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1. Multiple Ecosystem Effects of Extreme Weather Events in the Arctic

Author: Christensen, T. R., Lund, M., Skov, K., Abermann, J., López-Blanco, E., Scheller, J., Scheel, M., Jackowicz-Korczynski, M., Langley, K., Murphy, M. J., and Mastepanov, M.
Published: 2021
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2. Rapid shift in greenhouse forcing of emerging arctic peatlands

Author: Christensen, T. R. (Torben R.), Scheller, J. (Johan), Scheel, M. (Maria), Rudd, D. A. (Daniel Alexander), Jackowicz-Korczynski, M. (Marcin), Mastepanov, M. (Mikhail), López-Blanco, E. (Efrén), Christensen, T. R. (Torben R.), Scheller, J. (Johan), Scheel, M. (Maria), Rudd, D. A. (Daniel Alexander), Jackowicz-Korczynski, M. (Marcin), Mastepanov, M. (Mikhail), and López-Blanco, E. (Efrén)
Abstract: In this study, we hypothesised that the actual development stage (i.e., current age of the ecosystem) is a determining factor for the magnitude of methane production and emissions in young, northern high-latitude peatlands. We demonstrate that the earliest development of peat soil imposes a sink-to-source shift in the greenhouse warming potential of emerging peatlands in response to climate change that holds feedback mechanisms of importance for short-term (< 100 years) climate warming.
Published: 2023

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

Author: Virkkala, A., Natali, S., Rogers, B., Watts, J., Savage, K., Connon, S., Mauritz, M., Schuur, E., Peter, D., Minions, C., Nojeim, J., Commane, R., Emmerton, C., Göckede, M., Helbig, M., Holl, D., Iwata, H., Kobayashi, H., Kolari, P., López-Blanco, E., Marushchak, M., Mastepanov, M., Merbold, L., Parmentier, F., Peichl, M., Sachs, T., Sonnentag, O., Ueyama, M., Voigt, C., Aurela, M., Boike, J., Celis, G., Chae, N., Christensen, T., Bret-Harte, M., Dengel, S., Dolman, H., Edgar, C., Elberling, B., Euskirchen, E., Grelle, A., Hatakka, J., Humphreys, E., Järveoja, J., Kotani, A., Kutzbach, L., Laurila, T., Lohila, A., Mammarella, I., Matsuura, Y., Meyer, G., Nilsson, M., Oberbauer, S., Park, S., Petrov, R., Prokushkin, A., Schulze, C., St.Louis, V., Tuittila, E., Tuovinen, J., Quinton, W., Varlagin, A., Zona, D., Zyryanov, V., Earth Sciences, Institute for Atmospheric and Earth System Research (INAR), Micrometeorology and biogeochemical cycles, and Ecosystem processes (INAR Forest Sciences)
Subjects: hiilidioksidi, arktinen alue, maaperä, Climate Research, EDDY COVARIANCE TECHNIQUE, CARBON-DIOXIDE EXCHANGE, SPATIAL VARIABILITY, kausivaihtelut, FOREST, 114 Physical sciences, PERMAFROST CARBON, Physical Geography and Environmental Geoscience, TUNDRA, Atmospheric Sciences, NET, kasvihuonekaasut, Geochemistry, RESPIRATION, Meteorology and Atmospheric Sciences, SDG 13 - Climate Action, STOCKS, päästöt, tutkimusaineisto, CHAMBER
Abstract: Past efforts to synthesize and quantify the magnitude and change in carbon dioxide (CO2) fluxes in terrestrial ecosystems across the rapidly warming Arctic–boreal zone (ABZ) have provided valuable information but were limited in their geographical and temporal coverage. Furthermore, these efforts have been based on data aggregated over varying time periods, often with only minimal site ancillary data, thus limiting their potential to be used in large-scale carbon budget assessments. To bridge these gaps, we developed a standardized monthly database of Arctic–boreal CO2 fluxes (ABCflux) that aggregates in situ measurements of terrestrial net ecosystem CO2 exchange and its derived partitioned component fluxes: gross primary productivity and ecosystem respiration. The data span from 1989 to 2020 with over 70 supporting variables that describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. Here, we describe these variables, the spatial and temporal distribution of observations, the main strengths and limitations of the database, and the potential research opportunities it enables. In total, ABCflux includes 244 sites and 6309 monthly observations; 136 sites and 2217 monthly observations represent tundra, and 108 sites and 4092 observations represent the boreal biome. The database includes fluxes estimated with chamber (19 % of the monthly observations), snow diffusion (3 %) and eddy covariance (78 %) techniques. The largest number of observations were collected during the climatological summer (June–August; 32 %), and fewer observations were available for autumn (September–October; 25 %), winter (December–February; 18 %), and spring (March–May; 25 %). ABCflux can be used in a wide array of empirical, remote sensing and modeling studies to improve understanding of the regional and temporal variability in CO2 fluxes and to better estimate the terrestrial ABZ CO2 budget. ABCflux is openly and freely available online (Virkkala et al., 2021b, https://doi.org/10.3334/ORNLDAAC/1934).
Published: 2022
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4. What causes the recent jökulhlaup drainage perturbations in Zackenberg, NE-Greenland?

Author: Binder, D., Langley, K., Abermann, J., Larsen Hillerup, S., Citterio, M., Kjeldsen Kjellerup, K., Mastepanov, M., Rudd, D., Skov, K., Eibl, E., and Tamstorf, M.
Abstract: Since 2005 quasi-annual jökulhlaups, or glacial lake outburst floods, are registered at the Zackenberg research station (74°28′N, 20°34′W), NE-Greenland. The jökulhlaups typically happen during the sommer months, but were also observed during winter and spring. The Zackenberg jökulhlaups exhibit rapid-rising outburst type characteristics with durations of 12-24 hours, and maximum discharges of 120 to 380 m³/s. The source is a lake dammed by an outlet glacier of the A.P. Olsen ice cap about 35 km inland of the research station. The recorded maximum ice-dammed lake volumes are varying in between 5.7 to 15.6 x10⁶ m³.The year 2018 showed no drainage event and the lake remained filled until the 2019 melting season, accumulating the largest lake volume so far. The 2019 lake outburst happened with beginning of July rather early, but just drained slowly for more than a week to then switch to a rapid-type outburst emptying the lake in about half a day. The subsequent 2020 and 2021 floods continued to show characteristics of slower and mixed-type drainage events. The overall evolution of the 2019-2021 lake drainage patterns suggest a transition back to rapid-type jökulhlaup events. To our knowledge, the observed mixed-type drainage patterns within a single jökulhlaup event has been never reported before, and is challenging the current understanding of subglacial floods. We present all the available hydrometric data for the Zackenberg river and the ice-dammed lake to discuss potential causes for the observed jökulhlaup perturbations., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)
Published: 2023
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5. Winters are changing: snow effects on Arctic and alpine tundra ecosystems

Author: Rixen, C, Hoye, TT, Macek, P, Aerts, R, Alatalo, JM, Anderson, JT, Arnold, PA, Barrio, IC, Bjerke, JW, Bjorkman, MP, Blok, D, Blume-Werry, G, Boike, J, Bokhorst, S, Carbognani, M, Christiansen, CT, Convey, P, Cooper, EJ, Cornelissen, JHC, Coulson, SJ, Dorrepaal, E, Elberling, B, Elmendorf, SC, Elphinstone, C, Forte, TGW, Frei, ER, Geange, SR, Gerhrmann, F, Gibson, C, Grogan, P, Halbritter, AH, Harte, J, Henry, GHR, Inouye, DW, Irwin, RE, Jespersen, G, Jonsdottir, IS, Jung, JY, Klinges, DH, Kudo, G, Lamsa, J, Lee, H, Lembrechts, JJ, Lett, S, Lynn, JS, Mann, HMR, Mastepanov, M, Morse, J, Myers-Smith, IH, Olofsson, J, Paavola, R, Petraglia, A, Phoenix, GK, Semenchuk, P, Siewert, MB, Slatyer, R, Spasojevic, MJ, Suding, K, Sullivan, P, Thompson, KL, Vaisanen, M, Vandvik, V, Venn, Susanna, Walz, J, Way, R, Welker, JM, Wipf, S, Zong, S, Rixen, C, Hoye, TT, Macek, P, Aerts, R, Alatalo, JM, Anderson, JT, Arnold, PA, Barrio, IC, Bjerke, JW, Bjorkman, MP, Blok, D, Blume-Werry, G, Boike, J, Bokhorst, S, Carbognani, M, Christiansen, CT, Convey, P, Cooper, EJ, Cornelissen, JHC, Coulson, SJ, Dorrepaal, E, Elberling, B, Elmendorf, SC, Elphinstone, C, Forte, TGW, Frei, ER, Geange, SR, Gerhrmann, F, Gibson, C, Grogan, P, Halbritter, AH, Harte, J, Henry, GHR, Inouye, DW, Irwin, RE, Jespersen, G, Jonsdottir, IS, Jung, JY, Klinges, DH, Kudo, G, Lamsa, J, Lee, H, Lembrechts, JJ, Lett, S, Lynn, JS, Mann, HMR, Mastepanov, M, Morse, J, Myers-Smith, IH, Olofsson, J, Paavola, R, Petraglia, A, Phoenix, GK, Semenchuk, P, Siewert, MB, Slatyer, R, Spasojevic, MJ, Suding, K, Sullivan, P, Thompson, KL, Vaisanen, M, Vandvik, V, Venn, Susanna, Walz, J, Way, R, Welker, JM, Wipf, S, and Zong, S
Abstract: Snow is an important driver of ecosystem processes in cold biomes. Snow accumulation determines ground temperature, light conditions, and moisture availability during winter. It also affects the growing season’s start and end, and plant access to moisture and nutrients. Here, we review the current knowledge of the snow cover’s role for vegetation, plant-animal interactions, permafrost conditions, microbial processes, and biogeochemical cycling. We also compare studies of natural snow gradients with snow experimental manipulation studies to assess time scale difference of these approaches. The number of tundra snow studies has increased considerably in recent years, yet we still lack a comprehensive overview of how altered snow conditions will affect these ecosystems. Specifically, we found a mismatch in the timing of snowmelt when comparing studies of natural snow gradients with snow manipulations. We found that snowmelt timing achieved by snow addition and snow removal manipulations (average 7.9 days advance and 5.5 days delay, respectively) were substantially lower than the temporal variation over natural spatial gradients within a given year (mean range 56 days) or among years (mean range 32 days). Differences between snow study approaches need to be accounted for when projecting snow dynamics and their impact on ecosystems in future climates.
Published: 2022

6. A mobile observatory powered by sun and wind for near real time measurements of atmospheric, glacial, terrestrial, limnic and coastal oceanic conditions in remote off-grid areas

Author: Rysgaard, S. (Søren), Bjerge, K. (Kim), Boone, W. (Wieter), Frandsen, E. (Egon), Graversen, M. (Michael), Høye, T. T. (Toke Thomas), Jensen, B. (Bjarne), Johnen, G. (Geoffrey), Jackowicz-Korczynski, M. A. (Marcin Antoni), Kerby, J. T. (Jeffrey Taylor), Kortegaard, S. (Simon), Mastepanov, M. (Mikhail), Melvad, C. (Claus), Mikkelsen, P. S. (Peter Schmidt), Mortensen, K. (Keld), Nørgaard, C. (Carsten), Poulsen, E. (Ebbe), Riis, T. (Tenna), Sørensen, L. (Lotte), Christensen, T. R. (Torben Røjle), Rysgaard, S. (Søren), Bjerge, K. (Kim), Boone, W. (Wieter), Frandsen, E. (Egon), Graversen, M. (Michael), Høye, T. T. (Toke Thomas), Jensen, B. (Bjarne), Johnen, G. (Geoffrey), Jackowicz-Korczynski, M. A. (Marcin Antoni), Kerby, J. T. (Jeffrey Taylor), Kortegaard, S. (Simon), Mastepanov, M. (Mikhail), Melvad, C. (Claus), Mikkelsen, P. S. (Peter Schmidt), Mortensen, K. (Keld), Nørgaard, C. (Carsten), Poulsen, E. (Ebbe), Riis, T. (Tenna), Sørensen, L. (Lotte), and Christensen, T. R. (Torben Røjle)
Abstract: Climate change is rapidly altering the Arctic environment. Although long-term environmental observations have been made at a few locations in the Arctic, the incomplete coverage from ground stations is a main limitation to observations in these remote areas. Here we present a wind and sun powered multi-purpose mobile observatory (ARC-MO) that enables near real time measurements of air, ice, land, rivers, and marine parameters in remote off-grid areas. Two test units were constructed and placed in Northeast Greenland where they have collected data from cabled and wireless instruments deployed in the environment since late summer 2021. The two units can communicate locally via WiFi (units placed 25 km apart) and transmit near-real time data globally over satellite. Data are streamed live and accessible from (https://gios.org). The cost of one mobile observatory unit is c. 304.000€. These test units demonstrate the possibility for integrative and automated environmental data collection in remote coastal areas and could serve as models for a proposed global observatory system.
Published: 2022

