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2. The ABCflux database: Arctic–boreal CO2 flux observations and ancillary information aggregated to monthly time steps across terrestrial ecosystems

Author

Virkkala, Anna-Maria, Natali, Susan M, Rogers, Brendan M, Watts, Jennifer D, Savage, Kathleen, Connon, Sara June, Mauritz, Marguerite, Schuur, Edward AG, Peter, Darcy, Minions, Christina, Nojeim, Julia, Commane, Roisin, Emmerton, Craig A, Goeckede, Mathias, Helbig, Manuel, Holl, David, Iwata, Hiroki, Kobayashi, Hideki, Kolari, Pasi, López-Blanco, Efrén, Marushchak, Maija E, Mastepanov, Mikhail, Merbold, Lutz, Parmentier, Frans-Jan W, Peichl, Matthias, Sachs, Torsten, Sonnentag, Oliver, Ueyama, Masahito, Voigt, Carolina, Aurela, Mika, Boike, Julia, Celis, Gerardo, Chae, Namyi, Christensen, Torben R, Bret-Harte, M Syndonia, Dengel, Sigrid, Dolman, Han, Edgar, Colin W, Elberling, Bo, Euskirchen, Eugenie, Grelle, Achim, Hatakka, Juha, Humphreys, Elyn, Järveoja, Järvi, Kotani, Ayumi, Kutzbach, Lars, Laurila, Tuomas, Lohila, Annalea, Mammarella, Ivan, Matsuura, Yojiro, Meyer, Gesa, Nilsson, Mats B, Oberbauer, Steven F, Park, Sang-Jong, Petrov, Roman, Prokushkin, Anatoly S, Schulze, Christopher, St. Louis, Vincent L, Tuittila, Eeva-Stiina, Tuovinen, Juha-Pekka, Quinton, William, Varlagin, Andrej, Zona, Donatella, and Zyryanov, Viacheslav I

Subjects
Earth Sciences, Physical Geography and Environmental Geoscience, Atmospheric Sciences, Geoinformatics, Geochemistry, Atmospheric sciences, Physical geography and environmental geoscience
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, 10.3334/ORNLDAAC/1934). Copyright:

Published
2022

3. 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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7. Interannual and seasonal variability of the air–sea CO2 exchange at Utö in the coastal region of the Baltic Sea.

Author

Honkanen, Martti, Aurela, Mika, Hatakka, Juha, Haraguchi, Lumi, Kielosto, Sami, Mäkelä, Timo, Seppälä, Jukka, Siiriä, Simo-Matti, Stenbäck, Ken, Tuovinen, Juha-Pekka, Ylöstalo, Pasi, and Laakso, Lauri

Subjects
ATMOSPHERIC carbon dioxide, WIND speed measurement, WATER chemistry, CARBON dioxide, MIXING height (Atmospheric chemistry)
Abstract

Oceans alleviate the accumulation of atmospheric CO 2 by absorbing approximately a quarter of all anthropogenic emissions. In the deep oceans, carbon uptake is dominated by aquatic phase chemistry, whereas in biologically active coastal seas the marine ecosystem and biogeochemistry play an important role in the carbon uptake. Coastal seas are hotspots of organic and inorganic matter transport between the land and the oceans, and thus they are important for the marine carbon cycling. In this study, we investigate the net air–sea CO 2 exchange at the Utö Atmospheric and Marine Research Station, located at the southern edge of the Archipelago Sea within the Baltic Sea, using the data collected during 2017–2021. The air–sea fluxes of CO 2 were measured using the eddy covariance technique, supported by the flux parameterization based on the p CO 2 and wind speed measurements. During the spring–summer months (April–August), the sea was gaining carbon dioxide from the atmosphere, with the highest monthly sink fluxes typically occurring in May, being -0.26 µ mol m -2 s -1 on average. The sea was releasing the CO 2 to the atmosphere in September–March, and the highest source fluxes were typically observed in September, being 0.42 µ mol m -2 s -1 on average. On an annual basis, the study region was found to be a net source of atmospheric CO 2 , and on average, the annual net exchange was 27.1 gC m -1 yr -1 , which is comparable to the exchange observed in the Gulf of Bothnia, the Baltic Sea. The annual net air–sea CO 2 exchanges varied between 18.2 (2018) and 39.1 gC m -1 yr -1 (2017). During the coldest year, 2017, the spring–summer sink fluxes remained low compared to the other years, as a result of relatively high seawater p CO 2 in summer, which never fell below 220 µ atm during that year. The spring–summer phytoplankton blooms of 2017 were weak, possibly due to the cloudy summer and deeply mixed surface layer, which restrained the photosynthetic fixation of dissolved inorganic carbon in the surface waters. The algal blooms in spring–summer 2018 and the consequent p CO 2 drawdown were strong, fueled by high pre-spring nutrient concentrations. The systematic positive annual CO 2 balances suggest that our coastal study site is affected by carbon flows originating from elsewhere, possibly as organic carbon, which is remineralized and released to the atmosphere as CO 2. This coastal source of CO 2 fueled by the organic matter originating probably from land ecosystems stresses the importance of understanding the carbon cycling in the land–sea continuum. [ABSTRACT FROM AUTHOR]

Published
2024
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8. Early snowmelt significantly enhances boreal springtime carbon uptake.

