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1. Leaf-level coordination principles propagate to the ecosystem scale.

Author

Gomarasca, Ulisse, Migliavacca, Mirco, Kattge, Jens, Nelson, Jacob, Niinemets, Ülo, Wirth, Christian, Cescatti, Alessandro, Bahn, Michael, Nair, Richard, Acosta, Alicia, Arain, M, Beloiu, Mirela, Black, T, Bruun, Hans, Bucher, Solveig, Buchmann, Nina, Byun, Chaeho, Carrara, Arnaud, Conte, Adriano, da Silva, Ana, Duveiller, Gregory, Fares, Silvano, Ibrom, Andreas, Knohl, Alexander, Komac, Benjamin, Limousin, Jean-Marc, Lusk, Christopher, Mahecha, Miguel, Martini, David, Minden, Vanessa, Montagnani, Leonardo, Mori, Akira, Onoda, Yusuke, Peñuelas, Josep, Perez-Priego, Oscar, Poschlod, Peter, Powell, Thomas, Reich, Peter, Šigut, Ladislav, van Bodegom, Peter, Walther, Sophia, Wohlfahrt, Georg, Wright, Ian, and Reichstein, Markus

Subjects
Ecosystem, Plants, Climate Change, Plant Leaves, Phenotype
Abstract

Fundamental axes of variation in plant traits result from trade-offs between costs and benefits of resource-use strategies at the leaf scale. However, it is unclear whether similar trade-offs propagate to the ecosystem level. Here, we test whether trait correlation patterns predicted by three well-known leaf- and plant-level coordination theories - the leaf economics spectrum, the global spectrum of plant form and function, and the least-cost hypothesis - are also observed between community mean traits and ecosystem processes. We combined ecosystem functional properties from FLUXNET sites, vegetation properties, and community mean plant traits into three corresponding principal component analyses. We find that the leaf economics spectrum (90 sites), the global spectrum of plant form and function (89 sites), and the least-cost hypothesis (82 sites) all propagate at the ecosystem level. However, we also find evidence of additional scale-emergent properties. Evaluating the coordination of ecosystem functional properties may aid the development of more realistic global dynamic vegetation models with critical empirical data, reducing the uncertainty of climate change projections.

Published
2023

5. Global maps of soil temperature

Author

Lembrechts, Jonas J, Hoogen, Johan, Aalto, Juha, Ashcroft, Michael B, De Frenne, Pieter, Kemppinen, Julia, Kopecký, Martin, Luoto, Miska, Maclean, Ilya MD, Crowther, Thomas W, Bailey, Joseph J, Haesen, Stef, Klinges, David H, Niittynen, Pekka, Scheffers, Brett R, Van Meerbeek, Koenraad, Aartsma, Peter, Abdalaze, Otar, Abedi, Mehdi, Aerts, Rien, Ahmadian, Negar, Ahrends, Antje, Alatalo, Juha M, Alexander, Jake M, Allonsius, Camille Nina, Altman, Jan, Ammann, Christof, Andres, Christian, Andrews, Christopher, Ardö, Jonas, Arriga, Nicola, Arzac, Alberto, Aschero, Valeria, Assis, Rafael L, Assmann, Jakob Johann, Bader, Maaike Y, Bahalkeh, Khadijeh, Barančok, Peter, Barrio, Isabel C, Barros, Agustina, Barthel, Matti, Basham, Edmund W, Bauters, Marijn, Bazzichetto, Manuele, Marchesini, Luca Belelli, Bell, Michael C, Benavides, Juan C, Alonso, José Luis Benito, Berauer, Bernd J, Bjerke, Jarle W, Björk, Robert G, Björkman, Mats P, Björnsdóttir, Katrin, Blonder, Benjamin, Boeckx, Pascal, Boike, Julia, Bokhorst, Stef, Brum, Bárbara NS, Brůna, Josef, Buchmann, Nina, Buysse, Pauline, Camargo, José Luís, Campoe, Otávio C, Candan, Onur, Canessa, Rafaella, Cannone, Nicoletta, Carbognani, Michele, Carnicer, Jofre, Casanova‐Katny, Angélica, Cesarz, Simone, Chojnicki, Bogdan, Choler, Philippe, Chown, Steven L, Cifuentes, Edgar F, Čiliak, Marek, Contador, Tamara, Convey, Peter, Cooper, Elisabeth J, Cremonese, Edoardo, Curasi, Salvatore R, Curtis, Robin, Cutini, Maurizio, Dahlberg, C Johan, Daskalova, Gergana N, de Pablo, Miguel Angel, Della Chiesa, Stefano, Dengler, Jürgen, Deronde, Bart, Descombes, Patrice, Di Cecco, Valter, Di Musciano, Michele, Dick, Jan, Dimarco, Romina D, Dolezal, Jiri, Dorrepaal, Ellen, Dušek, Jiří, Eisenhauer, Nico, Eklundh, Lars, Erickson, Todd E, and Erschbamer, Brigitta

Subjects
Climate Action, Climate Change, Ecosystem, Microclimate, Soil, Temperature, bioclimatic variables, global maps, microclimate, near-surface temperatures, soil-dwelling organisms, soil temperature, temperature offset, weather stations, Environmental Sciences, Biological Sciences, Ecology
Abstract

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.

Published
2022

7. Standards and Open Access are the ICOS Pillars: Reply to 'Comments on 'The Integrated Carbon Observation System in Europe''

Author

Papale, Dario, Heiskanen, Jouni, Brummer, Christian, Buchmann, Nina, Calfapietra, Carlo, Carrara, Arnaud, Chen, Huilin, Gielen, Bert, Gkritzalis, Thanos, Hammer, Samuel, Hartman, Susan, Herbst, Mathias, Janssens, Ivan A., Jordan, Armin, Juurola, Eija, Karstens, Ute, Kasurinen, Ville, Kruijt, Bart, Lankreijer, Harry, Levin, Ingeborg, Linderson, Maj-Lena, Loustau, Denis, Merbold, Lutz, Myhre, Cathrine Lund, Pavelka, Marian, Pilegaard, Kim, Ramonet, Michel, Rebmann, Corinna, Rinne, Janne, Rivier, Leonard, Saltikoff, Elena, Sanders, Richard, Steinbacher, Martin, Steinhoff, Tobias, Watson, Andrew, Vermeulen, Alex T., Vesala, Timo, Vitkova, Gabriela, and Kutsch, Werner

Subjects
Business, Earth sciences
Abstract

In his comment (Kowalski 2023) on our recent publication (Heiskanen et al. 2022) where we present the Integrated Carbon Observation System (ICOS) research infrastructure, Andrew Kowalski introduces three important and, [...]

