542 results on '"Sonnentag, Oliver"'
Search Results
102. The challenges of measuring methane fluxes and concentrations over a peatland pasture
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Baldocchi, Dennis, Detto, Matteo, Sonnentag, Oliver, Verfaillie, Joe, Teh, Yit Arn, Silver, Whendee, and Kelly, N. Maggi
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- 2012
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103. Digital repeat photography for phenological research in forest ecosystems
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Sonnentag, Oliver, Hufkens, Koen, Teshera-Sterne, Cory, Young, Adam M., Friedl, Mark, Braswell, Bobby H., Milliman, Thomas, O’Keefe, John, and Richardson, Andrew D.
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- 2012
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104. Effects of Warming, Wildfire, and Permafrost Thaw on Carbon Dioxide Fluxes from Boreal Peat Landscapes in northwestern Canada
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Schulze, Christopher, primary, Olefeldt, David, additional, Emmerton, Craig, additional, Harris, Lorna, additional, Kljun, Natascha, additional, Chasmer, Laura, additional, Hopkinson, Chris, additional, Detto, Matteo, additional, Helbig, Manuel, additional, Gosselin, Gabriel Hould, additional, and Sonnentag, Oliver, additional
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- 2022
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105. A thirst for snowmelt? Tree water use in spring
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Nehemy, Magali F., primary, Maillet, Jason, additional, Perron, Nia, additional, Pappas, Christoforos, additional, Sonnentag, Oliver, additional, Baltzer, Jennifer L., additional, Laroque, Colin P., additional, and McDonnell, Jeffrey J., additional
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- 2022
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106. Methane and Environmental Impacts of Abandoned Oil And Gas Wells in the North American Arctic-Boreal Region
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Klotz, Louise Anne, primary, Sonnentag, Oliver, additional, and Kang, Mary, additional
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- 2022
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107. Range shifts in a foundation sedge potentially induce large Arctic ecosystem carbon losses and gains
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Curasi, Salvatore R, primary, Fetcher, Ned, additional, Hewitt, Rebecca E, additional, Lafleur, Peter M., additional, Loranty, Michael M., additional, Mack, Michelle C, additional, May, Jeremy, additional, Myers-Smith, Isla H., additional, Natali, Susan M, additional, Oberbauer, Steven, additional, Parker, Thomas C, additional, Sonnentag, Oliver, additional, Vargas Zesati, Sergio A, additional, Wullschleger, Stan D, additional, and Rocha, Adrian V, additional
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- 2022
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108. Thermodynamic basis for the demarcation of Arctic and alpine treelines
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Kumar, Praveen, primary, Martin, Meredith Richardson, additional, Sonnentag, Oliver, additional, and Marsh, Philip, additional
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- 2022
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109. Large Greenhouse Gas Emissions from a Temperate Peatland Pasture
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Teh, Yit Arn, Silver, Whendee L., Sonnentag, Oliver, Detto, Matteo, Kelly, Maggi, and Baldocchi, Dennis D.
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- 2011
110. Crop model validation and sensitivity to climate change scenarios
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El Maayar, Mustapha and Sonnentag, Oliver
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- 2009
111. Using digital repeat photography and eddy covariance data to model grassland phenology and photosynthetic CO 2 uptake
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Migliavacca, Mirco, Galvagno, Marta, Cremonese, Edoardo, Rossini, Micol, Meroni, Michele, Sonnentag, Oliver, Cogliati, Sergio, Manca, Giovanni, Diotri, Fabrizio, Busetto, Lorenzo, Cescatti, Alessandro, Colombo, Roberto, Fava, Francesco, Morra di Cella, Umberto, Pari, Emiliano, Siniscalco, Consolata, and Richardson, Andrew D.
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- 2011
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112. The Boreal–Arctic Wetland and Lake Dataset (BAWLD)
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Olefeldt, David, primary, Hovemyr, Mikael, additional, Kuhn, McKenzie A., additional, Bastviken, David, additional, Bohn, Theodore J., additional, Connolly, John, additional, Crill, Patrick, additional, Euskirchen, Eugénie S., additional, Finkelstein, Sarah A., additional, Genet, Hélène, additional, Grosse, Guido, additional, Harris, Lorna I., additional, Heffernan, Liam, additional, Helbig, Manuel, additional, Hugelius, Gustaf, additional, Hutchins, Ryan, additional, Juutinen, Sari, additional, Lara, Mark J., additional, Malhotra, Avni, additional, Manies, Kristen, additional, McGuire, A. David, additional, Natali, Susan M., additional, O'Donnell, Jonathan A., additional, Parmentier, Frans-Jan W., additional, Räsänen, Aleksi, additional, Schädel, Christina, additional, Sonnentag, Oliver, additional, Strack, Maria, additional, Tank, Suzanne E., additional, Treat, Claire, additional, Varner, Ruth K., additional, Virtanen, Tarmo, additional, Warren, Rebecca K., additional, and Watts, Jennifer D., additional
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- 2021
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113. Increases in aboveground biomass and leaf area 85 years after drainage in a bog
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Talbot, Julie, Roulet, Nigel T., Sonnentag, Oliver, and Moore, Tim R.
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Biomass -- Environmental aspects ,Bogs -- Environmental aspects ,Drainage -- Environmental aspects ,Biological sciences - Abstract
Climate change scenarios suggest that northern peatlands could become drier. To address the type and magnitude of vegetation change associated with persistent drying, we studied changes in biomass and leaf area index following drainage 85 years previously of a bog, using destructive sampling, allometric relationships, and optical measurements. Our results show a 10-fold increase in aboveground biomass between the reference site and the most severely drained site, resulting from the growth of a tree layer. The total leaf biomass increased slightly as a result of drainage, thus an increase in woody biomass was the main cause of the increase in aboveground biomass. Leaf area index approximately tripled in sites where trees grew. Sphagnum L. moss biomass decreased from 120 g x [m.sup.-2] at the reference site (20% of all aboveground biomass) to 8 g x [m.sup.-2] under the tree canopy ( Key words: aboveground biomass, leaf area index, water-table drawdown, biomass allocation, peatland. Les scenarios de changements climatiques suggerent que les tourbieres nordiques pourraient devenir plus seches. Pour determiner le type et la magnitude des changements de vegetation associes a un assechement persistant, nous avons etudie les changements de biomasse et indice de surface foliaire le long d'un gradient hydrique resultant du drainage il y a 85 ans d'une portion d'une tourbiere ombrotrophe a l'aide d'un echantillonnage destructif, de relations allometriques et de mesures optiques. La biomasse aerienne est superieure par un facteur de 10 dans le site severement draine (oU une strate arboree s'est developpee), comparativement au site de reference. La biomasse foliaire totale est legerement augmentee dans les sites draines, mais l'indice de superficie foliaire triple lorsque des arbres sont presents. L'augmentation de la biomasse aerienne est donc surtout tributaire de l'augmentation de la biomasse ligneuse. La mousse de sphaigne compte pour pres de 20 % de la biomasse aerienne au site de reference, mais pour moins de 1 % au site le plus severement draine (de 120 g x [m.sup.-2] a 8 g x [m.sup.-2] au total). La proportion d'arbustes a feuilles caduques passe de 3 a 72% de la biomasse arbustive totale, du site de reference au site le plus severement draine. Nos resultats indiquent qu'un abaissement de la nappe phreatique dans une tourbiere ombrotrophe peut affecter substantiellement la vegetation, mais l'effet net de ces changements sur le role de la tourbiere comme puits de carbone reste difficile a etablir. Mots-cles: biomasse aerienne, indice de superficie foliaire, nappe phreatique, allocation de la biomasse, tourbiere., Introduction Peatlands are important components of northern landscapes, covering more than 12% of the terrestrial area of Canada (Tarnocai et al. 2005). As a result of persistent water saturation that [...]
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- 2014
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114. Expanding global mapping of the foliage clumping index with multi-angular POLDER three measurements: Evaluation and topographic compensation
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Pisek, Jan, Chen, Jing M., Lacaze, Roselyne, Sonnentag, Oliver, and Alikas, Krista
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- 2010
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115. Testing the performance of a novel spectral reflectance sensor, built with light emitting diodes (LEDs), to monitor ecosystem metabolism, structure and function
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Ryu, Youngryel, Baldocchi, Dennis D., Verfaillie, Joseph, Ma, Siyan, Falk, Matthias, Ruiz-Mercado, Ilse, Hehn, Ted, and Sonnentag, Oliver
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- 2010
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116. On the correct estimation of effective leaf area index: Does it reveal information on clumping effects?
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Ryu, Youngryel, Nilson, Tiit, Kobayashi, Hideki, Sonnentag, Oliver, Law, Beverly E., and Baldocchi, Dennis D.
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- 2010
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117. How to quantify tree leaf area index in an open savanna ecosystem: A multi-instrument and multi-model approach
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Ryu, Youngryel, Sonnentag, Oliver, Nilson, Tiit, Vargas, Rodrigo, Kobayashi, Hideki, Wenk, Rebecca, and Baldocchi, Dennis D.
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- 2010
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118. FLUXNET-CH4 : a global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands
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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 Y.F., Lohila, Annalea, Mammarella, Ivan, Belelli Marchesini, Luca, 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 R.K., Ryu, Youngryel, Sachs, Torsten, Sakabe, Ayaka, Sanchez, Camilo Rey, Schuur, Edward A., Schäfer, Karina V.R., 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, Vazquez-Lule, Alma, Verfaillie, Joseph G., Vesala, Timo, Vourlitis, George L., Ward, Eric J., Wille, Christian, Wohlfahrt, Georg, Wong, Guan Xhuan, Zhang, Zhen, Zona, Donatella, Windham-Myers, Lisamarie, Poulter, Benjamin, Jackson, Robert B., Institute for Atmospheric and Earth System Research (INAR), Micrometeorology and biogeochemical cycles, Viikki Plant Science Centre (ViPS), Ecosystem processes (INAR Forest Sciences), Earth Sciences, and Earth and Climate
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1171 Geosciences ,Earth sciences ,SDG 17 - Partnerships for the Goals ,Physical Geography ,ddc:550 ,114 Physical sciences ,1172 Environmental sciences ,Atmospheric Sciences - Abstract
Methane (CH$_{4}$) emissions from natural landscapes constitute roughly half of global CH$_{4}$ 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 CH$_{4}$ flux are ideal for constraining ecosystem-scale CH$_{4}$ emissions due to quasi-continuous and high-temporal-resolution CH$_{4}$ 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-CH$_{4}$ Version 1.0, the first open-source global dataset of CH$_{4}$ 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 CH$_{4}$ 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-CH$_{4}$ representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH$_{4}$ Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH$_{4}$ emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH$_{4}$ 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 CH$_{4}$ emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20° S to 20° N) the spring onset of elevated CH$_{4}$ emissions starts 3 d earlier, and the CH$_{4}$ emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH$_{4}$ emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH$_{4}$ emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH$_{4}$ emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH$_{4}$ emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH$_{4}$ modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH$_{4}$ peak). FLUXNET-CH$_{4}$ is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH$_{4}$ cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH$_{4}$ 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.