Author

Pulliainen, Jouni, Aurela, Mika, Laurila, Tuomas, Aalto, Tuula, Takala, Matias, Salminen, Miia, Kulmala, Markku, Barr, Alan, Heimann, Martin, Lindroth, Anders, Laaksonen, Ari, Derksen, Chris, Mäkelä, Annikki, Markkanen, Tiina, Lemmetyinen, Juha, Susiluoto, Jouni, Dengel, Sigrid, Mammarella, Ivan, Tuovinen, Juha-Pekka, and Vesala, Timo

Subjects
carbon uptake, earth observation, snowmelt
Abstract

We determine the annual timing of spring recovery from space-borne microwave radiometer observations across northern hemisphere boreal evergreen forests for 1979-2014. We find a trend of advanced spring recovery of carbon uptake for this period, with a total average shift of 8.1 d (2.3 d/decade). We use this trend to estimate the corresponding changes in gross primary production (GPP) by applying in situ carbon flux observations. Micrometeorological CO2 measurements at four sites in northern Europe and North America indicate that such an advance in spring recovery would have increased the January-June GPP sum by 29 g⋅C⋅m-2 [8.4 g⋅C⋅m-2 (3.7%)/decade]. We find this sensitivity of the measured springtime GPP to the spring recovery to be in accordance with the corresponding sensitivity derived from simulations with a land ecosystem model coupled to a global circulation model. The model-predicted increase in springtime cumulative GPP was 0.035 Pg/decade [15.5 g⋅C⋅m-2 (6.8%)/decade] for Eurasian forests and 0.017 Pg/decade for forests in North America [9.8 g⋅C⋅m-2 (4.4%)/decade]. This change in the springtime sum of GPP related to the timing of spring snowmelt is quantified here for boreal evergreen forests.

Published
2017

11. Interannual and seasonal variability of the air-sea CO2 exchange at Utö in the coastal region of the Baltic Sea

Author

Honkanen, Martti, primary, Aurela, Mika, additional, Hatakka, Juha, additional, Haraguchi, Lumi, additional, Kielosto, Sami, additional, Mäkelä, Timo, additional, Seppälä, Jukka, additional, Siiriä, Simo-Matti, additional, Stenbäck, Ken, additional, Tuovinen, Juha-Pekka, additional, Ylöstalo, Pasi, additional, and Laakso, Lauri, additional

Published
2024
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12. Increasing contribution of peatlands to boreal evapotranspiration in a warming climate

Author

Helbig, Manuel, Waddington, James Michael, Alekseychik, Pavel, Amiro, Brian D., Aurela, Mika, Barr, Alan G., Black, T. Andrew, Blanken, Peter D., Carey, Sean K., Chen, Jiquan, Chi, Jinshu, Desai, Ankur R., Dunn, Allison, Euskirchen, Eugenie S., Flanagan, Lawrence B., Forbrich, Inke, Friborg, Thomas, Grelle, Achim, Harder, Silvie, Heliasz, Michal, Humphreys, Elyn R., Ikawa, Hiroki, Isabelle, Pierre-Erik, Iwata, Hiroki, Jassal, Rachhpal, Korkiakoski, Mika, Kurbatova, Juliya, Kutzbach, Lars, Lindroth, Anders, Löfvenius, Mikaell Ottosson, Lohila, Annalea, Mammarella, Ivan, Marsh, Philip, Maximov, Trofim, Melton, Joe R., Moore, Paul A., Nadeau, Daniel F., Nicholls, Erin M., Nilsson, Mats B., Ohta, Takeshi, Peichl, Matthias, Petrone, Richard M., Petrov, Roman, Prokushkin, Anatoly, Quinton, William L., Reed, David E., Roulet, Nigel T., Runkle, Benjamin R. K., Sonnentag, Oliver, Strachan, Ian B., Taillardat, Pierre, Tuittila, Eeva-Stiina, Tuovinen, Juha-Pekka, Turner, Jessica, Ueyama, Masahito, Varlagin, Andrej, Wilmking, Martin, Wofsy, Steven C., and Zyrianov, Vyacheslav

Published
2020
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13. The uncertain climate footprint of wetlands under human pressure

Author

Petrescu, Ana Maria Roxana, Lohila, Annalea, Tuovinen, Juha-Pekka, Baldocchi, Dennis D, Desai, Ankur R, Roulet, Nigel T, Vesala, Timo, Dolman, Albertus Johannes, Oechel, Walter C, Marcolla, Barbara, Friborg, Thomas, Rinne, Janne, Matthes, Jaclyn Hatala, Merbold, Lutz, Meijide, Ana, Kiely, Gerard, Sottocornola, Matteo, Sachs, Torsten, Zona, Donatella, Varlagin, Andrej, Lai, Derrick YF, Veenendaal, Elmar, Parmentier, Frans-Jan W, Skiba, Ute, Lund, Magnus, Hensen, Arjan, van Huissteden, Jacobus, Flanagan, Lawrence B, Shurpali, Narasinha J, Grünwald, Thomas, Humphreys, Elyn R, Jackowicz-Korczyński, Marcin, Aurela, Mika A, Laurila, Tuomas, Grüning, Carsten, Corradi, Chiara AR, Schrier-Uijl, Arina P, Christensen, Torben R, Tamstorf, Mikkel P, Mastepanov, Mikhail, Martikainen, Pertti J, Verma, Shashi B, Bernhofer, Christian, and Cescatti, Alessandro

Subjects
Climate Action, Life on Land, Carbon Dioxide, Climate, Climate Change, Ecology, Ecosystem, Geography, Human Activities, Humans, Methane, Models, Theoretical, Nitrous Oxide, Plants, Temperature, Uncertainty, Wetlands, wetland conversion, methane, radiative forcing, carbon dioxide
Abstract

Significant climate risks are associated with a positive carbon-temperature feedback in northern latitude carbon-rich ecosystems, making an accurate analysis of human impacts on the net greenhouse gas balance of wetlands a priority. Here, we provide a coherent assessment of the climate footprint of a network of wetland sites based on simultaneous and quasi-continuous ecosystem observations of CO2 and CH4 fluxes. Experimental areas are located both in natural and in managed wetlands and cover a wide range of climatic regions, ecosystem types, and management practices. Based on direct observations we predict that sustained CH4 emissions in natural ecosystems are in the long term (i.e., several centuries) typically offset by CO2 uptake, although with large spatiotemporal variability. Using a space-for-time analogy across ecological and climatic gradients, we represent the chronosequence from natural to managed conditions to quantify the "cost" of CH4 emissions for the benefit of net carbon sequestration. With a sustained pulse-response radiative forcing model, we found a significant increase in atmospheric forcing due to land management, in particular for wetland converted to cropland. Our results quantify the role of human activities on the climate footprint of northern wetlands and call for development of active mitigation strategies for managed wetlands and new guidelines of the Intergovernmental Panel on Climate Change (IPCC) accounting for both sustained CH4 emissions and cumulative CO2 exchange.