Published
2023
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8. Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing

Author

Xie, Mingjuan, Ma, Xiaofei, Wang, Yuangang, Li, Chaofan, Shi, Haiyang, Yuan, Xiuliang, Hellwich, Olaf, Chen, Chunbo, Zhang, Wenqiang, Zhang, Chen, Ling, Qing, Gao, Ruixiang, Zhang, Yu, Ochege, Friday Uchenna, Frankl, Amaury, De Maeyer, Philippe, Buchmann, Nina, Feigenwinter, Iris, Olesen, Jørgen E., Juszczak, Radoslaw, Jacotot, Adrien, Korrensalo, Aino, Pitacco, Andrea, Varlagin, Andrej, Shekhar, Ankit, Lohila, Annalea, Carrara, Arnaud, Brut, Aurore, Kruijt, Bart, Loubet, Benjamin, Heinesch, Bernard, Chojnicki, Bogdan, Helfter, Carole, Vincke, Caroline, Shao, Changliang, Bernhofer, Christian, Brümmer, Christian, Wille, Christian, Tuittila, Eeva-Stiina, Nemitz, Eiko, Meggio, Franco, Dong, Gang, Lanigan, Gary, Niedrist, Georg, Wohlfahrt, Georg, Zhou, Guoyi, Goded, Ignacio, Gruenwald, Thomas, Olejnik, Janusz, Jansen, Joachim, Neirynck, Johan, Tuovinen, Juha-Pekka, Zhang, Junhui, Klumpp, Katja, Pilegaard, Kim, Šigut, Ladislav, Klemedtsson, Leif, Tezza, Luca, Hörtnagl, Lukas, Urbaniak, Marek, Roland, Marilyn, Schmidt, Marius, Sutton, Mark A., Hehn, Markus, Saunders, Matthew, Mauder, Matthias, Aurela, Mika, Korkiakoski, Mika, Du, Mingyuan, Vendrame, Nadia, Kowalska, Natalia, Leahy, Paul G., Alekseychik, Pavel, Shi, Peili, Weslien, Per, Chen, Shiping, Fares, Silvano, Friborg, Thomas, Tallec, Tiphaine, Kato, Tomomichi, Sachs, Torsten, Maximov, Trofim, di Cella, Umberto Morra, Moderow, Uta, Li, Yingnian, He, Yongtao, Kosugi, Yoshiko, and Luo, Geping

Published
2023
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10. Assimilating Sentinel-2 data in a modified vegetation photosynthesis and respiration model (VPRM) to improve the simulation of croplands CO2 fluxes in Europe

Author

Bazzi, Hassan, Ciais, Philippe, Abbessi, Ezzeddine, Makowski, David, Santaren, Diego, Ceschia, Eric, Brut, Aurore, Tallec, Tiphaine, Buchmann, Nina, Maier, Regine, Acosta, Manuel, Loubet, Benjamin, Buysse, Pauline, Léonard, Joël, Bornet, Frédéric, Fayad, Ibrahim, Lian, Jinghui, Baghdadi, Nicolas, Segura Barrero, Ricard, Brümmer, Christian, Schmidt, Marius, Heinesch, Bernard, Mauder, Matthias, and Gruenwald, Thomas

Published
2024
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11. The three major axes of terrestrial ecosystem function

Author

Migliavacca, Mirco, Musavi, Talie, Mahecha, Miguel D, Nelson, Jacob A, Knauer, Jürgen, Baldocchi, Dennis D, Perez-Priego, Oscar, Christiansen, Rune, Peters, Jonas, Anderson, Karen, Bahn, Michael, Black, T Andrew, Blanken, Peter D, Bonal, Damien, Buchmann, Nina, Caldararu, Silvia, Carrara, Arnaud, Carvalhais, Nuno, Cescatti, Alessandro, Chen, Jiquan, Cleverly, Jamie, Cremonese, Edoardo, Desai, Ankur R, El-Madany, Tarek S, Farella, Martha M, Fernández-Martínez, Marcos, Filippa, Gianluca, Forkel, Matthias, Galvagno, Marta, Gomarasca, Ulisse, Gough, Christopher M, Göckede, Mathias, Ibrom, Andreas, Ikawa, Hiroki, Janssens, Ivan A, Jung, Martin, Kattge, Jens, Keenan, Trevor F, Knohl, Alexander, Kobayashi, Hideki, Kraemer, Guido, Law, Beverly E, Liddell, Michael J, Ma, Xuanlong, Mammarella, Ivan, Martini, David, Macfarlane, Craig, Matteucci, Giorgio, Montagnani, Leonardo, Pabon-Moreno, Daniel E, Panigada, Cinzia, Papale, Dario, Pendall, Elise, Penuelas, Josep, Phillips, Richard P, Reich, Peter B, Rossini, Micol, Rotenberg, Eyal, Scott, Russell L, Stahl, Clement, Weber, Ulrich, Wohlfahrt, Georg, Wolf, Sebastian, Wright, Ian J, Yakir, Dan, Zaehle, Sönke, and Reichstein, Markus

Subjects
Life on Land, Carbon Cycle, Carbon Dioxide, Climate, Datasets as Topic, Ecosystem, Humidity, Plants, Principal Component Analysis, Water Cycle, General Science & Technology
Abstract

The leaf economics spectrum1,2 and the global spectrum of plant forms and functions3 revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species2. Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities4. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability4,5. Here we derive a set of ecosystem functions6 from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems7,8.

