MOD17 under low/high solar radiation and sky clearness conditions. TL-LUEn is more applicable at individual sites at the half-hourly scale while TL-LUE could be regionally used at half-hourly, daily and 8-day scales. MOD17 is also an applicable option regionally at the 8-day scale.
Published: 2015
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10. Quantifying the effect of forest age in annual net forest carbon balance

Author: Simon Besnard, Nuno Carvalhais, M Altaf Arain, Andrew Black, Sytze de Bruin, Nina Buchmann, Alessandro Cescatti, Jiquan Chen, Jan G P W Clevers, Ankur R Desai, Christopher M Gough, Katerina Havrankova, Martin Herold, Lukas Hörtnagl, Martin Jung, Alexander Knohl, Bart Kruijt, Lenka Krupkova, Beverly E Law, Anders Lindroth, Asko Noormets, Olivier Roupsard, Rainer Steinbrecher, Andrej Varlagin, Caroline Vincke, and Markus Reichstein
Subjects: carbon cycle, eddy covariance, net ecosystem production, empirical modelling, forest age, climate, Environmental technology. Sanitary engineering, TD1-1066, Environmental sciences, GE1-350, Science, Physics, QC1-999
Abstract: Forests dominate carbon (C) exchanges between the terrestrial biosphere and the atmosphere on land. In the long term, the net carbon flux between forests and the atmosphere has been significantly impacted by changes in forest cover area and structure due to ecological disturbances and management activities. Current empirical approaches for estimating net ecosystem productivity (NEP) rarely consider forest age as a predictor, which represents variation in physiological processes that can respond differently to environmental drivers, and regrowth following disturbance. Here, we conduct an observational synthesis to empirically determine to what extent climate, soil properties, nitrogen deposition, forest age and management influence the spatial and interannual variability of forest NEP across 126 forest eddy-covariance flux sites worldwide. The empirical models explained up to 62% and 71% of spatio-temporal and across-site variability of annual NEP, respectively. An investigation of model structures revealed that forest age was a dominant factor of NEP spatio-temporal variability in both space and time at the global scale as compared to abiotic factors, such as nutrient availability, soil characteristics and climate. These findings emphasize the importance of forest age in quantifying spatio-temporal variation in NEP using empirical approaches.
Published: 2018
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11. Radiative Entropy Production along the Paludification Gradient in the Southern Taiga

Author: Olga Kuricheva, Vadim Mamkin, Robert Sandlersky, Juriy Puzachenko, Andrej Varlagin, and Juliya Kurbatova
Subjects: entropy production, thermodynamics, ecosystem, southern taiga, forest, bog, Science, Astrophysics, QB460-466, Physics, QC1-999
Abstract: Entropy production (σ) is a measure of ecosystem and landscape stability in a changing environment. We calculated the σ in the radiation balance for a well-drained spruce forest, a paludified spruce forest, and a bog in the southern taiga of the European part of Russia using long-term meteorological data. Though radiative σ depends both on surface temperature and absorbed radiation, the radiation effect in boreal ecosystems is much more important than the temperature effect. The dynamic of the incoming solar radiation was the main driver of the diurnal, seasonal, and intra-annual courses of σ for all ecosystems; the difference in ecosystem albedo was the second most important factor, responsible for seven-eighths of the difference in σ between the bog and forest in a warm period. Despite the higher productivity and the complex structure of the well-drained forest, the dynamics and sums of σ in two forests were very similar. Summer droughts had no influence on the albedo and σ efficiency of forests, demonstrating high self-regulation of the taiga forest ecosystems. On the contrary, a decreasing water supply significantly elevated the albedo and lowered the σ in bog. Bogs, being non-steady ecosystems, demonstrate unique thermodynamic behavior, which is fluctuant and strongly dependent on the moisture supply. Paludification of territories may result in increasing instability of the energy balance and entropy production in the landscape of the southern taiga.
Published: 2017
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12. Biotic and climatic controls on interannual variability in carbon fluxes across terrestrial ecosystems

Author: Shao, Junjiong, Andrej Varlagin, Andrew Suyker, Bo Li, David Billesbach, Guirui Yu, Huimin Wang, Jiquan Chen, Junhua Yan, Junhui Zhang, Krisztina Pinter, Lianhong Gu, Marc Fischer, Margaret Torn, Mika Aurela, Peili Shi, Peter D. Blanken, Rosvel Bracho, Shijie Han, Shuli Niu, Thomas Kolb, Walter C. Oechel, Xuhui Zhou, Yingnian Li, Yiqi Luo, Yongtao He, Yuling Fu, and Zoltan Nagy
Subjects: Net ecosystem exchange, Interannual variability, Biotic effect, Climatic effect, Relative importance, Climatic stress, Meteorology & Atmospheric Sciences, Earth Sciences, Biological Sciences, Agricultural and Veterinary Sciences
Abstract: Interannual variability (IAV, represented by standard deviation) in net ecosystem exchange of CO2 (NEE) is mainly driven by climatic drivers and biotic variations (i.e., the changes in photosynthetic and respiratory responses to climate), the effects of which are referred to as climatic (CE) and biotic effects (BE), respectively. Evaluating the relative contributions of CE and BE to the IAV in carbon (C) fluxes and understanding their controlling mechanisms are critical in projecting ecosystem changes in the future climate. In this study, we applied statistical methods with flux data from 65 sites located in the Northern Hemisphere to address this issue. Our results showed that the relative contribution of BE (CnBE) and CE (CnCE) to the IAV in NEE was 57%±14% and 43%±14%, respectively. The discrepancy in the CnBE among sites could be largely explained by water balance index (WBI). Across water-stressed ecosystems, the CnBE decreased with increasing aridity (slope=0.18%mm−1). In addition, the CnBE tended to increase and the uncertainty reduced as timespan of available data increased from 5 to 15 years. Inter-site variation of the IAV in NEE mainly resulted from the IAV in BE (72%) compared to that in CE (37%). Interestingly, positive correlations between BE and CE occurred in grasslands and dry ecosystems (r>0.45, P
Published: 2015

13. Solar‐induced chlorophyll fluorescence is strongly correlated with terrestrial photosynthesis for a wide variety of biomes: First global analysis based on OCO‐2 and flux tower observations

Author: Xing Li, Jingfeng Xiao, Binbin He, M. Altaf Arain, Jason Beringer, Ankur R. Desai, Carmen Emmel, David Y. Hollinger, Alisa Krasnova, Ivan Mammarella, Steffen M. Noe, Penélope Serrano Ortiz, A. Camilo Rey‐Sanchez, Adrian V. Rocha, and Andrej Varlagin
Published: 2018
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14. The ABCflux database: Arctic–boreal CO2 flux observations and ancillary information aggregated to monthly time steps across terrestrial ecosystems

Author: Anna-Maria Virkkala, Susan M. Natali, Brendan M. Rogers, Jennifer D. Watts, Kathleen Savage, Sara June Connon, Marguerite Mauritz, Edward A. G. Schuur, Darcy Peter, Christina Minions, Julia Nojeim, Roisin Commane, Craig A. Emmerton, Mathias Goeckede, Manuel Helbig, David Holl, Hiroki 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, Han Dolman, Colin W. Edgar, Bo Elberling, Eugenie Euskirchen, Achim Grelle, Juha Hatakka, Elyn Humphreys, Järvi Järveoja, Ayumi Kotani, Lars Kutzbach, Tuomas Laurila, Annalea Lohila, Ivan Mammarella, Yojiro Matsuura, Gesa Meyer, Mats B. Nilsson, Steven F. Oberbauer, Sang-Jong Park, Roman Petrov, Anatoly S. Prokushkin, Christopher Schulze, Vincent L. St. Louis, Eeva-Stiina Tuittila, Juha-Pekka Tuovinen, William Quinton, Andrej Varlagin, Donatella Zona, and Viacheslav I. Zyryanov
Subjects: General Earth and Planetary Sciences
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).
Published: 2022
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15. 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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16. Estimating ecosystem evaporation and transpiration using a soil moisture coupled two-source energy balance model across FLUXNET sites

Author: Kejia Xue, Lisheng Song, Yanhao Xu, Shaomin Liu, Gengle Zhao, Sinuo Tao, Enzo Magliulo, Antonio Manco, Michael Liddell, Georg Wohlfahrt, Andrej Varlagin, Leonardo Montagnani, William Woodgate, Benjamin Loubet, and Long Zhao
Subjects: Atmospheric Science, Global and Planetary Change, Forestry, Agronomy and Crop Science
Published: 2023
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17. Response of Spruce Forest Ecosystem CO2 Fluxes to Inter-Annual Climate Anomalies in the Southern Taiga

Author: Vadim Mamkin, Andrej Varlagin, and Kurbatova Juliya
Subjects: Forestry, southern taiga, net ecosystem exchange, CO2 fluxes, eddy covariance, heatwave 2018, soil moisture
Abstract: Climate extremes and anomalies modify the CO2 ecosystem–atmosphere exchange of the boreal forests and consequently alter the terrestrial carbon stocks and the atmospheric greenhouse gas concentrations. The effects of the anomalous weather conditions on the CO2 net ecosystem exchange (NEE), total ecosystem respiration (TER), and gross primary production (GPP) of the typical southern taiga nemorose spruce forest were analyzed using continuous eddy covariance flux measurements in the 2015–2020 period. The forest was found to be a source of atmospheric CO2 in 2016, 2017, 2019, and 2020 (the mean annual GPP/TER ratio was between 0.87 and 0.97). In 2018, the forest was found to act as a CO2 sink (GPP/TER = 1.47) when a positive temperature anomaly in the growing season was accompanied by a negative precipitation anomaly and increased global radiation. The early start of the CO2 uptake in the anomalously warm winter of 2019/2020 did not result in an increase in the annual GPP/TER ratio (0.90). The comparison of the flux data obtained from the nemorose spruce forest on the well-drained soils with the data obtained from paludified spruce forest in the same landscape showed that the mean annual GPP/TER ratio of the sites alternatively responded to the mentioned anomalies. This study suggests that a variety of soil moisture regimes across the southern taiga spruce forests provide a non-uniformity in the response reactions of the CO2 ecosystem–atmosphere exchange on the climate anomalies.
Published: 2022
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18. Warming does not delay the start of autumnal leaf coloration but slows its progress rate

Author: Nan Jiang, Miaogen Shen, Philippe Ciais, Matteo Campioli, Josep Peñuelas, Christian Körner, Ruyin Cao, Shilong Piao, Licong Liu, Shiping Wang, Eryuan Liang, Nicolas Delpierre, Kamel Soudani, Yuhan Rao, Leonardo Montagnani, Lukas Hörtnagl, Eugénie Paul‐Limoges, Ranga Myneni, Georg Wohlfahrt, Yongshuo Fu, Ladislav Šigut, Andrej Varlagin, Jin Chen, Yanhong Tang, Wenwu Zhao, Institute of Tibetan Plateau Research, Chinese Academy of Sciences [Changchun Branch] (CAS), Beijing Normal University (BNU), 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), Plant and Vegetation Ecology (PLECO), University of Antwerp (UA), CREAF BELLATERRA ESP, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), CREAF - Centre for Ecological Research and Applied Forestries, University of Basel (Unibas), Chengdu University of Technology (CDUT), Peking University [Beijing], AgroParisTech, Computer Science (North Carolina State University), North Carolina State University [Raleigh] (NC State), University of North Carolina System (UNC)-University of North Carolina System (UNC), Forest Service, Autonomous Province of Bolzano-Bozen, Bolzano-Bozen, Free University of Bozen-Bolzano, Institute of Agricultural Sciences [Zürich], Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Universität Zürich [Zürich] = University of Zurich (UZH), Boston University [Boston] (BU), Leopold Franzens Universität Innsbruck - University of Innsbruck, Czech Academy of Sciences [Prague] (CAS), Russian Academy of Sciences [Moscow] (RAS), European Project: 714916,LEAF-FALL, and European Project: 610028,EC:FP7:ERC,ERC-2013-SyG,IMBALANCE-P(2014)
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Global and Planetary Change, Chemistry, Ecology, Economics, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Biology, Ecology, Evolution, Behavior and Systematics
Abstract: Aim: Initiation of autumnal leaf senescence is critical for plant overwintering and ecosystem dynamics. Previous studies focused solely on the advanced stages of autumnal leaf senescence and claimed that climatic warming delays senescence, despite the fundamental differences among the stages of senescence. However, the timing of onset of leaf coloration (DLCO), the earliest visual sign of senescence, has been rarely studied. Our aim is to assess the response of DLCO to temperature across the Northern Hemisphere.Location: 30–75°N in the Northern Hemisphere.Time period: 2000–2018.Major taxa studied: Deciduous vegetation.Methods: We retrieved DLCO from high temporal-resolution satellite data, which was then validated by PhenoCam observations. We then investigated the temporal changes in DLCO and the relationship between DLCO and temperature by using DLCO from satellite data and ground phenological observations. We further estimated the timing of onset of autumnal decline in maximum canopy photosynthetic capacity, an indicator of leaf senescence earlier than DLCO, from FLUXNET CO2 fluxes data, and assessed its response to temperature.Results: DLCO was not significantly (P < 0.05) delayed between 2000 and 2018 in 94% of the area. DLCO was positively correlated with pre-DLCO mean daily minimum temperature (Tmin) in only 9% of the area, likely because of the overriding photoperiodic control, particularly for woody vegetation, whereas the end of leaf coloration (DLCE) was positively correlated with pre-DLCE mean Tmin over a larger area (34%).Main conclusions: The coloration progress rate is more sensitive than its start date to temperature, indicating an extension of the duration of leaf senescence under warming. This study indicates that the leaf coloration onset was not responsive to climate warming and provides observational evidence of photoperiod control of autumnal leaf senescence at biome and continental scales.
Published: 2022
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19. Uncovering the critical soil moisture thresholds of plant water stress for European ecosystems