Published
2015

14. 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, Gharun, Mana, Gianelle, Damiano, Gielen, Bert, Gioli, Beniamino, Gitelson, Anatoly, Goded, Ignacio, Goeckede, Mathias, Goldstein, Allen H., Gough, Christopher M., Goulden, Michael L., Graf, Alexander, Griebel, Anne, Gruening, Carsten, Grünwald, Thomas, Hammerle, Albin, Han, Shijie, Han, Xingguo, Hansen, Birger Ulf, Hanson, Chad, Hatakka, Juha, He, Yongtao, Hehn, Markus, Heinesch, Bernard, Hinko-Najera, Nina, Hörtnagl, Lukas, Hutley, Lindsay, Ibrom, Andreas, Ikawa, Hiroki, Jackowicz-Korczynski, Marcin, Janouš, Dalibor, Jans, Wilma, Jassal, Rachhpal, Jiang, Shicheng, Kato, Tomomichi, Khomik, Myroslava, Klatt, Janina, Knohl, Alexander, Knox, Sara, Kobayashi, Hideki, Koerber, Georgia, Kolle, Olaf, Kosugi, Yoshiko, Kotani, Ayumi, Kowalski, Andrew, Kruijt, Bart, Kurbatova, Julia, Kutsch, Werner L., Kwon, Hyojung, Launiainen, Samuli, Laurila, Tuomas, Law, Bev, Leuning, Ray, Li, Yingnian, Liddell, Michael, Limousin, Jean-Marc, Lion, Marryanna, Liska, Adam J., Lohila, Annalea, López-Ballesteros, Ana, López-Blanco, Efrén, Loubet, Benjamin, Loustau, Denis, Lucas-Moffat, Antje, Lüers, Johannes, Ma, Siyan, Macfarlane, Craig, Magliulo, Vincenzo, Maier, Regine, Mammarella, Ivan, Manca, Giovanni, Marcolla, Barbara, Margolis, Hank A., Marras, Serena, Massman, William, Mastepanov, Mikhail, Matamala, Roser, Matthes, Jaclyn Hatala, Mazzenga, Francesco, McCaughey, Harry, McHugh, Ian, McMillan, Andrew M. S., Merbold, Lutz, Meyer, Wayne, Meyers, Tilden, Miller, Scott D., Minerbi, Stefano, Moderow, Uta, Monson, Russell K., Montagnani, Leonardo, Moore, Caitlin E., Moors, Eddy, Moreaux, Virginie, Moureaux, Christine, Munger, J. William, Nakai, Taro, Neirynck, Johan, Nesic, Zoran, Nicolini, Giacomo, Noormets, Asko, Northwood, Matthew, Nosetto, Marcelo, Nouvellon, Yann, Novick, Kimberly, Oechel, Walter, Olesen, Jørgen Eivind, Ourcival, Jean-Marc, Papuga, Shirley A., Parmentier, Frans-Jan, Paul-Limoges, Eugenie, Pavelka, Marian, Peichl, Matthias, Pendall, Elise, Phillips, Richard P., Pilegaard, Kim, Pirk, Norbert, Posse, Gabriela, Powell, Thomas, Prasse, Heiko, Prober, Suzanne M., Rambal, Serge, Rannik, Üllar, Raz-Yaseef, Naama, Rebmann, Corinna, Reed, David, de Dios, Victor Resco, Restrepo-Coupe, Natalia, Reverter, Borja R., Roland, Marilyn, Sabbatini, Simone, Sachs, Torsten, Saleska, Scott R., Sánchez-Cañete, Enrique P., Sanchez-Mejia, Zulia M., Schmid, Hans Peter, Schmidt, Marius, Schneider, Karl, Schrader, Frederik, Schroder, Ivan, Scott, Russell L., Sedlák, Pavel, Serrano-Ortíz, Penélope, Shao, Changliang, Shi, Peili, Shironya, Ivan, Siebicke, Lukas, Šigut, Ladislav, Silberstein, Richard, Sirca, Costantino, Spano, Donatella, Steinbrecher, Rainer, Stevens, Robert M., Sturtevant, Cove, Suyker, Andy, Tagesson, Torbern, Takanashi, Satoru, Tang, Yanhong, Tapper, Nigel, Thom, Jonathan, Tomassucci, Michele, Tuovinen, Juha-Pekka, Urbanski, Shawn, Valentini, Riccardo, van der Molen, Michiel, van Gorsel, Eva, van Huissteden, Ko, Varlagin, Andrej, Verfaillie, Joseph, Vesala, Timo, Vincke, Caroline, Vitale, Domenico, Vygodskaya, Natalia, Walker, Jeffrey P., Walter-Shea, Elizabeth, Wang, Huimin, Weber, Robin, Westermann, Sebastian, Wille, Christian, Wofsy, Steven, Wohlfahrt, Georg, Wolf, Sebastian, Woodgate, William, Li, Yuelin, Zampedri, Roberto, Zhang, Junhui, Zhou, Guoyi, Zona, Donatella, Agarwal, Deb, Biraud, Sebastien, Torn, Margaret, and Papale, Dario