7. Winters are changing:snow effects on Arctic and alpine tundra ecosystems

Author: Rixen, C. (Christian), Høye, T. T. (Toke Thomas), Macek, P. (Petr), Aerts, R. (Rien), Alatalo, J. M. (Juha M.), Anderson, J. T. (Jill T.), Arnold, P. A. (Pieter A.), Barrio, I. C. (Isabel C), Bjerke, J. W. (Jarle W.), Björkman, M. P. (Mats P.), Blok, D. (Daan), Blume-Werry, G. (Gesche), Boike, J. (Julia), Bokhorst, S. (Stef), Carbognani, M. (Michele), Christiansen, C. T. (Casper T.), Convey, P. (Peter), Cooper, E. J. (Elisabeth J.), Cornelissen, J. H. (J. Hans C.), Coulson, S. J. (Stephen J.), Dorrepaal, E. (Ellen), Elberling, B. (Bo), Elmendorf, S. C. (Sarah C.), Elphinstone, C. (Cassandra), Forte, T. G. (T’ai G.W.), Frei, E. R. (Esther R.), Geange, S. R. (Sonya R.), Gehrmann, F. (Friederike), Gibson, C. (Casey), Grogan, P. (Paul), Halbritter, A. H. (Aud Helen), Harte, J. (John), Henry, G. H. (Gregory H.R.), Inouye, D. W. (David W.), Irwin, R. E. (Rebecca E.), Jespersen, G. (Gus), Jónsdóttir, I. S. (Ingibjörg Svala), Jung, J. Y. (Ji Young), Klinges, D. H. (David H.), Kudo, G. (Gaku), Lämsä, J. (Juho), Lee, H. (Hanna), Lembrechts, J. J. (Jonas J.), Lett, S. (Signe), Lynn, J. S. (Joshua Scott), Mann, H. M. (Hjalte M.R.), Mastepanov, M. (Mikhail), Morse, J. (Jennifer), Myers-Smith, I. H. (Isla H.), Olofsson, J. (Johan), Paavola, R. (Riku), Petraglia, A. (Alessandro), Phoenix, G. K. (Gareth K.), Semenchuk, P. (Philipp), Siewert, M. B. (Matthias B.), Slatyer, R. (Rachel), Spasojevic, M. J. (Marko J.), Suding, K. (Katharine), Sullivan, P. (Patrick), Thompson, K. L. (Kimberly L.), Väisänen, M. (Maria), Vandvik, V. (Vigdis), Venn, S. (Susanna), Walz, J. (Josefine), Way, R. (Robert), Welker, J. M. (Jeffrey M.), Wipf, S. (Sonja), Zong, S. (Shengwei), Rixen, C. (Christian), Høye, T. T. (Toke Thomas), Macek, P. (Petr), Aerts, R. (Rien), Alatalo, J. M. (Juha M.), Anderson, J. T. (Jill T.), Arnold, P. A. (Pieter A.), Barrio, I. C. (Isabel C), Bjerke, J. W. (Jarle W.), Björkman, M. P. (Mats P.), Blok, D. (Daan), Blume-Werry, G. (Gesche), Boike, J. (Julia), Bokhorst, S. (Stef), Carbognani, M. (Michele), Christiansen, C. T. (Casper T.), Convey, P. (Peter), Cooper, E. J. (Elisabeth J.), Cornelissen, J. H. (J. Hans C.), Coulson, S. J. (Stephen J.), Dorrepaal, E. (Ellen), Elberling, B. (Bo), Elmendorf, S. C. (Sarah C.), Elphinstone, C. (Cassandra), Forte, T. G. (T’ai G.W.), Frei, E. R. (Esther R.), Geange, S. R. (Sonya R.), Gehrmann, F. (Friederike), Gibson, C. (Casey), Grogan, P. (Paul), Halbritter, A. H. (Aud Helen), Harte, J. (John), Henry, G. H. (Gregory H.R.), Inouye, D. W. (David W.), Irwin, R. E. (Rebecca E.), Jespersen, G. (Gus), Jónsdóttir, I. S. (Ingibjörg Svala), Jung, J. Y. (Ji Young), Klinges, D. H. (David H.), Kudo, G. (Gaku), Lämsä, J. (Juho), Lee, H. (Hanna), Lembrechts, J. J. (Jonas J.), Lett, S. (Signe), Lynn, J. S. (Joshua Scott), Mann, H. M. (Hjalte M.R.), Mastepanov, M. (Mikhail), Morse, J. (Jennifer), Myers-Smith, I. H. (Isla H.), Olofsson, J. (Johan), Paavola, R. (Riku), Petraglia, A. (Alessandro), Phoenix, G. K. (Gareth K.), Semenchuk, P. (Philipp), Siewert, M. B. (Matthias B.), Slatyer, R. (Rachel), Spasojevic, M. J. (Marko J.), Suding, K. (Katharine), Sullivan, P. (Patrick), Thompson, K. L. (Kimberly L.), Väisänen, M. (Maria), Vandvik, V. (Vigdis), Venn, S. (Susanna), Walz, J. (Josefine), Way, R. (Robert), Welker, J. M. (Jeffrey M.), Wipf, S. (Sonja), and Zong, S. (Shengwei)
Abstract: Snow is an important driver of ecosystem processes in cold biomes. Snow accumulation determines ground temperature, light conditions, and moisture availability during winter. It also affects the growing season’s start and end, and plant access to moisture and nutrients. Here, we review the current knowledge of the snow cover’s role for vegetation, plant-animal interactions, permafrost conditions, microbial processes, and biogeochemical cycling. We also compare studies of natural snow gradients with snow experimental manipulation studies to assess time scale difference of these approaches. The number of tundra snow studies has increased considerably in recent years, yet we still lack a comprehensive overview of how altered snow conditions will affect these ecosystems. Specifically, we found a mismatch in the timing of snowmelt when comparing studies of natural snow gradients with snow manipulations. We found that snowmelt timing achieved by snow addition and snow removal manipulations (average 7.9 days advance and 5.5 days delay, respectively) were substantially lower than the temporal variation over natural spatial gradients within a given year (mean range 56 days) or among years (mean range 32 days). Differences between snow study approaches need to be accounted for when projecting snow dynamics and their impact on ecosystems in future climates.
Published: 2022

8. Earlier snowmelt may lead to late season declines in plant productivity and carbon sequestration in Arctic tundra ecosystems

Author: Zona, D. (Donatella), Lafleur, P. M. (Peter M.), Hufkens, K. (Koen), Bailey, B. (Barbara), Gioli, B. (Beniamino), Burba, G. (George), Goodrich, J. P. (Jordan P.), Liljedahl, A. K. (Anna K.), Euskirchen, E. S. (Eugénie S.), Watts, J. D. (Jennifer D.), Farina, M. (Mary), Kimball, J. S. (John S.), Heimann, M. (Martin), Göckede, M. (Mathias), Pallandt, M. (Martijn), Christensen, T. R. (Torben R.), Mastepanov, M. (Mikhail), López-Blanco, E. (Efrén), Jackowicz-Korczynski, M. (Marcin), Dolman, A. J. (Albertus J.), Belelli Marchesini, L. (Luca), Commane, R. (Roisin), Wofsy, S. C. (Steven C.), Miller, C. E. (Charles E.), Lipson, D. A. (David A.), Hashemi, J. (Josh), Arndt, K. A. (Kyle A.), Kutzbach, L. (Lars), Holl, D. (David), Boike, J. (Julia), Wille, C. (Christian), Sachs, T. (Torsten), Kalhori, A. (Aram), Song, X. (Xia), Xu, X. (Xiaofeng), Humphreys, E. R. (Elyn R.), Koven, C. D. (Charles D.), Sonnentag, O. (Oliver), Meyer, G. (Gesa), Gosselin, G. H. (Gabriel H.), Marsh, P. (Philip), Oechel, W. C. (Walter C.), Zona, D. (Donatella), Lafleur, P. M. (Peter M.), Hufkens, K. (Koen), Bailey, B. (Barbara), Gioli, B. (Beniamino), Burba, G. (George), Goodrich, J. P. (Jordan P.), Liljedahl, A. K. (Anna K.), Euskirchen, E. S. (Eugénie S.), Watts, J. D. (Jennifer D.), Farina, M. (Mary), Kimball, J. S. (John S.), Heimann, M. (Martin), Göckede, M. (Mathias), Pallandt, M. (Martijn), Christensen, T. R. (Torben R.), Mastepanov, M. (Mikhail), López-Blanco, E. (Efrén), Jackowicz-Korczynski, M. (Marcin), Dolman, A. J. (Albertus J.), Belelli Marchesini, L. (Luca), Commane, R. (Roisin), Wofsy, S. C. (Steven C.), Miller, C. E. (Charles E.), Lipson, D. A. (David A.), Hashemi, J. (Josh), Arndt, K. A. (Kyle A.), Kutzbach, L. (Lars), Holl, D. (David), Boike, J. (Julia), Wille, C. (Christian), Sachs, T. (Torsten), Kalhori, A. (Aram), Song, X. (Xia), Xu, X. (Xiaofeng), Humphreys, E. R. (Elyn R.), Koven, C. D. (Charles D.), Sonnentag, O. (Oliver), Meyer, G. (Gesa), Gosselin, G. H. (Gabriel H.), Marsh, P. (Philip), and Oechel, W. C. (Walter C.)
Abstract: Arctic warming is affecting snow cover and soil hydrology, with consequences for carbon sequestration in tundra ecosystems. The scarcity of observations in the Arctic has limited our understanding of the impact of covarying environmental drivers on the carbon balance of tundra ecosystems. In this study, we address some of these uncertainties through a novel record of 119 site-years of summer data from eddy covariance towers representing dominant tundra vegetation types located on continuous permafrost in the Arctic. Here we found that earlier snowmelt was associated with more tundra net CO₂ sequestration and higher gross primary productivity (GPP) only in June and July, but with lower net carbon sequestration and lower GPP in August. Although higher evapotranspiration (ET) can result in soil drying with the progression of the summer, we did not find significantly lower soil moisture with earlier snowmelt, nor evidence that water stress affected GPP in the late growing season. Our results suggest that the expected increased CO₂ sequestration arising from Arctic warming and the associated increase in growing season length may not materialize if tundra ecosystems are not able to continue sequestering CO₂ later in the season.
Published: 2022