Published
2021

15. Detection and attribution of an anomaly in terrestrial photosynthesis in Europe during the COVID-19 lockdown

Author

Tang, Angela Che Ing, Flechard, Christophe R., Arriga, Nicola, Papale, Dario, Stoy, Paul C., Buchmann, Nina, Cuntz, Matthias, Douros, John, Fares, Silvano, Knohl, Alexander, Šigut, Ladislav, Simioni, Guillaume, Timmermans, Renske, Grünwald, Thomas, Ibrom, Andreas, Loubet, Benjamin, Mammarella, Ivan, Belelli Marchesini, Luca, Nilsson, Mats, Peichl, Matthias, Rebmann, Corinna, Schmidt, Marius, Bernhofer, Christian, Berveiller, Daniel, Cremonese, Edoardo, El-Madany, Tarek S., Gharun, Mana, Gianelle, Damiano, Hörtnagl, Lukas, Roland, Marilyn, Varlagin, Andrej, Fu, Zheng, Heinesch, Bernard, Janssens, Ivan, Kowalska, Natalia, Dušek, Jiří, Gerosa, Giacomo, Mölder, Meelis, Tuittila, Eeva-Stiina, and Loustau, Denis

Published
2023
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18. Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data.

Author

Pastorello, Gilberto, Trotta, Carlo, Canfora, Eleonora, Chu, Housen, Christianson, Danielle, Cheah, You-Wei, Poindexter, Cristina, Chen, Jiquan, Elbashandy, Abdelrahman, Humphrey, Marty, Isaac, Peter, Polidori, Diego, Reichstein, Markus, Ribeca, Alessio, van Ingen, Catharine, Vuichard, Nicolas, Zhang, Leiming, Amiro, Brian, Ammann, Christof, Arain, M Altaf, Ardö, Jonas, Arkebauer, Timothy, Arndt, Stefan K, Arriga, Nicola, Aubinet, Marc, Aurela, Mika, Baldocchi, Dennis, Barr, Alan, Beamesderfer, Eric, Marchesini, Luca Belelli, Bergeron, Onil, Beringer, Jason, Bernhofer, Christian, Berveiller, Daniel, Billesbach, Dave, Black, Thomas Andrew, Blanken, Peter D, Bohrer, Gil, Boike, Julia, Bolstad, Paul V, Bonal, Damien, Bonnefond, Jean-Marc, Bowling, David R, Bracho, Rosvel, Brodeur, Jason, Brümmer, Christian, Buchmann, Nina, Burban, Benoit, Burns, Sean P, Buysse, Pauline, Cale, Peter, Cavagna, Mauro, Cellier, Pierre, Chen, Shiping, Chini, Isaac, Christensen, Torben R, Cleverly, James, Collalti, Alessio, Consalvo, Claudia, Cook, Bruce D, Cook, David, Coursolle, Carole, Cremonese, Edoardo, Curtis, Peter S, D'Andrea, Ettore, da Rocha, Humberto, Dai, Xiaoqin, Davis, Kenneth J, De Cinti, Bruno, de Grandcourt, Agnes, De Ligne, Anne, De Oliveira, Raimundo C, Delpierre, Nicolas, Desai, Ankur R, Di Bella, Carlos Marcelo, di Tommasi, Paul, Dolman, Han, Domingo, Francisco, Dong, Gang, Dore, Sabina, Duce, Pierpaolo, Dufrêne, Eric, Dunn, Allison, Dušek, Jiří, Eamus, Derek, Eichelmann, Uwe, ElKhidir, Hatim Abdalla M, Eugster, Werner, Ewenz, Cacilia M, Ewers, Brent, Famulari, Daniela, Fares, Silvano, Feigenwinter, Iris, Feitz, Andrew, Fensholt, Rasmus, Filippa, Gianluca, Fischer, Marc, Frank, John, Galvagno, Marta, and Gharun, Mana

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.

Published
2021

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

Author

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

Subjects
Earth Sciences, Atmospheric Sciences, Climate Action, Geochemistry, Physical Geography and Environmental Geoscience, Atmospheric sciences, Geoinformatics, Physical geography and environmental geoscience
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 20g g€¯S to 20g g€¯N) the spring onset of elevated CH4 emissions starts 3g€¯d earlier, and the CH4 emission season lasts 4g€¯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 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

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

Author

Bond‐Lamberty, Ben, Christianson, Danielle S, Malhotra, Avni, Pennington, Stephanie C, Sihi, Debjani, AghaKouchak, Amir, Anjileli, Hassan, Arain, M Altaf, Armesto, Juan J, Ashraf, Samaneh, Ataka, Mioko, Baldocchi, Dennis, Black, Thomas Andrew, Buchmann, Nina, Carbone, Mariah S, Chang, Shih‐Chieh, Crill, Patrick, Curtis, Peter S, Davidson, Eric A, Desai, Ankur R, Drake, John E, El‐Madany, Tarek S, Gavazzi, Michael, Görres, Carolyn‐Monika, Gough, Christopher M, Goulden, Michael, Gregg, Jillian, del Arroyo, Omar Gutiérrez, He, Jin‐Sheng, Hirano, Takashi, Hopple, Anya, Hughes, Holly, Järveoja, Järvi, Jassal, Rachhpal, Jian, Jinshi, Kan, Haiming, Kaye, Jason, Kominami, Yuji, Liang, Naishen, Lipson, David, Macdonald, Catriona A, Maseyk, Kadmiel, Mathes, Kayla, Mauritz, Marguerite, Mayes, Melanie A, McNulty, Steve, Miao, Guofang, Migliavacca, Mirco, Miller, Scott, Miniat, Chelcy F, Nietz, Jennifer G, Nilsson, Mats B, Noormets, Asko, Norouzi, Hamidreza, O’Connell, Christine S, Osborne, Bruce, Oyonarte, Cecilio, Pang, Zhuo, Peichl, Matthias, Pendall, Elise, Perez‐Quezada, Jorge F, Phillips, Claire L, Phillips, Richard P, Raich, James W, Renchon, Alexandre A, Ruehr, Nadine K, Sánchez‐Cañete, Enrique P, Saunders, Matthew, Savage, Kathleen E, Schrumpf, Marion, Scott, Russell L, Seibt, Ulli, Silver, Whendee L, Sun, Wu, Szutu, Daphne, Takagi, Kentaro, Takagi, Masahiro, Teramoto, Munemasa, Tjoelker, Mark G, Trumbore, Susan, Ueyama, Masahito, Vargas, Rodrigo, Varner, Ruth K, Verfaillie, Joseph, Vogel, Christoph, Wang, Jinsong, Winston, Greg, Wood, Tana E, Wu, Juying, Wutzler, Thomas, Zeng, Jiye, Zha, Tianshan, Zhang, Quan, and Zou, Junliang