Published
2021
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18. 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, Gharun, Mana, Gianelle, Damiano, Gielen, Bert, Gioli, Beniamino, Gitelson, Anatoly, Goded, Ignacio, Goeckede, Mathias, Goldstein, Allen H., Gough, Christopher M., Goulden, Michael L., Graf, Alexander, Griebel, Anne, Gruening, Carsten, Grünwald, Thomas, Hammerle, Albin, Han, Shijie, Han, Xingguo, Hansen, Birger Ulf, Hanson, Chad, Hatakka, Juha, He, Yongtao, Hehn, Markus, Heinesch, Bernard, Hinko-Najera, Nina, Hörtnagl, Lukas, Hutley, Lindsay, Ibrom, Andreas, Ikawa, Hiroki, Jackowicz-Korczynski, Marcin, Janouš, Dalibor, Jans, Wilma, Jassal, Rachhpal, Jiang, Shicheng, Kato, Tomomichi, Khomik, Myroslava, Klatt, Janina, Knohl, Alexander, Knox, Sara, Kobayashi, Hideki, Koerber, Georgia, Kolle, Olaf, Kosugi, Yoshiko, Kotani, Ayumi, Kowalski, Andrew, Kruijt, Bart, Kurbatova, Julia, Kutsch, Werner L., Kwon, Hyojung, Launiainen, Samuli, Laurila, Tuomas, Law, Bev, Leuning, Ray, Li, Yingnian, Liddell, Michael, Limousin, Jean-Marc, Lion, Marryanna, Liska, Adam J., Lohila, Annalea, López-Ballesteros, Ana, López-Blanco, Efrén, Loubet, Benjamin, Loustau, Denis, Lucas-Moffat, Antje, Lüers, Johannes, Ma, Siyan, Macfarlane, Craig, Magliulo, Vincenzo, Maier, Regine, Mammarella, Ivan, Manca, Giovanni, Marcolla, Barbara, Margolis, Hank A., Marras, Serena, Massman, William, Mastepanov, Mikhail, Matamala, Roser, Matthes, Jaclyn Hatala, Mazzenga, Francesco, McCaughey, Harry, McHugh, Ian, McMillan, Andrew M. S., Merbold, Lutz, Meyer, Wayne, Meyers, Tilden, Miller, Scott D., Minerbi, Stefano, Moderow, Uta, Monson, Russell K., Montagnani, Leonardo, Moore, Caitlin E., Moors, Eddy, Moreaux, Virginie, Moureaux, Christine, Munger, J. William, Nakai, Taro, Neirynck, Johan, Nesic, Zoran, Nicolini, Giacomo, Noormets, Asko, Northwood, Matthew, Nosetto, Marcelo, Nouvellon, Yann, Novick, Kimberly, Oechel, Walter, Olesen, Jørgen Eivind, Ourcival, Jean-Marc, Papuga, Shirley A., Parmentier, Frans-Jan, Paul-Limoges, Eugenie, Pavelka, Marian, Peichl, Matthias, Pendall, Elise, Phillips, Richard P., Pilegaard, Kim, Pirk, Norbert, Posse, Gabriela, Powell, Thomas, Prasse, Heiko, Prober, Suzanne M., Rambal, Serge, Rannik, Üllar, Raz-Yaseef, Naama, Rebmann, Corinna, Reed, David, Dios, Victor Resco de, Restrepo-Coupe, Natalia, Reverter, Borja R., Roland, Marilyn, Sabbatini, Simone, Sachs, Torsten, Saleska, Scott R., Sánchez-Cañete, Enrique P., Sanchez-Mejia, Zulia M., Schmid, Hans Peter, Schmidt, Marius, Schneider, Karl, Schrader, Frederik, Schroder, Ivan, Scott, Russell L., Sedlák, Pavel, Serrano-Ortíz, Penélope, Shao, Changliang, Shi, Peili, Shironya, Ivan, Siebicke, Lukas, Šigut, Ladislav, Silberstein, Richard, Sirca, Costantino, Spano, Donatella, Steinbrecher, Rainer, Stevens, Robert M., Sturtevant, Cove, Suyker, Andy, Tagesson, Torbern, Takanashi, Satoru, Tang, Yanhong, Tapper, Nigel, Thom, Jonathan, Tomassucci, Michele, Tuovinen, Juha-Pekka, Urbanski, Shawn, Valentini, Riccardo, van der Molen, Michiel, van Gorsel, Eva, van Huissteden, Ko, Varlagin, Andrej, Verfaillie, Joseph, Vesala, Timo, Vincke, Caroline, Vitale, Domenico, Vygodskaya, Natalia, Walker, Jeffrey P., Walter-Shea, Elizabeth, Wang, Huimin, Weber, Robin, Westermann, Sebastian, Wille, Christian, Wofsy, Steven, Wohlfahrt, Georg, Wolf, Sebastian, Woodgate, William, Li, Yuelin, Zampedri, Roberto, Zhang, Junhui, Zhou, Guoyi, Zona, Donatella, Agarwal, Deb, Biraud, Sebastien, Torn, Margaret, and Papale, Dario

Published
2020
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20. Interannual and seasonal variability of the air-sea CO2 exchange at Utö in the coastal region of the Baltic Sea.

Author

Honkanen, Martti, Aurela, Mika, Hatakka, Juha, Haraguchi, Lumi, Kielosto, Sami, Mäkelä, Timo, Seppälä, Jukka, Siiriä, Simo-Matti, Stenbäck, Ken, Tuovinen, Juha-Pekka, Ylöstalo, Pasi, and Laakso, Lauri

Subjects
ATMOSPHERIC carbon dioxide, WIND speed measurement, WATER chemistry, ALGAL blooms, CARBON cycle, ATMOSPHERE, BIOGEOCHEMISTRY
Abstract