Author: Zheng Fu, Philippe Ciais, David Makowski, Ana Bastos, Paul C. Stoy, Andreas Ibrom, Alexander Knohl, Mirco Migliavacca, Matthias Cuntz, Ladislav Šigut, Matthias Peichl, Denis Loustau, Tarek S. El‐Madany, Nina Buchmann, Mana Gharun, Ivan Janssens, Christian Markwitz, Thomas Grünwald, Corinna Rebmann, Meelis Mölder, Andrej Varlagin, Ivan Mammarella, Pasi Kolari, Christian Bernhofer, Michal Heliasz, Caroline Vincke, Andrea Pitacco, Edoardo Cremonese, Lenka Foltýnová, Jean‐Pierre Wigneron, 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), ICOS-ATC (ICOS-ATC), 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)-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), Mathématiques et Informatique Appliquées (MIA Paris-Saclay), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft, University of Wisconsin-Madison, Danmarks Tekniske Universitet = Technical University of Denmark (DTU), Georg-August-University = Georg-August-Universität Göttingen, SILVA (SILVA), AgroParisTech-Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Global Change Research Centre (CzechGlobe), Swedish University of Agricultural Sciences (SLU), 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), Department of Environmental Systems Science [ETH Zürich] (D-USYS), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), University of Antwerp (UA), Institute of Hydrology and Meteorology [Dresden], Technische Universität Dresden = Dresden University of Technology (TU Dresden), Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), Department of Physical Geography and Ecosystem Science [Lund], Lund University [Lund], A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences [Moscow] (RAS), Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Centre for Environmental and Climate Research [Lund] (CEC), Earth and Life Institute [Louvain-La-Neuve] (ELI), Université Catholique de Louvain = Catholic University of Louvain (UCL), Università degli Studi di Padova = University of Padua (Unipd), Funding information European Research Council Synergy project, Grant/Award Number: SyG2013-610028, European Project: 610028,EC:FP7:ERC,ERC-2013-SyG,IMBALANCE-P(2014), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), and Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)
Subjects: surface energy partitioning, critical soil moisture threshold, 010504 meteorology & atmospheric sciences, Gross primary production, Surface energy partitioning, 0207 environmental engineering, drought, 02 engineering and technology, Forests, 01 natural sciences, Vapor pressure deficit, Soil, Europe, evaporative fraction, gross primary production, vapor pressure deficit, SDG 13 - Climate Action, Humans, Environmental Chemistry, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, 020701 environmental engineering, Evaporative fraction, Biology, Ecosystem, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, General Environmental Science, SDG 15 - Life on Land, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Global and Planetary Change, Dehydration, Ecology, Drought, 15. Life on land, Droughts, Chemistry, 13. Climate action, Critical soil moisture threshold
Abstract: Understanding the critical soil moisture (SM) threshold (θcrit) of plant water stress and land surface energy partitioning is a basis to evaluate drought impacts and improve models for predicting future ecosystem condition and climate. Quantifying the θcrit across biomes and climates is challenging because observations of surface energy fluxes and SM remain sparse. Here, we used the latest database of eddy covariance measurements to estimate θcrit across Europe by evaluating evaporative fraction (EF)-SM relationships and investigating the covariance between vapor pressure deficit (VPD) and gross primary production (GPP) during SM dry-down periods. We found that the θcrit and soil matric potential threshold in Europe are 16.5% and −0.7 MPa, respectively. Surface energy partitioning characteristics varied among different vegetation types; EF in savannas had the highest sensitivities to SM in water-limited stage, and the lowest in forests. The sign of the covariance between daily VPD and GPP consistently changed from positive to negative during dry-down across all sites when EF shifted from relatively high to low values. This sign of the covariance changed after longer period of SM decline in forests than in grasslands and savannas. Estimated θcrit from the VPD–GPP covariance method match well with the EF–SM method, showing this covariance method can be used to detect the θcrit. We further found that soil texture dominates the spatial variability of θcrit while shortwave radiation and VPD are the major drivers in determining the spatial pattern of EF sensitivities. Our results highlight for the first time that the sign change of the covariance between daily VPD and GPP can be used as an indicator of how ecosystems transition from energy to SM limitation. We also characterized the corresponding θcrit and its drivers across diverse ecosystems in Europe, an essential variable to improve the representation of water stress in land surface models., Global Change Biology, 28 (6), ISSN:1354-1013, ISSN:1365-2486
Published: 2022
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20. Estimating Ecosystem Evaporation and Transpiration Using Soil Moisture Coupled Two-Source Energy Balance Model Across Fluxnet Sites

Author: Kejia Xue, Lisheng Song, Yanhao Xu, Shaomin Liu, Genle Zhao, Sinuo Tao, Enzo Magliulo, Antonio Manco, Michael J. Liddell, Georg Wohlfahrt, Andrej Varlagin, Leonardo Montagnani, William Woodgate, Benjamin Loubet, and Long Zhao
Published: 2022
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21. Gap-filling eddy covariance methane fluxes : Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Author: Sheel Bansal, Lisamarie Windham-Myers, Karina V. R. Schäfer, Christian Wille, Han Dolman, Hiroki Iwata, Mats Nilsson, Robert Shortt, Andrew D. Richardson, Pavel Alekseychik, Sarah Feron, Benjamin Poulter, David P. Billesbach, Kyle B. Delwiche, Walter C. Oechel, Anand Avati, Avni Malhotra, Jiquan Chen, Fred Lu, Ivan Mammarella, Lutz Merbold, Ankur R. Desai, Robert B. Jackson, Pia Gottschalk, Carole Helfter, Bhaskar Mitra, Kathrin Fuchs, Takashi Hirano, Manuel Helbig, Edward A. G. Schuur, M. Goeckede, Domenico Vitale, Zutao Ouyang, Andrew Y. Ng, Mangaliso J. Gondwe, Regine Maier, M. C. R. Alberto, Asko Noormets, Thomas Friborg, Patricia Y. Oikawa, Torsten Sachs, Franziska Koebsch, Eiko Nemitz, Andrej Varlagin, Dario Papale, Keisuke Ono, Jeremy Irvin, Matthias Peichl, Jordan P. Goodrich, Carlo Trotta, Gil Bohrer, Gerardo Celis, David I. Campbell, Camilo Rey-Sanchez, Vincent Liu, Sara H. Knox, Benjamin R. K. Runkle, Sébastien Gogo, Andrew Kondrich, Guan Xhuan Wong, Sharon Zhou, Housen Chu, Kuno Kasak, Lukas Hörtnagl, Timothy H. Morin, Oliver Sonnentag, George L. Vourlitis, Rodrigo Vargas, Derrick Y.F. Lai, Kyle S. Hemes, Ryan C. Sullivan, E. J. Ward, Masahito Ueyama, Annalea Lohila, Gerald Jurasinski, Daphne Szutu, Eeva-Stiina Tuittila, Gavin McNicol, Donatella Zona, Ayaka Sakabe, Cove Sturtevant, Aram Kalhori, Antje Lucas-Moffat, Mika Aurela, Dennis D. Baldocchi, Martin Heimann, Eugénie S. Euskirchen, Adrien Jacotot, Alex C. Valach, Ellen Stuart-Haëntjens, Joeseph G. Verfaillie, Higo J. Dalmagro, Etienne Fluet-Chouinard, Institute for Atmospheric and Earth System Research (INAR), Micrometeorology and biogeochemical cycles, Earth and Climate, Earth Sciences, Institut des Sciences de la Terre d'Orléans - UMR7327 (ISTO), Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers en région Centre (OSUC), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Bureau de Recherches Géologiques et Minières (BRGM) (BRGM), Biogéosystèmes Continentaux - UMR7327, and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Bureau de Recherches Géologiques et Minières (BRGM) (BRGM)-Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers en région Centre (OSUC)
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, imputation, computer.software_genre, 01 natural sciences, CARBON-DIOXIDE, FluxNet, Imputation (statistics), ENVIRONMENTAL DRIVERS, EMISSIONS, Global and Planetary Change, Artificial neural network, methane, Sampling (statistics), Forestry, 04 agricultural and veterinary sciences, 6. Clean water, machine learning, RESPIRATION, CO2, Marginal distribution, SDG 6 - Clean Water and Sanitation, gap-filling, CH4 FLUX, time series, methane flux, wetlands, ASSIMILATION, Eddy covariance, Decision tree, Machine learning, 114 Physical sciences, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Baseline (configuration management), 0105 earth and related environmental sciences, NET ECOSYSTEM EXCHANGE, business.industry, 15. Life on land, flux, PERSPECTIVES, [SDU]Sciences of the Universe [physics], 13. Climate action, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science, Artificial intelligence, business, METHODOLOGY, Agronomy and Crop Science, computer
Abstract: Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET). ISSN:0168-1923 ISSN:1873-2240
Published: 2021
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22. Interannual and spatial variability of net ecosystem production in forests explained by an integrated physiological indicator in summer

Author: T. Andrew Black, Fernando Moyano, Lin Liu, Rachhpal S. Jassal, M. Altaf Arain, Chengyan Gu, Lukas Hörtnagl, Andrej Varlagin, Ajit Govind, Chaoyang Wu, Ying Liu, Leonardo Montagnani, Chinese Academy of Sciences [Beijing] (CAS), University of Chinese Academy of Sciences [Beijing] (UCAS), Hebei GEO University, Shijiazhuang 050031, China, University of British Columbia (UBC), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Free University of Bozen-Bolzano, Göttingen State and University Library (SUB Göttingen), Georg-August-University [Göttingen], the Russian Academy of Sciences [Moscow, Russia] (RAS), McMaster University [Hamilton, Ontario], Interactions Sol Plante Atmosphère (UMR ISPA), and 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)
Subjects: 0106 biological sciences, 010504 meteorology & atmospheric sciences, Physiology, Phenology, Forest, Flux, Net ecosystem production, General Decision Sciences, Carbon sequestration, 010603 evolutionary biology, 01 natural sciences, Carbon cycle, FluxNet, Ecosystem model, Forest ecology, Ecosystem, Ecology, Evolution, Behavior and Systematics, QH540-549.5, 0105 earth and related environmental sciences, Ecology, Primary production, 15. Life on land, 13. Climate action, [SDE]Environmental Sciences, Environmental science, Ecosystem respiration
Abstract: Understanding the feedback of ecosystem carbon uptake on climate change at temporal and spatial scales is crucial for developing ecosystem models. Previous studies have focused on the role of spring and autumn phenology in regulating carbon sequestration in forest stands, but few on the impact of physiological status in summer. However, plant accumulated the most carbon in summer compared with spring and autumn, therefore, it is of great significance to explore the role of summer phenological metrics on the variability of carbon sequestration. Using 514 site-years of flux data obtained at 40 FLUXNET sites including three forest ecosystems (i.e. evergreen needleleaf forest (ENF), deciduous broadleaf forest (DBF) and mixed forest (MF)) in Europe and North America, we compared the potential of physiological and phenological metrics of Gross Primary Production (GPP) and Ecosystem Respiration (RECO) in explaining the interannual and spatial variability (IAV and SV) of forest net ecosystem production (NEP). In view of the better performance of physiological metrics, we developed the maximum carbon uptake index (MCUI), which integrated the physiology metrics of photosynthesis and respiration in summer, and further explored its ability in explaining the IAV and SV of NEP. The results suggest that the MCUI had a better ability than respiration-growth length ratio (RGR) in predicting NEP for all three forest types. The interpretation of MCUI based on meteorological variables illustrated that the controlling meteorological factors of MCUI differed substantially among ecosystems. The summer shortwave radiation had the greatest influence on MCUI at DBF sites, while the soil water content played an important but opposite role at ENF and DBF sites, and no significant meteorological driver was found at MF sites. The higher potential of MCUI in explaining IAV and SV of NEP highlights the importance of summer physiology in controlling the forest carbon sequestration, and further confirms the significant role of peak plant growth in regulating carbon cycle of forest ecosystems. Understanding the drivers of peak plant growth is therefore of a great significance for further improving the precious of ecosystem model in the future. ISSN:1470-160X ISSN:1872-7034
Published: 2021
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23. 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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24. Relative importance of climatic variables, soil properties and plant traits to spatial variability in net CO2 exchange across global forests and grasslands

Author: Takeshi Ohta, Ivan Mammarella, Thomas Grünwald, Ankit Shekhar, Yiping Zhang, Huiying Liu, Xuhui Zhou, Rachhpal S. Jassal, Ruiqiang Liu, Sébastien C. Biraud, Nina Buchmann, Andrej Varlagin, Torbern Tagesson, Mana Gharun, William Woodgate, Huimin Zhou, Zhi Chen, Christian Bernhofer, Junjiong Shao, Zhenggang Du, Guirui Yu, Antonio Manco, E. Magliulo, Richard Silberstein, Jiří Dušek, Lingyan Zhou, T. A. Black, Leonardo Montagnani, D. P. Billesbach, Institute for Atmospheric and Earth System Research (INAR), and Micrometeorology and biogeochemical cycles
Subjects: 0106 biological sciences, Atmospheric Science, 010504 meteorology & atmospheric sciences, Eddy covariance, Atmospheric sciences, 01 natural sciences, 114 Physical sciences, Spatial variability, Grassland, Evapotranspiration, Climatic variables, 0105 earth and related environmental sciences, 2. Zero hunger, Plant traits, Global and Planetary Change, geography, geography.geographical_feature_category, Forestry, 15. Life on land, Carbon, 13. Climate action, Soil water, Environmental science, Common spatial pattern, Terrestrial ecosystem, Soil properties, Ecosystem respiration, Net ecosystem exchange, Agronomy and Crop Science, 010606 plant biology & botany
Abstract: Compared to the well-known drivers of spatial variability in gross primary productivity (GPP), the relative importance of climatic variables, soil properties and plant traits to the spatial variability in net ecosystem exchange of CO2 between terrestrial ecosystem and atmosphere (NEE) is poorly understood. We used principal component regression to analyze data from 147 eddy flux sites to disentangle effects of climatic variables, soil properties and plant traits on the spatial variation in annual NEE and its components (GPP and ecosystem respiration (RE)) across global forests and grasslands. Our results showed that the largest unique contribution (proportion of variance only explained by one class of variables) to NEE variance came from climatic variables for forests (24%-30%) and soil properties for grasslands (41%-54%). Specifically, mean annual precipitation and potential evapotranspiration were the most important climatic variables driving forest NEE, whereas available soil water capacity, clay content and cation exchange capacity mainly influenced grassland NEE. Plant traits showed a small unique contribution to NEE in both forests and grasslands. However, leaf phosphorus content strongly interacted with soil total nitrogen density and clay content, and these combined factors represented a major contribution for grassland NEE. For GPP and RE, the majority of spatial variance was attributed to the common contribution of climate, soil and plant traits (50% - 62%, proportion of variance explained by more than one class of variables), rather than their unique contributions. Interestingly, those factors with only minor influences on GPP and RE variability (e.g., soil properties) have significant contributions to the spatial variability in NEE. Such emerging factors and the interactions between climatic variables, soil properties and plant traits are not well represented in current terrestrial biosphere models, which should be considered in future model improvement to accurately predict the spatial pattern of carbon cycling across forests and grasslands globally.
Published: 2021
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25. The ABCflux database: Arctic-Boreal CO2 flux observations and ancillary information aggregated to monthly time steps across terrestrial ecosystems

Author: Efrén López-Blanco, Roisin Commane, Han Dolman, Eugénie S. Euskirchen, Edward A. G. Schuur, David Holl, Mats Nilsson, Achim Grelle, Juha-Pekka Tuovinen, Ayumi Kotani, Darcy Peter, Annalea Lohila, Roman E. Petrov, M. Syndonia Bret-Harte, Anna-Maria Virkkala, Sigrid Dengel, Andrej Varlagin, Craig A. Emmerton, Steven F. Oberbauer, Mikhail Mastepanov, Kathleen Savage, Jennifer D. Watts, Gerardo Celis, Masahito Ueyama, Hiroki Iwata, Järvi Järveoja, Bo Elberling, Mika Aurela, Christopher Schulze, C. Edgar, Namyi Chae, Oliver Sonnentag, Viacheslav I. Zyryanov, Elyn Humphreys, Yojiro Matsuura, Susan M. Natali, Vincent L. St. Louis, Christina Minions, Hideki Kobayashi, Carolina Voigt, Julia Boike, Pasi Kolari, Julia Nojeim, Eeva-Stiina Tuittila, Juha Hatakka, Anatoly S. Prokushkin, Maija E. Marushchak, Tuomas Laurila, Sara June Connon, Manuel Helbig, M. Goeckede, William L. Quinton, Ivan Mammarella, Torben R. Christensen, Brendan M. Rogers, Lutz Merbold, Gesa Meyer, Frans-Jan W. Parmentier, Torsten Sachs, Marguerite Mauritz, Matthias Peichl, Donatella Zona, Sang-Jong Park, and Lars Kutzbach
Subjects: Database, Biome, Eddy covariance, Vegetation, 15. Life on land, computer.software_genre, Snow, Arctic, 13. Climate action, Environmental science, Ecosystem, Terrestrial ecosystem, Ecosystem respiration, computer
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 (https://doi.org/10.3334/ORNLDAAC/1934, Virkkala et al., 2021a).
Published: 2021
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26. Thermal field of the southern taiga landscape of the Russian plain