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- 2021
119. Earlier Snowmelt May Lead to Late Season Declines in Plant Productivity and Carbon Sequestration in Arctic Tundra Ecosystems
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Zona, Donatella, primary, Lafleur, Peter, additional, Hufkens, Koen, additional, Bailey, Barbara, additional, Gioli, Beniamino, additional, Burba, George, additional, Goodrich, Jordan, additional, Liljedahl, Anna, additional, Euskirchen, Eugenie, additional, Watts, Jennifer, additional, Farina, Mary, additional, Kimball, John, additional, Heimann, Martin, additional, Goeckede, Mathias, additional, Pallandt, Martijn, additional, Christensen, Torben, additional, Mastepanov, Mikhail, additional, Lopez-Blanco, Efren, additional, Jackowicz-Korczynski, Marcin, additional, Dolman, Albertus J., additional, Marchesini, Luca Belelli, additional, Commane, Roisin, additional, Wofsy, Steve, additional, Miller, Charles, additional, Lipson, David, additional, Hashemi, Josh, additional, Arndt, Kyle, additional, Kutzbach, Lars, additional, Holl, David, additional, Boike, Julia, additional, Wille, Christian, additional, Sachs, Torsten, additional, Kalhori, Aram, additional, Song, Xia, additional, Xu, Xiaofeng, additional, Humphreys, Elyn, additional, Koven, Charles, additional, Sonnentag, Oliver, additional, Meyer, Gesa, additional, Gosselin, Gabriel, additional, Marsh, Philip, additional, and Oechel, Walter, additional
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- 2021
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120. Impact of measured and simulated tundra snowpack properties on heat transfer
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Dutch, Victoria R., primary, Rutter, Nick, additional, Wake, Leanne, additional, Sandells, Melody, additional, Derksen, Chris, additional, Walker, Branden, additional, Hould Gosselin, Gabriel, additional, Sonnentag, Oliver, additional, Essery, Richard, additional, Kelly, Richard, additional, Marsh, Philip, additional, and King, Joshua, additional
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- 2021
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121. Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands
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Irvin, Jeremy, primary, Zhou, Sharon, additional, McNicol, Gavin, additional, Lu, Fred, additional, Liu, Vincent, additional, Fluet-Chouinard, Etienne, additional, Ouyang, Zutao, additional, Knox, Sara Helen, additional, Lucas-Moffat, Antje, additional, Trotta, Carlo, additional, Papale, Dario, additional, Vitale, Domenico, additional, Mammarella, Ivan, additional, Alekseychik, Pavel, additional, Aurela, Mika, additional, Avati, Anand, additional, Baldocchi, Dennis, additional, Bansal, Sheel, additional, Bohrer, Gil, additional, Campbell, David I, additional, Chen, Jiquan, additional, Chu, Housen, additional, Dalmagro, Higo J, additional, Delwiche, Kyle B, additional, Desai, Ankur R, additional, Euskirchen, Eugenie, additional, Feron, Sarah, additional, Goeckede, Mathias, additional, Heimann, Martin, additional, Helbig, Manuel, additional, Helfter, Carole, additional, Hemes, Kyle S, additional, Hirano, Takashi, additional, Iwata, Hiroki, additional, Jurasinski, Gerald, additional, Kalhori, Aram, additional, Kondrich, Andrew, additional, Lai, Derrick YF, additional, Lohila, Annalea, additional, Malhotra, Avni, additional, Merbold, Lutz, additional, Mitra, Bhaskar, additional, Ng, Andrew, additional, Nilsson, Mats B, additional, Noormets, Asko, additional, Peichl, Matthias, additional, Rey-Sanchez, A. Camilo, additional, Richardson, Andrew D, additional, Runkle, Benjamin RK, additional, Schäfer, Karina VR, additional, Sonnentag, Oliver, additional, Stuart-Haëntjens, Ellen, additional, Sturtevant, Cove, additional, Ueyama, Masahito, additional, Valach, Alex C, additional, Vargas, Rodrigo, additional, Vourlitis, George L, additional, Ward, Eric J, additional, Wong, Guan Xhuan, additional, Zona, Donatella, additional, Alberto, Ma. Carmelita R, additional, Billesbach, David P, additional, Celis, Gerardo, additional, Dolman, Han, additional, Friborg, Thomas, additional, Fuchs, Kathrin, additional, Gogo, Sébastien, additional, Gondwe, Mangaliso J, additional, Goodrich, Jordan P, additional, Gottschalk, Pia, additional, Hörtnagl, Lukas, additional, Jacotot, Adrien, additional, Koebsch, Franziska, additional, Kasak, Kuno, additional, Maier, Regine, additional, Morin, Timothy H, additional, Nemitz, Eiko, additional, Oechel, Walter C, additional, Oikawa, Patricia Y, additional, Ono, Keisuke, additional, Sachs, Torsten, additional, Sakabe, Ayaka, additional, Schuur, Edward A, additional, Shortt, Robert, additional, Sullivan, Ryan C, additional, Szutu, Daphne J, additional, Tuittila, Eeva-Stiina, additional, Varlagin, Andrej, additional, Verfaillie, Joeseph G, additional, Wille, Christian, additional, Windham-Myers, Lisamarie, additional, Poulter, Benjamin, additional, and Jackson, Robert B, additional
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- 2021
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122. The implications of permafrost thaw and land cover change on snow water equivalent accumulation, melt and runoff in discontinuous permafrost peatlands
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Connon, Ryan F., primary, Chasmer, Laura, additional, Haughton, Emily, additional, Helbig, Manuel, additional, Hopkinson, Chris, additional, Sonnentag, Oliver, additional, and Quinton, William L., additional
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- 2021
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123. Soil respiration strongly offsets carbon uptake in Alaska and Northwest Canada
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Watts, Jennifer D, primary, Natali, Susan M, additional, Minions, Christina, additional, Risk, Dave, additional, Arndt, Kyle, additional, Zona, Donatella, additional, Euskirchen, Eugénie S, additional, Rocha, Adrian V, additional, Sonnentag, Oliver, additional, Helbig, Manuel, additional, Kalhori, Aram, additional, Oechel, Walt, additional, Ikawa, Hiroki, additional, Ueyama, Masahito, additional, Suzuki, Rikie, additional, Kobayashi, Hideki, additional, Celis, Gerardo, additional, Schuur, Edward A G, additional, Humphreys, Elyn, additional, Kim, Yongwon, additional, Lee, Bang-Yong, additional, Goetz, Scott, additional, Madani, Nima, additional, Schiferl, Luke D, additional, Commane, Roisin, additional, Kimball, John S, additional, Liu, Zhihua, additional, Torn, Margaret S, additional, Potter, Stefano, additional, Wang, Jonathan A, additional, Jorgenson, M Torre, additional, Xiao, Jingfeng, additional, Li, Xing, additional, and Edgar, Colin, additional
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- 2021
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124. A spatially explicit hydro-ecological modeling framework (BEPS-TerrainLab V2.0): Model description and test in a boreal ecosystem in Eastern North America
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Govind, Ajit, Chen, Jing Ming, Margolis, Hank, Ju, Weimin, Sonnentag, Oliver, and Giasson, Marc-André
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- 2009
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125. Widespread decline in winds delayed autumn foliar senescence over high latitudes
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Fu, Yongshuo, Wu, Chaoyang, Wang, Jian, Ciais, Philippe, Peñuelas, Josep, Zhang, Xiaoyang, Sonnentag, Oliver, Tian, Feng, Wang, Xiaoyue, Wang, Huanjiong, Liu, Ronggao, Fu J, Yongshuo, Ge, Quansheng, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)
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0106 biological sciences ,China ,010504 meteorology & atmospheric sciences ,Climate ,Climate Change ,Climate change ,Wind ,Atmospheric sciences ,010603 evolutionary biology ,01 natural sciences ,Latitude ,Carbon Cycle ,Trees ,high latitudes ,Abscission ,Evapotranspiration ,Precipitation ,"high latitudes" ,[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment ,Weather ,Ecosystem ,0105 earth and related environmental sciences ,[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere ,Multidisciplinary ,Phenology ,Altitude ,Temperature ,15. Life on land ,Biological Sciences ,Plant Leaves ,13. Climate action ,"foliar senescence" ,foliar senescence ,Soil water ,Frost ,Remote Sensing Technology ,Environmental science ,Seasons ,Environmental Sciences ,"climate change" - Abstract
Significance Decline in winds over past decades were observed over high northern latitudes (>50°), yet its influence on the date of autumn leaf senescence (DFS) remains unknown. Using ground observations, flux measurements, and remote sensing imagery, here we show that decline in winds significantly extended DFS over high latitudes at a magnitude comparable with the temperature and precipitation effects. We found that decline in winds reduces evapotranspiration, causes fewer damaging effects, and also results in decreased cooling effect. Our results therefore are of great significance for carbon cycle modeling because an improved algorithm based on these findings projected overall widespread earlier DFS by the end of this century, contributing potentially to a positive feedback to climate., The high northern latitudes (>50°) experienced a pronounced surface stilling (i.e., decline in winds) with climate change. As a drying factor, the influences of changes in winds on the date of autumn foliar senescence (DFS) remain largely unknown and are potentially important as a mechanism explaining the interannual variability of autumn phenology. Using 183,448 phenological observations at 2,405 sites, long-term site-scale water vapor and carbon dioxide flux measurements, and 34 y of satellite greenness data, here we show that the decline in winds is significantly associated with extended DFS and could have a relative importance comparable with temperature and precipitation effects in contributing to the DFS trends. We further demonstrate that decline in winds reduces evapotranspiration, which results in less soil water losses and consequently more favorable growth conditions in late autumn. In addition, declining winds also lead to less leaf abscission damage which could delay leaf senescence and to a decreased cooling effect and therefore less frost damage. Our results are potentially useful for carbon flux modeling because an improved algorithm based on these findings projected overall widespread earlier DFS than currently expected by the end of this century, contributing potentially to a positive feedback to climate.