Subjects
Climate Change Impacts and Adaptation, Environmental Sciences, Climate Action, Atmosphere, Carbon Dioxide, Ecosystem, Greenhouse Gases, Methane, Nitrous Oxide, Reproducibility of Results, Respiration, Soil, carbon dioxide, greenhouse gases, methane, open data, open science, soil respiration, Biological Sciences, Ecology, Biological sciences, Earth sciences, Environmental sciences
Abstract

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

Published
2020

23. SoilTemp: A global database of near‐surface temperature

Author

Lembrechts, Jonas J, Aalto, Juha, Ashcroft, Michael B, De Frenne, Pieter, Kopecký, Martin, Lenoir, Jonathan, Luoto, Miska, Maclean, Ilya MD, Roupsard, Olivier, Fuentes‐Lillo, Eduardo, García, Rafael A, Pellissier, Loïc, Pitteloud, Camille, Alatalo, Juha M, Smith, Stuart W, Björk, Robert G, Muffler, Lena, Backes, Amanda Ratier, Cesarz, Simone, Gottschall, Felix, Okello, Joseph, Urban, Josef, Plichta, Roman, Svátek, Martin, Phartyal, Shyam S, Wipf, Sonja, Eisenhauer, Nico, Pușcaș, Mihai, Turtureanu, Pavel D, Varlagin, Andrej, Dimarco, Romina D, Jump, Alistair S, Randall, Krystal, Dorrepaal, Ellen, Larson, Keith, Walz, Josefine, Vitale, Luca, Svoboda, Miroslav, Higgens, Rebecca Finger, Halbritter, Aud H, Curasi, Salvatore R, Klupar, Ian, Koontz, Austin, Pearse, William D, Simpson, Elizabeth, Stemkovski, Michael, Graae, Bente Jessen, Sørensen, Mia Vedel, Høye, Toke T, Calzado, M Rosa Fernández, Lorite, Juan, Carbognani, Michele, Tomaselli, Marcello, Forte, T'ai GW, Petraglia, Alessandro, Haesen, Stef, Somers, Ben, Van Meerbeek, Koenraad, Björkman, Mats P, Hylander, Kristoffer, Merinero, Sonia, Gharun, Mana, Buchmann, Nina, Dolezal, Jiri, Matula, Radim, Thomas, Andrew D, Bailey, Joseph J, Ghosn, Dany, Kazakis, George, Pablo, Miguel A, Kemppinen, Julia, Niittynen, Pekka, Rew, Lisa, Seipel, Tim, Larson, Christian, Speed, James DM, Ardö, Jonas, Cannone, Nicoletta, Guglielmin, Mauro, Malfasi, Francesco, Bader, Maaike Y, Canessa, Rafaella, Stanisci, Angela, Kreyling, Juergen, Schmeddes, Jonas, Teuber, Laurenz, Aschero, Valeria, Čiliak, Marek, Máliš, František, De Smedt, Pallieter, Govaert, Sanne, Meeussen, Camille, Vangansbeke, Pieter, Gigauri, Khatuna, Lamprecht, Andrea, Pauli, Harald, Steinbauer, Klaus, Winkler, Manuela, Ueyama, Masahito, and Nuñez, Martin A

Subjects
Climate Action, Climate Change, Ecosystem, Microclimate, Snow, Temperature, climate change, database, ecosystem processes, microclimate, soil climate, species distributions, temperature, topoclimate, Environmental Sciences, Biological Sciences, Ecology
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.

Published
2020

25. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data.

Author

Pastorello, Gilberto, Trotta, Carlo, Canfora, Eleonora, Chu, Housen, Christianson, Danielle, Cheah, You-Wei, Poindexter, Cristina, Chen, Jiquan, Elbashandy, Abdelrahman, Humphrey, Marty, Isaac, Peter, Polidori, Diego, Reichstein, Markus, Ribeca, Alessio, van Ingen, Catharine, Vuichard, Nicolas, Zhang, Leiming, Amiro, Brian, Ammann, Christof, Arain, M Altaf, Ardö, Jonas, Arkebauer, Timothy, Arndt, Stefan K, Arriga, Nicola, Aubinet, Marc, Aurela, Mika, Baldocchi, Dennis, Barr, Alan, Beamesderfer, Eric, Marchesini, Luca Belelli, Bergeron, Onil, Beringer, Jason, Bernhofer, Christian, Berveiller, Daniel, Billesbach, Dave, Black, Thomas Andrew, Blanken, Peter D, Bohrer, Gil, Boike, Julia, Bolstad, Paul V, Bonal, Damien, Bonnefond, Jean-Marc, Bowling, David R, Bracho, Rosvel, Brodeur, Jason, Brümmer, Christian, Buchmann, Nina, Burban, Benoit, Burns, Sean P, Buysse, Pauline, Cale, Peter, Cavagna, Mauro, Cellier, Pierre, Chen, Shiping, Chini, Isaac, Christensen, Torben R, Cleverly, James, Collalti, Alessio, Consalvo, Claudia, Cook, Bruce D, Cook, David, Coursolle, Carole, Cremonese, Edoardo, Curtis, Peter S, D'Andrea, Ettore, da Rocha, Humberto, Dai, Xiaoqin, Davis, Kenneth J, Cinti, Bruno De, Grandcourt, Agnes de, Ligne, Anne De, De Oliveira, Raimundo C, Delpierre, Nicolas, Desai, Ankur R, Di Bella, Carlos Marcelo, Tommasi, Paul di, Dolman, Han, Domingo, Francisco, Dong, Gang, Dore, Sabina, Duce, Pierpaolo, Dufrêne, Eric, Dunn, Allison, Dušek, Jiří, Eamus, Derek, Eichelmann, Uwe, ElKhidir, Hatim Abdalla M, Eugster, Werner, Ewenz, Cacilia M, Ewers, Brent, Famulari, Daniela, Fares, Silvano, Feigenwinter, Iris, Feitz, Andrew, Fensholt, Rasmus, Filippa, Gianluca, Fischer, Marc, Frank, John, Galvagno, Marta, and Gharun, Mana