Author: Yu. G. Puzachenko, A. N. Krenke, Andrej Varlagin, A. S. Baibar, and Robert Sandlersky
Subjects: Heat flux, Spatial structure, Thermal radiation, Geography, Planning and Development, Taiga, Thermal, General Earth and Planetary Sciences, Satellite, Invariant (mathematics), Atmospheric sciences, Physics::Atmospheric and Oceanic Physics, Stationary state, Geology
Abstract: The technology of allocation of order parameters (invariants) of the spatial structure of the thermal field of the southern taiga landscape (Central Forest Nature Reserve) obtained on the basis of the analysis of the time series of measurements in the long-wave channel of Landsat satellites from 1986 to 2017 and reflecting its stationary state is considered. It is shown that the heat flux is measured by the satellite not directly from the forest crowns, but from the ground layer of the atmosphere, the state of which is determined by the parameters of the landscape. It is found that the invariant component of the spatiotemporal variation of the thermal field is displayed by two order parameters: the first mainly reflects the temperature of winter months, the second – of summer. The contribution of relief and vegetation to the determination of invariants and the autochthonous components of the thermal field determined by the transition zones between the landscape elements contrasting in thermal radiation are revealed. It is shown that the thermal field measured by the satellite reflects the heat flux from the ground layer of the atmosphere, which is in direct interaction with the landscape cover.
Published: 2019
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27. Energy and CO2 exchange in an undisturbed spruce forest and clear-cut in the Southern Taiga

Author: Dmitry Ivanov, Vitaly Avilov, Julia Kurbatova, Irina Yaseneva, Andrej Varlagin, Alexander Olchev, Vadim Mamkin, and Olga Kuricheva
Subjects: 0106 biological sciences, Clearcutting, Atmospheric Science, Global and Planetary Change, 010504 meteorology & atmospheric sciences, Taiga, Energy balance, Eddy covariance, Growing season, Forestry, Atmospheric sciences, 01 natural sciences, Atmosphere, Environmental science, Ecosystem respiration, Bowen ratio, Agronomy and Crop Science, 010606 plant biology & botany, 0105 earth and related environmental sciences
Abstract: Effects of clear cutting and other forest disturbances on surface radiative properties and the energy and CO2 fluxes between land surface and the atmosphere can vary significantly depending on local climatic and moisture conditions, forest structure and species composition, soil properties and many other factors. In this study we analyzed the influence of clear-cutting on the energy, water vapor and CO2 fluxes in the still very poorly investigated part of the boreal forest community in the European part of Russia. This issue has become particularly relevant due to intensified logging in the region during recent decades. The sensible (H) and latent (LE) heat, as well as CO2 fluxes were continuously measured at recently clear-cut and undisturbed mature spruce forest sites using eddy covariance technique during the first growing season following harvest. Because of their close location they are characterized by similar meteorological conditions. The results of our field measurements showed that the clear-cut strongly influenced the energy balance and CO2 fluxes between the land surface and atmosphere. Energy fluxes (LE and H) at the undisturbed forest site were consistently larger than at the clear-cut throughout the period of measurements. The Bowen ratio (β=H/LE) varied significantly over time, though was similar at both sites. Whereas H was almost equal to LE at both sites in spring, the LE significantly exceeded H over the summer (β≈0.2 - for mature spruce forest and β = 0.4 - for clear-cut). The mean β for the entire period was similar (β≈0.5) at both sites. Analysis of CO2 fluxes showed that the clear-cut was a consistent source of CO2 to the atmosphere. Net ecosystem exchange (NEE) at the clear-cut averaged 3.3 ± 1.3 gC∙m−2∙d-1 (±1 SD), while average NEE at the undisturbed mature forest was close to zero (0.1 ± 1.9 gC∙m−2∙d-1). Differences in NEE were mainly governed by differences in gross primary productivity (GPP) between sites (7.0 ± 4.1 gC∙m−2∙d-1 and 4.1 ± 3.0 gC∙m−2∙d-1, for the undisturbed forest and clear-cut, respectively). Total ecosystem respiration (TER) did not significantly (p
Published: 2019
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28. FLUXNET-CH4: A global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands

Author: Kyle B. Delwiche, Sara Helen Knox, Avni Malhotra, Etienne Fluet-Chouinard, Gavin McNicol, Sarah Feron, Zutao Ouyang, Dario Papale, Carlo Trotta, Eleonora Canfora, You-Wei Cheah, Danielle Christianson, M. Carmelita R. Alberto, Pavel Alekseychik, Mika Aurela, Dennis Baldocchi, Sheel Bansal, David P. Billesbach, Gil Bohrer, Rosvel Bracho, Nina Buchmann, David I. Campbell, Gerardo Celis, Jiquan Chen, Weinan Chen, Housen Chu, Higo J. Dalmagro, Sigrid Dengel, Ankur R. Desai, Matteo Detto, Han Dolman, Elke Eichelmann, Eugenie Euskirchen, Daniela Famulari, Thomas Friborg, Kathrin Fuchs, Mathias Goeckede, Sébastien Gogo, Mangaliso J. Gondwe, Jordan P. Goodrich, Pia Gottschalk, Scott L. Graham, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S. Hemes, Takashi Hirano, David Hollinger, Lukas Hörtnagl, Hiroki Iwata, Adrien Jacotot, Joachim Jansen, Gerald Jurasinski, Minseok Kang, Kuno Kasak, John King, Janina Klatt, Franziska Koebsch, Ken W. Krauss, Derrick Y. F. Lai, Ivan Mammarella, Giovanni Manca, Luca Belelli Marchesini, Jaclyn Hatala Matthes, Trofim Maximon, Lutz Merbold, Bhaskar Mitra, Timothy H. Morin, Eiko Nemitz, Mats B. Nilsson, Shuli Niu, Walter C. Oechel, Patricia Y. Oikawa, Keisuke Ono, Matthias Peichl, Olli Peltola, Michele L. Reba, Andrew D. Richardson, William Riley, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Camilo Rey Sanchez, Edward A. Schuur, Karina V. R. Schäfer, Oliver Sonnentag, Jed P. Sparks, Ellen Stuart-Haëntjens, Cove Sturtevant, Ryan C. Sullivan, Daphne J. Szutu, Jonathan E. Thom, Margaret S. Torn, Eeva-Stiina Tuittila, Jessica Turner, Masahito Ueyama, Alex C. Valach, Rodrigo Vargas, Andrej Varlagin, Alma Vazquez-Lule, Joseph G. Verfaillie, Timo Vesala, George L. Vourlitis, Eric J. Ward, Christian Wille, Georg Wohlfahrt, Guan Xhuan Wong, Zhen Zhang, Donatella Zona, Lisamarie Windham-Myers, Benjamin Poulter, and Robert B. Jackson
Subjects: 13. Climate action, Settore BIO/07 - ECOLOGIA, 0211 other engineering and technologies, 021107 urban & regional planning, 02 engineering and technology, 15. Life on land, 010501 environmental sciences, 01 natural sciences, 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, including their seasonality, due to quasi-continuous and high temporal resolution of flux measurements, coincident measurements of carbon, water, and energy fluxes, 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 global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4- community-product/). 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 and because freshwater wetlands are a substantial source of total atmospheric CH4 emissions; and 3) 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 three days earlier, and the CH4 emission season lasts 4 days longer, for each degree C increase in mean annual air temperature. On average, the onset of increasing CH4 emissions lags soil warming by one 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). The FLUXNET-CH4 dataset provides an open-access resource for CH4 flux synthesis, has a range of applications, and is unique in that it includes coupled measurements of important CH4 drivers such as GPP and temperature. Although FLUXNET-CH4 could certainly be improved by adding more sites in tropical ecosystems and by increasing the number of site-years at existing sites, it is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH4 cycle. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4408468. Additionally, raw FLUXNET-CH4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/, and a complete list of the 79 individual site data DOIs is provided in Table 2 in the Data Availability section of this document., Earth System Science Data Discussions, ISSN:1866-3591
Published: 2021

29. Temperature thresholds of ecosystem respiration at a global scale

Author: Damien Bonal, Leonardo Montagnani, Andy Black, Beniamino Gioli, Jørgen E. Olesen, Fernando Moyano, Christian Brümmer, Changliang Shao, Chris Venditti, Jiří Dušek, Christopher M. Gough, Hiroki Ikawa, Ignacio Goded, Alessandro Cescatti, Alexander Graf, Nicola Arriga, Sebastian Wolf, Alice S. A. Johnston, William Woodgate, Vincenzo Magliulo, Andrew Meade, Peter D. Blanken, Hideki Kobayashi, Georg Wohlfahrt, Andrej Varlagin, Torsten Sachs, Rachhpal S. Jassal, Jonas Ardö, Torbern Tagesson, and Giovanni Manca
Subjects: Ecology, ecosystem respiration, Respiration, Ecosystem ecology, Eddy covariance, Temperature, Climate change, Carbon sink, Atmospheric sciences, Carbon Cycle, Carbon cycle, Soil, ddc:570, global scale, Environmental science, Ecosystem, Ecosystem respiration, Ecology, Evolution, Behavior and Systematics
Abstract: Ecosystem respiration is a major component of the global terrestrial carbon cycle and is strongly influenced by temperature. The global extent of the temperature-ecosystem respiration relationship, however, has not been fully explored. Here, we test linear and threshold models of ecosystem respiration across 210 globally distributed eddy covariance sites over an extensive temperature range. We find thresholds to the global temperature-ecosystem respiration relationship at high and low air temperatures and mid soil temperatures, which represent transitions in the temperature dependence and sensitivity of ecosystem respiration. Annual ecosystem respiration rates show a markedly reduced temperature dependence and sensitivity compared to half-hourly rates, and a single mid-temperature threshold for both air and soil temperature. Our study indicates a distinction in the influence of environmental factors, including temperature, on ecosystem respiration between latitudinal and climate gradients at short (half-hourly) and long (annual) timescales. Such climatological differences in the temperature sensitivity of ecosystem respiration have important consequences for the terrestrial net carbon sink under ongoing climate change.The authors test for temperature dependency of ecosystem respiration rates across globally distributed eddy covariance sites, revealing consistent temperature thresholds where ecosystem metabolism changes.
Published: 2021
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30. SoilTemp: A global database of near-surface temperature