Oceans alleviate the accumulation of atmospheric CO2 by absorbing approximately a quarter of all anthropogenic emissions. In the deep oceans, carbon uptake is dominated by aquatic phase chemistry, whereas in biologically active coastal seas the marine ecosystem and biogeochemistry play an important role in the carbon uptake. Coastal seas are hotspots of organic and inorganic matter transport between the land and the oceans, and thus important for the marine carbon cycling. In this study, we investigate the net air-sea CO2 exchange at the Utö Atmospheric and Marine Research Station, located at the southern edge of the Archipelago Sea within the Baltic Sea, using the data collected during 2017–2021. The air-sea fluxes of CO2 were measured using the eddy covariance technique, supported by the flux parametrization based on the p CO2 and wind speed measurements. During the spring-summer months (April–August), the sea was gaining carbon dioxide from the atmosphere, with the highest monthly sink fluxes typically occurring in May, being -0.26 μmol m-2 s-1 on average. The sea was releasing the CO2 to the atmosphere in September–March, and the highest source fluxes were typically observed in September, being 0.42 μmol m-2 s-1 on average. On the annual basis, the study region was found to be a net source of atmospheric CO2, and on average, the annual net exchange was 27.1 gC m-2 y-1, which is comparable to the exchange observed in the Gulf of Bothnia, the Baltic Sea. The annual net air-sea CO2 exchanges varied between 18.2 gC m-2 y-1 (2018) and 39.1 gC m-2 y-1 (2017). During the coldest year, 2017, the spring-summer sink fluxes remained low compared to the other years, as a result of relatively high seawater p CO2 in summer, which never fell below 220 μatm during that year. The spring-summer phytoplankton blooms of 2017 were weak, possibly due to the cloudy summer and deeply mixed surface layer, which restrained the photosynthetic fixation of dissolved inorganic carbon in the surface waters. The algal blooms in spring-summer 2018 and the consequent p CO2 drawdown were strong, fueled by high pre-spring nutrient concentrations. The systematic positive annual CO2 balances suggest that our coastal study site is affected by carbon flows originating from elsewhere, possibly as organic carbon which is remineralized and released to the atmosphere as CO2. This coastal source of CO2 fueled by the organic matter originating probably from land ecosystems stresses the importance of understanding the carbon cycling in the land-sea continuum. [ABSTRACT FROM AUTHOR]

Published
2024
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28. The effect of rainfall amount and timing on annual transpiration in a grazed savanna grassland

Author

Räsänen, Matti, primary, Aurela, Mika, additional, Vakkari, Ville, additional, Beukes, Johan P., additional, Tuovinen, Juha-Pekka, additional, Van Zyl, Pieter G., additional, Josipovic, Miroslav, additional, Siebert, Stefan J., additional, Laurila, Tuomas, additional, Kulmala, Markku, additional, Laakso, Lauri, additional, Rinne, Janne, additional, Oren, Ram, additional, and Katul, Gabriel, additional

Published
2022
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30. Peatland Heterogeneity Impacts on Regional Carbon Flux and Its Radiative Effect Within a Boreal Landscape

Author

Kou, Dan, primary, Virtanen, Tarmo, additional, Treat, Claire C., additional, Tuovinen, Juha‐Pekka, additional, Räsänen, Aleksi, additional, Juutinen, Sari, additional, Mikola, Juha, additional, Aurela, Mika, additional, Heiskanen, Lauri, additional, Heikkilä, Maija, additional, Weckström, Jan, additional, Juselius, Teemu, additional, Piilo, Sanna R., additional, Deng, Jia, additional, Zhang, Yu, additional, Chaudhary, Nitin, additional, Huang, Conghong, additional, Väliranta, Minna, additional, Biasi, Christina, additional, Liu, Xiangyu, additional, Guo, Mingyang, additional, Zhuang, Qianlai, additional, Korhola, Atte, additional, and Shurpali, Narasinha J., additional

Published
2022
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32. Variation in CO2 and CH4 fluxes among land cover types in heterogeneous Arctic tundra in northeastern Siberia

Author

Juutinen, Sari, primary, Aurela, Mika, additional, Tuovinen, Juha-Pekka, additional, Ivakhov, Viktor, additional, Linkosalmi, Maiju, additional, Räsänen, Aleksi, additional, Virtanen, Tarmo, additional, Mikola, Juha, additional, Nyman, Johanna, additional, Vähä, Emmi, additional, Loskutova, Marina, additional, Makshtas, Alexander, additional, and Laurila, Tuomas, additional

Published
2022
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33. Peatland Heterogeneity Impacts on Regional Carbon Flux and its Radiative Effect within a Northern Boreal Landscape

Author

Kou, Dan, Virtanen, Tarmo, Treat, Claire C., Tuovinen, Juha-Pekka, Räsänen, Aleksi, Juutinen, Sari, Mikola, Juha, Aurela, Mika, Heiskanen, Lauri, Heikkilä, Maija, Weckström, Jan, Juselius, Teemu, Piilo, Sanna R., Deng, Jia, Zhang, Yu, Chaudhary, Nitin, Huang, Conghong, Väliranta, Minna, Biasi, Christina, Guo, Mingyang, Zhuang, Qianlai, Korhola, Atte, and Shurpali, Narasinha J.

Subjects
boreal, landscape, peatland, heterogeneity, carbon, radiative effect
Abstract

Peatlands form part of the boreal landscapes exhibiting diverse types and microforms that have different characteristics of topography, hydrology, vegetation, and soil. Our understanding is still limited concerning how boreal peatlands, especially their inherent heterogeneities, affect the regional biosphere-atmosphere exchange of carbon and related climate effects, and what level of detail is needed to characterize them in land cover maps. By combining remote sensing information, field measurements, and biogeochemical modeling, we estimated that the peatlands within the study area (26% of the area) contributed 22% of the landscape-scale carbon dioxide uptake and 93% of methane emissions. We also showed that, among different land cover types, peatlands played the dominant role in the variability of radiative climate effect due to carbon exchanges. Possible aggregation and misclassification of peatland types could induce significant biases in the regional balances and their radiative effect, but the distinction of non-inundated dry and inundated wet peatland types could reduce these biases effectively.