Abstract

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

Published
2020

26. TRY plant trait database – enhanced coverage and open access

Author

Kattge, Jens, Bönisch, Gerhard, Díaz, Sandra, Lavorel, Sandra, Prentice, Iain Colin, Leadley, Paul, Tautenhahn, Susanne, Werner, Gijsbert DA, Aakala, Tuomas, Abedi, Mehdi, Acosta, Alicia TR, Adamidis, George C, Adamson, Kairi, Aiba, Masahiro, Albert, Cécile H, Alcántara, Julio M, C, Carolina Alcázar, Aleixo, Izabela, Ali, Hamada, Amiaud, Bernard, Ammer, Christian, Amoroso, Mariano M, Anand, Madhur, Anderson, Carolyn, Anten, Niels, Antos, Joseph, Apgaua, Deborah Mattos Guimarães, Ashman, Tia‐Lynn, Asmara, Degi Harja, Asner, Gregory P, Aspinwall, Michael, Atkin, Owen, Aubin, Isabelle, Baastrup‐Spohr, Lars, Bahalkeh, Khadijeh, Bahn, Michael, Baker, Timothy, Baker, William J, Bakker, Jan P, Baldocchi, Dennis, Baltzer, Jennifer, Banerjee, Arindam, Baranger, Anne, Barlow, Jos, Barneche, Diego R, Baruch, Zdravko, Bastianelli, Denis, Battles, John, Bauerle, William, Bauters, Marijn, Bazzato, Erika, Beckmann, Michael, Beeckman, Hans, Beierkuhnlein, Carl, Bekker, Renee, Belfry, Gavin, Belluau, Michael, Beloiu, Mirela, Benavides, Raquel, Benomar, Lahcen, Berdugo‐Lattke, Mary Lee, Berenguer, Erika, Bergamin, Rodrigo, Bergmann, Joana, Carlucci, Marcos Bergmann, Berner, Logan, Bernhardt‐Römermann, Markus, Bigler, Christof, Bjorkman, Anne D, Blackman, Chris, Blanco, Carolina, Blonder, Benjamin, Blumenthal, Dana, Bocanegra‐González, Kelly T, Boeckx, Pascal, Bohlman, Stephanie, Böhning‐Gaese, Katrin, Boisvert‐Marsh, Laura, Bond, William, Bond‐Lamberty, Ben, Boom, Arnoud, Boonman, Coline CF, Bordin, Kauane, Boughton, Elizabeth H, Boukili, Vanessa, Bowman, David MJS, Bravo, Sandra, Brendel, Marco Richard, Broadley, Martin R, Brown, Kerry A, Bruelheide, Helge, Brumnich, Federico, Bruun, Hans Henrik, Bruy, David, Buchanan, Serra W, Bucher, Solveig Franziska, Buchmann, Nina, Buitenwerf, Robert, Bunker, Daniel E, and Bürger, Jana

Subjects
Climate Change Impacts and Adaptation, Biological Sciences, Ecology, Environmental Sciences, Access to Information, Biodiversity, Ecosystem, Plants, data coverage, data integration, data representativeness, functional diversity, plant traits, TRY plant trait database, Nutrient Network, Biological sciences, Earth sciences, Environmental sciences
Abstract

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Published
2020

31. Towards long-term standardised carbon and greenhouse gas observations for monitoring Europe’s terrestrial ecosystems: a review

Author

Franz, Daniela, Acosta, Manuel, Altimir, Núria, Arriga, Nicola, Arrouays, Dominique, Aubinet, Marc, Aurela, Mika, Ayres, Edward, López-Ballesteros, Ana, Barbaste, Mireille, Berveiller, Daniel, Biraud, Sébastien, Boukir, Hakima, Brown, Timothy, Brümmer, Christian, Buchmann, Nina, Burba, George, Carrara, Arnaud, Cescatti, Allessandro, Ceschia, Eric, Clement, Robert, Cremonese, Edoardo, Crill, Patrick, Darenova, Eva, Dengel, Sigrid, D’Odorico, Petra, Filippa, Gianluca, Fleck, Stefan, Fratini, Gerardo, Fuß, Roland, Gielen, Bert, Gogo, Sébastien, Grace, John, Graf, Alexander, Grelle, Achim, Gross, Patrick, Grünwald, Thomas, Haapanala, Sami, Hehn, Markus, Heinesch, Bernard, Heiskanen, Jouni, Herbst, Mathias, Herschlein, Christine, Hörtnagl, Lukas, Hufkens, Koen, Ibrom, Andreas, Jolivet, Claudy, Joly, Lilian, Jones, Michael, Kiese, Ralf, Klemedtsson, Leif, Kljun, Natascha, Klumpp, Katja, Kolari, Pasi, Kolle, Olaf, Kowalski, Andrew, Kutsch, Werner, Laurila, Tuomas, de Ligne, Anne, Linder, Sune, Lindroth, Anders, Lohila, Annalea, Longdoz, Bernhard, Mammarella, Ivan, Manise, Tanguy, Jiménez, Sara Maraňón, Matteucci, Giorgio, Mauder, Matthias, Meier, Philip, Merbold, Lutz, Mereu, Simone, Metzger, Stefan, Migliavacca, Mirco, Mölder, Meelis, Montagnani, Leonardo, Moureaux, Christine, Nelson, David, Nemitz, Eiko, Nicolini, Giacomo, Nilsson, Mats B, de Beeck, Maarten Op, Osborne, Bruce, Löfvenius, Mikaell Ottosson, Pavelka, Marian, Peichl, Matthias, Peltola, Olli, Pihlatie, Mari, Pitacco, Andrea, Pokorný, Radek, Pumpanen, Jukka, Ratié, Céline, Rebmann, Corinna, Roland, Marilyn, Sabbatini, Simone, Saby, Nicolas PA, Saunders, Matthew, Schmid, Hans Peter, Schrumpf, Marion, Sedlák, Pavel, and Ortiz, Penelope Serrano