Author: Juha M. Alatalo, Ilya M. D. Maclean, Ivan Nijs, Pascal Boeckx, Ronja E. M. Wedegärtner, Josefine Walz, Sergiy Medinets, Jonas Ardö, Martin Wilmking, Aníbal Pauchard, Onur Candan, Joseph Okello, Miguel Portillo-Estrada, Christian Rossi, Francesco Malfasi, Robert G. Björk, Tim Seipel, Pekka Niittynen, Kristoffer Hylander, Simone Cesarz, Michael B. Ashcroft, Dany Ghosn, T'Ai Gladys Whittingham Forte, Andrew D. Thomas, Nina Buchmann, Pavel Dan Turtureanu, Marcello Tomaselli, Martin Svátek, Luca Vitale, Christian Rixen, Valter Di Cecco, Pascal Vittoz, Jan Wild, Hans J. De Boeck, M. Rosa Fernández Calzado, Khatuna Gigauri, Haydn J.D. Thomas, Josef Brůna, Patrice Descombes, Robert Kanka, Roman Plichta, Julia Boike, Juan J. Jiménez, Mihai Pușcaș, James D. M. Speed, Tudor-Mihai Ursu, Maaike Y. Bader, Jian Zhang, Shengwei Zong, Marko Smiljanic, Ben Somers, Toke T. Høye, Martin Macek, Rebecca Finger Higgens, Jürgen Homeier, Fatih Fazlioglu, Ana Clara Mazzolari, Katja Tielbörger, Marek Čiliak, Sanne Govaert, Matěj Man, Loïc Pellissier, Bente J. Graae, Mana Gharun, Juan Lorite, Jhonatan Sallo Bravo, Thomas Scholten, Ian Klupar, Jonathan Lenoir, Martin Kopecký, Angela Stanisci, Joseph J. Bailey, Stuart W. Smith, Gergana N. Daskalova, Andrej Varlagin, Radim Matula, Meelis Pärtel, Ann Milbau, Peter Barančok, Jörg G. Stephan, Marijn Bauters, Jan Dick, Zuzana Sitková, Alistair S. Jump, Felix Gottschall, Fernando Moyano, Mario Trouillier, Filip Hrbáček, Eduardo Fuentes-Lillo, Nicoletta Cannone, Koenraad Van Meerbeek, Miska Luoto, Christopher Andrews, Charly Geron, Lisa J. Rew, Michael Stemkovski, Rafaella Canessa, Lucia Hederová, Peter Haase, Klaus Steinbauer, Keith W. Larson, Mats P. Björkman, Edoardo Cremonese, Lore T. Verryckt, Aud H. Halbritter, Jiri Dolezal, František Máliš, William D. Pearse, Zhaochen Zhang, Christian D. Larson, Sylvia Haider, Robert Weigel, Harald Pauli, Romina D. Dimarco, Nico Eisenhauer, Agustina Barros, Shyam S. Phartyal, Liesbeth van den Brink, Edmund W. Basham, Adrian V. Rocha, Mauro Guglielmin, Rafael A. García, Andrej Palaj, Josef Urban, Austin Koontz, Brett R. Scheffers, Mia Vedel Sørensen, Isla H. Myers-Smith, Camille Meeussen, Lena Muffler, Krystal Randall, Volodymyr I. Medinets, Sonia Merinero, Laurenz M. Teuber, Salvatore R. Curasi, José Luis Benito Alonso, Pieter De Frenne, Kamil Láska, Jonas Schmeddes, Martin A. Nuñez, Amanda Ratier Backes, Alessandro Petraglia, Miroslav Svoboda, Ellen Dorrepaal, Sonja Wipf, Juha Aalto, Masahito Ueyama, Benjamin Blonder, Jonas J. Lembrechts, Esther R. Frei, Lukas Siebicke, Bernard Heinesch, C. Johan Dahlberg, Juergen Kreyling, Camille Pitteloud, Florian Zellweger, Rebecca A. Senior, David H. Klinges, Miguel Ángel de Pablo, Elizabeth G. Simpson, George Kazakis, Jozef Kollár, Pallieter De Smedt, Olivier Roupsard, Jan Altman, Michele Carbognani, Julia Kemppinen, Manuela Winkler, Valeria Aschero, Pieter Vangansbeke, Andrea Lamprecht, Stef Haesen, University of Antwerp (UA), Finnish Meteorological Institute (FMI), Helsingin yliopisto = Helsingfors universitet = University of Helsinki, University of Wollongong [Australia], Australian Museum [Sydney], Universiteit Gent = Ghent University (UGENT), Institute of Botany of the Czech Academy of Sciences (IB / CAS), Czech Academy of Sciences [Prague] (CAS), Czech University of Life Sciences Prague (CZU), Ecologie et Dynamique des Systèmes Anthropisés - UMR CNRS 7058 (EDYSAN), Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS), University of Exeter, 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 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), LMI IESOL Intensification Ecologique des Sols Cultivés en Afrique de l’Ouest [Dakar] (IESOL), Institut de recherche pour le développement (IRD [Sénégal]), Universidad de Concepción - University of Concepcion [Chile], Instituto de Ecología y Biodiversidad (IEB), Universidad Adventista de Chile - Adventist University of Chile (UNACH), Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Qatar University, Norwegian University of Science and Technology [Trondheim] (NTNU), Norwegian University of Science and Technology (NTNU), Nanyang Technological University [Singapour], University of Gothenburg (GU), Universität Greifswald - University of Greifswald, Georg-August-University = Georg-August-Universität Göttingen, Martin-Luther-University Halle-Wittenberg, German Centre for Integrative Biodiversity Research (iDiv), Leipzig University, Mountains of the Moon University, Laboratory of Applied Physical Chemistry - ISOFYS (Gent, Belgium), Mendel University in Brno (MENDELU), Siberian Federal University (SibFU), Nalanda University, Hemvati Nandan Bahuguna Garhwal University (HNBGU), Babes-Bolyai University [Cluj-Napoca] (UBB), A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences [Moscow] (RAS), Instituto de Investigaciones Forestales y Agropecuarias Bariloche (IFAB), Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET)-Instituto Nacional de Tecnología Agropecuaria (INTA), University of Stirling, Umeå University, Istituto per i Sistemi Agricoli e Forestali del Mediterraneo (ISAFOM), National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), Dartmouth College [Hanover], University of Bergen (UiB), University of Notre Dame [Indiana] (UND), Utah State University (USU), Imperial College London, Arctic Research Centre [Aarhus] (ARC), Aarhus University [Aarhus], Universidad de Granada = University of Granada (UGR), Università degli studi di Parma = University of Parma (UNIPR), Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Stockholm University, University of South Bohemia, Aberystwyth University, York St John University, Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Chania (CIHEAM-IAMC), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM), Universidad de Alcalá - University of Alcalá (UAH), Montana State University (MSU), Lund University [Lund], Universitá degli Studi dell’Insubria = University of Insubria [Varese] (Uninsubria), Philipps Universität Marburg = Philipps University of Marburg, Università degli Studi del Molise = University of Molise (UNIMOL), Universidad Nacional de Cuyo [Mendoza] (UNCUYO), Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales [Mendoza] (CONICET-IANIGLA), Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET)-Universidad Nacional de Cuyo [Mendoza] (UNCUYO), Technical University in Zvolen (TUZVO), Georgian Institute of Public Affairs (GIPA), Austrian Academy of Sciences (OeAW), Universität für Bodenkultur Wien = University of Natural Resources and Life [Vienne, Autriche] (BOKU), Osaka Prefecture University, Instituto Nacional de Investigaciones en Biodiversidad y Medioambiente [Bariloche] (INIBIOMA-CONICET), Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET)-Universidad Nacional del Comahue [Neuquén] (UNCOMA), National Institute of Research and Development for Biological Sciences [Bucarest] (INCDSB), Université de Lausanne = University of Lausanne (UNIL), University of Tartu, Institute of Landscape Ecology of the Slovak Academy of Sciences, Slovak Academy of Sciences (SAS), Jolube Consultor Botánico, Northeast Normal University, Majella National Park - Parco Nazionale della Majella, National Forest Centre - Národné lesnícke centrum [Zvolen], University of Tübingen, County Administrative Board of Västra Götaland, Odessa National I.I.Mechnikov University, Research Institute for Nature and Forest (INBO), University of Edinburgh, University of California [Berkeley] (UC Berkeley), University of California (UC), Arizona State University [Tempe] (ASU), Swedish University of Agricultural Sciences (SLU), Gembloux Agro-Bio Tech [Gembloux], Université de Liège, Centre for Ecology and Hydrology [Bangor] (CEH), Natural Environment Research Council (NERC), Princeton University, Fundación Agencia Aragonesa para la Investigación y el Desarrollo (ARAID), Alfred Wegener Institute [Potsdam], Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Humboldt University Of Berlin, University of Florida [Gainesville] (UF), East China Normal University [Shangaï] (ECNU), Ordu University - Ordu Üniversitesi, Universidad Nacional de San Antonio Abad del Cusco (UNSAAC), Masaryk University [Brno] (MUNI), Aosta Valley Regional Environmental Protection Agency (ARPA), Senckenberg – Leibniz Institution for Biodiversity and Earth System Research - Senckenberg Gesellschaft für Naturforschung, Leibniz Association, Universität Duisburg-Essen = University of Duisburg-Essen [Essen], Swiss National Park - Parc Naziunal Svizzer, Universität Zürich [Zürich] = University of Zurich (UZH), ANR-19-CE32-0005,IMPRINT,IMpacts des PRocessus mIcroclimatiques sur la redistributioN de la biodiversiTé forestière en contexte de réchauffement du macroclimat(2019), University of Helsinki, Universiteit Gent = Ghent University [Belgium] (UGENT), Centre National de la Recherche Scientifique (CNRS)-Université de Picardie Jules Verne (UPJV), 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), Georg-August-University [Göttingen], Consiglio Nazionale delle Ricerche [Roma] (CNR), University of Granada [Granada], University of Parma = Università degli studi di Parma [Parme, Italie], Universitá degli Studi dell’Insubria, Philipps University of Marburg, Università degli Studi del Molise (Unimol), Universität für Bodenkultur Wien [Vienne, Autriche] (BOKU), University of Lausanne (UNIL), University of California [Berkeley], University of California, Humboldt-Universität zu Berlin, and University of Duisburg-Essen
Subjects: 0106 biological sciences, 010504 meteorology & atmospheric sciences, Biome, Biodiversity & Conservation, Microclimate, computer.software_genre, 01 natural sciences, topoclimate, Snow, HETEROGENEITY, SCALE, database, General Environmental Science, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, Global and Planetary Change, CLIMATE-CHANGE, Database, Ecology, Spatial database, Vegetation, Biological Sciences, Chemistry, soil climate, climate change, species distributions, Biodiversity Conservation, ecosystem processes, microclimate, temperature, Life Sciences & Biomedicine, Biologie, [SDE.MCG]Environmental Sciences/Global Changes, Climate change, Environmental Sciences & Ecology, [SDV.BID]Life Sciences [q-bio]/Biodiversity, MOISTURE, 010603 evolutionary biology, soil, LITTER DECOMPOSITION, species 19 distributions, Environmental Chemistry, DISTRIBUTIONS, SCALE SOIL, Biology, climate, Ecosystem, 0105 earth and related environmental sciences, Science & Technology, Global warming, SPECIES DISTRIBUTION MODELS, 15. Life on land, Radiative forcing, MACROCLIMATE, Agriculture and Soil Science, 13. Climate action, SNOW, Earth and Environmental Sciences, Environmental science, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, computer, Environmental Sciences
Abstract: Current analyses and predictions of spatially explicit patterns and processes in ecology most often rely on climate data interpolated from standardized weather stations. This interpolated climate data represents long-term average thermal conditions at coarse spatial resolutions only. Hence, many climate-forcing factors that operate at fine spatiotemporal resolutions are overlooked. This is particularly important in relation to effects of observation height (e.g. vegetation, snow and soil characteristics) and in habitats varying in their exposure to radiation, moisture and wind (e.g. topography, radiative forcing or cold-air pooling). Since organisms living close to the ground relate more strongly to these microclimatic conditions than to free-air temperatures, microclimatic ground and near-surface data are needed to provide realistic forecasts of the fate of such organisms under anthropogenic climate change, as well as of the functioning of the ecosystems they live in. To fill this critical gap, we highlight a call for temperature time series submissions to SoilTemp, a geospatial database initiative compiling soil and near-surface temperature data from all over the world. Currently, this database contains time series from 7,538 temperature sensors from 51 countries across all key biomes. The database will pave the way toward an improved global understanding of microclimate and bridge the gap between the available climate data and the climate at fine spatiotemporal resolutions relevant to most organisms and ecosystem processes. ispartof: GLOBAL CHANGE BIOLOGY vol:26 issue:11 pages:6616-6629 ispartof: location:England status: published
Published: 2020
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31. Sensitivity of gross primary productivity to climatic drivers during the summer drought of 2018 in Europe

Author: Philippe Ciais, Bingxue Wang, Zhaolei Li, Zheng Fu, Julia K. Green, Nadia Vendrame, Andrej Varlagin, Christian Brümmer, Louis Gourlez de la Motte, Ladislav Šigut, Caroline Vincke, Mana Gharun, Edoardo Cremonese, Matthias Cuntz, Nina Buchmann, Ana Bastos, Hui Yang, Alexander Knohl, Kailiang Yu, Paul C. Stoy, Yuanyuan Huang, Tarek S. El-Madany, Franziska Koebsch, Marilyn Roland, Nicola Arriga, Matthias Peichl, Silvano Fares, Mirco Migliavacca, E. Magliulo, Andrea Pitacco, 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), ICOS-ATC (ICOS-ATC), 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)-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), Ludwig-Maximilians-Universität München (LMU), SILVA (SILVA), AgroParisTech-Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), European Research Council Synergy project SyG-2013-610028 IMBALANCE-PFrench National Research Agency (ANR) National Science Foundation (NSF)1552976Alexander von Humboldt Foundation Swiss National Science Foundation project ICOS-CH Phase 2 20FI20_173691Russian Foundation for Basic Research (RFBR)19-04-01234-asuccessive European projects European regional development programmes Region Grand-Est French National Research Agency (ANR) SOERE F-ORE-T ADEME INRA Department of Forest, Grassland and Freshwater Ecology University of Padova CDPA148553project VitiSOM LIFE15 ENV/IT/000392FWO Ministry of Education, Youth and Sports of the Czech Republic within the CzeCOS program LM2015061SustES-Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions CZ.02.1.01/0.0/0.0/16_019/0000797European regional development programs French National Research Agency (ANR)ANR-11-LABX-0002-01, Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), European Research Council Synergy project SyG-2013-610028 IMBALANCE-PNational Science Foundation (NSF)1552976Alexander von Humboldt Foundation Swiss National Science Foundation project ICOS-CH Phase 2 20FI20_173691Russian Foundation for Basic Research (RFBR)19-04-01234-asuccessive European projects European regional development programmes Region Grand-Est SOERE F-ORE-T ADEME INRA Department of Forest, Grassland and Freshwater Ecology University of Padova CDPA148553project VitiSOM LIFE15 ENV/IT/000392FWO Ministry of Education, Youth and Sports of the Czech Republic within the CzeCOS program LM2015061SustES-Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions CZ.02.1.01/0.0/0.0/16_019/0000797European regional development programs, ANR-11-LABX-0002,ARBRE,Recherches Avancées sur l'Arbre et les Ecosytèmes Forestiers(2011), and UCL - SST/ELI/ELIE - Environmental Sciences
Subjects: 0106 biological sciences, 010504 meteorology & atmospheric sciences, Climate Change, Biome, evapotranspiration, Eddy covariance, Genetics and Molecular Biology, drought, Forests, Atmospheric sciences, 010603 evolutionary biology, 01 natural sciences, General Biochemistry, Genetics and Molecular Biology, Gross primary productivity, primary productivity, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, Ecosystem carbon, eddy covariance, climate change, Sensitivity (control systems), [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Water content, Biology, Plant Physiological Phenomena, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Atmosphere, gross primary productivity, sensitivity, Europe, soil moisture, Articles, 15. Life on land, Grassland, Droughts, 13. Climate action, General Biochemistry, [SDE]Environmental Sciences, Environmental science, climatic drivers, Seasons, Human medicine, General Agricultural and Biological Sciences
Abstract: In summer 2018, Europe experienced a record drought, but it remains unknown how the drought affected ecosystem carbon dynamics. Using observations from 34 eddy covariance sites in different biomes across Europe, we studied the sensitivity of gross primary productivity (GPP) to environmental drivers during the summer drought of 2018 versus the reference summer of 2016. We found a greater drought-induced decline of summer GPP in grasslands (−38%) than in forests (−10%), which coincided with reduced evapotranspiration and soil water content (SWC). As compared to the ‘normal year’ of 2016, GPP in different ecosystems exhibited more negative sensitivity to summer air temperature (Ta) but stronger positive sensitivity to SWC during summer drought in 2018, that is, a stronger reduction of GPP with soil moisture deficit. We found larger negative effects of Ta and vapour pressure deficit (VPD) but a lower positive effect of photosynthetic photon flux density on GPP in 2018 compared to 2016, which contributed to reduced summer GPP in 2018. Our results demonstrate that high temperature-induced increases in VPD and decreases in SWC aggravated drought impacts on GPP. This article is part of the theme issue ‘Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale’., Philosophical Transactions of the Royal Society B: Biological Sciences, 375 (1810), ISSN:0962-8436, ISSN:1471-2970, ISSN:0080-4622
Published: 2020
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32. The biophysical climate mitigation potential of boreal peatlands during the growing season

Author: Mats Nilsson, Alan G. Barr, Mika Aurela, Trofim C. Maximov, Elena D. Lapshina, Jiquan Chen, Hiroki Iwata, Philip Marsh, Masahito Ueyama, Silvie Harder, Christopher Schulze, Elyn Humphreys, Pavel Alekseychik, Martin Wilmking, Brian D. Amiro, Ivan Mammarella, Daniel F. Nadeau, Annalea Lohila, Lawrence B. Flanagan, T. Andrew Black, Juha-Pekka Tuovinen, Hiroki Ikawa, Eugénie S. Euskirchen, Manuel Helbig, Benjamin R. K. Runkle, Achim Grelle, Ankur R. Desai, Ian B. Strachan, Michelle Garneau, Allison L. Dunn, Richard M. Petrone, Eeva-Stiina Tuittila, Pierre-Erik Isabelle, Matthias Peichl, Mika Korkiakoski, Thomas Friborg, Rachhpal S. Jassal, Juliya Kurbatova, Paul A. Moore, Erin M. Nicholls, William L. Quinton, Pierre Taillardat, Anatoly S. Prokushkin, Sean K. Carey, Oliver Sonnentag, Lars Kutzbach, Jinshu Chi, Vyacheslav Zyrianov, Anders Lindroth, Jessica Turner, Michal Heliasz, Timo Vesala, Mikaell Ottosson Löfvenius, James M. Waddington, Takeshi Ohta, Andrej Varlagin, Nigel T. Roulet, Institute for Atmospheric and Earth System Research (INAR), Micrometeorology and biogeochemical cycles, Biosciences, Viikki Plant Science Centre (ViPS), and Ecosystem processes (INAR Forest Sciences)
Subjects: Peat, 010504 meteorology & atmospheric sciences, Vapour Pressure Deficit, IMPACT, STOMATAL CONDUCTANCE, Climate change, Growing season, 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, CARBON, boreal forest, peatlands, 1172 Environmental sciences, 0105 earth and related environmental sciences, General Environmental Science, RESTORATION, LAND-COVER CHANGE, 4112 Forestry, climate mitigation, Renewable Energy, Sustainability and the Environment, SURFACE CONDUCTANCE, regional climate, Taiga, Global warming, Public Health, Environmental and Occupational Health, PERMAFROST THAW, NORTH-AMERICA, 15. Life on land, FOREST, Subarctic climate, energy balance, Boreal, 13. Climate action, Environmental science, ENERGY-BALANCE
Abstract: Peatlands and forests cover large areas of the boreal biome and are critical for global climate regulation. They also regulate regional climate through heat and water vapour exchange with the atmosphere. Understanding how land-atmosphere interactions in peatlands differ from forests may therefore be crucial for modelling boreal climate system dynamics and for assessing climate benefits of peatland conservation and restoration. To assess the biophysical impacts of peatlands and forests on peak growing season air temperature and humidity, we analysed surface energy fluxes and albedo from 35 peatlands and 37 evergreen needleleaf forests-the dominant boreal forest type-and simulated air temperature and vapour pressure deficit (VPD) over hypothetical homogeneous peatland and forest landscapes. We ran an evapotranspiration model using land surface parameters derived from energy flux observations and coupled an analytical solution for the surface energy balance to an atmospheric boundary layer (ABL) model. We found that peatlands, compared to forests, are characterized by higher growing season albedo, lower aerodynamic conductance, and higher surface conductance for an equivalent VPD. This combination of peatland surface properties results in a similar to 20% decrease in afternoon ABL height, a cooling (from 1.7 to 2.5 degrees C) in afternoon air temperatures, and a decrease in afternoon VPD (from 0.4 to 0.7 kPa) for peatland landscapes compared to forest landscapes. These biophysical climate impacts of peatlands are most pronounced at lower latitudes (similar to 45 degrees N) and decrease toward the northern limit of the boreal biome (similar to 70 degrees N). Thus, boreal peatlands have the potential to mitigate the effect of regional climate warming during the growing season. The biophysical climate mitigation potential of peatlands needs to be accounted for when projecting the future climate of the boreal biome, when assessing the climate benefits of conserving pristine boreal peatlands, and when restoring peatlands that have experienced peatland drainage and mining.
Published: 2020
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33. Supplementary material to 'Global transpiration data from sap flow measurements: the SAPFLUXNET database'