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

Author: Virkkala, A.-M. (Anna-Maria), Natali, S. M. (Susan M.), Rogers, B. M. (Brendan M.), Watts, J. D. (Jennifer D.), Savage, K. (Kathleen), Connon, S. J. (Sara June), Mauritz, M. (Marguerite), Schuur, E. A. (Edward A. G.), Peter, D. (Darcy), Minions, C. (Christina), Nojeim, J. (Julia), Commane, R. (Roisin), Emmerton, C. A. (Craig A.), Goeckede, M. (Mathias), Helbig, M. (Manuel), Holl, D. (David), Iwata, H. (Hiroki), Kobayashi, H. (Hideki), Kolari, P. (Pasi), López-Blanco, E. (Efrén), Marushchak, M. E. (Maija E.), Mastepanov, M. (Mikhail), Merbold, L. (Lutz), Parmentier, F. W. (Frans-Jan W.), Peichl, M. (Matthias), Sachs, T. (Torsten), Sonnentag, O. (Oliver), Ueyama, M. (Masahito), Voigt, C. (Carolina), Aurela, M. (Mika), Boike, J. (Julia), Celis, G. (Gerardo), Chae, N. (Namyi), Christensen, T. R. (Torben R.), Bret-Harte, M. S. (M. Syndonia), Dengel, S. (Sigrid), Dolman, H. (Han), Edgar, C. W. (Colin W.), Elberling, B. (Bo), Euskirchen, E. (Eugenie), Grelle, A. (Achim), Hatakka, J. (Juha), Humphreys, E. (Elyn), Järveoja, J. (Järvi), Kotani, A. (Ayumi), Kutzbach, L. (Lars), Laurila, T. (Tuomas), Lohila, A. (Annalea), Mammarella, I. (Ivan), Matsuura, Y. (Yojiro), Meyer, G. (Gesa), Nilsson, M. B. (Mats B.), Oberbauer, S. F. (Steven F.), Park, S.-J. (Sang-Jong), Petrov, R. (Roman), Prokushkin, A. S. (Anatoly S.), Schulze, C. (Christopher), St. Louis, V. L. (Vincent L.), Tuittila, E.-S. (Eeva-Stiina), Tuovinen, J.-P. (Juha-Pekka), Quinton, W. (William), Varlagin, A. (Andrej), Zona, D. (Donatella), Zyryanov, V. I. (Viacheslav I.), Virkkala, A.-M. (Anna-Maria), Natali, S. M. (Susan M.), Rogers, B. M. (Brendan M.), Watts, J. D. (Jennifer D.), Savage, K. (Kathleen), Connon, S. J. (Sara June), Mauritz, M. (Marguerite), Schuur, E. A. (Edward A. G.), Peter, D. (Darcy), Minions, C. (Christina), Nojeim, J. (Julia), Commane, R. (Roisin), Emmerton, C. A. (Craig A.), Goeckede, M. (Mathias), Helbig, M. (Manuel), Holl, D. (David), Iwata, H. (Hiroki), Kobayashi, H. (Hideki), Kolari, P. (Pasi), López-Blanco, E. (Efrén), Marushchak, M. E. (Maija E.), Mastepanov, M. (Mikhail), Merbold, L. (Lutz), Parmentier, F. W. (Frans-Jan W.), Peichl, M. (Matthias), Sachs, T. (Torsten), Sonnentag, O. (Oliver), Ueyama, M. (Masahito), Voigt, C. (Carolina), Aurela, M. (Mika), Boike, J. (Julia), Celis, G. (Gerardo), Chae, N. (Namyi), Christensen, T. R. (Torben R.), Bret-Harte, M. S. (M. Syndonia), Dengel, S. (Sigrid), Dolman, H. (Han), Edgar, C. W. (Colin W.), Elberling, B. (Bo), Euskirchen, E. (Eugenie), Grelle, A. (Achim), Hatakka, J. (Juha), Humphreys, E. (Elyn), Järveoja, J. (Järvi), Kotani, A. (Ayumi), Kutzbach, L. (Lars), Laurila, T. (Tuomas), Lohila, A. (Annalea), Mammarella, I. (Ivan), Matsuura, Y. (Yojiro), Meyer, G. (Gesa), Nilsson, M. B. (Mats B.), Oberbauer, S. F. (Steven F.), Park, S.-J. (Sang-Jong), Petrov, R. (Roman), Prokushkin, A. S. (Anatoly S.), Schulze, C. (Christopher), St. Louis, V. L. (Vincent L.), Tuittila, E.-S. (Eeva-Stiina), Tuovinen, J.-P. (Juha-Pekka), Quinton, W. (William), Varlagin, A. (Andrej), Zona, D. (Donatella), and Zyryanov, V. I. (Viacheslav I.)
Abstract: Past efforts to synthesize and quantify the magnitude and change in carbon dioxide (CO₂) fluxes in terrestrial ecosystems across the rapidly warming Arctic–boreal zone (ABZ) have provided valuable information but were limited in their geographical and temporal coverage. Furthermore, these efforts have been based on data aggregated over varying time periods, often with only minimal site ancillary data, thus limiting their potential to be used in large-scale carbon budget assessments. To bridge these gaps, we developed a standardized monthly database of Arctic–boreal CO₂ fluxes (ABCflux) that aggregates in situ measurements of terrestrial net ecosystem CO₂ exchange and its derived partitioned component fluxes: gross primary productivity and ecosystem respiration. The data span from 1989 to 2020 with over 70 supporting variables that describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. Here, we describe these variables, the spatial and temporal distribution of observations, the main strengths and limitations of the database, and the potential research opportunities it enables. In total, ABCflux includes 244 sites and 6309 monthly observations; 136 sites and 2217 monthly observations represent tundra, and 108 sites and 4092 observations represent the boreal biome. The database includes fluxes estimated with chamber (19 % of the monthly observations), snow diffusion (3 %) and eddy covariance (78 %) techniques. The largest number of observations were collected during the climatological summer (June–August; 32 %), and fewer observations were available for autumn (September–October; 25 %), winter (December–February; 18 %), and spring (March–May; 25 %). ABCflux can be used in a wide array of empirical, remote sensing and modeling studies to improve understanding of the regional and temporal variability in CO₂ fluxes and to better es
Published: 2022

10. Toward UAV-based methane emission mapping of Arctic terrestrial ecosystems

Author: Scheller, J. H. (Johan H.), Mastepanov, M. (Mikhail), Christensen, T. R. (Torben R.), Scheller, J. H. (Johan H.), Mastepanov, M. (Mikhail), and Christensen, T. R. (Torben R.)
Abstract: Methane is an important greenhouse gas, and emissions are expected to rise in Arctic wetland ecosystems when temperatures increase due to climate change. However, current emission estimates are associated with large uncertainties because methane shows high spatial variability. A central problem is that existing methods are often spatially restricted due to limitations in access, cost, power availability, and in need of high maintenance levels. Our study explores how a setup consisting of an unmanned aerial vehicle and a high-precision trace gas analyzer can complement well-established methods, like mobile flux chambers and eddy covariance towers, by providing independent maps of spatial variability in emissions at the landscape scale. In Zackenberg Valley, Northeast Greenland, we mapped concentration measurements from a high-precision trace gas analyzer with a reported precision of 0.6 parts per billion in a high-Arctic tundra fen ecosystem. We connected the analyzer via a long tube to a consumer-grade quadcopter, finding that the combined setup could differentiate near-surface methane concentrations of less than 5 parts per billion within a few meters under favorable weather conditions. Five of ten campaigns showed that relative methane concentration hot spots and cold spots significantly correlated with areas showing relatively high and low emissions (ranging from 1.40 to 7.4 mg m⁻² h⁻¹) during study campaigns in previous years. Concurrent measurements in a stationary automated chamber setup showed comparatively low methane emissions (~0.1 to 3.9 mg m⁻² h⁻¹) compared to previous years, indicating that a further improved UAV-analyzer setup could demonstrate clear differences in an ecosystem where methane emissions are generally higher. Calm conditions with some degree of air mixing near the surface were best suited for the mapping. Windy and wet conditions should be avoided, both for the reliability of the mapping and for safely navigating the unmanned aer
Published: 2022

11. Harmonized in-situ observations of surface energy fluxes and environmental drivers at 64 Arctic vegetation and glacier sites

Author: Oehri, J., Schaepman-Strub, G., Kim, J., Grysko, R., Kropp, H., Grünberg, I., Zemlianskii, V., Sonnentag, O., Euskirchen, E., Reji Chacko, M., Muscari, G., Blanken, P., Dean, J., di Sarra, A., Harding, R., Sobota, I., Kutzbach, L., Plekhanova, E., Riihelä, A., Boike, J., Miller, N., Beringer, J., López-Blanco, E., Stoy, P., Sullivan, R., Kejna, M., Parmentier, F., Gamon, J., Mastepanov, M., Wille, C., Jackowicz-Korczynski, M., Karger, D., Quinton, W., Putkonen, J., van As, D., Christensen, T., Hakuba, M., Stone, R., Metzger, S., Vandecrux, B., Frost, G., Wild, M., Hansen, B., Meloni, D., Domine, F., te Beest, M., Sachs, T., Kalhori, A., Rocha, A., Williamson, S., Morris, S., Atchley, A., Essery, R., Runkle, B., Holl, D., Riihimaki, L., Iwata, H., Schuur, E., Cox, C., Grachev, A., McFadden, J., Fausto, R., Göckede, M., Ueyama, M., Pirk, N., de Boer, G., Bret-Harte, M., Leppäranta, M., Steffen, K., Friborg, T., Ohmura, A., Edgar, C., Olofsson, J., and Chambers, S.
Abstract: Despite the importance of surface energy budgets (SEBs) for land-climate interactions in the Arctic, uncertainties in their prediction persist. In-situ observational data of SEB components - useful for research and model validation - are collected at relatively few sites across the terrestrial Arctic, and not all available datasets are readily interoperable. Furthermore, the terrestrial Arctic consists of a diversity of vegetation types, which are generally not well represented in land surface schemes of current Earth system models. Therefore, we here provide four datasets comprising: 1. Harmonized, standardized and aggregated in situ observations of SEB components at 64 vegetated and glaciated sites north of 60° latitude, in the time period 1994-2021 2. A description of all study sites and associated environmental conditions, including the vegetation types, which correspond to the classification of the Circumpolar Arctic Vegetation Map (CAVM, Raynolds et al. 2019). 3. Data generated in a literature synthesis from 358 study sites on vegetation or glacier (>=60°N latitude) covered by 148 publications. 4. Metadata, including data contributor information and measurement heights of variables associated with Oehri et al. 2022.
Published: 2022

12. Harmonized in-situ observations of surface energy fluxes and environmental drivers at 64 Arctic vegetation and glacier sites - Environmental conditions

Author: Oehri, J., Schaepman-Strub, G., Kim, J., Grysko, R., Kropp, H., Grünberg, I., Zemlianskii, V., Sonnentag, O., Euskirchen, E., Reji Chacko, M., Muscari, G., Blanken, P., Dean, J., di Sarra, A., Harding, R., Sobota, I., Kutzbach, L., Plekhanova, E., Riihelä, A., Boike, J., Miller, N., Beringer, J., López-Blanco, E., Stoy, P., Sullivan, R., Kejna, M., Parmentier, F., Gamon, J., Mastepanov, M., Wille, C., Jackowicz-Korczynski, M., Karger, D., Quinton, W., Putkonen, J., van As, D., Christensen, T., Hakuba, M., Stone, R., Metzger, S., Vandecrux, B., Frost, G., Wild, M., Hansen, B., Meloni, D., Domine, F., te Beest, M., Sachs, T., Kalhori, A., Rocha, A., Williamson, S., Morris, S., Atchley, A., Essery, R., Runkle, B., Holl, D., Riihimaki, L., Iwata, H., Schuur, E., Cox, C., Grachev, A., McFadden, J., Fausto, R., Göckede, M., Ueyama, M., Pirk, N., de Boer, G., Bret-Harte, M., Leppäranta, M., Steffen, K., Friborg, T., Ohmura, A., Edgar, C., Olofsson, J., and Chambers, S.
Abstract: Despite the importance of surface energy budgets (SEBs) for land-climate interactions in the Arctic, uncertainties in their prediction persist. In situ observational data of SEB components - useful for research and model validation - are collected at relatively few sites across the terrestrial Arctic, and not all available datasets are readily interoperable. Furthermore, the terrestrial Arctic consists of a diversity of vegetation types, which are generally not well represented in land surface schemes of current Earth system models. This dataset describes the environmental conditions for 64 tundra and glacier sites (>=60°N latitude) across the Arctic, for which in situ measurements of surface energy budget components were harmonized (see Oehri et al. 2022). These environmental conditions are (proxies of) potential drivers of SEB-components and could therefore be called SEB-drivers. The associated environmental conditions, include the vegetation types graminoid tundra, prostrate dwarf-shrub tundra, erect-shrub tundra, wetland complexes, barren complexes (≤ 40% horizontal plant cover), boreal peat bogs and glacier. These land surface types (apart from boreal peat bogs) correspond to the main classification units of the Circumpolar Arctic Vegetation Map (CAVM, Raynolds et al. 2019). For each site, additional climatic and biophysical variables are available, including cloud cover, snow cover duration, permafrost characteristics, climatic conditions and topographic conditions.
Published: 2022

13. Harmonized in-situ observations of surface energy fluxes and environmental drivers at 64 Arctic vegetation and glacier sites - Surface energy budget componenent data