Published
2022
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34. The ABCflux database: Arctic–boreal CO2 flux observations and ancillary information aggregated to monthly time steps across terrestrial ecosystems

Author

Virkkala​​​​​​​, Anna-Maria, Natali, Susan M., Rogers, Brendan M., Watts, Jennifer D., Savage, Kathleen, Connon, Sara June, Mauritz, Marguerite, Schuur, Edward A. G., Peter, Darcy, Minions, Christina, Nojeim, Julia, Commane, Roisin, Emmerton, Craig A., Goeckede, Mathias, Helbig, Manuel, Holl, David, Iwata, Hiroki, Kobayashi, Hideki, Kolari, Pasi, López-Blanco, Efrén, Marushchak, Maija E., Mastepanov, Mikhail, Merbold, Lutz, Parmentier, Frans-Jan W., Peichl, Matthias, Sachs, Torsten, Sonnentag, Oliver, Ueyama, Masahito, Voigt, Carolina, Aurela, Mika, Boike, Julia, Celis, Gerardo, Chae, Namyi, Christensen, Torben R., Bret-Harte, M. Syndonia, Dengel, Sigrid, Dolman, Han, Edgar, Colin W., Elberling, Bo, Euskirchen, Eugenie, Grelle, Achim, Hatakka, Juha, Humphreys, Elyn, Järveoja, Järvi, Kotani, Ayumi, Kutzbach, Lars, Laurila, Tuomas, Lohila, Annalea, Mammarella, Ivan, Matsuura, Yojiro, Meyer, Gesa, Nilsson, Mats B., Oberbauer, Steven F., Park, Sang-Jong, Petrov, Roman, Prokushkin, Anatoly S., Schulze, Christopher, St. Louis, Vincent L., Tuittila, Eeva-Stiina, Tuovinen, Juha-Pekka, Quinton, William, Varlagin, Andrej, Zona, Donatella, Zyryanov, Viacheslav I., Virkkala​​​​​​​, Anna-Maria, Natali, Susan M., Rogers, Brendan M., Watts, Jennifer D., Savage, Kathleen, Connon, Sara June, Mauritz, Marguerite, Schuur, Edward A. G., Peter, Darcy, Minions, Christina, Nojeim, Julia, Commane, Roisin, Emmerton, Craig A., Goeckede, Mathias, Helbig, Manuel, Holl, David, Iwata, Hiroki, Kobayashi, Hideki, Kolari, Pasi, López-Blanco, Efrén, Marushchak, Maija E., Mastepanov, Mikhail, Merbold, Lutz, Parmentier, Frans-Jan W., Peichl, Matthias, Sachs, Torsten, Sonnentag, Oliver, Ueyama, Masahito, Voigt, Carolina, Aurela, Mika, Boike, Julia, Celis, Gerardo, Chae, Namyi, Christensen, Torben R., Bret-Harte, M. Syndonia, Dengel, Sigrid, Dolman, Han, Edgar, Colin W., Elberling, Bo, Euskirchen, Eugenie, Grelle, Achim, Hatakka, Juha, Humphreys, Elyn, Järveoja, Järvi, Kotani, Ayumi, Kutzbach, Lars, Laurila, Tuomas, Lohila, Annalea, Mammarella, Ivan, Matsuura, Yojiro, Meyer, Gesa, Nilsson, Mats B., Oberbauer, Steven F., Park, Sang-Jong, Petrov, Roman, Prokushkin, Anatoly S., Schulze, Christopher, St. Louis, Vincent L., Tuittila, Eeva-Stiina, Tuovinen, Juha-Pekka, Quinton, William, Varlagin, Andrej, Zona, Donatella, and Zyryanov, Viacheslav I.

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 th

Published
2022

35. Peatland Heterogeneity Impacts on Regional Carbon Flux and its Radiative Effect within a Boreal Landscape

Author

Kou, Dan, Virtanen, Tarmo, Treat, Claire C, Tuovinen, Juha‐Pekka, Räsänen, Aleksi, Juutinen, Sari, Mikola, Juha, Aurela, Mika, Heiskanen, Lauri, Heikkilä, Maija, Weckström, Jan, Juselius, Teemu, Piilo, Sanna R, Deng, Jia, Zhang, Yu, Chaudhary, Nitin, Huang, Conghong, Väliranta, Minna, Biasi, Christina, Liu, Xiangyu, Guo, Mingyang, Zhuang, Qianlai, Korhola, Atte, Shurpali, Narasinha J, Kou, Dan, Virtanen, Tarmo, Treat, Claire C, Tuovinen, Juha‐Pekka, Räsänen, Aleksi, Juutinen, Sari, Mikola, Juha, Aurela, Mika, Heiskanen, Lauri, Heikkilä, Maija, Weckström, Jan, Juselius, Teemu, Piilo, Sanna R, Deng, Jia, Zhang, Yu, Chaudhary, Nitin, Huang, Conghong, Väliranta, Minna, Biasi, Christina, Liu, Xiangyu, Guo, Mingyang, Zhuang, Qianlai, Korhola, Atte, and Shurpali, Narasinha J

Abstract

Peatlands, with high spatial variability in ecotypes and microforms, constitute a significant part of the boreal landscape and play an important role in the global carbon (C) cycle. However, the effects of this peatland heterogeneity within the boreal landscape are rarely quantified. Here, we use field-based measurements, high-resolution land cover classification, and biogeochemical and atmospheric models to estimate the atmosphere-ecosystem C fluxes and corresponding radiative effect (RE) for a boreal landscape (Kaamanen) in northern Finland. Our result shows that the Kaamanen catchment currently functioned as a sink of carbon dioxide (CO2) and a source of methane (CH4). Peatlands (26% of the area) contributed 22% of the total CO2 uptake and 89% of CH4 emissions; forests (61%) accounted for 78% of CO2 uptake and offset 6% of CH4 emissions; water bodies (13%) offset 7% of CO2 uptake and contributed 11% of CH4 emissions. The heterogeneity of peatlands accounted for 11%, 88%, and 75% of the area-weighted variability (deviation from the area-weighted mean among different land cover types (LCTs) within the catchment) in CO2 flux, CH4 flux, and the combined RE of CO2 and CH4 exchanges over the 25-yr time horizon, respectively. Aggregating peatland LCTs or misclassifying them as non-peatland LCTs can significantly (p < 0.05) bias the regional CH4 exchange and RE estimates, while differentiating between drier non-inundated and wetter inundated peatlands can effectively reduce the bias. Current land cover products lack such details in peatland heterogeneity, which would be needed to better constrain boreal C budgets and global C-climate feedbacks.