Author: Rafael Poyatos, Víctor Granda, Víctor Flo, Mark A. Adams, Balázs Adorján, David Aguadé, Marcos P.M. Aidar, Scott Allen, M. Susana Alvarado-Barrientos, Kristina J. Anderson-Teixeira, Luiza Maria Aparecido, M. Altaf Arain, Ismael Aranda, Heidi Asbjornsen, Robert Baxter, Eric Beamesderfer, Z. Carter Berry, Daniel Berveiller, Bethany Blakely, Johnny Boggs, Gil Bohrer, Paul V. Bolstad, Damien Bonal, Rosvel Bracho, Patricia Brito, Jason Brodeur, Fernando Casanoves, Jérôme Chave, Hui Chen, Cesar Cisneros, Kenneth Clark, Edoardo Cremonese, Jorge S. David, Teresa S. David, Nicolas Delpierre, Ankur R. Desai, Frederic C. Do, Michal Dohnal, Jean-Christophe Domec, Sebinasi Dzikiti, Colin Edgar, Rebekka Eichstaedt, Tarek S. El-Madany, Jan Elbers, Cleiton B. Eller, Eugénie S. Euskirchen, Brent Ewers, Patrick Fonti, Alicia Forner, David I. Forrester, Helber C. Freitas, Marta Galvagno, Omar Garcia-Tejera, Chandra Prasad Ghimire, Teresa E. Gimeno, John Grace, André Granier, Anne Griebel, Yan Guangyu, Mark B. Gush, Paul Hanson, Niles J. Hasselquist, Ingo Heinrich, Virginia Hernandez-Santana, Valentine Herrmann, Teemu Hölttä, Friso Holwerda, Dang Hongzhong, James Irvine, Supat Isarangkool Na Ayutthaya, Paul G. Jarvis, Hubert Jochheim, Carlos A. Joly, Julia Kaplick, Hyun Seok Kim, Leif Klemedtsson, Heather Kropp, Fredrik Lagergren, Patrick Lane, Petra Lang, Andrei Lapenas, Víctor Lechuga, Minsu Lee, Christoph Leuschner, Jean-Marc Limousin, Juan Carlos Linares, Maj-Lena Linderson, Andres Lindroth, Pilar Llorens, Álvaro López-Bernal, Michael M. Loranty, Dietmar Lüttschwager, Cate Macinnis-Ng, Isabelle Maréchaux, Timothy A. Martin, Ashley Matheny, Nate McDowell, Sean McMahon, Patrick Meir, Ilona Mészáros, Mirco Migliavacca, Patrick Mitchell, Meelis Mölder, Leonardo Montagnani, Georgianne W. Moore, Ryogo Nakada, Furong Niu, Rachael H. Nolan, Richard Norby, Kimberly Novick, Walter Oberhuber, Nikolaus Obojes, Christopher A. Oishi, Rafael S. Oliveira, Ram Oren, Jean-Marc Ourcival, Teemu Paljakka, Oscar Perez-Priego, Pablo L. Peri, Richard L. Peters, Sebastian Pfautsch, William T. Pockman, Yakir Preisler, Katherine Rascher, George Robinson, Humberto Rocha, Alain Rocheteau, Alexander Röll, Bruno Rosado, Lucy Rowland, Alexey V. Rubtsov, Santiago Sabaté, Yann Salmon, Roberto L. Salomón, Elisenda Sánchez-Costa, Karina V. R. Schäfer, Bernhard Schuldt, Alexandr Shashkin, Clément Stahl, Marko Stojanović, Juan Carlos Suárez, Ge Sun, Justyna Szatniewska, Fyodor Tatarinov, Miroslav Tesař, Frank M. Thomas, Pantana Tor-ngern, Josef Urban, Fernando Valladares, Christiaan van der Tol, Ilja van Meerveld, Andrej Varlagin, Holm Voigt, Jeffrey Warren, Christiane Werner, Willy Werner, Gerhard Wieser, Lisa Wingate, Stan Wullschleger, Koong Yi, Roman Zweifel, Kathy Steppe, Maurizio Mencuccini, and Jordi Martínez-Vilalta
Published: 2020
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34. Ecosystem transpiration and evaporation: insights from three water flux partitioning methods across FLUXNET sites

Author: T. Andrew Black, Kathrin Fuchs, Beniamino Gioli, Rafael Poyatos, Ankur R. Desai, Ulrich Weber, Georg Wohlfahrt, Ladislav Šigut, Sebastian Wolf, Damien Bonal, Jean-Marc Limousin, Simon Besnard, Eugénie Paul-Limoges, Mana Gharun, Jacob A. Nelson, Sha Zhou, Markus Reichstein, Daniel Berveiller, Teresa E. Gimeno, Vincenzo Magliulo, Nicolas Delpierre, Nuno Carvalhais, Ivan Mammarella, Peter D. Blanken, Martin Jung, Oscar Perez-Priego, Leonardo Montagnani, Yao Zhang, Luca Belelli Marchesini, Alexander Knohl, Damiano Gianelle, Andrej Varlagin, Russell L. Scott, Mirco Migliavacca, Lukas Siebicke, Lukas Hörtnagl, Department of Biogeochemical Integration [Jena], Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft-Max-Planck-Gesellschaft, Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-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 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), SILVA (SILVA), AgroParisTech-Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Ecologie Systématique et Evolution (ESE), AgroParisTech-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ANR-11-LABX-0002,ARBRE,Recherches Avancées sur l'Arbre et les Ecosytèmes Forestiers(2011), ANR-10-LABX-0025,CEBA,CEnter of the study of Biodiversity in Amazonia(2010), FWF, Austrian National Science Fund, Ministry of Education, Youth and Sports of the Czech Republic, Swiss National Science Foundation, ChinaFlux, INAR Physics, Micrometeorology and biogeochemical cycles, Macquarie University, Lamont-Doherty Earth Observatory (LDEO), Columbia University [New York], CREAF - Centre for Ecological Research and Applied Forestries, Universitat Autònoma de Barcelona (UAB), University of Colorado [Colorado Springs] (UCCS), University of the Basque Country/Euskal Herriko Unibertsitatea (UPV/EHU), Ikerbasque - Basque Foundation for Science, Leopold Franzens Universität Innsbruck - University of Innsbruck, University of Wisconsin-Madison, Institute for BioEconomy [Sesto Fiorentino] (IBE | CNR), National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), 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, 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), Universität Zürich [Zürich] = University of Zurich (UZH), USDA-ARS : Agricultural Research Service, Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Fondazione Edmund Mach - Edmund Mach Foundation [Italie] (FEM), Agrarian and Technological Institute, Peoples Friendship University of Russia [RUDN University] (RUDN), Global Change Research Centre (CzechGlobe), Helsingin yliopisto = Helsingfors universitet = University of Helsinki, University of British Columbia (UBC), Istituto per i Sistemi Agricoli e Forestali del Mediterraneo (ISAFOM), Max-Planck-Gesellschaft, Wageningen University and Research [Wageningen] (WUR), Universidade Nova de Lisboa = NOVA University Lisbon (NOVA), University of Zurich, and Nelson, Jacob A
Subjects: 0106 biological sciences, 010504 meteorology & atmospheric sciences, Vapour Pressure Deficit, Rain, FLUXNET, Eddy covariance, evapotranspiration, 2306 Global and Planetary Change, Atmospheric sciences, Poaceae, 01 natural sciences, 114 Physical sciences, ecohydrology, transpiration, evaporation, 2300 General Environmental Science, Soil, FluxNet, Laboratory of Geo-information Science and Remote Sensing, Evapotranspiration, Ecohydrology, Settore BIO/07 - ECOLOGIA, ddc:550, eddy covariance, Environmental Chemistry, Laboratorium voor Geo-informatiekunde en Remote Sensing, 910 Geography & travel, Leaf area index, Ecosystem, 0105 earth and related environmental sciences, General Environmental Science, Transpiration, Global and Planetary Change, Ecology, Water, Plant Transpiration, 15. Life on land, Earth sciences, 10122 Institute of Geography, 13. Climate action, 2304 Environmental Chemistry, [SDE]Environmental Sciences, Environmental science, Spatial variability, 2303 Ecology, 010606 plant biology & botany
Abstract: We apply and compare three widely applicable methods for estimating ecosystem transpiration (T) from eddy covariance (EC) data across 251 FLUXNET sites globally. All three methods are based on the coupled water and carbon relationship, but they differ in assumptions and parameterizations. Intercomparison of the three daily T estimates shows high correlation among methods (R between .89 and .94), but a spread in magnitudes of T/ET (evapotranspiration) from 45% to 77%. When compared at six sites with concurrent EC and sap flow measurements, all three EC‐based T estimates show higher correlation to sap flow‐based T than EC‐based ET. The partitioning methods show expected tendencies of T/ET increasing with dryness (vapor pressure deficit and days since rain) and with leaf area index (LAI). Analysis of 140 sites with high‐quality estimates for at least two continuous years shows that T/ET variability was 1.6 times higher across sites than across years. Spatial variability of T/ET was primarily driven by vegetation and soil characteristics (e.g., crop or grass designation, minimum annual LAI, soil coarse fragment volume) rather than climatic variables such as mean/standard deviation of temperature or precipitation. Overall, T and T/ET patterns are plausible and qualitatively consistent among the different water flux partitioning methods implying a significant advance made for estimating and understanding T globally, while the magnitudes remain uncertain. Our results represent the first extensive EC data‐based estimates of ecosystem T permitting a data‐driven perspective on the role of plants’ water use for global water and carbon cycling in a changing climate. We acknowledge insightful discussions with Dario Papale and apologize for having a cappuccino after lunch. We further acknowledge Ulrich Weber for preparing the cappuccino. M.G. acknowledges funding by Swiss National Science Foundation project ICOS‐CH Phase 2 20FI20_173691. L.Š. was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the CzeCOS program, grant number LM2015061, and by SustES‐Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16_019/0000797). G.W. acknowledges support by the Austrian National Science Fund (FWF, project I03859) and the Province of South Tyrol (“Cycling of carbon and water in mountain ecosystems under changing climate and land use”). R.P. was supported by grants CGL2014‐55883‐JIN, RTI2018‐095297‐J‐I00 (Spain), and by a Humboldt Research Fellowship for Experienced Researchers (Germany). This work used eddy covariance data acquired and shared by the FLUXNET community, including these networks: Ameri‐Flux, AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet‐Canada, GreenGrass, ICOS, KoFlux, LBA, NECC, OzFlux‐TERN, TCOS‐Siberia, and USCCC. The ERA‐Interim reanalysis data are provided by ECMWF and processed by LSCE. The FLUXNET eddy covariance data processing and harmonization was carried out by the European Fluxes Database Cluster, AmeriFlux Management Project, and Fluxdata project of FLUXNET, with the support of CDIAC and ICOS Ecosystem Thematic Center, and the OzFlux, ChinaFlux, and AsiaFlux offices. Open access funding enabled and organized by Projekt DEAL.
Published: 2020
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35. Inferring CO2 fertilization effect based on global monitoring land-atmosphere exchange with a theoretical model

Author: Satoru Takanashi, Eugénie S. Euskirchen, Masahito Ueyama, Takanori Shimizu, Yoshiko Kosugi, Tomo'omi Kumagai, Luca Belelli Marchesini, Joon Kim, Kentaro Takagi, Keisuke Ono, M. Syndonia Bret-Harte, Andrej Varlagin, Kazuhito Ichii, Yojiro Matsuura, Dennis D. Baldocchi, Minseok Kang, Yasuko Mizoguchi, Takashi Hirano, Lutz Merbold, Hideki Kobayashi, Jason Beringer, Takeshi Ohta, Yukio Yasuda, Takashi Machimura, and Taku M. Saitoh
Subjects: CO2 fertilization effect, geography, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, Evapotranspiration, Settore AGR/05 - ASSESTAMENTO FORESTALE E SELVICOLTURA, Renewable Energy, Sustainability and the Environment, Public Health, Environmental and Occupational Health, Eddy covariance, 010501 environmental sciences, Photosynthesis, Atmospheric sciences, 01 natural sciences, Sink (geography), Human fertilization, Environmental science, Ecosystem, Water vapor, 0105 earth and related environmental sciences, General Environmental Science, Transpiration, Sun/shade model
Abstract: Rising atmospheric CO2 concentration ([CO2]) enhances photosynthesis and reduces transpiration at the leaf, ecosystem, and global scale via the CO2 fertilization effect. The CO2 fertilization effect is among the most important processes for predicting the terrestrial carbon budget and future climate, yet it has been elusive to quantify. For evaluating the CO2 fertilization effect on land photosynthesis and transpiration, we developed a technique that isolated this effect from other confounding effects, such as changes in climate, using a noisy time series of observed land-atmosphere CO2 and water vapor exchange. Here, we evaluate the magnitude of this effect from 2000 to 2014 globally based on constraint optimization of gross primary productivity (GPP) and evapotranspiration in a canopy photosynthesis model over 104 global eddy-covariance stations. We found a consistent increase of GPP (0.138 ± 0.007% ppm−1; percentile per rising ppm of [CO2]) and a concomitant decrease in transpiration (−0.073% ± 0.006% ppm−1) due to rising [CO2]. Enhanced GPP from CO2 fertilization after the baseline year 2000 is, on average, 1.2% of global GPP, 12.4 g C m−2 yr−1 or 1.8 Pg C yr−1 at the years from 2001 to 2014. Our result demonstrates that the current increase in [CO2] could potentially explain the recent land CO2 sink at the global scale.
Published: 2020