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- 2021
126. Linking Cree hunters’ and scientific observations of changing inland ice and meteorological conditions in the subarctic eastern James Bay region, Canada
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Royer, Marie-Jeanne S., Herrmann, Thora Martina, Sonnentag, Oliver, Fortier, Daniel, Delusca, Kenel, and Cuciurean, Rick
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- 2013
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127. The ABCflux database: Arctic-Boreal CO2 flux observations and ancillary information aggregated to monthly time steps across terrestrial ecosystems
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Virkkala, Anna-Maria, primary, Natali, Susan M., additional, Rogers, Brendan M., additional, Watts, Jennifer D., additional, Savage, Kathleen, additional, Connon, Sara June, additional, Mauritz, Marguerite, additional, Schuur, Edward A. G., additional, Peter, Darcy, additional, Minions, Christina, additional, Nojeim, Julia, additional, Commane, Roisin, additional, Emmerton, Craig A., additional, Goeckede, Mathias, additional, Helbig, Manuel, additional, Holl, David, additional, Iwata, Hiroki, additional, Kobayashi, Hideki, additional, Kolari, Pasi, additional, López-Blanco, Efrén, additional, Marushchak, Maija E., additional, Mastepanov, Mikhail, additional, Merbold, Lutz, additional, Parmentier, Frans-Jan W., additional, Peichl, Matthias, additional, Sachs, Torsten, additional, Sonnentag, Oliver, additional, Ueyama, Masahito, additional, Voigt, Carolina, additional, Aurela, Mika, additional, Boike, Julia, additional, Celis, Gerardo, additional, Chae, Namyi, additional, Christensen, Torben R., additional, Bret-Harte, M. Syndonia, additional, Dengel, Sigrid, additional, Dolman, Han, additional, Edgar, Colin W., additional, Elberling, Bo, additional, Euskirchen, Eugenie, additional, Grelle, Achim, additional, Hatakka, Juha, additional, Humphreys, Elyn, additional, Järveoja, Järvi, additional, Kotani, Ayumi, additional, Kutzbach, Lars, additional, Laurila, Tuomas, additional, Lohila, Annalea, additional, Mammarella, Ivan, additional, Matsuura, Yojiro, additional, Meyer, Gesa, additional, Nilsson, Mats B., additional, Oberbauer, Steven F., additional, Park, Sang-Jong, additional, Petrov, Roman, additional, Prokushkin, Anatoly S., additional, Schulze, Christopher, additional, St.Louis, Vincent L., additional, Tuittila, Eeva-Stiina, additional, Tuovinen, Juha-Pekka, additional, Quinton, William, additional, Varlagin, Andrej, additional, Zona, Donatella, additional, and Zyryanov, Viacheslav I., additional
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- 2021
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128. Statistical upscaling of ecosystem CO 2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties
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Virkkala, Anna‐Maria, primary, Aalto, Juha, additional, Rogers, Brendan M., additional, Tagesson, Torbern, additional, Treat, Claire C., additional, Natali, Susan M., additional, Watts, Jennifer D., additional, Potter, Stefano, additional, Lehtonen, Aleksi, additional, Mauritz, Marguerite, additional, Schuur, Edward A. G., additional, Kochendorfer, John, additional, Zona, Donatella, additional, Oechel, Walter, additional, Kobayashi, Hideki, additional, Humphreys, Elyn, additional, Goeckede, Mathias, additional, Iwata, Hiroki, additional, Lafleur, Peter M., additional, Euskirchen, Eugenie S., additional, Bokhorst, Stef, additional, Marushchak, Maija, additional, Martikainen, Pertti J., additional, Elberling, Bo, additional, Voigt, Carolina, additional, Biasi, Christina, additional, Sonnentag, Oliver, additional, Parmentier, Frans‐Jan W., additional, Ueyama, Masahito, additional, Celis, Gerardo, additional, St.Louis, Vincent L., additional, Emmerton, Craig A., additional, Peichl, Matthias, additional, Chi, Jinshu, additional, Järveoja, Järvi, additional, Nilsson, Mats B., additional, Oberbauer, Steven F., additional, Torn, Margaret S., additional, Park, Sang‐Jong, additional, Dolman, Han, additional, Mammarella, Ivan, additional, Chae, Namyi, additional, Poyatos, Rafael, additional, López‐Blanco, Efrén, additional, Christensen, Torben Røjle, additional, Kwon, Min Jung, additional, Sachs, Torsten, additional, Holl, David, additional, and Luoto, Miska, additional
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129. Supplementary material to "The Boreal-Arctic Wetland and Lake Dataset (BAWLD)"
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Olefeldt, David, primary, Hovemyr, Mikael, additional, Kuhn, McKenzie A., additional, Bastviken, David, additional, Bohn, Theodore J., additional, Connolly, John, additional, Crill, Patrick, additional, Euskirchen, Eugénie S., additional, Finkelstein, Sarah A., additional, Genet, Hélène, additional, Grosse, Guido, additional, Harris, Lorna I., additional, Heffernan, Liam, additional, Helbig, Manuel, additional, Hugelius, Gustaf, additional, Hutchins, Ryan, additional, Juutinen, Sari, additional, Lara, Mark J., additional, Malhotra, Avni, additional, Manies, Kristen, additional, McGuire, A. David, additional, Natali, Susan M., additional, O'Donnell, Jonathan A., additional, Parmentier, Frans-Jan W., additional, Räsänen, Aleksi, additional, Schädel, Christina, additional, Sonnentag, Oliver, additional, Strack, Maria, additional, Tank, Suzanne, additional, Treat, Claire, additional, Varner, Ruth K., additional, Virtanen, Tarmo, additional, Warren, Rebecca K., additional, and Watts, Jennifer D., additional
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130. Tower‐Based Remote Sensing Reveals Mechanisms Behind a Two‐phased Spring Transition in a Mixed‐Species Boreal Forest
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Pierrat, Zoe, primary, Nehemy, Magali F., additional, Roy, Alexandre, additional, Magney, Troy, additional, Parazoo, Nicholas C., additional, Laroque, Colin, additional, Pappas, Christoforos, additional, Sonnentag, Oliver, additional, Grossmann, Katja, additional, Bowling, David R., additional, Seibt, Ulli, additional, Ramirez, Alexandra, additional, Johnson, Bruce, additional, Helgason, Warren, additional, Barr, Alan, additional, and Stutz, Jochen, additional
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131. Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites
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Chu, Housen, primary, Luo, Xiangzhong, additional, Ouyang, Zutao, additional, Chan, W. Stephen, additional, Dengel, Sigrid, additional, Biraud, Sébastien C., additional, Torn, Margaret S., additional, Metzger, Stefan, additional, Kumar, Jitendra, additional, Arain, M. Altaf, additional, Arkebauer, Tim J., additional, Baldocchi, Dennis, additional, Bernacchi, Carl, additional, Billesbach, Dave, additional, Black, T. Andrew, additional, Blanken, Peter D., additional, Bohrer, Gil, additional, Bracho, Rosvel, additional, Brown, Shannon, additional, Brunsell, Nathaniel A., additional, Chen, Jiquan, additional, Chen, Xingyuan, additional, Clark, Kenneth, additional, Desai, Ankur R., additional, Duman, Tomer, additional, Durden, David, additional, Fares, Silvano, additional, Forbrich, Inke, additional, Gamon, John A., additional, Gough, Christopher M., additional, Griffis, Timothy, additional, Helbig, Manuel, additional, Hollinger, David, additional, Humphreys, Elyn, additional, Ikawa, Hiroki, additional, Iwata, Hiroki, additional, Ju, Yang, additional, Knowles, John F., additional, Knox, Sara H., additional, Kobayashi, Hideki, additional, Kolb, Thomas, additional, Law, Beverly, additional, Lee, Xuhui, additional, Litvak, Marcy, additional, Liu, Heping, additional, Munger, J. William, additional, Noormets, Asko, additional, Novick, Kim, additional, Oberbauer, Steven F., additional, Oechel, Walter, additional, Oikawa, Patty, additional, Papuga, Shirley A., additional, Pendall, Elise, additional, Prajapati, Prajaya, additional, Prueger, John, additional, Quinton, William L, additional, Richardson, Andrew D., additional, Russell, Eric S., additional, Scott, Russell L., additional, Starr, Gregory, additional, Staebler, Ralf, additional, Stoy, Paul C., additional, Stuart-Haëntjens, Ellen, additional, Sonnentag, Oliver, additional, Sullivan, Ryan C., additional, Suyker, Andy, additional, Ueyama, Masahito, additional, Vargas, Rodrigo, additional, Wood, Jeffrey D., additional, and Zona, Donatella, additional
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132. sj-pdf-1-hol-10.1177_0959683617693899 ��� Supplemental material for Influence of Holocene permafrost aggradation and thaw on the paleoecology and carbon storage of a peatland complex in northwestern Canada
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Pelletier, Nicolas, Talbot, Julie, Olefeldt, David, Turetsky, Merritt, Blodau, Christian, Sonnentag, Oliver, and Quinton, William L
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History ,Geography - Abstract
Supplemental material, sj-pdf-1-hol-10.1177_0959683617693899 for Influence of Holocene permafrost aggradation and thaw on the paleoecology and carbon storage of a peatland complex in northwestern Canada by Nicolas Pelletier, Julie Talbot, David Olefeldt, Merritt Turetsky, Christian Blodau, Oliver Sonnentag and William L Quinton in The Holocene
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133. FLUXNET-CH4: a global, multi-ecosystem datasetand analysis of methane seasonalityfrom freshwater wetlands
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Knox, Sara, Alberto, Ma, Matthes, Jaclyn, Sanchez, Camilo, Wong, Guan, Delwiche, Kyle, 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, Bohrer, Gil, Bracho, Rosvel, Buchmann, Nina, Campbell, David, Celis, Gerardo, Chen, Jiquan, Chen, Weinan, Chu, Housen, Dalmagro, Higo, Dengel, Sigrid, Desai, Ankur, Detto, Matteo, Dolman, Han, Eichelmann, Elke, Euskirchen, Eugenie, Famulari, Daniela, Fuchs, Kathrin, Goeckede, Mathias, Gogo, Sébastien, Gondwe, Mangaliso, Goodrich, Jordan, Gottschalk, Pia, Graham, Scott, Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle, Hirano, Takashi, Hollinger, David, Hörtnagl, Lukas, Iwata, Hiroki, Jacotot, Adrien, Jurasinski, Gerald, Kang, Minseok, Kasak, Kuno, King, John, Klatt, Janina, Koebsch, Franziska, Krauss, Ken, Lai, Derrick, Lohila, Annalea, Mammarella, Ivan, Belelli Marchesini, Luca, Manca, Giovanni, Matthes, Jaclyn Hatala, Maximov, Trofim, Merbold, Lutz, Mitra, Bhaskar, Morin, Timothy, Nemitz, Eiko, Nilsson, Mats, Niu, Shuli, Oechel, Walter, Oikawa, Patricia, Ono, Keisuke, Peichl, Matthias, Peltola, Olli, Reba, Michele, Richardson, Andrew, Riley, William, Runkle, Benjamin, Ryu, Youngryel, Sachs, Torsten, Sakabe, Ayaka, Sanchez, Camilo Rey, Schuur, Edward, Schäfer, Karina, Sonnentag, Oliver, Sparks, Jed, Stuart-Haëntjens, Ellen, Sturtevant, Cove, Sullivan, Ryan, Szutu, Daphne, Thom, Jonathan, Torn, Margaret, Tuittila, Eeva-Stiina, Turner, Jessica, Ueyama, Masahito, Valach, Alex, Vargas, Rodrigo, Varlagin, Andrej, Vazquez-Lule, Alma, Verfaillie, Joseph, Vesala, Timo, Vourlitis, George, Ward, Eric, Wille, Christian, Wohlfahrt, Georg, Wong, Guan Xhuan, Zhang, Zhen, Zona, Donatella, Windham-Myers, Lisamarie, Poulter, Benjamin, Jackson, Robert, Institut des Sciences de la Terre d'Orléans - UMR7327 (ISTO), Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers en région Centre (OSUC), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Bureau de Recherches Géologiques et Minières (BRGM) (BRGM), Biogéosystèmes Continentaux - UMR7327, and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Bureau de Recherches Géologiques et Minières (BRGM) (BRGM)-Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers en région Centre (OSUC)
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[SDU]Sciences of the Universe [physics] ,[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment - Abstract
International audience; Abstract. Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20∘ S to 20∘ N) the spring onset of elevated CH4 emissions starts 3 d earlier, and the CH4 emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH4 emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH4 modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH4 cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.