Author: Oehri, J., Schaepman-Strub, G., Kim, J., Grysko, R., Kropp, H., Grünberg, I., Zemlianskii, V., Sonnentag, O., Euskirchen, E., Reji Chacko, M., Muscari, G., Blanken, P., Dean, J., di Sarra, A., Harding, R., Sobota, I., Kutzbach, L., Plekhanova, E., Riihelä, A., Boike, J., Miller, N., Beringer, J., López-Blanco, E., Stoy, P., Sullivan, R., Kejna, M., Parmentier, F., Gamon, J., Mastepanov, M., Wille, C., Jackowicz-Korczynski, M., Karger, D., Quinton, W., Putkonen, J., van As, D., Christensen, T., Hakuba, M., Stone, R., Metzger, S., Vandecrux, B., Frost, G., Wild, M., Hansen, B., Meloni, D., Domine, F., te Beest, M., Sachs, T., Kalhori, A., Rocha, A., Williamson, S., Morris, S., Atchley, A., Essery, R., Runkle, B., Holl, D., Riihimaki, L., Iwata, H., Schuur, E., Cox, C., Grachev, A., McFadden, J., Fausto, R., Göckede, M., Ueyama, M., Pirk, N., de Boer, G., Bret-Harte, M., Leppäranta, M., Steffen, K., Friborg, T., Ohmura, A., Edgar, C., Olofsson, J., and Chambers, S.
Abstract: Despite the importance of surface energy budgets (SEBs) for land-climate interactions in the Arctic, uncertainties in their prediction persist. In situ observational data of SEB components - useful for research and model validation - are collected at relatively few sites across the terrestrial Arctic, and not all available datasets are readily interoperable. Furthermore, the terrestrial Arctic consists of a diversity of vegetation types, which are generally not well represented in land surface schemes of current Earth system models. This dataset comprises harmonized, standardized and aggregated in-situ observations of surface energy budget components measured at 64 sites on vegetated and glaciated sites north of 60° latitude, in the time period from 1994 till 2021. The surface energy budget components include net radiation, sensible heat flux, latent heat flux, ground heat flux, net shortwave radiation, net longwave radiation, surface temperature and albedo, which were aggregated to daily mean, minimum and maximum values from hourly and half-hourly measurements. Data were retrieved from the monitoring networks FLUXNET, AmeriFlux, AON, GC-Net and PROMICE.
Published: 2022

14. Literature synthesis data of surface energy fluxes and environmental drivers from Arctic vegetation and glacier sites

Author: Oehri, J., Schaepman-Strub, G., Kim, J., Grysko, R., Kropp, H., Grünberg, I., Zemlianskii, V., Sonnentag, O., Euskirchen, E., Reji Chacko, M., Muscari, G., Blanken, P., Dean, J., di Sarra, A., Harding, R., Sobota, I., Kutzbach, L., Plekhanova, E., Riihelä, A., Boike, J., Miller, N., Beringer, J., López-Blanco, E., Stoy, P., Sullivan, R., Kejna, M., Parmentier, F., Gamon, J., Mastepanov, M., Wille, C., Jackowicz-Korczynski, M., Karger, D., Quinton, W., Putkonen, J., van As, D., Christensen, T., Hakuba, M., Stone, R., Metzger, S., Vandecrux, B., Frost, G., Wild, M., Hansen, B., Meloni, D., Domine, F., te Beest, M., Sachs, T., Kalhori, A., Rocha, A., Williamson, S., Morris, S., Atchley, A., Essery, R., Runkle, B., Holl, D., Riihimaki, L., Iwata, H., Schuur, E., Cox, C., Grachev, A., McFadden, J., Fausto, R., Göckede, M., Ueyama, M., Pirk, N., de Boer, G., Bret-Harte, M., Leppäranta, M., Steffen, K., Friborg, T., Ohmura, A., Edgar, C., Olofsson, J., and Chambers, S.
Abstract: Despite the importance of surface energy budgets (SEBs) for land-climate interactions in the Arctic, uncertainties in their prediction persist. In situ observational data of SEB components - useful for research and model validation - are collected at relatively few sites across the terrestrial Arctic, and not all available datasets are readily interoperable. Furthermore, the terrestrial Arctic consists of a diversity of vegetation types, which are generally not well represented in land surface schemes of current Earth system models. This dataset describes the data generated in a literature synthesis, covering 358 study sites on vegetation or glacier (>=60°N latitude), which contained surface energy budget observations. The literature synthesis comprised 148 publications searched on the ISI Web of Science Core Collection.
Published: 2022

15. A Catchment-Scale Carbon and Greenhouse Gas Budget of a Subarctic Landscape

Author: Christensen, T. R., Johansson, T., Olsrud, M., Ström, L., Lindroth, A., Mastepanov, M., Malmer, N., Friborg, T., Crill, P., and Callaghan, T. V.
Published: 2007
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16. The ABCflux Database: Arctic-Boreal CO2 Flux and Site Environmental Data, 1989-2020

Author: Virkkala, A., Natali, S., Rogers, B., Watts, J., Savage, K., Connon, S., Mauritz-tozer, M., Schuur, E., Peter, D., Minions, C., Nojeim, J., Commane, R., Emmerton, C., Goeckede, M., Helbig, M., Holl, D., Iwata, H., Kobayashi, H., Kolari, P., Lopez-blanco, E., Marushchak, M., Mastepanov, M., Merbold, L., Peichl, M., Sonnentag, O., Sachs, T., Ueyama, M., Voigt, C., Aurela, M., Boike, J., Celis, G., Chae, N., Christensen, T., Bret-Harte, S., Dengel, S., Dolman, H., Edgar, C., Elberling, B., Euskirchen, S., Grelle, A., Hatakka, J., Humphreys, E., Jaerveoja, J., Kotani, A., Kutzbach, L., Laurila, T., Lohila, A., Mammarella, I., Matsuura, Y., Meyer, G., Nilsson, M., Oberbauer, S., Park, S., Parmentier, F., Petrov, R., Prokushkin, A., Zyrianov, S., Schulze, C., St.louis, V., Tuittila, E., Tuovinen, J., Quinton, W., Varlagin, A., Zona, D., and Zyryanov, V.
Abstract: This Arctic-Boreal CO2 fluxes (ABCflux) dataset contains monthly aggregates of terrestrial net ecosystem CO2 exchange and its derived partitioned component fluxes: gross primary productivity (GPP) and ecosystem respiration. Over 70 supporting variables describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. The data contained in this ABCflux dataset form a standardized monthly database of Arctic-Boreal CO2 fluxes (i.e., ABCflux Database) and include 244 sites and 6,309 monthly observations; 136 sites and 2,217 monthly observations represent tundra, and 108 sites and 4,092 observations represent the boreal biome. The data are for the period 1989 to 2020.
Published: 2021

17. Methane in Zackenberg Valley, NE Greenland:multidecadal growing season fluxes of a high-Arctic tundra

Author: Scheller, J. H. (Johan H.), Mastepanov, M. (Mikhail), Christiansen, H. H. (Hanne H.), and Christensen, T. R. (Torben R.)
Abstract: The carbon balance of high-latitude terrestrial ecosystems plays an essential role in the atmospheric concentration of trace gases, including carbon dioxide (CO₂) and methane (CH₄). Increasing atmospheric methane levels have contributed to ∼ 20 % of the observed global warming since the pre-industrial era. Rising temperatures in the Arctic are expected to promote the release of methane from Arctic ecosystems. Still, existing methane flux measurement efforts are sparse and highly scattered, and further attempts to assess the landscape fluxes over multiple years are needed. Here we combine multi-year July–August methane flux monitoring (2006–2019) from automated flux chambers in the central fens of Zackenberg Valley, northeast Greenland, with several flux measurement campaigns on the most common vegetation types in the valley to estimate the landscape fluxes over 14 years. Methane fluxes based on manual chamber measurements are available from campaigns in 1997, 1999–2000, and in shorter periods from 2007–2013 and were summarized in several published studies. The landscape fluxes are calculated for the entire valley floor and a smaller subsection of the valley floor, containing the productive fen area, Rylekærene. When integrated for the valley floor, the estimated July–August landscape fluxes were low compared to the single previous estimate, while the landscape fluxes for Rylekærene were comparable to previous estimates. The valley floor was a net methane source during July–August, with estimated mean methane fluxes ranging from 0.18 to 0.67 mg m⁻² h⁻¹. The mean methane fluxes in the fen-rich Rylekærene were substantially higher, with fluxes ranging from 0.98 to 3.26 mg m⁻² h⁻¹. A 2017–2018 erosion event indicates that some fen and grassland areas in the center of the valley are becoming unstable following pronounced fluvial erosion and a prolonged period of permafrost warming. Although such physical disturbance in the landscape can disrupt the current ecosystem–atmosphere flux patterns, even pronounced future erosion of ice-rich areas is unlikely to impact methane fluxes on a landscape scale significantly. Instead, projected changes in future climate in the valley play a more critical role. The results show that multi-year landscape methane fluxes are highly variable on a landscape scale and stress the need for long-term spatially distributed measurements in the Arctic.
Published: 2021

18. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data (vol 7, 225, 2020)