36. 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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37. New data-driven estimation of terrestrial CO2 fluxes in Asia using a standardized database of eddy covariance measurements, remote sensing data, and support vector regression

Author: Yiping Zhang, Lutz Merbold, Yoshiko Kosugi, Taku M. Saitoh, Nobuko Saigusa, Yukio Yasuda, Takashi Machimura, Masahito Ueyama, Akira Miyata, Jonas Ardö, Hideki Kobayashi, Ayumi Kotani, Takeshi Ohta, Luca Belelli Marchesini, Fenghua Zhao, Yojiro Matsuura, Kenzo Kitamura, Eugénie S. Euskirchen, M. C. R. Alberto, Kireet Kumar, Masayuki Kondo, Andrej Varlagin, Yuji Yanagi, Joon Kim, Kentaro Takagi, Sandipan Mukherjee, M. Syndonia Bret-Harte, Yasuko Mizoguchi, Takashi Hirano, Kazuhito Ichii, Shenggong Li, Minseok Kang, Joanna Joiner, and Earth and Climate
Subjects: upscaling, Atmospheric Science, data-driven model, Asia, 010504 meteorology & atmospheric sciences, Eddy covariance, Soil Science, Aquatic Science, computer.software_genre, 01 natural sciences, remote sensing, eddy covariance data, East Asia, Ecosystem, 0105 earth and related environmental sciences, Water Science and Technology, Remote sensing, Ecology, Database, Paleontology, Forestry, 04 agricultural and veterinary sciences, Vegetation, Greenhouse gas, Climatology, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science, Satellite, Terrestrial ecosystem, terrestrial CO flux, Scale (map), computer
Abstract: The lack of a standardized database of eddy covariance observations has been an obstacle for data-driven estimation of terrestrial CO2 fluxes in Asia. In this study, we developed such a standardized database using 54 sites from various databases by applying consistent postprocessing for data-driven estimation of gross primary productivity (GPP) and net ecosystem CO2 exchange (NEE). Data-driven estimation was conducted by using a machine learning algorithm: support vector regression (SVR), with remote sensing data for 2000 to 2015 period. Site-level evaluation of the estimated CO2 fluxes shows that although performance varies in different vegetation and climate classifications, GPP and NEE at 8 days are reproduced (e.g., r2 = 0.73 and 0.42 for 8 day GPP and NEE). Evaluation of spatially estimated GPP with Global Ozone Monitoring Experiment 2 sensor-based Sun-induced chlorophyll fluorescence shows that monthly GPP variations at subcontinental scale were reproduced by SVR (r2 = 1.00, 0.94, 0.91, and 0.89 for Siberia, East Asia, South Asia, and Southeast Asia, respectively). Evaluation of spatially estimated NEE with net atmosphere-land CO2 fluxes of Greenhouse Gases Observing Satellite (GOSAT) Level 4A product shows that monthly variations of these data were consistent in Siberia and East Asia; meanwhile, inconsistency was found in South Asia and Southeast Asia. Furthermore, differences in the land CO2 fluxes from SVR-NEE and GOSAT Level 4A were partially explained by accounting for the differences in the definition of land CO2 fluxes. These data-driven estimates can provide a new opportunity to assess CO2 fluxes in Asia and evaluate and constrain terrestrial ecosystem models.
Published: 2017
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38. Winter respiratory C losses provide explanatory power for net ecosystem productivity

Author: Leonardo Montagnani, Marian Pavelka, Mart-Jan Schelhaas, Andrej Varlagin, A A Rodrigues, Riccardo Valentini, J. H. McCaughey, Fredrik Lagergren, Alexander Knohl, Michal V. Marek, Cécile Vincke, Bernard Heinesch, Christian Bernhofer, M. J. Sanz Sánchez, Werner Eugster, Mathias Herbst, Janusz Olejnik, Marek Urbaniak, Jian Wu, Andreas Ibrom, Stefano Minerbi, Kateřina Havránková, Timo Vesala, Arnaud Carrara, Giorgio Matteucci, Gabriel Pita, S. Zielis, Matthias Haeni, Kim Pilegaard, Eddy Moors, Arthur Gessler, Roman Zweifel, Thomas Grünwald, Nina Buchmann, and Beverly E. Law
Subjects: 0106 biological sciences, Atmospheric Science, 010504 meteorology & atmospheric sciences, Ecology, Paleontology, Soil Science, Carbon sink, Climate change, Forestry, Context (language use), 15. Life on land, Aquatic Science, Evergreen, Temperate deciduous forest, 01 natural sciences, 13. Climate action, Climatology, Forest ecology, Temperate climate, Environmental science, Ecosystem, Physical geography, 010606 plant biology & botany, 0105 earth and related environmental sciences, Water Science and Technology
Abstract: Accurate predictions of net ecosystem productivity (NEPc) of forest ecosystems are essential for climate change decisions and requirements in the context of national forest growth and greenhouse gas inventories. However, drivers and underlying mechanisms determining NEPc (e.g., climate and nutrients) are not entirely understood yet, particularly when considering the influence of past periods. Here we explored the explanatory power of the compensation day (cDOY)-defined as the day of year when winter net carbon losses are compensated by spring assimilation-for NEPc in 26 forests in Europe, North America, and Australia, using different NEPc integration methods. We found cDOY to be a particularly powerful predictor for NEPc of temperate evergreen needleleaf forests (R2=0.58) and deciduous broadleaf forests (R2=0.68). In general, the latest cDOY correlated with the lowest NEPc. The explanatory power of cDOY depended on the integration method for NEPc, forest type, and whether the site had a distinct winter net respiratory carbon loss or not. The integration methods starting in autumn led to better predictions of NEPc from cDOY then the classical calendar method starting 1 January. Limited explanatory power of cDOY for NEPc was found for warmer sites with no distinct winter respiratory loss period. Our findings highlight the importance of the influence of winter processes and the delayed responses of previous seasons' climatic conditions on current year's NEPc. Such carry-over effects may contain information from climatic conditions, carbon storage levels, and hydraulic traits of several years back in time. (Less)
Published: 2017
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39. Supplementary material to 'Carbon / nitrogen interactions in European forests and semi-natural vegetation. Part I: Fluxes and budgets of carbon, nitrogen and greenhouse gases from ecosystem monitoring and modelling'

Author: Chris R. Flechard, Andreas Ibrom, Ute M. Skiba, Wim de Vries, Marcel van Oijen, David R. Cameron, Nancy B. Dise, Janne F. J. Korhonen, Nina Buchmann, Arnaud Legout, David Simpson, Maria J. Sanz, Marc Aubinet, Denis Loustau, Leonardo Montagnani, Johan Neirynck, Ivan A. Janssens, Mari Pihlatie, Ralf Kiese, Jan Siemens, André-Jean Francez, Jürgen Augustin, Andrej Varlagin, Janusz Olejnik, Radosław Juszczak, Mika Aurela, Bogdan H. Chojnicki, Ulrich Dämmgen, Vesna Djuricic, Julia Drewer, Werner Eugster, Yannick Fauvel, David Fowler, Arnoud Frumau, André Granier, Patrick Gross, Yannick Hamon, Carole Helfter, Arjan Hensen, László Horváth, Barbara Kitzler, Bart Kruijt, Werner L. Kutsch, Raquel Lobo-do-Vale, Annalea Lohila, Bernard Longdoz, Michal V. Marek, Giorgio Matteucci, Marta Mitosinkova, Virginie Moreaux, Albrecht Neftel, Jean-Marc Ourcival, Kim Pilegaard, Gabriel Pita, Francisco Sanz, Jan K. Schjoerring, Maria-Teresa Sebastià, Y. Sim Tang, Hilde Uggerud, Marek Urbaniak, Netty van Dijk, Timo Vesala, Sonja Vidic, Caroline Vincke, Tamás Weidinger, Sophie Zechmeister-Boltenstern, Klaus Butterbach-Bahl, Eiko Nemitz, and Mark A. Sutton
Published: 2019
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40. Carbon / nitrogen interactions in European forests and semi-natural vegetation. Part II: Untangling climatic, edaphic, management and nitrogen deposition effects on carbon sequestration potentials

Author: Chris R. Flechard, Marcel van Oijen, David R. Cameron, Wim de Vries, Andreas Ibrom, Nina Buchmann, Nancy B. Dise, Ivan A. Janssens, Johan Neirynck, Leonardo Montagnani, Andrej Varlagin, Denis Loustau, Arnaud Legout, Klaudia Ziemblińska, Marc Aubinet, Mika Aurela, Bogdan H. Chojnicki, Julia Drewer, Werner Eugster, André-Jean Francez, Radosław Juszczak, Barbara Kitzler, Werner L. Kutsch, Annalea Lohila, Bernard Longdoz, Giorgio Matteucci, Virginie Moreaux, Albrecht Neftel, Janusz Olejnik, Maria J. Sanz, Jan Siemens, Timo Vesala, Caroline Vincke, Eiko Nemitz, Sophie Zechmeister-Boltenstern, Klaus Butterbach-Bahl, Ute M. Skiba, and Mark A. Sutton
Subjects: 0106 biological sciences, 010504 meteorology & atmospheric sciences, 13. Climate action, 010604 marine biology & hydrobiology, 15. Life on land, 01 natural sciences, 0105 earth and related environmental sciences
Abstract: The effects of atmospheric nitrogen deposition (Ndep) on carbon (C) sequestration in forests have often been assessed by relating differences in productivity to spatial variations of Ndep across a large geographic domain. These correlations generally suffer from covariation of other confounding variables related to climate and other growth-limiting factors, as well as large uncertainties in total (dry + wet) reactive nitrogen (Nr) deposition. We propose a methodology for untangling the effects of Ndep from those of meteorological variables, soil water retention capacity and stand age, using a mechanistic forest growth model in combination with eddy covariance CO2 exchange fluxes from a Europe-wide network of forest flux towers. Total Nr deposition rates were estimated from local measurements as far as possible. The forest data were compared with data from natural or semi-natural, non-woody vegetation sites. The carbon sequestration response of forests to nitrogen deposition (dC / dN) was estimated after accounting for the effects of the co-correlates by means of a meta-modelling standardization procedure, which resulted in a reduction by a factor of about 2 of the uncorrected, apparent dC / dN value. This model-enhanced analysis of the C and Ndep flux observations at the scale of the European network suggests a mean overall dC / dN response of forest lifetime C sequestration to Ndep of the order of 40–50 g (C) g−1 (N), which is slightly larger but not significantly different from the range of estimates published in the most recent reviews. Importantly, patterns of gross primary and net ecosystem productivity versus Ndep were non-linear, with no further responses at high Ndep levels (Ndep > 2.5–3 g (N) m−2 yr−1) partly due to large ecosystem N losses by leaching and gaseous emissions. The reduced increase in productivity per unit N deposited at high Ndep levels implies that the forecast increased Nr emissions and increased Ndep levels in large areas of Asia may not positively impact the continent's forest CO2 sink. The large level of unexplained variability in observed carbon sequestration efficiency (CSE) across sites further adds to the uncertainty in the dC / dN response.
Published: 2019
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41. Supplementary material to 'Carbon / nitrogen interactions in European forests and semi-natural vegetation. Part II: Untangling climatic, edaphic, management and nitrogen deposition effects on carbon sequestration potentials'

Author: Chris R. Flechard, Marcel van Oijen, David R. Cameron, Wim de Vries, Andreas Ibrom, Nina Buchmann, Nancy B. Dise, Ivan A. Janssens, Johan Neirynck, Leonardo Montagnani, Andrej Varlagin, Denis Loustau, Arnaud Legout, Klaudia Ziemblińska, Marc Aubinet, Mika Aurela, Bogdan H. Chojnicki, Julia Drewer, Werner Eugster, André-Jean Francez, Radosław Juszczak, Barbara Kitzler, Werner L. Kutsch, Annalea Lohila, Bernard Longdoz, Giorgio Matteucci, Virginie Moreaux, Albrecht Neftel, Janusz Olejnik, Maria J. Sanz, Jan Siemens, Timo Vesala, Caroline Vincke, Eiko Nemitz, Sophie Zechmeister-Boltenstern, Klaus Butterbach-Bahl, Ute M. Skiba, and Mark A. Sutton
Published: 2019
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42. Carbon / nitrogen interactions in European forests and semi-natural vegetation. Part I: Fluxes and budgets of carbon, nitrogen and greenhouse gases from ecosystem monitoring and modelling

Author: Chris R. Flechard, Andreas Ibrom, Ute M. Skiba, Wim de Vries, Marcel van Oijen, David R. Cameron, Nancy B. Dise, Janne F. J. Korhonen, Nina Buchmann, Arnaud Legout, David Simpson, Maria J. Sanz, Marc Aubinet, Denis Loustau, Leonardo Montagnani, Johan Neirynck, Ivan A. Janssens, Mari Pihlatie, Ralf Kiese, Jan Siemens, André-Jean Francez, Jürgen Augustin, Andrej Varlagin, Janusz Olejnik, Radosław Juszczak, Mika Aurela, Bogdan H. Chojnicki, Ulrich Dämmgen, Vesna Djuricic, Julia Drewer, Werner Eugster, Yannick Fauvel, David Fowler, Arnoud Frumau, André Granier, Patrick Gross, Yannick Hamon, Carole Helfter, Arjan Hensen, László Horváth, Barbara Kitzler, Bart Kruijt, Werner L. Kutsch, Raquel Lobo-do-Vale, Annalea Lohila, Bernard Longdoz, Michal V. Marek, Giorgio Matteucci, Marta Mitosinkova, Virginie Moreaux, Albrecht Neftel, Jean-Marc Ourcival, Kim Pilegaard, Gabriel Pita, Francisco Sanz, Jan K. Schjoerring, Maria-Teresa Sebastià, Y. Sim Tang, Hilde Uggerud, Marek Urbaniak, Netty van Dijk, Timo Vesala, Sonja Vidic, Caroline Vincke, Tamás Weidinger, Sophie Zechmeister-Boltenstern, Klaus Butterbach-Bahl, Eiko Nemitz, and Mark A. Sutton
Subjects: 0106 biological sciences, 010504 meteorology & atmospheric sciences, 13. Climate action, 010604 marine biology & hydrobiology, 15. Life on land, 01 natural sciences, 0105 earth and related environmental sciences
Abstract: The impact of atmospheric reactive nitrogen (Nr) deposition on carbon (C) sequestration in soils and biomass of unfertilised, natural, semi-natural and forest ecosystems has been much debated. Many previous results of this dC / dN response were based on changes in carbon stocks from periodical soil and ecosystem inventories, associated with estimates of Nr deposition obtained from large-scale chemical transport models. This study and a companion paper (Flechard et al., 2019) strive to reduce uncertainties of N effects on C sequestration by linking multi-annual gross and net ecosystem productivity estimates from 40 eddy covariance flux towers across Europe to local measurement-based estimates of dry and wet Nr deposition from a dedicated collocated monitoring network. To identify possible ecological drivers and processes affecting the interplay between C and Nr inputs and losses, these data were also combined with in situ flux measurements of NO, N2O and CH4 fluxes, soil NO3− leaching sampling, as well as results of soil incubation experiments for N and greenhouse gas (GHG) emissions, surveys of available data from online databases and from the literature, together with forest ecosystem (BASFOR) modelling. Multi-year averages of net ecosystem productivity (NEP) in forests ranged from −70 to 826 g (C) m−2 yr−1 at total wet + dry inorganic Nr deposition rates (Ndep) of 0.3 to 4.3 g (N) m−2 yr−1; and from −4 to 361 g (C) m−2 yr−1 at Ndep rates of 0.1 to 3.1 g (N) m−2 yr−1 in short semi-natural vegetation (moorlands, wetlands and unfertilised extensively managed grasslands). The GHG budgets of the forests were strongly dominated by CO2 exchange, while CH4 and N2O exchange comprised a larger proportion of the GHG balance in short semi-natural vegetation. Nitrogen losses in the form of NO, N2O and especially NO3− were of the order of 10–20 % of Ndep at sites with Ndep 3 g (N) m−2 yr−1, indicating that perhaps one third of the sites were in a state of early to advanced N saturation. Net ecosystem productivity increased with Nr deposition up to 2–2.5 g (N) m−2 yr−1, with large scatter associated with a wide range in carbon sequestration efficiency (CSE, defined as the NEP / GPP ratio). At elevated Ndep levels (> 2.5 g (N) m−2 yr−1), where inorganic Nr losses were also increasingly large, NEP levelled off and then decreased. The apparent increase in NEP at low to intermediate Ndep levels was partly the result of geographical cross-correlations between Ndep and climate, indicating that the actual mean dC / dN response at individual sites was significantly lower than would be suggested by a simple, straightforward regression of NEP vs. Ndep.
Published: 2019
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43. Solar‐induced chlorophyll fluorescence exhibits a universal relationship with gross primary productivity across a wide variety of biomes