Subjects
Agriculture, Land and Farm Management, Agricultural, Veterinary and Food Sciences, Climate Action, ICOS, GHG exchange, carbon cycle, standardised monitoring, observational network, Agronomy & Agriculture, Agriculture, land and farm management
Abstract

Research infrastructures play a key role in launching a new generation of integrated long-Term, geographically distributed observation programmes designed to monitor climate change, better understand its impacts on global ecosystems, and evaluate possible mitigation and adaptation strategies. The pan-European Integrated Carbon Observation System combines carbon and greenhouse gas (GHG; CO 2 , CH 4 , N 2 O, H 2 O) observations within the atmosphere, terrestrial ecosystems and oceans. High-precision measurements are obtained using standardised methodologies, are centrally processed and openly available in a traceable and verifiable fashion in combination with detailed metadata. The Integrated Carbon Observation System ecosystem station network aims to sample climate and land-cover variability across Europe. In addition to GHG flux measurements, a large set of complementary data (including management practices, vegetation and soil characteristics) is collected to support the interpretation, spatial upscaling and modelling of observed ecosystem carbon and GHG dynamics. The applied sampling design was developed and formulated in protocols by the scientific community, representing a trade-off between an ideal dataset and practical feasibility. The use of open-Access, high-quality and multi-level data products by different user communities is crucial for the Integrated Carbon Observation System in order to achieve its scientific potential and societal value.

Published
2018

38. Reply to: Plant traits alone are good predictors of ecosystem properties when used carefully

Author

van der Plas, Fons, Schröder-Georgi, Thomas, Weigelt, Alexandra, Barry, Kathryn, Meyer, Sebastian, Alzate, Adriana, Barnard, Romain L., Buchmann, Nina, de Kroon, Hans, Ebeling, Anne, Eisenhauer, Nico, Engels, Christof, Fischer, Markus, Gleixner, Gerd, Hildebrandt, Anke, Koller-France, Eva, Leimer, Sophia, Milcu, Alexandru, Mommer, Liesje, Niklaus, Pascal A., Oelmann, Yvonne, Roscher, Christiane, Scherber, Christoph, Scherer-Lorenzen, Michael, Scheu, Stefan, Schmid, Bernhard, Schulze, Ernst-Detlef, Temperton, Vicky, Tscharntke, Teja, Voigt, Winfried, Weisser, Wolfgang, Wilcke, Wolfgang, and Wirth, Christian

Published
2023
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39. Compound soil and atmospheric drought (CSAD) events and CO2 fluxes of a mixed deciduous forest: the occurrence, impact, and temporal contribution of main drivers.

Author

Scapucci, Liliana, Shekhar, Ankit, Aranda-Barranco, Sergio, Bolshakova, Anastasiia, Hörtnagl, Lukas, Gharun, Mana, and Buchmann, Nina

Abstract

With global warming, forests are increasingly exposed to "compound soil and atmospheric drought" (CSAD) events, characterized by low soil water content (SWC) and high vapour pressure deficit (VPD). Such CSAD events trigger responses in both ecosystem and forest-floor CO2 fluxes, which we know little about. In this study, we used multi-year daily and daytime above-canopy (18 years; 2005–2022) and daily forest-floor (5 years; 2018–2022) eddy covariance CO2 fluxes from a Swiss forest site by the name of CH-Lae (a mixed deciduous montane forest). The objectives were (1) to characterize CSAD events at CH-Lae, (2) to quantify the impact of CSAD events on ecosystem and forest-floor CO2 fluxes, and (3) to identify the major drivers and their temporal contributions to changing ecosystem and forest-floor CO2 fluxes during CSAD events and CSAD growing seasons. Our results showed that the growing seasons of 2015, 2018, and 2022 were the three driest at CH-Lae since 2005 (referred to as the CSAD years), exhibiting similar intensity and duration of the CSAD events but considerably different pre-drought conditions. The CSAD events reduced daily mean net ecosystem productivity (NEP) in all 3 CSAD years by about 38 % compared to the long-term mean, with the highest reduction observed during 2022 (41 %). This reduction in daily mean NEP was largely due to decreased gross primary productivity (GPP; > 16 % below the long-term mean) rather than increased ecosystem respiration (Reco) during CSAD events. Furthermore, forest-floor respiration (Rff) decreased during the CSAD events in 2018 and 2022 (with no measurements in 2015), with a larger reduction in 2022 (41 %) than in 2018 (16 %), relative to the long-term mean (2019–2021). Using data-driven machine learning methods, we identified the major drivers of NEP and Rff during CSAD events. While daytime mean NEP (NEPDT) during the 2015 and 2018 CSAD events was limited by VPD and SWC, respectively, NEPDT during the 2022 CSAD event was strongly limited by both SWC and VPD. Air temperature had negative effects, while net radiation showed positive effects on NEPDT during all CSAD events. Daily mean Rff during the 2018 CSAD event was driven by soil temperature and SWC but was severely limited by SWC during the 2022 CSAD event. We found that a multi-layer analysis of CO2 fluxes in forests is necessary to better understand forest responses to CSAD events, particularly if the first signs of NEP acclimation to CSAD events – evident in our forest – are also found elsewhere. We conclude that CSAD events have multiple drivers with different temporal contributions, making predictions about site-specific CSAD events and long-term forest responses to such conditions more challenging. [ABSTRACT FROM AUTHOR]