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134. The Boreal–Arctic Wetland and Lake Dataset (BAWLD)
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Olefeldt, David, Hovemyr, Mikael, Kuhn, McKenzie A., Bastviken, David, Bohn, Theodore J., Connolly, John, Crill, Patrick, Euskirchen, Eugénie S., Finkelstein, Sarah A., Genet, Hélène, Grosse, Guido, Harris, Lorna I., Heffernan, Liam, Helbig, Manuel, Hugelius, Gustaf, Hutchins, Ryan, Juutinen, Sari, Lara, Mark J., Malhotra, Avni, Manies, Kristen, McGuire, A. David, Natali, Susan M., O'Donnell, Jonathan A., Parmentier, Frans-Jan W., Räsänen, Aleksi, Schädel, Christina, Sonnentag, Oliver, Strack, Maria, Tank, Suzanne E., Treat, Claire, Varner, Ruth K., Virtanen, Tarmo, Warren, Rebecca K., Watts, Jennifer D., Olefeldt, David, Hovemyr, Mikael, Kuhn, McKenzie A., Bastviken, David, Bohn, Theodore J., Connolly, John, Crill, Patrick, Euskirchen, Eugénie S., Finkelstein, Sarah A., Genet, Hélène, Grosse, Guido, Harris, Lorna I., Heffernan, Liam, Helbig, Manuel, Hugelius, Gustaf, Hutchins, Ryan, Juutinen, Sari, Lara, Mark J., Malhotra, Avni, Manies, Kristen, McGuire, A. David, Natali, Susan M., O'Donnell, Jonathan A., Parmentier, Frans-Jan W., Räsänen, Aleksi, Schädel, Christina, Sonnentag, Oliver, Strack, Maria, Tank, Suzanne E., Treat, Claire, Varner, Ruth K., Virtanen, Tarmo, Warren, Rebecca K., and Watts, Jennifer D.
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Methane emissions from boreal and arctic wetlands, lakes, and rivers are expected to increase in response to warming and associated permafrost thaw. However, the lack of appropriate land cover datasets for scaling field-measured methane emissions to circumpolar scales has contributed to a large uncertainty for our understanding of present-day and future methane emissions. Here we present the Boreal–Arctic Wetland and Lake Dataset (BAWLD), a land cover dataset based on an expert assessment, extrapolated using random forest modelling from available spatial datasets of climate, topography, soils, permafrost conditions, vegetation, wetlands, and surface water extents and dynamics. In BAWLD, we estimate the fractional coverage of five wetland, seven lake, and three river classes within 0.5 × 0.5∘ grid cells that cover the northern boreal and tundra biomes (17 % of the global land surface). Land cover classes were defined using criteria that ensured distinct methane emissions among classes, as indicated by a co-developed comprehensive dataset of methane flux observations. In BAWLD, wetlands occupied 3.2 × 106 km2 (14 % of domain) with a 95 % confidence interval between 2.8 and 3.8 × 106 km2. Bog, fen, and permafrost bog were the most abundant wetland classes, covering ∼ 28 % each of the total wetland area, while the highest-methane-emitting marsh and tundra wetland classes occupied 5 % and 12 %, respectively. Lakes, defined to include all lentic open-water ecosystems regardless of size, covered 1.4 × 106 km2 (6 % of domain). Low-methane-emitting large lakes (>10 km2) and glacial lakes jointly represented 78 % of the total lake area, while high-emitting peatland and yedoma lakes covered 18 % and 4 %, respectively. Small (<0.1 km2) glacial, peatland, and yedoma lakes combined covered 17 % of the total lake area but contributed disproportionally to the overall spatial uncertainty in lake area with a 95 % confidence interval between 0.15 and 0.38 × 106 km2. Rivers and streams
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135. Statistical upscaling of ecosystem CO 2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties
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Virkkala, Anna‐Maria, Aalto, Juha, Rogers, Brendan M., Tagesson, Torbern, Treat, Claire C., Natali, Susan M., Watts, Jennifer D., Potter, Stefano, Lehtonen, Aleksi, Mauritz, Marguerite, Schuur, Edward A. G., Kochendorfer, John, Zona, Donatella, Oechel, Walter, Kobayashi, Hideki, Humphreys, Elyn, Goeckede, Mathias, Iwata, Hiroki, Lafleur, Peter M., Euskirchen, Eugenie S., Bokhorst, Stef, Marushchak, Maija, Martikainen, Pertti J., Elberling, Bo, Voigt, Carolina, Biasi, Christina, Sonnentag, Oliver, Parmentier, Frans‐Jan W., Ueyama, Masahito, Celis, Gerardo, St.Louis, Vincent L., Emmerton, Craig A., Peichl, Matthias, Chi, Jinshu, Järveoja, Järvi, Nilsson, Mats B., Oberbauer, Steven F., Torn, Margaret S., Park, Sang‐Jong, Dolman, Han, Mammarella, Ivan, Chae, Namyi, Poyatos, Rafael, López‐Blanco, Efrén, Christensen, Torben Røjle, Kwon, Min Jung, Sachs, Torsten, Holl, David, Luoto, Miska, Virkkala, Anna‐Maria, Aalto, Juha, Rogers, Brendan M., Tagesson, Torbern, Treat, Claire C., Natali, Susan M., Watts, Jennifer D., Potter, Stefano, Lehtonen, Aleksi, Mauritz, Marguerite, Schuur, Edward A. G., Kochendorfer, John, Zona, Donatella, Oechel, Walter, Kobayashi, Hideki, Humphreys, Elyn, Goeckede, Mathias, Iwata, Hiroki, Lafleur, Peter M., Euskirchen, Eugenie S., Bokhorst, Stef, Marushchak, Maija, Martikainen, Pertti J., Elberling, Bo, Voigt, Carolina, Biasi, Christina, Sonnentag, Oliver, Parmentier, Frans‐Jan W., Ueyama, Masahito, Celis, Gerardo, St.Louis, Vincent L., Emmerton, Craig A., Peichl, Matthias, Chi, Jinshu, Järveoja, Järvi, Nilsson, Mats B., Oberbauer, Steven F., Torn, Margaret S., Park, Sang‐Jong, Dolman, Han, Mammarella, Ivan, Chae, Namyi, Poyatos, Rafael, López‐Blanco, Efrén, Christensen, Torben Røjle, Kwon, Min Jung, Sachs, Torsten, Holl, David, and Luoto, Miska
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The regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink-source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high-latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km2) across the high-latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE-focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m−2 yr−1, respectively) compared to tundra (average annual NEE +10 and −2 g C m−2 yr−1). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high-latitude region was on average an annual CO2 sink during 1990–2015, although uncertainty remains high.