Published
2022

36. The ABCflux database:Arctic-boreal CO2flux observations and ancillary information aggregated to monthly time steps across terrestrial ecosystems

Author

Virkkala, Anna Maria, Natali, Susan M., Rogers, Brendan M., Watts, Jennifer D., Savage, Kathleen, Connon, Sara June, Mauritz, Marguerite, Schuur, Edward A.G., Peter, Darcy, Minions, Christina, Nojeim, Julia, Commane, Roisin, Emmerton, Craig A., Goeckede, Mathias, Helbig, Manuel, Holl, David, Iwata, Hiroki, Kobayashi, Hideki, Kolari, Pasi, López-Blanco, Efrén, Marushchak, Maija E., Mastepanov, Mikhail, Merbold, Lutz, Parmentier, Frans Jan W., Peichl, Matthias, Sachs, Torsten, Sonnentag, Oliver, Ueyama, Masahito, Voigt, Carolina, Aurela, Mika, Boike, Julia, Celis, Gerardo, Chae, Namyi, Christensen, Torben R., Bret-Harte, M. Syndonia, Dengel, Sigrid, Dolman, Han, Edgar, Colin W., Elberling, Bo, Euskirchen, Eugenie, Grelle, Achim, Hatakka, Juha, Humphreys, Elyn, Järveoja, Järvi, Kotani, Ayumi, Kutzbach, Lars, Laurila, Tuomas, Lohila, Annalea, Mammarella, Ivan, Matsuura, Yojiro, Meyer, Gesa, Nilsson, Mats B., Oberbauer, Steven F., Park, Sang Jong, Petrov, Roman, Prokushkin, Anatoly S., Schulze, Christopher, St. Louis, Vincent L., Tuittila, Eeva Stiina, Tuovinen, Juha Pekka, Quinton, William, Varlagin, Andrej, Zona, Donatella, Zyryanov, Viacheslav I., Virkkala, Anna Maria, Natali, Susan M., Rogers, Brendan M., Watts, Jennifer D., Savage, Kathleen, Connon, Sara June, Mauritz, Marguerite, Schuur, Edward A.G., Peter, Darcy, Minions, Christina, Nojeim, Julia, Commane, Roisin, Emmerton, Craig A., Goeckede, Mathias, Helbig, Manuel, Holl, David, Iwata, Hiroki, Kobayashi, Hideki, Kolari, Pasi, López-Blanco, Efrén, Marushchak, Maija E., Mastepanov, Mikhail, Merbold, Lutz, Parmentier, Frans Jan W., Peichl, Matthias, Sachs, Torsten, Sonnentag, Oliver, Ueyama, Masahito, Voigt, Carolina, Aurela, Mika, Boike, Julia, Celis, Gerardo, Chae, Namyi, Christensen, Torben R., Bret-Harte, M. Syndonia, Dengel, Sigrid, Dolman, Han, Edgar, Colin W., Elberling, Bo, Euskirchen, Eugenie, Grelle, Achim, Hatakka, Juha, Humphreys, Elyn, Järveoja, Järvi, Kotani, Ayumi, Kutzbach, Lars, Laurila, Tuomas, Lohila, Annalea, Mammarella, Ivan, Matsuura, Yojiro, Meyer, Gesa, Nilsson, Mats B., Oberbauer, Steven F., Park, Sang Jong, Petrov, Roman, Prokushkin, Anatoly S., Schulze, Christopher, St. Louis, Vincent L., Tuittila, Eeva Stiina, Tuovinen, Juha Pekka, Quinton, William, Varlagin, Andrej, Zona, Donatella, and Zyryanov, Viacheslav I.

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 te

Published
2022

43. Towards agricultural soil carbon monitoring, reporting, and verification through the Field Observatory Network (FiON)

Author

Nevalainen, Olli, primary, Niemitalo, Olli, additional, Fer, Istem, additional, Juntunen, Antti, additional, Mattila, Tuomas, additional, Koskela, Olli, additional, Kukkamäki, Joni, additional, Höckerstedt, Layla, additional, Mäkelä, Laura, additional, Jarva, Pieta, additional, Heimsch, Laura, additional, Vekuri, Henriikka, additional, Kulmala, Liisa, additional, Stam, Åsa, additional, Kuusela, Otto, additional, Gerin, Stephanie, additional, Viskari, Toni, additional, Vira, Julius, additional, Hyväluoma, Jari, additional, Tuovinen, Juha-Pekka, additional, Lohila, Annalea, additional, Laurila, Tuomas, additional, Heinonsalo, Jussi, additional, Aalto, Tuula, additional, Kunttu, Iivari, additional, and Liski, Jari, additional

Published
2022
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45. Author Correction:The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data (Scientific Data, (2020), 7, 1, (225), 10.1038/s41597-020-0534-3)