Author: Pastorello, G, Trotta, C, Canfora, E, Chu, H, Christianson, D, Cheah, Y-W, Poindexter, C, Chen, J, Elbashandy, A, Humphrey, M, Isaac, P, Polidori, D, Reichstein, M, Ribeca, A, van Ingen, C, Vuichard, N, Zhang, L, Amiro, B, Ammann, C, Arain, MA, Ardo, J, Arkebauer, T, Arndt, SK, Arriga, N, Aubinet, M, Aurela, M, Baldocchi, D, Barr, A, Beamesderfer, E, Marchesini, LB, Bergeron, O, Beringer, J, Bernhofer, C, Berveiller, D, Billesbach, D, Black, TA, Blanken, PD, Bohrer, G, Boike, J, Bolstad, PV, Bonal, D, Bonnefond, J-M, Bowling, DR, Bracho, R, Brodeur, J, Brummer, C, Buchmann, N, Burban, B, Burns, SP, Buysse, P, Cale, P, Cavagna, M, Cellier, P, Chen, S, Chini, I, Christensen, TR, Cleverly, J, Collalti, A, Consalvo, C, Cook, BD, Cook, D, Coursolle, C, Cremonese, E, Curtis, PS, D'Andrea, E, da Rocha, H, Dai, X, Davis, KJ, De Cinti, B, de Grandcourt, A, De Ligne, A, De Oliveira, RC, Delpierre, N, Desai, AR, Di Bella, CM, di Tommasi, P, Dolman, H, Domingo, F, Dong, G, Dore, S, Duce, P, Dufrene, E, Dunn, A, Dusek, J, Eamus, D, Eichelmann, U, ElKhidir, HAM, Eugster, W, Ewenz, CM, Ewers, B, Famulari, D, Fares, S, Feigenwinter, I, Feitz, A, Fensholt, R, Filippa, G, Fischer, M, Frank, J, Galvagno, M, Gharun, M, Gianelle, D, Gielen, B, Gioli, B, Gitelson, A, Goded, I, Goeckede, M, Goldstein, AH, Gough, CM, Goulden, ML, Graf, A, Griebel, A, Gruening, C, Grunwald, T, Hammerle, A, Han, S, Han, X, Hansen, BU, Hanson, C, Hatakka, J, He, Y, Hehn, M, Heinesch, B, Hinko-Najera, N, Hortnagl, L, Hutley, L, Ibrom, A, Ikawa, H, Jackowicz-Korczynski, M, Janous, D, Jans, W, Jassal, R, Jiang, S, Kato, T, Khomik, M, Klatt, J, Knohl, A, Knox, S, Kobayashi, H, Koerber, G, Kolle, O, Kosugi, Y, Kotani, A, Kowalski, A, Kruijt, B, Kurbatova, J, Kutsch, WL, Kwon, H, Launiainen, S, Laurila, T, Law, B, Leuning, R, Li, Y, Liddell, M, Limousin, J-M, Lion, M, Liska, AJ, Lohila, A, Lopez-Ballesteros, A, Lopez-Blanco, E, Loubet, B, Loustau, D, Lucas-Moffat, A, Luers, J, Ma, S, Macfarlane, C, Magliulo, V, Maier, R, Mammarella, I, Manca, G, Marcolla, B, Margolis, HA, Marras, S, Massman, W, Mastepanov, M, Matamala, R, Matthes, JH, Mazzenga, F, McCaughey, H, McHugh, I, McMillan, AMS, Merbold, L, Meyer, W, Meyers, T, Miller, SD, Minerbi, S, Moderow, U, Monson, RK, Montagnani, L, Moore, CE, Moors, E, Moreaux, V, Moureaux, C, Munger, JW, Nakai, T, Neirynck, J, Nesic, Z, Nicolini, G, Noormets, A, Northwood, M, Nosetto, M, Nouvellon, Y, Novick, K, Oechel, W, Olesen, JE, Ourcival, J-M, Papuga, SA, Parmentier, F-J, Paul-Limoges, E, Pavelka, M, Peichl, M, Pendall, E, Phillips, RP, Pilegaard, K, Pirk, N, Posse, G, Powell, T, Prasse, H, Prober, SM, Rambal, S, Rannik, U, Raz-Yaseef, N, Rebmann, C, Reed, D, de Dios, VR, Restrepo-Coupe, N, Reverter, BR, Roland, M, Sabbatini, S, Sachs, T, Saleska, SR, Sanchez-Canete, EP, Sanchez-Mejia, ZM, Schmid, HP, Schmidt, M, Schneider, K, Schrader, F, Schroder, I, Scott, RL, Sedlak, P, Serrano-Ortiz, P, Shao, C, Shi, P, Shironya, I, Siebicke, L, Sigut, L, Silberstein, R, Sirca, C, Spano, D, Steinbrecher, R, Stevens, RM, Sturtevant, C, Suyker, A, Tagesson, T, Takanashi, S, Tang, Y, Tapper, N, Thom, J, Tomassucci, M, Tuovinen, J-P, Urbanski, S, Valentini, R, van der Molen, M, van Gorsel, E, van Huissteden, K, Varlagin, A, Verfaillie, J, Vesala, T, Vincke, C, Vitale, D, Vygodskaya, N, Walker, JP, Walter-Shea, E, Wang, H, Weber, R, Westermann, S, Wille, C, Wofsy, S, Wohlfahrt, G, Wolf, S, Woodgate, W, Zampedri, R, Zhang, J, Zhou, G, Zona, D, Agarwal, D, Biraud, S, Torn, M, Papale, D, Pastorello, G, Trotta, C, Canfora, E, Chu, H, Christianson, D, Cheah, Y-W, Poindexter, C, Chen, J, Elbashandy, A, Humphrey, M, Isaac, P, Polidori, D, Reichstein, M, Ribeca, A, van Ingen, C, Vuichard, N, Zhang, L, Amiro, B, Ammann, C, Arain, MA, Ardo, J, Arkebauer, T, Arndt, SK, Arriga, N, Aubinet, M, Aurela, M, Baldocchi, D, Barr, A, Beamesderfer, E, Marchesini, LB, Bergeron, O, Beringer, J, Bernhofer, C, Berveiller, D, Billesbach, D, Black, TA, Blanken, PD, Bohrer, G, Boike, J, Bolstad, PV, Bonal, D, Bonnefond, J-M, Bowling, DR, Bracho, R, Brodeur, J, Brummer, C, Buchmann, N, Burban, B, Burns, SP, Buysse, P, Cale, P, Cavagna, M, Cellier, P, Chen, S, Chini, I, Christensen, TR, Cleverly, J, Collalti, A, Consalvo, C, Cook, BD, Cook, D, Coursolle, C, Cremonese, E, Curtis, PS, D'Andrea, E, da Rocha, H, Dai, X, Davis, KJ, De Cinti, B, de Grandcourt, A, De Ligne, A, De Oliveira, RC, Delpierre, N, Desai, AR, Di Bella, CM, di Tommasi, P, Dolman, H, Domingo, F, Dong, G, Dore, S, Duce, P, Dufrene, E, Dunn, A, Dusek, J, Eamus, D, Eichelmann, U, ElKhidir, HAM, Eugster, W, Ewenz, CM, Ewers, B, Famulari, D, Fares, S, Feigenwinter, I, Feitz, A, Fensholt, R, Filippa, G, Fischer, M, Frank, J, Galvagno, M, Gharun, M, Gianelle, D, Gielen, B, Gioli, B, Gitelson, A, Goded, I, Goeckede, M, Goldstein, AH, Gough, CM, Goulden, ML, Graf, A, Griebel, A, Gruening, C, Grunwald, T, Hammerle, A, Han, S, Han, X, Hansen, BU, Hanson, C, Hatakka, J, He, Y, Hehn, M, Heinesch, B, Hinko-Najera, N, Hortnagl, L, Hutley, L, Ibrom, A, Ikawa, H, Jackowicz-Korczynski, M, Janous, D, Jans, W, Jassal, R, Jiang, S, Kato, T, Khomik, M, Klatt, J, Knohl, A, Knox, S, Kobayashi, H, Koerber, G, Kolle, O, Kosugi, Y, Kotani, A, Kowalski, A, Kruijt, B, Kurbatova, J, Kutsch, WL, Kwon, H, Launiainen, S, Laurila, T, Law, B, Leuning, R, Li, Y, Liddell, M, Limousin, J-M, Lion, M, Liska, AJ, Lohila, A, Lopez-Ballesteros, A, Lopez-Blanco, E, Loubet, B, Loustau, D, Lucas-Moffat, A, Luers, J, Ma, S, Macfarlane, C, Magliulo, V, Maier, R, Mammarella, I, Manca, G, Marcolla, B, Margolis, HA, Marras, S, Massman, W, Mastepanov, M, Matamala, R, Matthes, JH, Mazzenga, F, McCaughey, H, McHugh, I, McMillan, AMS, Merbold, L, Meyer, W, Meyers, T, Miller, SD, Minerbi, S, Moderow, U, Monson, RK, Montagnani, L, Moore, CE, Moors, E, Moreaux, V, Moureaux, C, Munger, JW, Nakai, T, Neirynck, J, Nesic, Z, Nicolini, G, Noormets, A, Northwood, M, Nosetto, M, Nouvellon, Y, Novick, K, Oechel, W, Olesen, JE, Ourcival, J-M, Papuga, SA, Parmentier, F-J, Paul-Limoges, E, Pavelka, M, Peichl, M, Pendall, E, Phillips, RP, Pilegaard, K, Pirk, N, Posse, G, Powell, T, Prasse, H, Prober, SM, Rambal, S, Rannik, U, Raz-Yaseef, N, Rebmann, C, Reed, D, de Dios, VR, Restrepo-Coupe, N, Reverter, BR, Roland, M, Sabbatini, S, Sachs, T, Saleska, SR, Sanchez-Canete, EP, Sanchez-Mejia, ZM, Schmid, HP, Schmidt, M, Schneider, K, Schrader, F, Schroder, I, Scott, RL, Sedlak, P, Serrano-Ortiz, P, Shao, C, Shi, P, Shironya, I, Siebicke, L, Sigut, L, Silberstein, R, Sirca, C, Spano, D, Steinbrecher, R, Stevens, RM, Sturtevant, C, Suyker, A, Tagesson, T, Takanashi, S, Tang, Y, Tapper, N, Thom, J, Tomassucci, M, Tuovinen, J-P, Urbanski, S, Valentini, R, van der Molen, M, van Gorsel, E, van Huissteden, K, Varlagin, A, Verfaillie, J, Vesala, T, Vincke, C, Vitale, D, Vygodskaya, N, Walker, JP, Walter-Shea, E, Wang, H, Weber, R, Westermann, S, Wille, C, Wofsy, S, Wohlfahrt, G, Wolf, S, Woodgate, W, Zampedri, R, Zhang, J, Zhou, G, Zona, D, Agarwal, D, Biraud, S, Torn, M, and Papale, D
Abstract: A Correction to this paper has been published: https://doi.org/10.1038/s41597-021-00851-9.
Published: 2021

19. Multiple ecosystem effects of extreme weather events in the Arctic

Author: Christensen, T. R. (T. R.), Lund, M. (M.), Skov, K. (K.), Abermann, J. (J.), López-Blanco, E. (E.), Scheller, J. (J.), Scheel, M. (M.), Jackowicz-Korczynski, M. (M.), Langley, K. (K.), Murphy, M. J. (M. J.), Mastepanov, M. (M.), Christensen, T. R. (T. R.), Lund, M. (M.), Skov, K. (K.), Abermann, J. (J.), López-Blanco, E. (E.), Scheller, J. (J.), Scheel, M. (M.), Jackowicz-Korczynski, M. (M.), Langley, K. (K.), Murphy, M. J. (M. J.), and Mastepanov, M. (M.)
Abstract: The Arctic is getting warmer and wetter. Here, we document two independent examples of how associated extreme precipitation patterns have severe implications for high Arctic ecosystems. The events stand out in a 23-year record of continuous observations of a wide range of ecosystem parameters and act as an early indication of conditions projected to increase in the future. In NE Greenland, August 2015, one-quarter of the average annual precipitation fell during a 9-day intensive rain event. This ranked number one for daily sums during the 1996–2018 period and caused a strong and prolonged reduction in solar radiation decreasing CO₂ uptake in the order of 18–23 g C m⁻², a reduction comparable to typical annual C budgets in Arctic tundra. In a different type of event, but also due to changed weather patterns, an extreme snow melt season in 2018 triggered a dramatic gully thermokarst causing rapid transformation in ecosystem functioning from consistent annual ecosystem CO₂ uptake and low methane exchange to highly elevated methane release, net source of CO₂, and substantial export of organic carbon downstream as riverine and coastal input. In addition to climate warming alone, more frequent occurrence of extreme weather patterns will have large implications for otherwise undisturbed tundra ecosystems including their element transport and carbon interactions with the atmosphere and ocean.
Published: 2021