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- 2021
136. Representativeness of eddy-covariance flux footprints for areas surrounding AmeriFlux sites
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Chu, Housen, Luo, Xiangzhong, Ouyang, Zutao, Chan, W. Stephen, Dengel, Sigrid, Biraud, Sebastien, Torn, Margaret S., Metzger, Stefan, Kumar, Jitendra, Arain, M. Altaf, Arkebauer, Tim J., Baldocchi, Dennis D., Bernacchi, Carl, Billesbach, Dave, Black, T. Andrew, Blanken, Peter D., Bohrer, Gil, Bracho, Rosvel, Brown, Shannon, Brunsell, Nathaniel A., Chen, Jiquan, Chen, Xingyuan, Clark, Kenneth, Desai, Ankur R., Duman, Tomer, Durden, David J., Fares, Silvano, Forbrich, Inke, Gamon, John, Gough, Christopher M., Griffis, Timothy, Helbig, Manuel, Hollinger, David, Humphreys, Elyn, Ikawa, Hiroki, Iwata, Hiroki, Ju, Yang, Knowles, John F., Knox, Sara H., Kobayashi, Hideki, Kolb, Thomas, Law, Beverly, Lee, Xuhui, Litvak, Marcy, Liu, Heping, Munger, J. William, Noormets, Asko, Novick, Kim, Oberbauer, Steven F., Oechel, Walter, Oikawa, Patty, Papuga, Shirley A., Pendall, Elise, Prajapati, Prajaya, Prueger, John, Quinton, William L., Richardson, Andrew D., Russell, Eric S., Scott, Russell L., Starr, Gregory, Staebler, Ralf, Stoy, Paul C., Stuart-Haëntjens, Ellen, Sonnentag, Oliver, Sullivan, Ryan C., Suyker, Andy, Ueyama, Masahito, Vargas, Rodrigo, Wood, Jeffrey D., Zona, Donatella, Chu, Housen, Luo, Xiangzhong, Ouyang, Zutao, Chan, W. Stephen, Dengel, Sigrid, Biraud, Sebastien, Torn, Margaret S., Metzger, Stefan, Kumar, Jitendra, Arain, M. Altaf, Arkebauer, Tim J., Baldocchi, Dennis D., Bernacchi, Carl, Billesbach, Dave, Black, T. Andrew, Blanken, Peter D., Bohrer, Gil, Bracho, Rosvel, Brown, Shannon, Brunsell, Nathaniel A., Chen, Jiquan, Chen, Xingyuan, Clark, Kenneth, Desai, Ankur R., Duman, Tomer, Durden, David J., Fares, Silvano, Forbrich, Inke, Gamon, John, Gough, Christopher M., Griffis, Timothy, Helbig, Manuel, Hollinger, David, Humphreys, Elyn, Ikawa, Hiroki, Iwata, Hiroki, Ju, Yang, Knowles, John F., Knox, Sara H., Kobayashi, Hideki, Kolb, Thomas, Law, Beverly, Lee, Xuhui, Litvak, Marcy, Liu, Heping, Munger, J. William, Noormets, Asko, Novick, Kim, Oberbauer, Steven F., Oechel, Walter, Oikawa, Patty, Papuga, Shirley A., Pendall, Elise, Prajapati, Prajaya, Prueger, John, Quinton, William L., Richardson, Andrew D., Russell, Eric S., Scott, Russell L., Starr, Gregory, Staebler, Ralf, Stoy, Paul C., Stuart-Haëntjens, Ellen, Sonnentag, Oliver, Sullivan, Ryan C., Suyker, Andy, Ueyama, Masahito, Vargas, Rodrigo, Wood, Jeffrey D., and Zona, Donatella
- Abstract
© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Chu, H., Luo, X., Ouyang, Z., Chan, W. S., Dengel, S., Biraud, S. C., Torn, M. S., Metzger, S., Kumar, J., Arain, M. A., Arkebauer, T. J., Baldocchi, D., Bernacchi, C., Billesbach, D., Black, T. A., Blanken, P. D., Bohrer, G., Bracho, R., Brown, S., Brunsell, N. A., Chen, J., Chen, X., Clark, K., Desai, A. R., Duman, T., Durden, D., Fares, S., Forbrich, I., Gamon, J. A., Gough, C. M., Griffis, T., Helbig, M., Hollinger, D., Humphreys, E., Ikawa, H., Iwata, H., Ju, Y., Knowles, J. F., Knox, S. H., Kobayashi, H., Kolb, T., Law, B., Lee, X., Litvak, M., Liu, H., Munger, J. W., Noormets, A., Novick, K., Oberbauer, S. F., Oechel, W., Oikawa, P., Papuga, S. A., Pendall, E., Prajapati, P., Prueger, J., Quinton, W. L., Richardson, A. D., Russell, E. S., Scott, R. L., Starr, G., Staebler, R., Stoy, P. C., Stuart-Haentjens, E., Sonnentag, O., Sullivan, R. C., Suyker, A., Ueyama, M., Vargas, R., Wood, J. D., & Zona, D. Representativeness of eddy-covariance flux footprints for areas surrounding AmeriFlux sites. Agricultural and Forest Meteorology, 301, (2021): 108350, https://doi.org/10.1016/j.agrformet.2021.108350., Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 103 to 107 m2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applicat, We thank the AmeriFlux site teams for sharing their data and metadata with the network. Funding for these flux sites is acknowledged in the site data DOI, shown in Table S1. This analysis was supported in part by funding provided to the AmeriFlux Management Project by the U.S. Department of Energy's Office of Science under Contract No. DE-AC02-05CH11231. All footprint climatologies, site-level representativeness indices, and monthly EVI and sensor location biases can be accessed via the Zenodo Data Repository (Datasets S1–S6, http://doi.org/10.5281/zenodo.4015350).
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137. Shallow soils are warmer under trees and tall shrubs across arctic and boreal ecosystems
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Kropp, Heather, Loranty, Michael M., Natali, Susan M., Kholodov, Alexander L., Rocha, Adrian V., Myers-Smith, Isla H., Abbott, Benjamin W., Abermann, Jakob, Blanc-Betes, Elena, Blok, Daan, Blume-Werry, Gesche, Boike, Julia, Breen, Amy L., Cahoon, Sean M. P., Christiansen, Casper T., Douglas, Thomas A., Epstein, Howard E., Frost, Gerald V., Goeckede, Mathias, Høye, Toke T., Mamet, Steven D., O’Donnell, Jonathan A., Olefeldt, David, Phoenix, Gareth K., Salmon, Verity G., Sannel, A. Britta K., Smith, Sharon L., Sonnentag, Oliver, Smith Vaughn, Lydia, Williams, Mathew, Elberling, Bo, Gough, Laura, Hjort, Jan, Lafleur, Peter M., Euskirchen, Eugenie, Heijmans, Monique M. P. D., Humphreys, Elyn, Iwata, Hiroki, Jones, Benjamin M., Jorgenson, M. Torre, Grünberg, Inge, Kim, Yongwon, Laundre, James A., Mauritz, Marguerite, Michelsen, Anders, Schaepman-Strub, Gabriela, Tape, Ken D., Ueyama, Masahito, Lee, Bang-Yong, Langley, Kirsty, Lund, Magnus, Kropp, Heather, Loranty, Michael M., Natali, Susan M., Kholodov, Alexander L., Rocha, Adrian V., Myers-Smith, Isla H., Abbott, Benjamin W., Abermann, Jakob, Blanc-Betes, Elena, Blok, Daan, Blume-Werry, Gesche, Boike, Julia, Breen, Amy L., Cahoon, Sean M. P., Christiansen, Casper T., Douglas, Thomas A., Epstein, Howard E., Frost, Gerald V., Goeckede, Mathias, Høye, Toke T., Mamet, Steven D., O’Donnell, Jonathan A., Olefeldt, David, Phoenix, Gareth K., Salmon, Verity G., Sannel, A. Britta K., Smith, Sharon L., Sonnentag, Oliver, Smith Vaughn, Lydia, Williams, Mathew, Elberling, Bo, Gough, Laura, Hjort, Jan, Lafleur, Peter M., Euskirchen, Eugenie, Heijmans, Monique M. P. D., Humphreys, Elyn, Iwata, Hiroki, Jones, Benjamin M., Jorgenson, M. Torre, Grünberg, Inge, Kim, Yongwon, Laundre, James A., Mauritz, Marguerite, Michelsen, Anders, Schaepman-Strub, Gabriela, Tape, Ken D., Ueyama, Masahito, Lee, Bang-Yong, Langley, Kirsty, and Lund, Magnus
- Abstract
© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Kropp, H., Loranty, M. M., Natali, S. M., Kholodov, A. L., Rocha, A., V., Myers-Smith, I., Abbot, B. W., Abermann, J., Blanc-Betes, E., Blok, D., Blume-Werry, G., Boike, J., Breen, A. L., Cahoon, S. M. P., Christiansen, C. T., Douglas, T. A., Epstein, H. E., Frost, G., V., Goeckede, M., Hoye, T. T., Mamet, S. D., O'Donnell, J. A., Olefeldt, D., Phoenix, G. K., Salmon, V. G., Sannel, A. B. K., Smith, S. L., Sonnentag, O., Vaughn, L. S., Williams, M., Elberling, B., Gough, L., Hjort, J., Lafleur, P. M., Euskirchen, E. S., Heijmans, M. M. P. D., Humphreys, E. R., Iwata, H., Jones, B. M., Jorgenson, M. T., Gruenberg, I., Kim, Y., Laundre, J., Mauritz, M., Michelsen, A., Schaepman-Strub, G., Tape, K. D., Ueyama, M., Lee, B., Langley, K., & Lund, M. Shallow soils are warmer under trees and tall shrubs across arctic and boreal ecosystems. Environmental Research Letters, 16(1), (2021): 015001. doi:10.1088/1748-9326/abc994., Soils are warming as air temperatures rise across the Arctic and Boreal region concurrent with the expansion of tall-statured shrubs and trees in the tundra. Changes in vegetation structure and function are expected to alter soil thermal regimes, thereby modifying climate feedbacks related to permafrost thaw and carbon cycling. However, current understanding of vegetation impacts on soil temperature is limited to local or regional scales and lacks the generality necessary to predict soil warming and permafrost stability on a pan-Arctic scale. Here we synthesize shallow soil and air temperature observations with broad spatial and temporal coverage collected across 106 sites representing nine different vegetation types in the permafrost region. We showed ecosystems with tall-statured shrubs and trees (>40 cm) have warmer shallow soils than those with short-statured tundra vegetation when normalized to a constant air temperature. In tree and tall shrub vegetation types, cooler temperatures in the warm season do not lead to cooler mean annual soil temperature indicating that ground thermal regimes in the cold-season rather than the warm-season are most critical for predicting soil warming in ecosystems underlain by permafrost. Our results suggest that the expansion of tall shrubs and trees into tundra regions can amplify shallow soil warming, and could increase the potential for increased seasonal thaw depth and increase soil carbon cycling rates and lead to increased carbon dioxide loss and further permafrost thaw., We thank G Peter Kershaw, LeeAnn Fishback, Cathy Wilson, and Coleen Iversen for assistance in collection of data. We thank the Permafrost Carbon Network for support and organization of the data synthesis. We thank Vladimir Romanovsky for his feedback and contribution of publicly available data. This project was supported by the National Science Foundation (Grant No. 1417745 to M L, Grant No. 1417700 to S M N, Grant No. 1417908 to A K, Grant No. 1556772 to A R, Grant No. 1637459 to L G, Grant No. 1636476 and Grant No. 1503912 to E S E, Grant No. 1806213 to B M J, Grant No. 1833056 to K D T), UK Natural Environment Research Council (Grant No. NE/M016323/1 to I H M S, Grant No. NE/K00025X/1 to G K P, Grant No. NE/K000292/1 to M W), Natural Sciences and Engineering Research (to P L, I H M S, Grant No. RGPIN-2016-04688 to D O), Council of Canada, Canadian Graduate Scholarship to (I H M -S), Greenland Ecosystem Monitoring Programme: ClimateBasis (to J A and K A), The Next-Generation Ecosystem Experiments (NGEE Arctic) project is supported by the Office of Biological and Environmental Research in the DOE Office of Science (to A L B), Engineer Research and Development Center Army Direct (6.1) Research Program and the Strategic Environmental Research and Development Program (projects RC-2110 and 18-1170 to T A D), United States Geological Survey (to E E S), Arctic Challenge for Sustainability (ArCS; Grant No. JPMXD1300000000) and ArCS II (Grant No. JPMXD1420318865) (to M U and H I), the Danish National Research Foundation (Grant No. CENPERM DNRF100 to B E), the Academy of Finland (Grant No. 315519), the National Research Foundation of Korea (Grant Nos. NRF-2016M1A5A1901769; KOPRI-PN20081 to K Y and B Y L), Research Network for Geosciences in Berlin and Potsdam (to I G), the Swiss National Science Foundation (Grant No. 140631 to G S S), the URPP Global Change and Biodiversity, University of Zurich (to G S S), the University of Alberta Northern Research Awards (to D O), and th
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- 2021
138. Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales.