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, Ardo, 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, Brummer, 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, Dufrene, Eric, Dunn, Allison, Dusek, Jiri, 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, Gharun, Mana, Gianelle, Damiano, Gielen, Bert, Gioli, Beniamino, Gitelson, Anatoly, Goded, Ignacio, Goeckede, Mathias, Goldstein, Allen H., Gough, Christopher M., Goulden, Michael L., Graf, Alexander, Griebel, Anne, Gruening, Carsten, Grunwald, Thomas, Hammerle, Albin, Han, Shijie, Han, Xingguo, Hansen, Birger Ulf, Hanson, Chad, Hatakka, Juha, He, Yongtao, Hehn, Markus, Heinesch, Bernard, Hinko-Najera, Nina, Hortnagl, Lukas, Hutley, Lindsay, Ibrom, Andreas, Ikawa, Hiroki, Jackowicz-Korczynski, Marcin, Janous, Dalibor, Jans, Wilma, Jassal, Rachhpal, Jiang, Shicheng, Kato, Tomomichi, Khomik, Myroslava, Klatt, Janina, Knohl, Alexander, Knox, Sara, Kobayashi, Hideki, Koerber, Georgia, Kolle, Olaf, Kosugi, Yoshiko, Kotani, Ayumi, Kowalski, Andrew, Kruijt, Bart, Kurbatova, Julia, Kutsch, Werner L., Kwon, Hyojung, Launiainen, Samuli, Laurila, Tuomas, Law, Bev, Leuning, Ray, Li, Yingnian, Liddell, Michael, Limousin, Jean-Marc, Lion, Marryanna, Liska, Adam J., Lohila, Annalea, Lopez-Ballesteros, Ana, Lopez-Blanco, Efren, Loubet, Benjamin, Loustau, Denis, Lucas-Moffat, Antje, Luers, Johannes, Ma, Siyan, Macfarlane, Craig, Magliulo, Vincenzo, Maier, Regine, Mammarella, Ivan, Manca, Giovanni, Marcolla, Barbara, Margolis, Hank A., Marras, Serena, Massman, William, Mastepanov, Mikhail, Matamala, Roser, Matthes, Jaclyn Hatala, Mazzenga, Francesco, McCaughey, Harry, McHugh, Ian, McMillan, Andrew M. S., Merbold, Lutz, Meyer, Wayne, Meyers, Tilden, Miller, Scott D., Minerbi, Stefano, Moderow, Uta, Monson, Russell K., Montagnani, Leonardo, Moore, Caitlin E., Moors, Eddy, Moreaux, Virginie, Moureaux, Christine, Munger, J. William, Nakai, Taro, Neirynck, Johan, Nesic, Zoran, Nicolini, Giacomo, Noormets, Asko, Northwood, Matthew, Nosetto, Marcelo, Nouvellon, Yann, Novick, Kimberly, Oechel, Walter, Olesen, Jorgen Eivind, Ourcival, Jean-Marc, Papuga, Shirley A., Parmentier, Frans-Jan, Paul-Limoges, Eugenie, Pavelka, Marian, Peichl, Matthias, Pendall, Elise, Phillips, Richard P., Pilegaard, Kim, Pirk, Norbert, Posse, Gabriela, Powell, Thomas, Prasse, Heiko, Prober, Suzanne M., Rambal, Serge, Rannik, Ullar, Raz-Yaseef, Naama, Rebmann, Corinna, Reed, David, de Dios, Victor Resco, Restrepo-Coupe, Natalia, Reverter, Borja R., Roland, Marilyn, Sabbatini, Simone, Sachs, Torsten, Saleska, Scott R., Sanchez-Canete, Enrique P., Sanchez-Mejia, Zulia M., Schmid, Hans Peter, Schmidt, Marius, Schneider, Karl, Schrader, Frederik, Schroder, Ivan, Scott, Russell L., Sedlak, Pavel, Serrano-Ortiz, Penelope, Shao, Changliang, Shi, Peili, Shironya, Ivan, Siebicke, Lukas, Sigut, Ladislav, Silberstein, Richard, Sirca, Costantino, Spano, Donatella, Steinbrecher, Rainer, Stevens, Robert M., Sturtevant, Cove, Suyker, Andy, Tagesson, Torbern, Takanashi, Satoru, Tang, Yanhong, Tapper, Nigel, Thom, Jonathan, Tomassucci, Michele, Tuovinen, Juha-Pekka, Urbanski, Shawn, Valentini, Riccardo, van der Molen, Michiel, van Gorsel, Eva, van Huissteden, Ko, Varlagin, Andrej, Verfaillie, Joseph, Vesala, Timo, Vincke, Caroline, Vitale, Domenico, Vygodskaya, Natalia, Walker, Jeffrey P., Walter-Shea, Elizabeth, Wang, Huimin, Weber, Robin, Westermann, Sebastian, Wille, Christian, Wofsy, Steven, Wohlfahrt, Georg, Wolf, Sebastian, Woodgate, William, Li, Yuelin, Zampedri, Roberto, Zhang, Junhui, Zhou, Guoyi, Zona, Donatella, Agarwal, Deb, Biraud, Sebastien, Torn, Margaret, and Papale, Dario

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
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46. Spatiotemporal lagging of predictors improves machine learning estimates of atmosphere–forest CO2 exchange.

Author

Kämäräinen, Matti, Tuovinen, Juha-Pekka, Kulmala, Markku, Mammarella, Ivan, Aalto, Juha, Vekuri, Henriikka, Lohila, Annalea, and Lintunen, Anna

Subjects
MACHINE learning, CARBON dioxide, TAIGAS, GRID cells, BIOSPHERE, RANDOM forest algorithms, CARBON cycle
Abstract

Accurate estimates of net ecosystem CO 2 exchange (NEE) would improve the understanding of natural carbon sources and sinks and their role in the regulation of global atmospheric carbon. In this work, we use and compare the random forest (RF) and the gradient boosting (GB) machine learning (ML) methods for predicting year-round 6 h NEE over 1996–2018 in a pine-dominated boreal forest in southern Finland and analyze the predictability of NEE. Additionally, aggregation to weekly NEE values was applied to get information about longer term behavior of the method. The meteorological ERA5 reanalysis variables were used as predictors. Spatial and temporal neighborhood (predictor lagging) was used to provide the models more data to learn from, which was found to improve considerably the accuracy of both ML approaches compared to using only the nearest grid cell and time step. Both ML methods can explain temporal variability of NEE in the observational site of this study with meteorological predictors, but the GB method was more accurate. Only minor signs of overfitting could be detected for the GB algorithm when redundant variables were included. The accuracy of the approaches, measured mainly using cross-validated R2 score between the model result and the observed NEE, was high, reaching a best estimate value of 0.92 for GB and 0.88 for RF. In addition to the standard RF approach, we recommend using GB for modeling the CO 2 fluxes of the ecosystems due to its potential for better performance. [ABSTRACT FROM AUTHOR]

Published
2023
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50. Supplementary material to "The effect of rainfall amount and timing on annual transpiration in a grazed savanna grassland"

Author

Räsänen, Matti, primary, Aurela, Mika, additional, Vakkari, Ville, additional, Beukes, Johan P., additional, Tuovinen, Juha-Pekka, additional, Van Zyl, Pieter G., additional, Josipovic, Miroslav, additional, Siebert, Stefan J., additional, Laurila, Tuomas, additional, Kulmala, Markku, additional, Laakso, Lauri, additional, Rinne, Janne, additional, Oren, Ram, additional, and Katul, Gabriel, additional

Published
2021
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