Published
2024
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40. Altered energy partitioning across terrestrial ecosystems in the European drought year 2018

Author

Graf, Alexander, Klosterhalfen, Anne, Arriga, Nicola, Bernhofer, Christian, Bogena, Heye, Bornet, Frédéric, Brüggemann, Nicolas, Brümmer, Christian, Buchmann, Nina, Chi, Jinshu, Chipeaux, Christophe, Cremonese, Edoardo, Cuntz, Matthias, Dušek, Jiří, El-Madany, Tarek S., Fares, Silvano, Fischer, Milan, Foltýnová, Lenka, Gharun, Mana, Ghiasi, Shiva, Gielen, Bert, Gottschalk, Pia, Grünwald, Thomas, Heinemann, Günther, Heinesch, Bernard, Heliasz, Michal, Holst, Jutta, Hörtnagl, Lukas, Ibrom, Andreas, Ingwersen, Joachim, Jurasinski, Gerald, Klatt, Janina, Knohl, Alexander, Koebsch, Franziska, Konopka, Jan, Korkiakoski, Mika, Kowalska, Natalia, Kremer, Pascal, Kruijt, Bart, Lafont, Sebastien, Léonard, Joël, De Ligne, Anne, Longdoz, Bernard, Loustau, Denis, Magliulo, Vincenzo, Mammarella, Ivan, Manca, Giovanni, Mauder, Matthias, Migliavacca, Mirco, Mölder, Meelis, Neirynck, Johan, Ney, Patrizia, Nilsson, Mats, Paul-Limoges, Eugénie, Peichl, Matthias, Pitacco, Andrea, Poyda, Arne, Rebmann, Corinna, Roland, Marilyn, Sachs, Torsten, Schmidt, Marius, Schrader, Frederik, Siebicke, Lukas, Šigut, Ladislav, Tuittila, Eeva-Stiina, Varlagin, Andrej, Vendrame, Nadia, Vincke, Caroline, Völksch, Ingo, Weber, Stephan, Wille, Christian, Wizemann, Hans-Dieter, Zeeman, Matthias, and Vereecken, Harry

Published
2020

41. Sensitivity of gross primary productivity to climatic drivers during the summer drought of 2018 in Europe

Author

Fu, Zheng, Ciais, Philippe, Bastos, Ana, Stoy, Paul C., Yang, Hui, Green, Julia K., Wang, Bingxue, Yu, Kailiang, Huang, Yuanyuan, Knohl, Alexander, Šigut, Ladislav, Gharun, Mana, Cuntz, Matthias, Arriga, Nicola, Roland, Marilyn, Peichl, Matthias, Migliavacca, Mirco, Cremonese, Edoardo, Varlagin, Andrej, Brümmer, Christian, de la Motte, Louis Gourlez, Fares, Silvano, Buchmann, Nina, El-Madany, Tarek S., Pitacco, Andrea, Vendrame, Nadia, Li, Zhaolei, Vincke, Caroline, Magliulo, Enzo, and Koebsch, Franziska

Published
2020

43. Climate and soils together regulate photosynthetic carbon isotope discrimination within C3 plants worldwide

Author

Cornwell, William K, Wright, Ian J, Turner, Joel, Maire, Vincent, Barbour, Margaret M, Cernusak, Lucas A, Dawson, Todd, Ellsworth, David, Farquhar, Graham D, Griffiths, Howard, Keitel, Claudia, Knohl, Alexander, Reich, Peter B, Williams, David G, Bhaskar, Radika, Cornelissen, Johannes HC, Richards, Anna, Schmidt, Susanne, Valladares, Fernando, Körner, Christian, Schulze, Ernst‐Detlef, Buchmann, Nina, and Santiago, Louis S

Subjects
Climate Action, carbon isotopes, environmental drivers, global, leaf traits, leaves, soil, Ecology
Abstract

Aim: Within C3 plants, photosynthesis is a balance between CO2 supply from the atmosphere via stomata and demand by enzymes within chloroplasts. This process is dynamic and a complex but crucial aspect of photosynthesis. We sought to understand the spatial pattern in CO2 supply–demand balance on a global scale, via analysis of stable isotopes of carbon within leaves (Δ13C), which provide an integrative record of CO2 drawdown during photosynthesis. LocationGlobal. Time period1951–2011. Major taxa studiedVascular plants. Methods: We assembled a database of leaf carbon isotope ratios containing 3,979 species–site combinations from across the globe, including 3,645 for C3 species. We examined a wide array of potential climate and soil drivers of variation in Δ13C. Results: The strongest drivers of carbon isotope discrimination at the global scale included atmospheric pressure, potential evapotranspiration and soil pH, which explained 44% of the variation in Δ13C. Addition of eight more climate and soil variables (each explaining small but highly significant amounts of variation) increased the explained variation to 60%. On top of this, the largest plant trait effect was leaf nitrogen per area, which explained 11% of Δ13C variation. Main conclusions: By considering variation in Δ13C at a considerably larger scale than previously, we were able to identify and quantify key drivers in CO2 supply–demand balance previously unacknowledged. Of special note is the key role of soil properties, with greater discrimination on low-pH and high-silt soils. Unlike other plant traits, which show typically wide variation within sets of coexisting species, the global pattern in carbon stable isotope ratios is much more conservative; there is relatively narrow variation in time-integrated CO2 concentrations at the site of carboxylation among plants in a given soil and climate.