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Knox, Sara H, Knox, Sara H, Bansal, Sheel, McNicol, Gavin, Schafer, Karina, Sturtevant, Cove, Ueyama, Masahito, Valach, Alex C, Baldocchi, Dennis, Delwiche, Kyle, Desai, Ankur R, Euskirchen, Eugenie, Liu, Jinxun, Lohila, Annalea, Malhotra, Avni, Melling, Lulie, Riley, William, Runkle, Benjamin RK, Turner, Jessica, Vargas, Rodrigo, Zhu, Qing, Alto, Tuula, Fluet-Chouinard, Etienne, Goeckede, Mathias, Melton, Joe R, Sonnentag, Oliver, Vesala, Timo, Ward, Eric, Zhang, Zhen, Feron, Sarah, Ouyang, Zutao, Alekseychik, Pavel, Aurela, Mika, Bohrer, Gil, Campbell, David I, Chen, Jiquan, Chu, Housen, Dalmagro, Higo J, Goodrich, Jordan P, Gottschalk, Pia, Hirano, Takashi, Iwata, Hiroki, Jurasinski, Gerald, Kang, Minseok, Koebsch, Franziska, Mammarella, Ivan, Nilsson, Mats B, Ono, Keisuke, Peichl, Matthias, Peltola, Olli, Ryu, Youngryel, Sachs, Torsten, Sakabe, Ayaka, Sparks, Jed P, Tuittila, Eeva-Stiina, Vourlitis, George L, Wong, Guan X, Windham-Myers, Lisamarie, Poulter, Benjamin, Jackson, Robert B, Knox, Sara H, Knox, Sara H, Bansal, Sheel, McNicol, Gavin, Schafer, Karina, Sturtevant, Cove, Ueyama, Masahito, Valach, Alex C, Baldocchi, Dennis, Delwiche, Kyle, Desai, Ankur R, Euskirchen, Eugenie, Liu, Jinxun, Lohila, Annalea, Malhotra, Avni, Melling, Lulie, Riley, William, Runkle, Benjamin RK, Turner, Jessica, Vargas, Rodrigo, Zhu, Qing, Alto, Tuula, Fluet-Chouinard, Etienne, Goeckede, Mathias, Melton, Joe R, Sonnentag, Oliver, Vesala, Timo, Ward, Eric, Zhang, Zhen, Feron, Sarah, Ouyang, Zutao, Alekseychik, Pavel, Aurela, Mika, Bohrer, Gil, Campbell, David I, Chen, Jiquan, Chu, Housen, Dalmagro, Higo J, Goodrich, Jordan P, Gottschalk, Pia, Hirano, Takashi, Iwata, Hiroki, Jurasinski, Gerald, Kang, Minseok, Koebsch, Franziska, Mammarella, Ivan, Nilsson, Mats B, Ono, Keisuke, Peichl, Matthias, Peltola, Olli, Ryu, Youngryel, Sachs, Torsten, Sakabe, Ayaka, Sparks, Jed P, Tuittila, Eeva-Stiina, Vourlitis, George L, Wong, Guan X, Windham-Myers, Lisamarie, Poulter, Benjamin, and Jackson, Robert B
- Abstract
While wetlands are the largest natural source of methane (CH4 ) to the atmosphere, they represent a large source of uncertainty in the global CH4 budget due to the complex biogeochemical controls on CH4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17 ± 11 days, and lagged air and soil temperature by median values of 8 ± 16 and 5 ± 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH4 . At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of
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- 2021
139. Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions.
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Chang, Kuang-Yu, Chang, Kuang-Yu, Riley, William J, Knox, Sara H, Jackson, Robert B, McNicol, Gavin, Poulter, Benjamin, Aurela, Mika, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I, Cescatti, Alessandro, Chu, Housen, Delwiche, Kyle B, Desai, Ankur R, Euskirchen, Eugenie, Friborg, Thomas, Goeckede, Mathias, Helbig, Manuel, Hemes, Kyle S, Hirano, Takashi, Iwata, Hiroki, Kang, Minseok, Keenan, Trevor, Krauss, Ken W, Lohila, Annalea, Mammarella, Ivan, Mitra, Bhaskar, Miyata, Akira, Nilsson, Mats B, Noormets, Asko, Oechel, Walter C, Papale, Dario, Peichl, Matthias, Reba, Michele L, Rinne, Janne, Runkle, Benjamin RK, Ryu, Youngryel, Sachs, Torsten, Schäfer, Karina VR, Schmid, Hans Peter, Shurpali, Narasinha, Sonnentag, Oliver, Tang, Angela CI, Torn, Margaret S, Trotta, Carlo, Tuittila, Eeva-Stiina, Ueyama, Masahito, Vargas, Rodrigo, Vesala, Timo, Windham-Myers, Lisamarie, Zhang, Zhen, Zona, Donatella, Chang, Kuang-Yu, Chang, Kuang-Yu, Riley, William J, Knox, Sara H, Jackson, Robert B, McNicol, Gavin, Poulter, Benjamin, Aurela, Mika, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I, Cescatti, Alessandro, Chu, Housen, Delwiche, Kyle B, Desai, Ankur R, Euskirchen, Eugenie, Friborg, Thomas, Goeckede, Mathias, Helbig, Manuel, Hemes, Kyle S, Hirano, Takashi, Iwata, Hiroki, Kang, Minseok, Keenan, Trevor, Krauss, Ken W, Lohila, Annalea, Mammarella, Ivan, Mitra, Bhaskar, Miyata, Akira, Nilsson, Mats B, Noormets, Asko, Oechel, Walter C, Papale, Dario, Peichl, Matthias, Reba, Michele L, Rinne, Janne, Runkle, Benjamin RK, Ryu, Youngryel, Sachs, Torsten, Schäfer, Karina VR, Schmid, Hans Peter, Shurpali, Narasinha, Sonnentag, Oliver, Tang, Angela CI, Torn, Margaret S, Trotta, Carlo, Tuittila, Eeva-Stiina, Ueyama, Masahito, Vargas, Rodrigo, Vesala, Timo, Windham-Myers, Lisamarie, Zhang, Zhen, and Zona, Donatella
- Abstract
Wetland methane (CH4) emissions ([Formula: see text]) are important in global carbon budgets and climate change assessments. Currently, [Formula: see text] projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent [Formula: see text] temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that [Formula: see text] are often controlled by factors beyond temperature. Here, we evaluate the relationship between [Formula: see text] and temperature using observations from the FLUXNET-CH4 database. Measurements collected across the globe show substantial seasonal hysteresis between [Formula: see text] and temperature, suggesting larger [Formula: see text] sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH4 production are thus needed to improve global CH4 budget assessments.
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- 2021
140. Gap-filling eddy covariance methane fluxes:Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands
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Irvin, Jeremy, Zhou, Sharon, Mcnicol, Gavin, Lu, Fred, Liu, Vincent, Fluet-chouinard, Etienne, Ouyang, Zutao, Knox, Sara Helen, Lucas-moffat, Antje, Trotta, Carlo, Papale, Dario, Vitale, Domenico, Mammarella, Ivan, Alekseychik, Pavel, Aurela, Mika, Avati, Anand, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I, Chen, Jiquan, Chu, Housen, Dalmagro, Higo J, Delwiche, Kyle B, Desai, Ankur R, Euskirchen, Eugenie, Feron, Sarah, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S, Hirano, Takashi, Iwata, Hiroki, Jurasinski, Gerald, Kalhori, Aram, Kondrich, Andrew, Lai, Derrick Yf, Lohila, Annalea, Malhotra, Avni, Merbold, Lutz, Mitra, Bhaskar, Ng, Andrew, Nilsson, Mats B, Noormets, Asko, Peichl, Matthias, Rey-sanchez, A. Camilo, Richardson, Andrew D, Runkle, Benjamin Rk, Schäfer, Karina Vr, Sonnentag, Oliver, Stuart-haëntjens, Ellen, Sturtevant, Cove, Ueyama, Masahito, Valach, Alex C, Vargas, Rodrigo, Vourlitis, George L, Ward, Eric J, Wong, Guan Xhuan, Zona, Donatella, Alberto, Ma. Carmelita R, Billesbach, David P, Celis, Gerardo, Dolman, Han, Friborg, Thomas, Fuchs, Kathrin, Gogo, Sébastien, Gondwe, Mangaliso J, Goodrich, Jordan P, Gottschalk, Pia, Hörtnagl, Lukas, Jacotot, Adrien, Koebsch, Franziska, Kasak, Kuno, Maier, Regine, Morin, Timothy H, Nemitz, Eiko, Oechel, Walter C, Oikawa, Patricia Y, Ono, Keisuke, Sachs, Torsten, Sakabe, Ayaka, Schuur, Edward A, Shortt, Robert, Sullivan, Ryan C, Szutu, Daphne J, Tuittila, Eeva-stiina, Varlagin, Andrej, Verfaillie, Joeseph G, Wille, Christian, Windham-myers, Lisamarie, Poulter, Benjamin, Jackson, Robert B, Irvin, Jeremy, Zhou, Sharon, Mcnicol, Gavin, Lu, Fred, Liu, Vincent, Fluet-chouinard, Etienne, Ouyang, Zutao, Knox, Sara Helen, Lucas-moffat, Antje, Trotta, Carlo, Papale, Dario, Vitale, Domenico, Mammarella, Ivan, Alekseychik, Pavel, Aurela, Mika, Avati, Anand, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I, Chen, Jiquan, Chu, Housen, Dalmagro, Higo J, Delwiche, Kyle B, Desai, Ankur R, Euskirchen, Eugenie, Feron, Sarah, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S, Hirano, Takashi, Iwata, Hiroki, Jurasinski, Gerald, Kalhori, Aram, Kondrich, Andrew, Lai, Derrick Yf, Lohila, Annalea, Malhotra, Avni, Merbold, Lutz, Mitra, Bhaskar, Ng, Andrew, Nilsson, Mats B, Noormets, Asko, Peichl, Matthias, Rey-sanchez, A. Camilo, Richardson, Andrew D, Runkle, Benjamin Rk, Schäfer, Karina Vr, Sonnentag, Oliver, Stuart-haëntjens, Ellen, Sturtevant, Cove, Ueyama, Masahito, Valach, Alex C, Vargas, Rodrigo, Vourlitis, George L, Ward, Eric J, Wong, Guan Xhuan, Zona, Donatella, Alberto, Ma. Carmelita R, Billesbach, David P, Celis, Gerardo, Dolman, Han, Friborg, Thomas, Fuchs, Kathrin, Gogo, Sébastien, Gondwe, Mangaliso J, Goodrich, Jordan P, Gottschalk, Pia, Hörtnagl, Lukas, Jacotot, Adrien, Koebsch, Franziska, Kasak, Kuno, Maier, Regine, Morin, Timothy H, Nemitz, Eiko, Oechel, Walter C, Oikawa, Patricia Y, Ono, Keisuke, Sachs, Torsten, Sakabe, Ayaka, Schuur, Edward A, Shortt, Robert, Sullivan, Ryan C, Szutu, Daphne J, Tuittila, Eeva-stiina, Varlagin, Andrej, Verfaillie, Joeseph G, Wille, Christian, Windham-myers, Lisamarie, Poulter, Benjamin, and Jackson, Robert B
- Abstract
Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an impro