Author: Alisa Krasnova, Ivan Mammarella, Adrian V. Rocha, Ankur R. Desai, Binbin He, M. Altaf Arain, Steffen M. Noe, Penélope Serrano Ortiz, Jingfeng Xiao, Carmen Emmel, Jason Beringer, Xing Li, Andrej Varlagin, Camilo Rey-Sanchez, and David Y. Hollinger
Subjects: 0106 biological sciences, Global and Planetary Change, 010504 meteorology & atmospheric sciences, Ecology, Biome, Medizin, Eddy covariance, Flux, Photosynthesis, Atmospheric sciences, 7. Clean energy, 010603 evolutionary biology, 01 natural sciences, Gross primary productivity, 13. Climate action, Environmental Chemistry, Environmental science, Global Change Biology, Chlorophyll fluorescence, 0105 earth and related environmental sciences, General Environmental Science
Abstract: In our recent study in Global Change Biology (Li et al., ), we examined the relationship between solar-induced chlorophyll fluorescence (SIF) measured from the Orbiting Carbon Observatory-2 (OCO-2) and gross primary productivity (GPP) derived from eddy covariance flux towers across the globe, and we discovered that there is a nearly universal relationship between SIF and GPP across a wide variety of biomes. This finding reveals the tremendous potential of SIF for accurately mapping terrestrial photosynthesis globally.
Published: 2019
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44. Covariations between plant functional traits emerge from constraining parameterization of a terrestrial biosphere model

Author: Georg Wohlfahrt, Marc Peaucelle, Damiano Gianelle, Nicolas Delpierre, Dan Yakir, Philippe Ciais, Timo Vesala, Sylvain Kuppel, Eric Dufrêne, Mark A. Sutton, Thomas Kolb, Nicolas Vuichard, Cédric Bacour, Andreas Ibrom, Ladislav Šigut, Lutz Merbold, Sebastian Wolf, Leonardo Montagnani, Anders Lindroth, Nina Buchmann, Jiquan Chen, Carsten Gruening, Josep Peñuelas, Luca Belelli Marchesini, Tomomichi Kato, Stefano Minerbi, Andrej Varlagin, Beverly E. Law, Ivan Mammarella, Cristina Gimeno-Colera, Ankur R. Desai, Richard Joffre, Nicolas Viovy, Lukas Hörtnagl, Carole Helfter, Peter D. Blanken, 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), NOVELTIS [Sté], ICOS-ATC (ICOS-ATC), 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)-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), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Global Ecology Unit CREAF-CEAB-CSIC, Universitat Autònoma de Barcelona (UAB), Vrije Universiteit Amsterdam [Amsterdam] (VU), Institute of Agricultural Sciences [Zürich], Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Department of Environmental Sciences [Toledo USA], University of Toledo, Ecologie Systématique et Evolution (ESE), Université Paris-Sud - Paris 11 (UP11)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), Department of Atmospheric and Oceanic Sciences [Madison], University of Wisconsin-Madison, Centro di Ecologia Alpina, Fondazione Edmund Mach - Edmund Mach Foundation [Italie] (FEM), Joint Research Centre, Edinburgh Research Station, Centre for Ecology and Hydrology, Swiss Federal Institute of Technology, Danmarks Tekniske Universitet = Technical University of Denmark (DTU), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-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 d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Hokkaido University [Sapporo, Japan], Department of Physical Geography and Ecosystem Science [Lund], Lund University [Lund], Department of Physics [Helsinki], Falculty of Science [Helsinki], Helsingin yliopisto = Helsingfors universitet = University of Helsinki-Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Institute of Agricultural Sciences, Ecole Polytechnique Fédérale de Zurich, Provincia Autonoma di Bolzano Servizi Forestali, Servizi Forestali, Provincia Autonoma di Bolzano, Agenzia per l'Ambiente, Department of Physics [Montréal], McGill University = Université McGill [Montréal, Canada], A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences [Moscow] (RAS), Department of Physics, Institute of Ecology, Leopold Franzens Universität Innsbruck - University of Innsbruck, Kiel University, Weizmann Institute of Science [Rehovot, Israël], Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU), Technical University of Denmark [Lyngby] (DTU), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Université Paul-Valéry - Montpellier 3 (UPVM)-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 de Recherche pour le Développement (IRD [France-Sud]), University of Helsinki-University of Helsinki, University of Innsbruck, Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS), Universitat Autònoma de Barcelona [Barcelona] (UAB), VU University Amsterdam, Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology in Zürich [Zürich] (ETH Zürich), Université Paul-Valéry - Montpellier 3 (UM3)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Hokkaido University, McGill University, A.N.Severtsov Institute of Ecology and Evolution, and Weizmann Institute of Science
Subjects: 0106 biological sciences, Biosphere model, Optimization, Eddy covariance, Atmospheric sciences, 010603 evolutionary biology, 01 natural sciences, Ecology and Environment, Terrestrial model, Data assimilation, FluxNet, Ecosystem model, Settore BIO/07 - ECOLOGIA, ORCHIDEE, Plant functional traits, Ecosystem, Plant acclimatation, Ecology, Evolution, Behavior and Systematics, ComputingMilieux_MISCELLANEOUS, SDG 15 - Life on Land, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, Global and Planetary Change, Ecology, 010604 marine biology & hydrobiology, Biosphere, 15. Life on land, Assimilation, Trait, Environmental science, Plant acclimation
Abstract: Aim: The mechanisms of plant trait adaptation and acclimation are still poorly understood and, consequently, lack a consistent representation in terrestrial biosphere models (TBMs). Despite the increasing availability of geo-referenced trait observations, current databases are still insufficient to cover all vegetation types and environmental conditions. In parallel, the growing number of continuous eddy-covariance observations of energy and CO2 fluxes has enabled modellers to optimize TBMs with these data. Past attempts to optimize TBM parameters mostly focused on model performance, overlooking the ecological properties of ecosystems. The aim of this study was to assess the ecological consistency of optimized trait-related parameters while improving the model performances for gross primary productivity (GPP) at sites.Location: Worldwide. Time period: 1992–2012. Major taxa studied: Trees and C3 grasses. Methods: We optimized parameters of the ORCHIDEE model against 371 site-years of GPP estimates from the FLUXNET network, and we looked at global covariation among parameters and with climate. Results: The optimized parameter values were shown to be consistent with leaf-scale traits, in particular, with well-known trade-offs observed at the leaf level, echoing the leaf economic spectrum theory. Results showed a marked sensitivity of trait-related parameters to local bioclimatic variables and reproduced the observed relationships between traits and climate. Main conclusions: Our approach validates some biological processes implemented in the model and enables us to study ecological properties of vegetation at the canopy level, in addition to some traits that are difficult to observe experimentally. This study stresses the need for: (a) implementing explicit trade-offs and acclimation processes in TBMs; (b) improving the representation of processes to avoid model-specific parameterization; and (c) performing systematic measurements of traits at FLUXNET sites in order to gather information on plant ecophysiology and plant diversity, together with micro-meteorological conditions.
Published: 2019
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45. Satellite chlorophyll fluorescence measurements reveal large-scale decoupling of photosynthesis and greenness dynamics in boreal evergreen forests

Author: Alemu Gonsamo, Phillipp Köhler, Tea Thum, Martin Jung, Yongguang Zhang, Luis Guanter, Maximilian Voigt, Sophia Walther, and Andrej Varlagin
Subjects: Chlorophyll, 0106 biological sciences, 010504 meteorology & atmospheric sciences, Population, Forests, Atmospheric sciences, 01 natural sciences, Carbon Cycle, Taiga, Environmental Chemistry, Photosynthesis, education, 0105 earth and related environmental sciences, General Environmental Science, Remote sensing, Global and Planetary Change, education.field_of_study, Ecology, Primary production, Enhanced vegetation index, 15. Life on land, Evergreen, Freezing point, Deciduous, Boreal, 13. Climate action, Environmental science, Seasons, 010606 plant biology & botany
Abstract: Mid-to-high latitude forests play an important role in the terrestrial carbon cycle, but the representation of photosynthesis in boreal forests by current modelling and observational methods is still challenging. In particular, the applicability of existing satellite-based proxies of greenness to indicate photosynthetic activity is hindered by small annual changes in green biomass of the often evergreen tree population and by the confounding effects of background materials such as snow. As an alternative, satellite measurements of sun-induced chlorophyll fluorescence (SIF) can be used as a direct proxy of photosynthetic activity. In this study, the start and end of the photosynthetically active season of the main boreal forests are analysed using spaceborne SIF measurements retrieved from the GOME-2 instrument and compared to that of green biomass, proxied by vegetation indices including the Enhanced Vegetation Index (EVI) derived from MODIS data. We find that photosynthesis and greenness show a similar seasonality in deciduous forests. In high-latitude evergreen needleleaf forests, however, the length of the photosynthetically active period indicated by SIF is up to 6 weeks longer than the green biomass changing period proxied by EVI, with SIF showing a start-of-season of approximately 1 month earlier than EVI. On average, the photosynthetic spring recovery as signalled by SIF occurs as soon as air temperatures exceed the freezing point (2-3 °C) and when the snow on the ground has not yet completely melted. These findings are supported by model data of gross primary production and a number of other studies which evaluated in situ observations of CO2 fluxes, meteorology and the physiological state of the needles. Our results demonstrate the sensitivity of space-based SIF measurements to light-use efficiency of boreal forests and their potential for an unbiased detection of photosynthetic activity even under the challenging conditions interposed by evergreen boreal ecosystems.
Published: 2016
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46. Altered energy partitioning across terrestrial ecosystems in the European drought year 2018