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

Author: Pastorello, G, Trotta, C, Canfora, E, Chu, H, Christianson, D, Cheah, Y-W, Poindexter, C, Chen, J, Elbashandy, A, Humphrey, M, Isaac, P, Polidori, D, Reichstein, M, Ribeca, A, van Ingen, C, Vuichard, N, Zhang, L, Amiro, B, Ammann, C, Arain, MA, Ardö, J, Arkebauer, T, Arndt, SK, Arriga, N, Aubinet, M, Aurela, M, Baldocchi, D, Barr, A, Beamesderfer, E, Marchesini, LB, Bergeron, O, Beringer, J, Bernhofer, C, Berveiller, D, Billesbach, D, Black, TA, Blanken, PD, Bohrer, G, Boike, J, Bolstad, PV, Bonal, D, Bonnefond, J-M, Bowling, DR, Bracho, R, Brodeur, J, Brümmer, C, Buchmann, N, Burban, B, Burns, SP, Buysse, P, Cale, P, Cavagna, M, Cellier, P, Chen, S, Chini, I, Christensen, TR, Cleverly, J, Collalti, A, Consalvo, C, Cook, BD, Cook, D, Coursolle, C, Cremonese, E, Curtis, PS, D’Andrea, E, da Rocha, H, Dai, X, Davis, KJ, De Cinti, B, de Grandcourt, A, De Ligne, A, De Oliveira, RC, Delpierre, N, Desai, AR, Di Bella, CM, di Tommasi, P, Dolman, H, Domingo, F, Dong, G, Dore, S, Duce, P, Dufrêne, E, Dunn, A, Dušek, J, Eamus, D, Eichelmann, U, ElKhidir, HAM, Eugster, W, Ewenz, CM, Ewers, B, Famulari, D, Fares, S, Feigenwinter, I, Feitz, A, Fensholt, R, Filippa, G, Fischer, M, Frank, J, Galvagno, M, Gharun, M, Gianelle, D, Gielen, B, Gioli, B, Gitelson, A, Goded, I, Goeckede, M, Goldstein, AH, Gough, CM, Goulden, ML, Graf, A, Griebel, A, Gruening, C, Grünwald, T, Hammerle, A, Han, S, Han, X, Hansen, BU, Hanson, C, Hatakka, J, He, Y, Hehn, M, Heinesch, B, Hinko-Najera, N, Hörtnagl, L, Hutley, L, Ibrom, A, Ikawa, H, Jackowicz-Korczynski, M, Janouš, D, Jans, W, Jassal, R, Jiang, S, Kato, T, Khomik, M, Klatt, J, Knohl, A, Knox, S, Kobayashi, H, Koerber, G, Kolle, O, Kosugi, Y, Kotani, A, Kowalski, A, Kruijt, B, Kurbatova, J, Kutsch, WL, Kwon, H, Launiainen, S, Laurila, T, Law, B, Leuning, R, Li, Y, Liddell, M, Limousin, J-M, Lion, M, Liska, AJ, Lohila, A, López-Ballesteros, A, López-Blanco, E, Loubet, B, Loustau, D, Lucas-Moffat, A, Lüers, J, Ma, S, Macfarlane, C, Magliulo, V, Maier, R, Mammarella, I, Manca, G, Marcolla, B, Margolis, HA, Marras, S, Massman, W, Mastepanov, M, Matamala, R, Matthes, JH, Mazzenga, F, McCaughey, H, McHugh, I, McMillan, AMS, Merbold, L, Meyer, W, Meyers, T, Miller, SD, Minerbi, S, Moderow, U, Monson, RK, Montagnani, L, Moore, CE, Moors, E, Moreaux, V, Moureaux, C, Munger, JW, Nakai, T, Neirynck, J, Nesic, Z, Nicolini, G, Noormets, A, Northwood, M, Nosetto, M, Nouvellon, Y, Novick, K, Oechel, W, Olesen, JE, Ourcival, J-M, Papuga, SA, Parmentier, F-J, Paul-Limoges, E, Pavelka, M, Peichl, M, Pendall, E, Phillips, RP, Pilegaard, K, Pirk, N, Posse, G, Powell, T, Prasse, H, Prober, SM, Rambal, S, Rannik, Ü, Raz-Yaseef, N, Rebmann, C, Reed, D, de Dios, VR, Restrepo-Coupe, N, Reverter, BR, Roland, M, Sabbatini, S, Sachs, T, Saleska, SR, Sánchez-Cañete, EP, Sanchez-Mejia, ZM, Schmid, HP, Schmidt, M, Schneider, K, Schrader, F, Schroder, I, Scott, RL, Sedlák, P, Serrano-Ortíz, P, Shao, C, Shi, P, Shironya, I, Siebicke, L, Šigut, L, Silberstein, R, Sirca, C, Spano, D, Steinbrecher, R, Stevens, RM, Sturtevant, C, Suyker, A, Tagesson, T, Takanashi, S, Tang, Y, Tapper, N, Thom, J, Tomassucci, M, Tuovinen, J-P, Urbanski, S, Valentini, R, van der Molen, M, van Gorsel, E, van Huissteden, K, Varlagin, A, Verfaillie, J, Vesala, T, Vincke, C, Vitale, D, Vygodskaya, N, Walker, JP, Walter-Shea, E, Wang, H, Weber, R, Westermann, S, Wille, C, Wofsy, S, Wohlfahrt, G, Wolf, S, Woodgate, W, Zampedri, R, Zhang, J, Zhou, G, Zona, D, Agarwal, D, Biraud, S, Torn, M, Papale, D, Pastorello, G, Trotta, C, Canfora, E, Chu, H, Christianson, D, Cheah, Y-W, Poindexter, C, Chen, J, Elbashandy, A, Humphrey, M, Isaac, P, Polidori, D, Reichstein, M, Ribeca, A, van Ingen, C, Vuichard, N, Zhang, L, Amiro, B, Ammann, C, Arain, MA, Ardö, J, Arkebauer, T, Arndt, SK, Arriga, N, Aubinet, M, Aurela, M, Baldocchi, D, Barr, A, Beamesderfer, E, Marchesini, LB, Bergeron, O, Beringer, J, Bernhofer, C, Berveiller, D, Billesbach, D, Black, TA, Blanken, PD, Bohrer, G, Boike, J, Bolstad, PV, Bonal, D, Bonnefond, J-M, Bowling, DR, Bracho, R, Brodeur, J, Brümmer, C, Buchmann, N, Burban, B, Burns, SP, Buysse, P, Cale, P, Cavagna, M, Cellier, P, Chen, S, Chini, I, Christensen, TR, Cleverly, J, Collalti, A, Consalvo, C, Cook, BD, Cook, D, Coursolle, C, Cremonese, E, Curtis, PS, D’Andrea, E, da Rocha, H, Dai, X, Davis, KJ, De Cinti, B, de Grandcourt, A, De Ligne, A, De Oliveira, RC, Delpierre, N, Desai, AR, Di Bella, CM, di Tommasi, P, Dolman, H, Domingo, F, Dong, G, Dore, S, Duce, P, Dufrêne, E, Dunn, A, Dušek, J, Eamus, D, Eichelmann, U, ElKhidir, HAM, Eugster, W, Ewenz, CM, Ewers, B, Famulari, D, Fares, S, Feigenwinter, I, Feitz, A, Fensholt, R, Filippa, G, Fischer, M, Frank, J, Galvagno, M, Gharun, M, Gianelle, D, Gielen, B, Gioli, B, Gitelson, A, Goded, I, Goeckede, M, Goldstein, AH, Gough, CM, Goulden, ML, Graf, A, Griebel, A, Gruening, C, Grünwald, T, Hammerle, A, Han, S, Han, X, Hansen, BU, Hanson, C, Hatakka, J, He, Y, Hehn, M, Heinesch, B, Hinko-Najera, N, Hörtnagl, L, Hutley, L, Ibrom, A, Ikawa, H, Jackowicz-Korczynski, M, Janouš, D, Jans, W, Jassal, R, Jiang, S, Kato, T, Khomik, M, Klatt, J, Knohl, A, Knox, S, Kobayashi, H, Koerber, G, Kolle, O, Kosugi, Y, Kotani, A, Kowalski, A, Kruijt, B, Kurbatova, J, Kutsch, WL, Kwon, H, Launiainen, S, Laurila, T, Law, B, Leuning, R, Li, Y, Liddell, M, Limousin, J-M, Lion, M, Liska, AJ, Lohila, A, López-Ballesteros, A, López-Blanco, E, Loubet, B, Loustau, D, Lucas-Moffat, A, Lüers, J, Ma, S, Macfarlane, C, Magliulo, V, Maier, R, Mammarella, I, Manca, G, Marcolla, B, Margolis, HA, Marras, S, Massman, W, Mastepanov, M, Matamala, R, Matthes, JH, Mazzenga, F, McCaughey, H, McHugh, I, McMillan, AMS, Merbold, L, Meyer, W, Meyers, T, Miller, SD, Minerbi, S, Moderow, U, Monson, RK, Montagnani, L, Moore, CE, Moors, E, Moreaux, V, Moureaux, C, Munger, JW, Nakai, T, Neirynck, J, Nesic, Z, Nicolini, G, Noormets, A, Northwood, M, Nosetto, M, Nouvellon, Y, Novick, K, Oechel, W, Olesen, JE, Ourcival, J-M, Papuga, SA, Parmentier, F-J, Paul-Limoges, E, Pavelka, M, Peichl, M, Pendall, E, Phillips, RP, Pilegaard, K, Pirk, N, Posse, G, Powell, T, Prasse, H, Prober, SM, Rambal, S, Rannik, Ü, Raz-Yaseef, N, Rebmann, C, Reed, D, de Dios, VR, Restrepo-Coupe, N, Reverter, BR, Roland, M, Sabbatini, S, Sachs, T, Saleska, SR, Sánchez-Cañete, EP, Sanchez-Mejia, ZM, Schmid, HP, Schmidt, M, Schneider, K, Schrader, F, Schroder, I, Scott, RL, Sedlák, P, Serrano-Ortíz, P, Shao, C, Shi, P, Shironya, I, Siebicke, L, Šigut, L, Silberstein, R, Sirca, C, Spano, D, Steinbrecher, R, Stevens, RM, Sturtevant, C, Suyker, A, Tagesson, T, Takanashi, S, Tang, Y, Tapper, N, Thom, J, Tomassucci, M, Tuovinen, J-P, Urbanski, S, Valentini, R, van der Molen, M, van Gorsel, E, van Huissteden, K, Varlagin, A, Verfaillie, J, Vesala, T, Vincke, C, Vitale, D, Vygodskaya, N, Walker, JP, Walter-Shea, E, Wang, H, Weber, R, Westermann, S, Wille, C, Wofsy, S, Wohlfahrt, G, Wolf, S, Woodgate, W, Zampedri, R, Zhang, J, Zhou, G, Zona, D, Agarwal, D, Biraud, S, Torn, M, and Papale, D
Abstract: The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions.
Published: 2021

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

Author: Pastorello, G, Trotta, C, Canfora, E, Chu, H, Christianson, D, Cheah, Y-W, Poindexter, C, Chen, J, Elbashandy, A, Humphrey, M, Isaac, P, Polidori, D, Ribeca, A, van Ingen, C, Zhang, L, Amiro, B, Ammann, C, Arain, MA, Ardo, J, Arkebauer, T, Arndt, SK, Arriga, N, Aubinet, M, Aurela, M, Baldocchi, D, Barr, A, Beamesderfer, E, Marchesini, LB, Bergeron, O, Beringer, J, Bernhofer, C, Berveiller, D, Billesbach, D, Black, TA, Blanken, PD, Bohrer, G, Boike, J, Bolstad, PV, Bonal, D, Bonnefond, J-M, Bowling, DR, Bracho, R, Brodeur, J, Bruemmer, C, Buchmann, N, Burban, B, Burns, SP, Buysse, P, Cale, P, Cavagna, M, Cellier, P, Chen, S, Chini, I, Christensen, TR, Cleverly, J, Collalti, A, Consalvo, C, Cook, BD, Cook, D, Coursolle, C, Cremonese, E, Curtis, PS, D'Andrea, E, da Rocha, H, Dai, X, Davis, KJ, De Cinti, B, de Grandcourt, A, De Ligne, A, De Oliveira, RC, Delpierre, N, Desai, AR, Di Bella, CM, di Tommasi, P, Dolman, H, Domingo, F, Dong, G, Dore, S, Duce, P, Dufrene, E, Dunn, A, Dusek, J, Eamus, D, Eichelmann, U, ElKhidir, HAM, Eugster, W, Ewenz, CM, Ewers, B, Famulari, D, Fares, S, Feigenwinter, I, Feitz, A, Fensholt, R, Filippa, G, Fischer, M, Frank, J, Galvagno, M, Gharun, M, Gianelle, D, Gielen, B, Gioli, B, Gitelson, A, Goded, I, Goeckede, M, Goldstein, AH, Gough, CM, Goulden, ML, Graf, A, Griebel, A, Gruening, C, Gruenwald, T, Hammerle, A, Han, S, Han, X, Hansen, BU, Hanson, C, Hatakka, J, He, Y, Hehn, M, Heinesch, B, Hinko-Najera, N, Hoertnagl, L, Hutley, L, Ibrom, A, Ikawa, H, Jackowicz-Korczynski, M, Janous, D, Jans, W, Jassal, R, Jiang, S, Kato, T, Khomik, M, Klatt, J, Knohl, A, Knox, S, Kobayashi, H, Koerber, G, Kolle, O, Kosugi, Y, Kotani, A, Kowalski, A, Kruijt, B, Kurbatova, J, Kutsch, WL, Kwon, H, Launiainen, S, Laurila, T, Law, B, Leuning, R, Li, Y, Liddell, M, Limousin, J-M, Lion, M, Liska, AJ, Lohila, A, Lopez-Ballesteros, A, Lopez-Blanco, E, Loubet, B, Loustau, D, Lucas-Moffat, A, Lueers, J, Ma, S, Macfarlane, C, Magliulo, V, Maier, R, Mammarella, I, Manca, G, Marcolla, B, Margolis, HA, Marras, S, Massman, W, Mastepanov, M, Matamala, R, Matthes, JH, Mazzenga, F, McCaughey, H, McHugh, I, McMillan, AMS, Merbold, L, Meyer, W, Meyers, T, Miller, SD, Minerbi, S, Moderow, U, Monson, RK, Montagnani, L, Moore, CE, Moors, E, Moreaux, V, Moureaux, C, Munger, JW, Nakai, T, Neirynck, J, Nesic, Z, Nicolini, G, Noormets, A, Northwood, M, Nosetto, M, Nouvellon, Y, Novick, K, Oechel, W, Olesen, JE, Ourcival, J-M, Papuga, SA, Parmentier, F-J, Paul-Limoges, E, Pavelka, M, Peichl, M, Pendall, E, Phillips, RP, Pilegaard, K, Pirk, N, Posse, G, Powell, T, Prasse, H, Prober, SM, Rambal, S, Rannik, U, Raz-Yaseef, N, Reed, D, de Dios, VR, Restrepo-Coupe, N, Reverter, BR, Roland, M, Sabbatini, S, Sachs, T, Saleska, SR, Sanchez-Canete, EP, Sanchez-Mejia, ZM, Schmid, HP, Schmidt, M, Schneider, K, Schrader, F, Schroder, I, Scott, RL, Sedlak, P, Serrano-Ortiz, P, Shao, C, Shi, P, Shironya, I, Siebicke, L, Sigut, L, Silberstein, R, Sirca, C, Spano, D, Steinbrecher, R, Stevens, RM, Sturtevant, C, Suyker, A, Tagesson, T, Takanashi, S, Tang, Y, Tapper, N, Thom, J, Tiedemann, F, Tomassucci, M, Tuovinen, J-P, Urbanski, S, Valentini, R, van der Molen, M, van Gorsel, E, van Huissteden, K, Varlagin, A, Verfaillie, J, Vesala, T, Vincke, C, Vitale, D, Vygodskaya, N, Walker, JP, Walter-Shea, E, Wang, H, Weber, R, Westermann, S, Wille, C, Wofsy, S, Wohlfahrt, G, Wolf, S, Woodgate, W, Zampedri, R, Zhang, J, Zhou, G, Zona, D, Agarwal, D, Biraud, S, Torn, M, Papale, D, Pastorello, G, Trotta, C, Canfora, E, Chu, H, Christianson, D, Cheah, Y-W, Poindexter, C, Chen, J, Elbashandy, A, Humphrey, M, Isaac, P, Polidori, D, Ribeca, A, van Ingen, C, Zhang, L, Amiro, B, Ammann, C, Arain, MA, Ardo, J, Arkebauer, T, Arndt, SK, Arriga, N, Aubinet, M, Aurela, M, Baldocchi, D, Barr, A, Beamesderfer, E, Marchesini, LB, Bergeron, O, Beringer, J, Bernhofer, C, Berveiller, D, Billesbach, D, Black, TA, Blanken, PD, Bohrer, G, Boike, J, Bolstad, PV, Bonal, D, Bonnefond, J-M, Bowling, DR, Bracho, R, Brodeur, J, Bruemmer, C, Buchmann, N, Burban, B, Burns, SP, Buysse, P, Cale, P, Cavagna, M, Cellier, P, Chen, S, Chini, I, Christensen, TR, Cleverly, J, Collalti, A, Consalvo, C, Cook, BD, Cook, D, Coursolle, C, Cremonese, E, Curtis, PS, D'Andrea, E, da Rocha, H, Dai, X, Davis, KJ, De Cinti, B, de Grandcourt, A, De Ligne, A, De Oliveira, RC, Delpierre, N, Desai, AR, Di Bella, CM, di Tommasi, P, Dolman, H, Domingo, F, Dong, G, Dore, S, Duce, P, Dufrene, E, Dunn, A, Dusek, J, Eamus, D, Eichelmann, U, ElKhidir, HAM, Eugster, W, Ewenz, CM, Ewers, B, Famulari, D, Fares, S, Feigenwinter, I, Feitz, A, Fensholt, R, Filippa, G, Fischer, M, Frank, J, Galvagno, M, Gharun, M, Gianelle, D, Gielen, B, Gioli, B, Gitelson, A, Goded, I, Goeckede, M, Goldstein, AH, Gough, CM, Goulden, ML, Graf, A, Griebel, A, Gruening, C, Gruenwald, T, Hammerle, A, Han, S, Han, X, Hansen, BU, Hanson, C, Hatakka, J, He, Y, Hehn, M, Heinesch, B, Hinko-Najera, N, Hoertnagl, L, Hutley, L, Ibrom, A, Ikawa, H, Jackowicz-Korczynski, M, Janous, D, Jans, W, Jassal, R, Jiang, S, Kato, T, Khomik, M, Klatt, J, Knohl, A, Knox, S, Kobayashi, H, Koerber, G, Kolle, O, Kosugi, Y, Kotani, A, Kowalski, A, Kruijt, B, Kurbatova, J, Kutsch, WL, Kwon, H, Launiainen, S, Laurila, T, Law, B, Leuning, R, Li, Y, Liddell, M, Limousin, J-M, Lion, M, Liska, AJ, Lohila, A, Lopez-Ballesteros, A, Lopez-Blanco, E, Loubet, B, Loustau, D, Lucas-Moffat, A, Lueers, J, Ma, S, Macfarlane, C, Magliulo, V, Maier, R, Mammarella, I, Manca, G, Marcolla, B, Margolis, HA, Marras, S, Massman, W, Mastepanov, M, Matamala, R, Matthes, JH, Mazzenga, F, McCaughey, H, McHugh, I, McMillan, AMS, Merbold, L, Meyer, W, Meyers, T, Miller, SD, Minerbi, S, Moderow, U, Monson, RK, Montagnani, L, Moore, CE, Moors, E, Moreaux, V, Moureaux, C, Munger, JW, Nakai, T, Neirynck, J, Nesic, Z, Nicolini, G, Noormets, A, Northwood, M, Nosetto, M, Nouvellon, Y, Novick, K, Oechel, W, Olesen, JE, Ourcival, J-M, Papuga, SA, Parmentier, F-J, Paul-Limoges, E, Pavelka, M, Peichl, M, Pendall, E, Phillips, RP, Pilegaard, K, Pirk, N, Posse, G, Powell, T, Prasse, H, Prober, SM, Rambal, S, Rannik, U, Raz-Yaseef, N, Reed, D, de Dios, VR, Restrepo-Coupe, N, Reverter, BR, Roland, M, Sabbatini, S, Sachs, T, Saleska, SR, Sanchez-Canete, EP, Sanchez-Mejia, ZM, Schmid, HP, Schmidt, M, Schneider, K, Schrader, F, Schroder, I, Scott, RL, Sedlak, P, Serrano-Ortiz, P, Shao, C, Shi, P, Shironya, I, Siebicke, L, Sigut, L, Silberstein, R, Sirca, C, Spano, D, Steinbrecher, R, Stevens, RM, Sturtevant, C, Suyker, A, Tagesson, T, Takanashi, S, Tang, Y, Tapper, N, Thom, J, Tiedemann, F, Tomassucci, M, Tuovinen, J-P, Urbanski, S, Valentini, R, van der Molen, M, van Gorsel, E, van Huissteden, K, Varlagin, A, Verfaillie, J, Vesala, T, Vincke, C, Vitale, D, Vygodskaya, N, Walker, JP, Walter-Shea, E, Wang, H, Weber, R, Westermann, S, Wille, C, Wofsy, S, Wohlfahrt, G, Wolf, S, Woodgate, W, Zampedri, R, Zhang, J, Zhou, G, Zona, D, Agarwal, D, Biraud, S, Torn, M, and Papale, D
Abstract: The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.
Published: 2020