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- 2021
141. Gap-filling eddy covariance methane fluxes: comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands
- Author
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Irvin, Jeremy, Zhou, Sharon, McNicol, Gavin, Lu, Fred, Liu, Vincent, Fluet-Chouinard, Etienne, Ouyang, Zutao, Knox, Sara Helen, Lucas-Moffat, Antje, Trotta, Carlo, Papale, Dario, Vitale, Domenico, Mammarella, Ivan, Alekseychik, Pavel, Aurela, Mika, Avati, Anand, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I., Chen, Jiquan, Chu, Housen, Dalmagro, Higo J., Delwiche, Kyle B., Desai, Ankur R., Euskirchen, Eugenie, Feron, Sarah, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S., Hirano, Takashi, Iwata, Hiroki, Jurasinski, Gerald, Kalhori, Aram, Kondrich, Andrew, Lai, Derrick Y.F., Lohila, Annalea, Malhotra, Avni, Merbold, Lutz, Mitra, Bhaskar, Ng, Andrew, Nilsson, Mats B., Noormets, Asko, Peichl, Matthias, Rey-Sanchez, A. Camilo, Richardson, Andrew D., Runkle, Benjamin R.K., Schäfer, Karina V.R., Sonnentag, Oliver, Stuart-Haëntjens, Ellen, Sturtevant, Cove, Ueyama, Masahito, Valach, Alex C., Vargas, Rodrigo, Vourlitis, George L., Ward, Eric J., Wong, Guan Xhuan, Zona, Donatella, Alberto, Ma. Carmelita R., Billesbach, David P., Celis, Gerardo, Dolman, Han, Friborg, Thomas, Fuchs, Kathrin, Gogo, Sébastien, Gondwe, Mangaliso J., Goodrich, Jordan P., Gottschalk, Pia, Hörtnagl, Lukas, Jacotot, Adrien, Koebsch, Franziska, Kasak, Kuno, Maier, Regine, Morin, Timothy H., Nemitz, Eiko, Oechel, Walter C., Oikawa, Patricia Y., Ono, Keisuke, Sachs, Torsten, Sakabe, Ayaka, Schuur, Edward A., Shortt, Robert, Sullivan, Ryan C., Szutu, Daphne J., Tuittila, Eeva-Stiina, Varlagin, Andrej, Verfaillie, Joeseph G., Wille, Christian, Windham-Myers, Lisamarie, Poulter, Benjamin, Jackson, Robert B., Irvin, Jeremy, Zhou, Sharon, McNicol, Gavin, Lu, Fred, Liu, Vincent, Fluet-Chouinard, Etienne, Ouyang, Zutao, Knox, Sara Helen, Lucas-Moffat, Antje, Trotta, Carlo, Papale, Dario, Vitale, Domenico, Mammarella, Ivan, Alekseychik, Pavel, Aurela, Mika, Avati, Anand, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I., Chen, Jiquan, Chu, Housen, Dalmagro, Higo J., Delwiche, Kyle B., Desai, Ankur R., Euskirchen, Eugenie, Feron, Sarah, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S., Hirano, Takashi, Iwata, Hiroki, Jurasinski, Gerald, Kalhori, Aram, Kondrich, Andrew, Lai, Derrick Y.F., Lohila, Annalea, Malhotra, Avni, Merbold, Lutz, Mitra, Bhaskar, Ng, Andrew, Nilsson, Mats B., Noormets, Asko, Peichl, Matthias, Rey-Sanchez, A. Camilo, Richardson, Andrew D., Runkle, Benjamin R.K., Schäfer, Karina V.R., Sonnentag, Oliver, Stuart-Haëntjens, Ellen, Sturtevant, Cove, Ueyama, Masahito, Valach, Alex C., Vargas, Rodrigo, Vourlitis, George L., Ward, Eric J., Wong, Guan Xhuan, Zona, Donatella, Alberto, Ma. Carmelita R., Billesbach, David P., Celis, Gerardo, Dolman, Han, Friborg, Thomas, Fuchs, Kathrin, Gogo, Sébastien, Gondwe, Mangaliso J., Goodrich, Jordan P., Gottschalk, Pia, Hörtnagl, Lukas, Jacotot, Adrien, Koebsch, Franziska, Kasak, Kuno, Maier, Regine, Morin, Timothy H., Nemitz, Eiko, Oechel, Walter C., Oikawa, Patricia Y., Ono, Keisuke, Sachs, Torsten, Sakabe, Ayaka, Schuur, Edward A., Shortt, Robert, Sullivan, Ryan C., Szutu, Daphne J., Tuittila, Eeva-Stiina, Varlagin, Andrej, Verfaillie, Joeseph G., Wille, Christian, Windham-Myers, Lisamarie, Poulter, Benjamin, and Jackson, Robert B.
- Abstract
Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an impro
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- 2021
142. Statistical upscaling of ecosystem CO2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties
- Author
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Virkkala, Anna‐Maria, Aalto, Juha, Rogers, Brendan M., Tagesson, Torbern, Treat, Claire C., Natali, Susan M., Watts, Jennifer D., Potter, Stefano, Lehtonen, Aleksi, Mauritz, Marguerite, Schuur, Edward A. G., Kochendorfer, John, Zona, Donatella, Oechel, Walter, Kobayashi, Hideki, Humphreys, Elyn, Goeckede, Mathias, Iwata, Hiroki, Lafleur, Peter M., Euskirchen, Eugenie S., Bokhorst, Stef, Marushchak, Maija, Martikainen, Pertti J., Elberling, Bo, Voigt, Carolina, Biasi, Christina, Sonnentag, Oliver, Parmentier, Frans‐Jan W., Ueyama, Masahito, Celis, Gerardo, St.Louis, Vincent L., Emmerton, Craig A., Peichl, Matthias, Chi, Jinshu, Järveoja, Järvi, Nilsson, Mats B., Oberbauer, Steven F., Torn, Margaret S., Park, Sang‐Jong, Dolman, Han, Mammarella, Ivan, Chae, Namyi, Poyatos, Rafael, López‐Blanco, Efrén, Christensen, Torben Røjle, Kwon, Min Jung, Sachs, Torsten, Holl, David, Luoto, Miska, Virkkala, Anna‐Maria, Aalto, Juha, Rogers, Brendan M., Tagesson, Torbern, Treat, Claire C., Natali, Susan M., Watts, Jennifer D., Potter, Stefano, Lehtonen, Aleksi, Mauritz, Marguerite, Schuur, Edward A. G., Kochendorfer, John, Zona, Donatella, Oechel, Walter, Kobayashi, Hideki, Humphreys, Elyn, Goeckede, Mathias, Iwata, Hiroki, Lafleur, Peter M., Euskirchen, Eugenie S., Bokhorst, Stef, Marushchak, Maija, Martikainen, Pertti J., Elberling, Bo, Voigt, Carolina, Biasi, Christina, Sonnentag, Oliver, Parmentier, Frans‐Jan W., Ueyama, Masahito, Celis, Gerardo, St.Louis, Vincent L., Emmerton, Craig A., Peichl, Matthias, Chi, Jinshu, Järveoja, Järvi, Nilsson, Mats B., Oberbauer, Steven F., Torn, Margaret S., Park, Sang‐Jong, Dolman, Han, Mammarella, Ivan, Chae, Namyi, Poyatos, Rafael, López‐Blanco, Efrén, Christensen, Torben Røjle, Kwon, Min Jung, Sachs, Torsten, Holl, David, and Luoto, Miska
- Abstract
The regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink-source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high-latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km2) across the high-latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE-focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m −2 yr−1, respectively) compared to tundra (average annual NEE +10 and −2 g C m−2 yr−1). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high-latitude region was on average a
- Published
- 2021
143. Statistical upscaling of ecosystem CO2 fluxes across the terrestrial tundra and boreal domain:regional patterns and uncertainties
- Author
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Virkkala, Anna-Maria, Aalto, Juha, Rogers, Brendan M, Tagesson, Torbern, Treat, Claire C, Natali, Susan M, Watts, Jennifer D, Potter, Stefano, Lehtonen, Aleksi, Mauritz, Marguerite, Schuur, Edward A G, Kochendorfer, John, Zona, Donatella, Oechel, Walter, Kobayashi, Hideki, Humphreys, Elyn, Goeckede, Mathias, Iwata, Hiroki, Lafleur, Peter M, Euskirchen, Eugenie S, Bokhorst, Stef, Marushchak, Maija, Martikainen, Pertti J, Elberling, Bo, Voigt, Carolina, Biasi, Christina, Sonnentag, Oliver, Parmentier, Frans-Jan W, Ueyama, Masahito, Celis, Gerardo, St Loius, Vincent L, Emmerton, Craig A, Peichl, Matthias, Chi, Jinshu, Järveoja, Järvi, Nilsson, Mats B, Oberbauer, Steven F, Torn, Margaret S, Park, Sang-Jong, Dolman, Han, Mammarella, Ivan, Chae, Namyi, Poyatos, Rafael, López-Blanco, Efrén, Røjle Christensen, Torben, Jung Kwon, Min, Sachs, Torsten, Holl, David, Luoto, Miska, Virkkala, Anna-Maria, Aalto, Juha, Rogers, Brendan M, Tagesson, Torbern, Treat, Claire C, Natali, Susan M, Watts, Jennifer D, Potter, Stefano, Lehtonen, Aleksi, Mauritz, Marguerite, Schuur, Edward A G, Kochendorfer, John, Zona, Donatella, Oechel, Walter, Kobayashi, Hideki, Humphreys, Elyn, Goeckede, Mathias, Iwata, Hiroki, Lafleur, Peter M, Euskirchen, Eugenie S, Bokhorst, Stef, Marushchak, Maija, Martikainen, Pertti J, Elberling, Bo, Voigt, Carolina, Biasi, Christina, Sonnentag, Oliver, Parmentier, Frans-Jan W, Ueyama, Masahito, Celis, Gerardo, St Loius, Vincent L, Emmerton, Craig A, Peichl, Matthias, Chi, Jinshu, Järveoja, Järvi, Nilsson, Mats B, Oberbauer, Steven F, Torn, Margaret S, Park, Sang-Jong, Dolman, Han, Mammarella, Ivan, Chae, Namyi, Poyatos, Rafael, López-Blanco, Efrén, Røjle Christensen, Torben, Jung Kwon, Min, Sachs, Torsten, Holl, David, and Luoto, Miska
- Abstract
The regional variability in tundra and boreal carbon dioxide (CO2 ) fluxes can be high, complicating efforts to quantify sink-source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990-2015 from 148 terrestrial high-latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km2 ) across the high-latitude region using five commonly-used statistical models and their ensemble, i.e., the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE-focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE -46 and -29 g C m-2 yr-1 , respectively) compared to tundra (average annual NEE +10 and -2 g C m-2 yr-1 ). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high-latitude region was on average an annual CO2 sink during 1990-2015, although uncertainty remains high.