Author: Christian Brümmer, Bart Kruijt, Arne Poyda, Bert Gielen, Giovanni Manca, Marilyn Roland, Janina Klatt, Michal Heliasz, Jan Holst, Caroline Vincke, Corinna Rebmann, Meelis Mölder, Natalia Kowalska, Nadia Vendrame, Jinshu Chi, Nina Buchmann, Andreas Ibrom, Jiří Dušek, Stephan Weber, Lenka Foltýnová, Tarek S. El-Madany, Ladislav Šigut, Joachim Ingwersen, Alexander Graf, Mika Korkiakoski, Franziska Koebsch, Frédéric Bornet, Anne De Ligne, Denis Loustau, Eugénie Paul-Limoges, Mats Nilsson, Christophe Chipeaux, Eeva-Stiina Tuittila, Christian Wille, Torsten Sachs, Pascal Kremer, Shiva Ghiasi, Matthias Peichl, Gerald Jurasinski, Harry Vereecken, Matthias Mauder, Mana Gharun, Patrizia Ney, Thomas Grünwald, Hans-Dieter Wizemann, Pia Gottschalk, Marius Schmidt, Vincenzo Magliulo, Edoardo Cremonese, Joël Léonard, Ivan Mammarella, Anne Klosterhalfen, Mirco Migliavacca, Nicola Arriga, Silvano Fares, Milan Fischer, Matthias Cuntz, Andrej Varlagin, Alexander Knohl, Christian Bernhofer, Bernard Longdoz, Ingo Völksch, Frederik Schrader, Günther Heinemann, Sébastien Lafont, Nicolas Brüggemann, Heye Bogena, Bernard Heinesch, Jan Konopka, Matthias Zeeman, Johan Neirynck, Andrea Pitacco, Lukas Siebicke, Lukas Hörtnagl, SILVA (SILVA), AgroParisTech-Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), French National Research Agency (ANR)ANR-11-LABX-0002-01ANR-16-SUMF-0001-01Alexander von Humbold Stiftung (MaNiP) Federal Ministry of Education & Research (BMBF)01LN1313AGerman Federal Ministry of Food and Agriculture BMEL (ERA-NET FACCE ERAGAS) German Research Foundation (DFG)BE1721/23PAK 346FOR 1695INST 186/1118-1 FUGGGIP Ecofor SOERE F-ORE-T Finnish Center of Excellence 307331FWOG0H3317NHelmholtz Association HGF (TERENO) VH-NG-821Hainich National Park Horizon 2020 696356ICOS-FINLAND 281255Kempe Foundation SMK-1743Knut & Alice Wallenberg Foundation2015.0047Max-Planck Institute for Biogeochemistry Russian Foundation for Basic Research (RFBR)19-0401234-aSwiss National Science Foundation (SNSF)ICOS-CH Phase 2 20FI20_173691InnoFarm 407340_172433European Commission (SUPER-G) European Commission (RINGO) European Commission (ERA-NET Sumforest) 606803Service Public de Wallonie (DGO6) 1217769SustES CZ. 02.1.01/0.0/0.0/16_019/0000797CzeCOS LM2015061Swedish Research CouncilSwedish Research Council Formas201601289942-2015-49University of Padua CDPA148553, Ludwig-Maximilians University Munich, ∗Agrosphere (IBG-3), Institute of Bio- and Geosciences, Forschungszentrum Jülich GmbH, Jülich, Germany, Institute of Bio- and Geosciences [Jülich] (IBG), Forschungszentrum Jülich GmbH | Centre de recherche de Juliers, Helmholtz-Gemeinschaft = Helmholtz Association-Helmholtz-Gemeinschaft = Helmholtz Association-Forschungszentrum Jülich GmbH | Centre de recherche de Juliers, Helmholtz-Gemeinschaft = Helmholtz Association-Helmholtz-Gemeinschaft = Helmholtz Association, Department of Biology, University of Antwerp (UA), Institute of Hydrology and Meteorology [Dresden], Technische Universität Dresden = Dresden University of Technology (TU Dresden), Agrosphere, IBG-3, Transfrontalière BioEcoAgro (Transfrontalière BioEcoAgro), Université d'Artois (UA)-Université de Liège-Université de Picardie Jules Verne (UPJV)-Université du Littoral Côte d'Opale (ULCO)-Université de Lille-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Helmholtz-Gemeinschaft = Helmholtz Association, Thünen 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), Department of Forest Ecology and Management, Swedish University of Agricultural Sciences (SLU), 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), Federal Ministry of Education & Research (BMBF)01LN1313AGerman Federal Ministry of Food and Agriculture BMEL (ERA-NET FACCE ERAGAS) German Research Foundation (DFG)BE1721/23PAK 346FOR 1695INST 186/1118-1 FUGGGIP Ecofor SOERE F-ORE-T Finnish Center of Excellence 307331FWOG0H3317NHelmholtz Association HGF (TERENO) VH-NG-821Hainich National Park Horizon 2020 696356ICOS-FINLAND 281255Kempe Foundation SMK-1743Knut & Alice Wallenberg Foundation2015.0047Max-Planck Institute for Biogeochemistry Russian Foundation for Basic Research (RFBR)19-0401234-aSwiss National Science Foundation (SNSF)ICOS-CH Phase 2 20FI20_173691InnoFarm 407340_172433European Commission (SUPER-G) European Commission (RINGO) European Commission (ERA-NET Sumforest) 606803Service Public de Wallonie (DGO6) 1217769SustES CZ. 02.1.01/0.0/0.0/16_019/0000797CzeCOS LM2015061Swedish Research CouncilSwedish Research Council Formas201601289942-2015-49University of Padua CDPA148553, ANR-16-SUMF-0001,ForRISK,Forest density reduction to minimize the vulnerability of Norway spruce and silver fir to extreme drought – a risk assessment(2016), ANR-11-LABX-0002,ARBRE,Recherches Avancées sur l'Arbre et les Ecosytèmes Forestiers(2011), Ludwig-Maximilians University [Munich] (LMU), Transfrontalière BioEcoAgro - UMR 1158 (BioEcoAgro), Université d'Artois (UA)-Université de Liège-Université de Picardie Jules Verne (UPJV)-Université du Littoral Côte d'Opale (ULCO)-Université de Lille-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-JUNIA (JUNIA), and Université catholique de Lille (UCL)-Université catholique de Lille (UCL)
Subjects: Peat, 010504 meteorology & atmospheric sciences, Forests, Atmospheric sciences, 01 natural sciences, Evapotranspiration, water-use efficiency, SDG 15 - Life on Land, Environmental Sciences (social aspects to be 507), Articles, 04 agricultural and veterinary sciences, Grassland, Droughts, Europe, Meteorology and Atmospheric Sciences, [SDE]Environmental Sciences, eddy-covariance, Terrestrial ecosystem, SDG 6 - Clean Water and Sanitation, General Agricultural and Biological Sciences, Farms, net carbon uptake, Climate Change, evapotranspiration, Eddy covariance, heat flux, Sensible heat, General Biochemistry, Genetics and Molecular Biology, ddc:570, Latent heat, eddy covariance, energy balance, Water-use efficiency, Biology, 0105 earth and related environmental sciences, WIMEK, Atmosphere, Global warming, 15. Life on land, 13. Climate action, Wetlands, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science, Water Systems and Global Change, Human medicine
Abstract: Drought and heat events, such as the 2018 European drought, interact with the exchange of energy between the land surface and the atmosphere, potentially affecting albedo, sensible and latent heat fluxes, as well as CO 2 exchange. Each of these quantities may aggravate or mitigate the drought, heat, their side effects on productivity, water scarcity and global warming. We used measurements of 56 eddy covariance sites across Europe to examine the response of fluxes to extreme drought prevailing most of the year 2018 and how the response differed across various ecosystem types (forests, grasslands, croplands and peatlands). Each component of the surface radiation and energy balance observed in 2018 was compared to available data per site during a reference period 2004–2017. Based on anomalies in precipitation and reference evapotranspiration, we classified 46 sites as drought affected. These received on average 9% more solar radiation and released 32% more sensible heat to the atmosphere compared to the mean of the reference period. In general, drought decreased net CO 2 uptake by 17.8%, but did not significantly change net evapotranspiration. The response of these fluxes differed characteristically between ecosystems; in particular, the general increase in the evaporative index was strongest in peatlands and weakest in croplands. This article is part of the theme issue ‘Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale’.
Published: 2020
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47. Quantifying the effect of forest age in annual net forest carbon balance

Author: Bart Kruijt, Martin Herold, Christopher M Gough, Andrej Varlagin, Katerina Havrankova, Rainer Steinbrecher, Jan G. P. W. Clevers, Simon Besnard, Lukas Hörtnagl, Martin Jung, Alexander Knohl, Alessandro Cescatti, Asko Noormets, Anders Lindroth, Jiquan Chen, Markus Reichstein, Nina Buchmann, Olivier Roupsard, Caroline Vincke, Beverly E. Law, Sytze de Bruin, Nuno Carvalhais, M. Altaf Arain, Lenka Krupkova, Andrew Black, Ankur R. Desai, Max Planck Society, Wageningen University and Research Centre (WUR), Universidade Nova de Lisboa = NOVA University Lisbon (NOVA), McMaster University, Faculty of Land and Food Systems, University of British Columbia (UBC), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), European Commission, Michigan State University [East Lansing], Michigan State University System, Department of Atmospheric and Oceanic Sciences [Madison], University of Wisconsin-Madison, Department of Biology, University of Antwerp (UA), Czech Academy of Sciences [Prague] (CAS), Bioclimatology, Georg-August-University = Georg-August-Universität Göttingen, Wageningen Environmental Research (Alterra), College of Forestry, Oregon State University (OSU), Department of Physical Geography and Ecosystem Science, Lund University [Lund], Department of Forestry and Environmental Resources, North Carolina State University [Raleigh] (NC State), University of North Carolina System (UNC)-University of North Carolina System (UNC), Department of Ecosystem Science and Management, Pennsylvania State University (Penn State), Penn State System-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 la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Karlsruhe Institute of Technology (KIT), A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences [Moscow] (RAS), Earth and Life Institute‐Environmental Sciences, Université Catholique de Louvain = Catholic University of Louvain (UCL), Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme I (NPU I), grant number LO1415, BACI project and the Independent Monitoring Project, NOVA grant UID/AMB/04085/2013, GlobBiomass project., Georg-August-University [Göttingen], Lund University, and 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)
Subjects: 0106 biological sciences, [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, 010504 meteorology & atmospheric sciences, Climate, F62 - Physiologie végétale - Croissance et développement, Eddy covariance, 01 natural sciences, Laboratory of Geo-information Science and Remote Sensing, K01 - Foresterie - Considérations générales, ddc:550, Net ecosystem production, carbon cycle, eddy covariance, net ecosystem production, empirical modelling, forest age, climate, soil properties, General Environmental Science, Abiotic component, Vegetal Biology, Biosphere, Carbon cycle, PE&RC, Agricultural sciences, Physiologie végétale, Forêt, accroissement forestier, modèle empirique, Empirical modelling, ecosystem approaches [EN], F40 - Écologie végétale, P40 - Météorologie et climatologie, Aménagement forestier, Forest management, 010603 evolutionary biology, Fertilité du sol, production primaire nette, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Laboratorium voor Geo-informatiekunde en Remote Sensing, Ecosystem, Modélisation environnementale, écosystème forestier, 0105 earth and related environmental sciences, empirical modeling, WIMEK, Forest age, Renewable Energy, Sustainability and the Environment, Public Health, Environmental and Occupational Health, 15. Life on land, Soil properties, eddy covariance, net ecosystem production, Earth sciences, Disturbance (ecology), 13. Climate action, Environmental science, age de la foret, Water Systems and Global Change, Spatial variability, Physical geography, Cycle du carbone, Sciences agricoles, Biologie végétale
Abstract: Forests dominate carbon (C) exchanges between the terrestrial biosphere and the atmosphere on land. In the long term, the net carbon flux between forests and the atmosphere has been significantly impacted by changes in forest cover area and structure due to ecological disturbances and management activities. Current empirical approaches for estimating net ecosystem productivity (NEP) rarely consider forest age as a predictor, which represents variation in physiological processes that can respond differently to environmental drivers, and regrowth following disturbance. Here, we conduct an observational synthesis to empirically determine to what extent climate, soil properties, nitrogen deposition, forest age and management influence the spatial and interannual variability of forest NEP across 126 forest eddy-covariance flux sites worldwide. The empirical models explained up to 62% and 71% of spatio-temporal and across-site variability of annual NEP, respectively. An investigation of model structures revealed that forest age was a dominant factor of NEP spatio-temporal variability in both space and time at the global scale as compared to abiotic factors, such as nutrient availability, soil characteristics and climate. These findings emphasize the importance of forest age in quantifying spatio-temporal variation in NEP using empirical approaches. ISSN:1748-9326 ISSN:1748-9318
Published: 2018
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48. Solar-induced chlorophyll fluorescence is strongly correlated with terrestrial photosynthesis for a wide variety of biomes: First global analysis based on OCO-2 and flux tower observations

Author: David Y. Hollinger, Steffen M. Noe, Carmen Emmel, Jingfeng Xiao, Jason Beringer, Andrej Varlagin, Camilo Rey-Sanchez, Xing Li, Adrian V. Rocha, Ankur R. Desai, Binbin He, M. Altaf Arain, Ivan Mammarella, Penélope Serrano Ortiz, and Alisa Krasnova
Subjects: Chlorophyll, Satellite Imagery, 010504 meteorology & atmospheric sciences, Biome, 0211 other engineering and technologies, Eddy covariance, 02 engineering and technology, Forests, Atmospheric sciences, 01 natural sciences, Fluorescence, Carbon cycle, Carbon Cycle, Vegetation type, Environmental Chemistry, Ecosystem, Photosynthesis, Chlorophyll fluorescence, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, General Environmental Science, Global and Planetary Change, Ecology, 15. Life on land, Evergreen, Carbon, 13. Climate action, Photosynthetically active radiation, Sunlight, Environmental science, Environmental Monitoring
Abstract: Solar-induced chlorophyll fluorescence (SIF) has been increasingly used as a proxy for terrestrial gross primary productivity (GPP). Previous work mainly evaluated the relationship between satellite-observed SIF and gridded GPP products both based on coarse spatial resolutions. Finer resolution SIF (1.3 km × 2.25 km) measured from the Orbiting Carbon Observatory-2 (OCO-2) provides the first opportunity to examine the SIF-GPP relationship at the ecosystem scale using flux tower GPP data. However, it remains unclear how strong the relationship is for each biome and whether a robust, universal relationship exists across a variety of biomes. Here we conducted the first global analysis of the relationship between OCO-2 SIF and tower GPP for a total of 64 flux sites across the globe encompassing eight major biomes. OCO-2 SIF showed strong correlations with tower GPP at both midday and daily timescales, with the strongest relationship observed for daily SIF at the 757 nm (R2 = 0.72, p
Published: 2018

49. Global Lagrangian Atmospheric Dispersion Model

Author: Ruslan Zhuravlev, Andrej Varlagin, Alexander Ganshin, A. N. Luk’yanov, and S. Maksyutov
Subjects: Physics, Atmospheric Science, Work (thermodynamics), Turbulent diffusion, Meteorology, вулканический пепел, углекислый газ, Atmospheric dispersion modeling, атмосфера, Oceanography, Atmospheric sciences, глобальная лагранжева атмосферная дисперсионная модель, Trace gas, Regular grid, TRACER, турбулентная диффузия, Trajectory (fluid mechanics), Physics::Atmospheric and Oceanic Physics, Air mass
Abstract: The Global Lagrangian Atmospheric Dispersion Model (GLADIM) is described. GLADIM is based on the global trajectory model, which had been developed earlier and uses fields of weather parameters from different atmospheric reanalysis centers for calculations of trajectories of air mass that include trace gases. GLADIM includes the parameterization of turbulent diffusion and allows the forward calculation of concentrations of atmospheric tracers at nodes of a global regular grid when a source is specified. Thus, GLADIM can be used for the forward simulation of pollutant propagation (volcanic ash, radionuclides, and so on). Working in the reverse direction, GLADIM allows the detection of remote sources that mainly contribute to the tracer concentration at an observation point. This property of Lagrangian models is widely used for data analysis and the reverse modeling of emission sources of a pollutant specified. In this work we describe the model and some results of its validation through a comparison with results of a similar model and observation data.
Published: 2015
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50. Performance of Linear and Nonlinear Two-Leaf Light Use Efficiency Models at Different Temporal Scales

Author: T. Andrew Black, Timothy J. Griffis, Beverly E. Law, Asko Noormets, Bing-Bing Zhou, Shaoqiang Wang, Yibo Liu, Mingzhu He, Xiaocui Wu, Lianhong Gu, Hank A. Margolis, Andrej Varlagin, Weimin Ju, Kim Pilegaard, Leonardo Montagnani, Peter D. Blanken, Junhua Yan, Yanlian Zhou, Yingnian Li, Huimin Wang, Shijie Han, Alessandro Cescatti, and Riccardo Valentini
Subjects: Scale (ratio), Science, light use efficiency model, Flux, Gross primary productivity (GPP), Vegetation types, Sunlit and shaded leaves, 7. Clean energy, gross primary productivity (GPP), sunlit and shaded leaves, vegetation types, temporal scales, Atmosphere, Light use efficiency model, Temporal scales, SDG 15 - Life on Land, Primary production, 15. Life on land, Nonlinear system, 13. Climate action, Climatology, General Earth and Planetary Sciences, Environmental science, Terrestrial ecosystem
Abstract: The reliable simulation of gross primary productivity (GPP) at various spatial and temporal scales is of significance to quantifying the net exchange of carbon between terrestrial ecosystems and the atmosphere. This study aimed to verify the ability of a nonlinear two-leaf model (TL-LUEn), a linear two-leaf model (TL-LUE), and a big-leaf light use efficiency model (MOD17) to simulate GPP at half-hourly, daily and 8-day scales using GPP derived from 58 eddy-covariance flux sites in Asia, Europe and North America as benchmarks. Model evaluation showed that the overall performance of TL-LUEn was slightly but not significantly better than TL-LUE at half-hourly and daily scale, while the overall performance of both TL-LUEn and TL-LUE were significantly better (p < 0.0001) than MOD17 at the two temporal scales. The improvement of TL-LUEn over TL-LUE was relatively small in comparison with the improvement of TL-LUE over MOD17. However, the differences between TL-LUEn and MOD17, and TL-LUE and MOD17 became less distinct at the 8-day scale. As for different vegetation types, TL-LUEn and TL-LUE performed better than MOD17 for all vegetation types except crops at the half-hourly scale. At the daily and 8-day scales, both TL-LUEn and TL-LUE outperformed MOD17 for forests. However, TL-LUEn had a mixed performance for the three non-forest types while TL-LUE outperformed MOD17 slightly for all these non-forest types at daily and 8-day scales. The better performance of TL-LUEn and TL-LUE for forests was mainly achieved by the correction of the underestimation/overestimation of GPP simulated by MOD17 under low/high solar radiation and sky clearness conditions. TL-LUEn is more applicable at individual sites at the half-hourly scale while TL-LUE could be regionally used at half-hourly, daily and 8-day scales. MOD17 is also an applicable option regionally at the 8-day scale.
Published: 2015
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