22. A new dataset of soil carbon and nitrogen stocks and profiles from an instrumented Greenlandic fen designed to evaluate land-surface models

Author: Morel, X. (Xavier), Hansen, B. (Birger), Delire, C. (Christine), Ambus, P. (Per), Mastepanov, M. (Mikhail), Decharme, B. (Bertrand), Morel, X. (Xavier), Hansen, B. (Birger), Delire, C. (Christine), Ambus, P. (Per), Mastepanov, M. (Mikhail), and Decharme, B. (Bertrand)
Abstract: Arctic and boreal peatlands play a major role in the global carbon (C) cycle. They are particularly efficient at sequestering carbon because their high water content limits decomposition rates to levels below their net primary productivity. Their future in a climate-change context is quite uncertain in terms of carbon emissions and carbon sequestration. Nuuk fen is a well-instrumented Greenlandic fen with monitoring of soil physical variables and greenhouse gas fluxes (CH₄ and CO₂) and is of particular interest for testing and validating land-surface models. But knowledge of soil carbon stocks and profiles is missing. This is a crucial shortcoming for a complete evaluation of models, as soil carbon is one of the primary drivers of CH₄ and CO₂ soil emissions. To address this issue, we measured, for the first time, soil carbon and nitrogen density, profiles and stocks in the Nuuk peatland (64∘07′51′′ N, 51∘23′10′′ W), colocated with the greenhouse gas measurements. Measurements were made along two transects, 60 and 90 m long and with a horizontal resolution of 5 m and a vertical resolution of 5 to 10 cm, using a 4 cm diameter gouge auger. A total of 135 soil samples were analyzed. Soil carbon density varied between 6.2 and 160.2 kg C m⁻³ with a mean value of 50.2 kg C m⁻³. Mean soil nitrogen density was 2.37 kg N m⁻³. Mean soil carbon and nitrogen stocks are 36.3 kg C m⁻² and 1.7 kg N m⁻². These new data are in the range of those encountered in other arctic peatlands. This new dataset, one of very few in Greenland, can contribute to further development of joint modeling of greenhouse gas emissions and soil carbon and nitrogen in land-surface models. The dataset is open-access and available at https://doi.org/10.1594/PANGAEA.909899 (Morel et al., 2019b).
Published: 2020