- Published
- 2021
144. Arctic soil methane sink increases with drier conditions and higher ecosystem respiration
- Author
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Voigt, Carolina, Virkkala, Anna-Maria, Hould Gosselin, Gabriel, Bennett, Kathryn A., Black, T. Andrew, Detto, Matteo, Chevrier-Dion, Charles, Guggenberger, Georg, Hashmi, Wasi, Kohl, Lukas, Kou, Dan, Marquis, Charlotte, Marsh, Philip, Marushchak, Maija E., Nesic, Zoran, Nykänen, Hannu, Saarela, Taija, Sauheitl, Leopold, Walker, Branden, Weiss, Niels, Wilcox, Evan J., and Sonnentag, Oliver
- Abstract
Arctic wetlands are known methane (CH4) emitters but recent studies suggest that the Arctic CH4sink strength may be underestimated. Here we explore the capacity of well-drained Arctic soils to consume atmospheric CH4using >40,000 hourly flux observations and spatially distributed flux measurements from 4 sites and 14 surface types. While consumption of atmospheric CH4occurred at all sites at rates of 0.092 ± 0.011 mgCH4m−2h−1(mean ± s.e.), CH4uptake displayed distinct diel and seasonal patterns reflecting ecosystem respiration. Combining in situ flux data with laboratory investigations and a machine learning approach, we find biotic drivers to be highly important. Soil moisture outweighed temperature as an abiotic control and higher CH4uptake was linked to increased availability of labile carbon. Our findings imply that soil drying and enhanced nutrient supply will promote CH4uptake by Arctic soils, providing a negative feedback to global climate change.
- Published
- 2023
- Full Text
- View/download PDF
145. Thermodynamic basis for the demarcation of Arctic and alpine treelines.
- Author
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Martin, Meredith Richardson, Kumar, Praveen, Sonnentag, Oliver, and Marsh, Philip
- Subjects
TUNDRAS ,SURFACE of the earth ,MOUNTAIN ecology ,MOUNTAIN meadows ,TIMBERLINE ,TEMPERATURE inversions ,ATMOSPHERE - Abstract
At the edge of alpine and Arctic ecosystems all over the world, a transition zone exists beyond which it is either infeasible or unfavorable for trees to exist, colloquially identified as the treeline. We explore the possibility of a thermodynamic basis behind this demarcation in vegetation by considering ecosystems as open systems driven by thermodynamic advantage—defined by vegetation's ability to dissipate heat from the earth's surface to the air above the canopy. To deduce whether forests would be more thermodynamically advantageous than existing ecosystems beyond treelines, we construct and examine counterfactual scenarios in which trees exist beyond a treeline instead of the existing alpine meadow or Arctic tundra. Meteorological data from the Italian Alps, United States Rocky Mountains, and Western Canadian Taiga-Tundra are used as forcing for model computation of ecosystem work and temperature gradients at sites on both sides of each treeline with and without trees. Model results indicate that the alpine sites do not support trees beyond the treeline, as their presence would result in excessive CO 2 loss and extended periods of snowpack due to temperature inversions (i.e., positive temperature gradient from the earth surface to the atmosphere). Further, both Arctic and alpine sites exhibit negative work resulting in positive feedback between vegetation heat dissipation and temperature gradient, thereby extending the duration of temperature inversions. These conditions demonstrate thermodynamic infeasibility associated with the counterfactual scenario of trees existing beyond a treeline. Thus, we conclude that, in addition to resource constraints, a treeline is an outcome of an ecosystem's ability to self-organize towards the most advantageous vegetation structure facilitated by thermodynamic feasibility. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
146. Pan-Arctic soil element availability estimations.
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Stimmler, Peter, Goeckede, Mathias, Elberling, Bo, Natali, Susan, Kuhry, Peter, Perron, Nia, Lacroix, Fabrice, Hugelius, Gustaf, Sonnentag, Oliver, Strauss, Jens, Minions, Christina, Sommer, Michael, and Schaller, Jörg
- Subjects
TUNDRAS ,CLIMATE feedbacks ,SILICA ,SOILS ,GLOBAL warming ,BIOGEOCHEMICAL cycles - Abstract
Arctic soils store large amounts of organic carbon and other elements such as amorphous silica, silicon, calcium, iron, aluminium, and phosphorous. Global warming is projected to be most pronounced in the Arctic leading to thawing permafrost, which in turn is changing the soil element availability. To project how biogeochemical cycling in Arctic ecosystems will be affected by climate change, there is a need for data on element availability. Here, we analysed amorphous silica (ASi), silicon (Si), calcium (Ca), iron (Fe), phosphorus (P), and aluminium (Al) availability from 574 soil samples from the circumpolar Arctic region. We show large differences in ASi, Si, Ca, Fe, P, and Al availability among different lithologies and Arctic regions. We summarized these data in pan-Arctic maps of ASi, Si, Ca, Fe, P, and Al concentrations focussing on the top 100 cm of Arctic soil. Furthermore, we provide values for element availability for the organic and the mineral layer of the seasonally thawing active layer as well as for the uppermost permafrost layer. Our spatially explicit data on differences in the availability of elements between the different lithological classes and regions now and in the future will improve Arctic Earth system models for estimating current and future carbon and nutrient feedbacks under climate change. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
147. Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions
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Chang, Kuang-Yu, primary, Riley, William J., additional, Knox, Sara H., additional, Jackson, Robert B., additional, McNicol, Gavin, additional, Poulter, Benjamin, additional, Aurela, Mika, additional, Baldocchi, Dennis, additional, Bansal, Sheel, additional, Bohrer, Gil, additional, Campbell, David I., additional, Cescatti, Alessandro, additional, Chu, Housen, additional, Delwiche, Kyle B., additional, Desai, Ankur R., additional, Euskirchen, Eugenie, additional, Friborg, Thomas, additional, Goeckede, Mathias, additional, Helbig, Manuel, additional, Hemes, Kyle S., additional, Hirano, Takashi, additional, Iwata, Hiroki, additional, Kang, Minseok, additional, Keenan, Trevor, additional, Krauss, Ken W., additional, Lohila, Annalea, additional, Mammarella, Ivan, additional, Mitra, Bhaskar, additional, Miyata, Akira, additional, Nilsson, Mats B., additional, Noormets, Asko, additional, Oechel, Walter C., additional, Papale, Dario, additional, Peichl, Matthias, additional, Reba, Michele L., additional, Rinne, Janne, additional, Runkle, Benjamin R. K., additional, Ryu, Youngryel, additional, Sachs, Torsten, additional, Schäfer, Karina V. R., additional, Schmid, Hans Peter, additional, Shurpali, Narasinha, additional, Sonnentag, Oliver, additional, Tang, Angela C. I., additional, Torn, Margaret S., additional, Trotta, Carlo, additional, Tuittila, Eeva-Stiina, additional, Ueyama, Masahito, additional, Vargas, Rodrigo, additional, Vesala, Timo, additional, Windham-Myers, Lisamarie, additional, Zhang, Zhen, additional, and Zona, Donatella, additional
- Published
- 2021
- Full Text
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148. Widespread decline in winds delayed autumn foliar senescence over high latitudes
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Wu, Chaoyang, primary, Wang, Jian, additional, Ciais, Philippe, additional, Peñuelas, Josep, additional, Zhang, Xiaoyang, additional, Sonnentag, Oliver, additional, Tian, Feng, additional, Wang, Xiaoyue, additional, Wang, Huanjiong, additional, Liu, Ronggao, additional, Fu, Yongshuo H., additional, and Ge, Quansheng, additional
- Published
- 2021
- Full Text
- View/download PDF
149. Effects of Warming and Permafrost Thaw on Carbon Dioxide Fluxes from Boreal Peatlands in northwestern Canada
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Schulze, Christopher, primary, Olefeldt, David, additional, Kljun, Natascha, additional, Chasmer, Laura, additional, Hopkinson, Chris, additional, Helbig, Manuel, additional, Gosselin, Gabriel Hould, additional, and Sonnentag, Oliver, additional
- Published
- 2021
- Full Text
- View/download PDF
150. L-band vegetation optical depth as an indicator of plant water potential in a temperate deciduous forest stand
- Author
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Holtzman, Nataniel, primary, Anderegg, Leander, additional, Kraatz, Simon, additional, Mavrovic, Alex, additional, Sonnentag, Oliver, additional, Pappas, Christoforos, additional, Cosh, Michael, additional, Langlois, Alexandre, additional, Lakhankar, Tarendra, additional, Tesser, Derek, additional, Steiner, Nicholas, additional, Colliander, Andreas, additional, Roy, Alexandre, additional, and Konings, Alexandra, additional
- Published
- 2021
- Full Text
- View/download PDF
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