Published
2018

44. Crops, Nitrogen, Water: Are Legumes Friend, Foe, or Misunderstood Ally?

Author

Adams, Mark A, Buchmann, Nina, Sprent, Janet, Buckley, Thomas N, and Turnbull, Tarryn L

Subjects
Zero Hunger, Biological Transport, Crops, Agricultural, Fabaceae, Nitrogen, Nitrogen Fixation, Plant Breeding, Plant Stomata, Water, crops, energy–water–food nexus, grain legumes, nitrogen, water use efficiency, Ecology, Plant Biology, Crop and Pasture Production, Plant Biology & Botany
Abstract

Biological nitrogen fixation (BNF) by crop legumes reduces demand for industrial nitrogen fixation (INF). Nonetheless, rates of BNF in agriculture remain low, with strong negative feedback to BNF from reactive soil nitrogen (N) and drought. We show that breeding for yield has resulted in strong relationships between photosynthesis and leaf N in non-leguminous crops, whereas grain legumes show strong relations between leaf N and water use efficiency (WUE). We contrast these understandings with other studies that draw attention to the water costs of grain legume crops, and their potential for polluting the biosphere with N. We propose that breeding grain legumes for reduced stomatal conductance can increase WUE without compromising production or BNF. Legume crops remain a better bet than relying on INF.

Published
2018

45. Contrasting responses of crop legumes and cereals to nitrogen availability

Author

Adams, Mark A, Buckley, Thomas N, Salter, William T, Buchmann, Nina, Blessing, Carola H, and Turnbull, Tarryn L

Subjects
Plant Biology, Biological Sciences, Crops, Agricultural, Edible Grain, Fabaceae, Nitrogen, Photosynthesis, Plant Stomata, Water, breeding, crops, legumes, photosynthesis, stomatal conductance, water-use efficiency, Agricultural and Veterinary Sciences, Plant Biology & Botany, Plant biology, Climate change impacts and adaptation, Ecological applications
Abstract

In nonagricultural systems, the relationship between intrinsic water-use efficiency (WUEi ) and leaf nitrogen (Narea ) is known to be stronger for legumes than for nonlegumes. We tested whether these relationships are retained for major agricultural legumes and nonlegumes. We compared the response to N nutrition of WUEi (and its component parts, photosynthesis (Asat ) and stomatal conductance (gs )) for legumes Cicer arietinum, Glycine max, Lupinus alba and Vicia faba, nonlegume dicots Brassica napus and Helianthus annus, and nonlegume cereals Hordeum vulgare and Triticum aestivum. Surprisingly, and in contrast to studied cereals and nonlegume dicots, Narea was positively related to photosynthesis in the legumes, explaining nearly half of the variance in Asat . WUEi was tightly coupled to Narea for agricultural legumes and nonlegume dicots, but not for cereal crops. Our analysis suggests that breeding efforts to reduce gs in legumes could increase WUEi by 120-218% while maintaining Asat at nonlegume values. Physiologically informed breeding of legumes can enhance sustainable agriculture by reducing requirements for water and N.

Published
2018

46. Development of Plant Communities in Time

Author

Schulze, Ernst-Detlef, Beck, Erwin, Buchmann, Nina, Clemens, Stephan, Müller-Hohenstein, Klaus, Scherer-Lorenzen, Michael, Schulze, Ernst-Detlef, Beck, Erwin, Buchmann, Nina, Clemens, Stephan, Müller-Hohenstein, Klaus, Scherer-Lorenzen, Michael, Arneth, Almut, With Contrib. by, Zähle, Sönke, With Contrib. by, Sierra, Carlos, With Contrib. by, Schäfer, Martin, With Contrib. by, and Dormann, Carsten, With Contrib. by

Published
2019
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47. Global Change and Terrestrial Ecosystems

Author

Schulze, Ernst-Detlef, Beck, Erwin, Buchmann, Nina, Clemens, Stephan, Müller-Hohenstein, Klaus, Scherer-Lorenzen, Michael, Schulze, Ernst-Detlef, Beck, Erwin, Buchmann, Nina, Clemens, Stephan, Müller-Hohenstein, Klaus, Scherer-Lorenzen, Michael, Arneth, Almut, With Contrib. by, Zähle, Sönke, With Contrib. by, Sierra, Carlos, With Contrib. by, Schäfer, Martin, With Contrib. by, and Dormann, Carsten, With Contrib. by

Published
2019
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48. Dynamic Global Vegetation Models : Contribution by S. Zaehle

Author

Schulze, Ernst-Detlef, Beck, Erwin, Buchmann, Nina, Clemens, Stephan, Müller-Hohenstein, Klaus, Scherer-Lorenzen, Michael, Schulze, Ernst-Detlef, Beck, Erwin, Buchmann, Nina, Clemens, Stephan, Müller-Hohenstein, Klaus, Scherer-Lorenzen, Michael, Arneth, Almut, With Contrib. by, Zähle, Sönke, With Contrib. by, Sierra, Carlos, With Contrib. by, Schäfer, Martin, With Contrib. by, and Dormann, Carsten, With Contrib. by

Published
2019
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49. Global Biogeochemical Cycles

Author

Schulze, Ernst-Detlef, Beck, Erwin, Buchmann, Nina, Clemens, Stephan, Müller-Hohenstein, Klaus, Scherer-Lorenzen, Michael, Schulze, Ernst-Detlef, Beck, Erwin, Buchmann, Nina, Clemens, Stephan, Müller-Hohenstein, Klaus, Scherer-Lorenzen, Michael, Arneth, Almut, With Contrib. by, Zähle, Sönke, With Contrib. by, Sierra, Carlos, With Contrib. by, Schäfer, Martin, With Contrib. by, and Dormann, Carsten, With Contrib. by

Published
2019
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50. Spatial Distribution of Plants and Plant Communities

Author

Schulze, Ernst-Detlef, Beck, Erwin, Buchmann, Nina, Clemens, Stephan, Müller-Hohenstein, Klaus, Scherer-Lorenzen, Michael, Schulze, Ernst-Detlef, Beck, Erwin, Buchmann, Nina, Clemens, Stephan, Müller-Hohenstein, Klaus, Scherer-Lorenzen, Michael, Arneth, Almut, With Contrib. by, Zähle, Sönke, With Contrib. by, Sierra, Carlos, With Contrib. by, Schäfer, Martin, With Contrib. by, and Dormann, Carsten, With Contrib. by

Published
2019
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