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

Author: Pastorello, G. (Gilberto), Trotta, C. (Carlo), Canfora, E. (Eleonora), Chu, H. (Housen), Christianson, D. (Danielle), Cheah, Y.-W. (You-Wei), Poindexter, C. (Cristina), Chen, J. (Jiquan), Elbashandy, A. (Abdelrahman), Humphrey, M. (Marty), Isaac, P. (Peter), Polidori, D. (Diego), Ribeca, A. (Alessio), van Ingen, C. (Catharine), Zhang, L. (Leiming), Amiro, B. (Brian), Ammann, C. (Christof), Arain, M. A. (M. Altaf), Ardo, J. (Jonas), Arkebauer, T. (Timothy), Arndt, S. K. (Stefan K.), Arriga, N. (Nicola), Aubinet, M. (Marc), Aurela, M. (Mika), Baldocchi, D. (Dennis), Barr, A. (Alan), Beamesderfer, E. (Eric), Marchesini, L. B. (Luca Belelli), Bergeron, O. (Onil), Beringer, J. (Jason), Bernhofer, C. (Christian), Berveiller, D. (Daniel), Billesbach, D. (Dave), Black, T. A. (Thomas Andrew), Blanken, P. D. (Peter D.), Bohrer, G. (Gil), Boike, J. (Julia), Bolstad, P. V. (Paul V.), Bonal, D. (Damien), Bonnefond, J.-M. (Jean-Marc), Bowling, D. R. (David R.), Bracho, R. (Rosvel), Brodeur, J. (Jason), Bruemmer, C. (Christian), Buchmann, N. (Nina), Burban, B. (Benoit), Burns, S. P. (Sean P.), Buysse, P. (Pauline), Cale, P. (Peter), Cavagna, M. (Mauro), Cellier, P. (Pierre), Chen, S. (Shiping), Chini, I. (Isaac), Christensen, T. R. (Torben R.), Cleverly, J. (James), Collalti, A. (Alessio), Consalvo, C. (Claudia), Cook, B. D. (Bruce D.), Cook, D. (David), Coursolle, C. (Carole), Cremonese, E. (Edoardo), Curtis, P. S. (Peter S.), D'Andrea, E. (Ettore), da Rocha, H. (Humberto), Dai, X. (Xiaoqin), Davis, K. J. (Kenneth J.), De Cinti, B. (Bruno), de Grandcourt, A. (Agnes), De Ligne, A. (Anne), De Oliveira, R. C. (Raimundo C.), Delpierre, N. (Nicolas), Desai, A. R. (Ankur R.), Di Bella, C. M. (Carlos Marcelo), di Tommasi, P. (Paul), Dolman, H. (Han), Domingo, F. (Francisco), Dong, G. (Gang), Dore, S. (Sabina), Duce, P. (Pierpaolo), Dufrene, E. (Eric), Dunn, A. (Allison), Dusek, J. (Jiri), Eamus, D. (Derek), Eichelmann, U. (Uwe), ElKhidir, H. A. (Hatim Abdalla M.), Eugster, W. (Werner), Ewenz, C. M. (Cacilia M.), Ewers, B. (Brent), Famulari, D. (Daniela), Fares, S. (Silvano), Feigenwinter, I. (Iris), Feitz, A. (Andrew), Fensholt, R. (Rasmus), Filippa, G. (Gianluca), Fischer, M. (Marc), Frank, J. (John), Galvagno, M. (Marta), Gharun, M. (Mana), Gianelle, D. (Damiano), Gielen, B. (Bert), Gioli, B. (Beniamino), Gitelson, A. (Anatoly), Goded, I. (Ignacio), Goeckede, M. (Mathias), Goldstein, A. H. (Allen H.), Gough, C. M. (Christopher M.), Goulden, M. L. (Michael L.), Graf, A. (Alexander), Griebel, A. (Anne), Gruening, C. (Carsten), Gruenwald, T. (Thomas), Hammerle, A. (Albin), Han, S. (Shijie), Han, X. (Xingguo), Hansen, B. U. (Birger Ulf), Hanson, C. (Chad), Hatakka, J. (Juha), He, Y. (Yongtao), Hehn, M. (Markus), Heinesch, B. (Bernard), Hinko-Najera, N. (Nina), Hoertnagl, L. (Lukas), Hutley, L. (Lindsay), Ibrom, A. (Andreas), Ikawa, H. (Hiroki), Jackowicz-Korczynski, M. (Marcin), Janous, D. (Dalibor), Jans, W. (Wilma), Jassal, R. (Rachhpal), Jiang, S. (Shicheng), Kato, T. (Tomomichi), Khomik, M. (Myroslava), Klatt, J. (Janina), Knohl, A. (Alexander), Knox, S. (Sara), Kobayashi, H. (Hideki), Koerber, G. (Georgia), Kolle, O. (Olaf), Kosugi, Y. (Yoshiko), Kotani, A. (Ayumi), Kowalski, A. (Andrew), Kruijt, B. (Bart), Kurbatova, J. (Julia), Kutsch, W. L. (Werner L.), Kwon, H. (Hyojung), Launiainen, S. (Samuli), Laurila, T. (Tuomas), Law, B. (Bev), Leuning, R. (Ray), Li, Y. (Yingnian), Liddell, M. (Michael), Limousin, J.-M. (Jean-Marc), Lion, M. (Marryanna), Liska, A. J. (Adam J.), Lohila, A. (Annalea), Lopez-Ballesteros, A. (Ana), Lopez-Blanco, E. (Efren), Loubet, B. (Benjamin), Loustau, D. (Denis), Lucas-Moffat, A. (Antje), Lueers, J. (Johannes), Ma, S. (Siyan), Macfarlane, C. (Craig), Magliulo, V. (Vincenzo), Maier, R. (Regine), Mammarella, I. (Ivan), Manca, G. (Giovanni), Marcolla, B. (Barbara), Margolis, H. A. (Hank A.), Marras, S. (Serena), Massman, W. (William), Mastepanov, M. (Mikhail), Matamala, R. (Roser), Matthes, J. H. (Jaclyn Hatala), Mazzenga, F. (Francesco), McCaughey, H. (Harry), McHugh, I. (Ian), McMillan, A. M. (Andrew M. S.), Merbold, L. (Lutz), Meyer, W. (Wayne), Meyers, T. (Tilden), Miller, S. D. (Scott D.), Minerbi, S. (Stefano), Moderow, U. (Uta), Monson, R. K. (Russell K.), Montagnani, L. (Leonardo), Moore, C. E. (Caitlin E.), Moors, E. (Eddy), Moreaux, V. (Virginie), Moureaux, C. (Christine), Munger, J. W. (J. William), Nakai, T. (Taro), Neirynck, J. (Johan), Nesic, Z. (Zoran), Nicolini, G. (Giacomo), Noormets, A. (Asko), Northwood, M. (Matthew), Nosetto, M. (Marcelo), Nouvellon, Y. (Yann), Novick, K. (Kimberly), Oechel, W. (Walter), Olesen, J. E. (Jorgen Eivind), Ourcival, J.-M. (Jean-Marc), Papuga, S. A. (Shirley A.), Parmentier, F.-J. (Frans-Jan), Paul-Limoges, E. (Eugenie), Pavelka, M. (Marian), Peichl, M. (Matthias), Pendall, E. (Elise), Phillips, R. P. (Richard P.), Pilegaard, K. (Kim), Pirk, N. (Norbert), Posse, G. (Gabriela), Powell, T. (Thomas), Prasse, H. (Heiko), Prober, S. M. (Suzanne M.), Rambal, S. (Serge), Rannik, U. (Ullar), Raz-Yaseef, N. (Naama), Reed, D. (David), de Dios, V. R. (Victor Resco), Restrepo-Coupe, N. (Natalia), Reverter, B. R. (Borja R.), Roland, M. (Marilyn), Sabbatini, S. (Simone), Sachs, T. (Torsten), Saleska, S. R. (Scott R.), Sanchez-Canete, E. P. (Enrique P.), Sanchez-Mejia, Z. M. (Zulia M.), Schmid, H. P. (Hans Peter), Schmidt, M. (Marius), Schneider, K. (Karl), Schrader, F. (Frederik), Schroder, I. (Ivan), Scott, R. L. (Russell L.), Sedlak, P. (Pavel), Serrano-Ortiz, P. (Penelope), Shao, C. (Changliang), Shi, P. (Peili), Shironya, I. (Ivan), Siebicke, L. (Lukas), Sigut, L. (Ladislav), Silberstein, R. (Richard), Sirca, C. (Costantino), Spano, D. (Donatella), Steinbrecher, R. (Rainer), Stevens, R. M. (Robert M.), Sturtevant, C. (Cove), Suyker, A. (Andy), Tagesson, T. (Torbern), Takanashi, S. (Satoru), Tang, Y. (Yanhong), Tapper, N. (Nigel), Thom, J. (Jonathan), Tiedemann, F. (Frank), Tomassucci, M. (Michele), Tuovinen, J.-P. (Juha-Pekka), Urbanski, S. (Shawn), Valentini, R. (Riccardo), van der Molen, M. (Michiel), van Gorsel, E. (Eva), van Huissteden, K. (Ko), Varlagin, A. (Andrej), Verfaillie, J. (Joseph), Vesala, T. (Timo), Vincke, C. (Caroline), Vitale, D. (Domenico), Vygodskaya, N. (Natalia), Walker, J. P. (Jeffrey P.), Walter-Shea, E. (Elizabeth), Wang, H. (Huimin), Weber, R. (Robin), Westermann, S. (Sebastian), Wille, C. (Christian), Wofsy, S. (Steven), Wohlfahrt, G. (Georg), Wolf, S. (Sebastian), Woodgate, W. (William), Li, Y. (Yuelin), Zampedri, R. (Roberto), Zhang, J. (Junhui), Zhou, G. (Guoyi), Zona, D. (Donatella), Agarwal, D. (Deb), Biraud, S. (Sebastien), Torn, M. (Margaret), Papale, D. (Dario), Pastorello, G. (Gilberto), Trotta, C. (Carlo), Canfora, E. (Eleonora), Chu, H. (Housen), Christianson, D. (Danielle), Cheah, Y.-W. (You-Wei), Poindexter, C. (Cristina), Chen, J. (Jiquan), Elbashandy, A. (Abdelrahman), Humphrey, M. (Marty), Isaac, P. (Peter), Polidori, D. (Diego), Ribeca, A. (Alessio), van Ingen, C. (Catharine), Zhang, L. (Leiming), Amiro, B. (Brian), Ammann, C. (Christof), Arain, M. A. (M. Altaf), Ardo, J. (Jonas), Arkebauer, T. (Timothy), Arndt, S. K. (Stefan K.), Arriga, N. (Nicola), Aubinet, M. (Marc), Aurela, M. (Mika), Baldocchi, D. (Dennis), Barr, A. (Alan), Beamesderfer, E. (Eric), Marchesini, L. B. (Luca Belelli), Bergeron, O. (Onil), Beringer, J. (Jason), Bernhofer, C. (Christian), Berveiller, D. (Daniel), Billesbach, D. (Dave), Black, T. A. (Thomas Andrew), Blanken, P. D. (Peter D.), Bohrer, G. (Gil), Boike, J. (Julia), Bolstad, P. V. (Paul V.), Bonal, D. (Damien), Bonnefond, J.-M. (Jean-Marc), Bowling, D. R. (David R.), Bracho, R. (Rosvel), Brodeur, J. (Jason), Bruemmer, C. (Christian), Buchmann, N. (Nina), Burban, B. (Benoit), Burns, S. P. (Sean P.), Buysse, P. (Pauline), Cale, P. (Peter), Cavagna, M. (Mauro), Cellier, P. (Pierre), Chen, S. (Shiping), Chini, I. (Isaac), Christensen, T. R. (Torben R.), Cleverly, J. (James), Collalti, A. (Alessio), Consalvo, C. (Claudia), Cook, B. D. (Bruce D.), Cook, D. (David), Coursolle, C. (Carole), Cremonese, E. (Edoardo), Curtis, P. S. (Peter S.), D'Andrea, E. (Ettore), da Rocha, H. (Humberto), Dai, X. (Xiaoqin), Davis, K. J. (Kenneth J.), De Cinti, B. (Bruno), de Grandcourt, A. (Agnes), De Ligne, A. (Anne), De Oliveira, R. C. (Raimundo C.), Delpierre, N. (Nicolas), Desai, A. R. (Ankur R.), Di Bella, C. M. (Carlos Marcelo), di Tommasi, P. (Paul), Dolman, H. (Han), Domingo, F. (Francisco), Dong, G. (Gang), Dore, S. (Sabina), Duce, P. (Pierpaolo), Dufrene, E. (Eric), Dunn, A. (Allison), Dusek, J. (Jiri), Eamus, D. (Derek), Eichelmann, U. (Uwe), ElKhidir, H. A. (Hatim Abdalla M.), Eugster, W. (Werner), Ewenz, C. M. (Cacilia M.), Ewers, B. (Brent), Famulari, D. (Daniela), Fares, S. (Silvano), Feigenwinter, I. (Iris), Feitz, A. (Andrew), Fensholt, R. (Rasmus), Filippa, G. (Gianluca), Fischer, M. (Marc), Frank, J. (John), Galvagno, M. (Marta), Gharun, M. (Mana), Gianelle, D. (Damiano), Gielen, B. (Bert), Gioli, B. (Beniamino), Gitelson, A. (Anatoly), Goded, I. (Ignacio), Goeckede, M. (Mathias), Goldstein, A. H. (Allen H.), Gough, C. M. (Christopher M.), Goulden, M. L. (Michael L.), Graf, A. (Alexander), Griebel, A. (Anne), Gruening, C. (Carsten), Gruenwald, T. (Thomas), Hammerle, A. (Albin), Han, S. (Shijie), Han, X. (Xingguo), Hansen, B. U. (Birger Ulf), Hanson, C. (Chad), Hatakka, J. (Juha), He, Y. (Yongtao), Hehn, M. (Markus), Heinesch, B. (Bernard), Hinko-Najera, N. (Nina), Hoertnagl, L. (Lukas), Hutley, L. (Lindsay), Ibrom, A. (Andreas), Ikawa, H. (Hiroki), Jackowicz-Korczynski, M. (Marcin), Janous, D. (Dalibor), Jans, W. (Wilma), Jassal, R. (Rachhpal), Jiang, S. (Shicheng), Kato, T. (Tomomichi), Khomik, M. (Myroslava), Klatt, J. (Janina), Knohl, A. (Alexander), Knox, S. (Sara), Kobayashi, H. (Hideki), Koerber, G. (Georgia), Kolle, O. (Olaf), Kosugi, Y. (Yoshiko), Kotani, A. (Ayumi), Kowalski, A. (Andrew), Kruijt, B. (Bart), Kurbatova, J. (Julia), Kutsch, W. L. (Werner L.), Kwon, H. (Hyojung), Launiainen, S. (Samuli), Laurila, T. (Tuomas), Law, B. (Bev), Leuning, R. (Ray), Li, Y. (Yingnian), Liddell, M. (Michael), Limousin, J.-M. (Jean-Marc), Lion, M. (Marryanna), Liska, A. J. (Adam J.), Lohila, A. (Annalea), Lopez-Ballesteros, A. (Ana), Lopez-Blanco, E. (Efren), Loubet, B. (Benjamin), Loustau, D. (Denis), Lucas-Moffat, A. (Antje), Lueers, J. (Johannes), Ma, S. (Siyan), Macfarlane, C. (Craig), Magliulo, V. (Vincenzo), Maier, R. (Regine), Mammarella, I. (Ivan), Manca, G. (Giovanni), Marcolla, B. (Barbara), Margolis, H. A. (Hank A.), Marras, S. (Serena), Massman, W. (William), Mastepanov, M. (Mikhail), Matamala, R. (Roser), Matthes, J. H. (Jaclyn Hatala), Mazzenga, F. (Francesco), McCaughey, H. (Harry), McHugh, I. (Ian), McMillan, A. M. (Andrew M. S.), Merbold, L. (Lutz), Meyer, W. (Wayne), Meyers, T. (Tilden), Miller, S. D. (Scott D.), Minerbi, S. (Stefano), Moderow, U. (Uta), Monson, R. K. (Russell K.), Montagnani, L. (Leonardo), Moore, C. E. (Caitlin E.), Moors, E. (Eddy), Moreaux, V. (Virginie), Moureaux, C. (Christine), Munger, J. W. (J. William), Nakai, T. (Taro), Neirynck, J. (Johan), Nesic, Z. (Zoran), Nicolini, G. (Giacomo), Noormets, A. (Asko), Northwood, M. (Matthew), Nosetto, M. (Marcelo), Nouvellon, Y. (Yann), Novick, K. (Kimberly), Oechel, W. (Walter), Olesen, J. E. (Jorgen Eivind), Ourcival, J.-M. (Jean-Marc), Papuga, S. A. (Shirley A.), Parmentier, F.-J. (Frans-Jan), Paul-Limoges, E. (Eugenie), Pavelka, M. (Marian), Peichl, M. (Matthias), Pendall, E. (Elise), Phillips, R. P. (Richard P.), Pilegaard, K. (Kim), Pirk, N. (Norbert), Posse, G. (Gabriela), Powell, T. (Thomas), Prasse, H. (Heiko), Prober, S. M. (Suzanne M.), Rambal, S. (Serge), Rannik, U. (Ullar), Raz-Yaseef, N. (Naama), Reed, D. (David), de Dios, V. R. (Victor Resco), Restrepo-Coupe, N. (Natalia), Reverter, B. R. (Borja R.), Roland, M. (Marilyn), Sabbatini, S. (Simone), Sachs, T. (Torsten), Saleska, S. R. (Scott R.), Sanchez-Canete, E. P. (Enrique P.), Sanchez-Mejia, Z. M. (Zulia M.), Schmid, H. P. (Hans Peter), Schmidt, M. (Marius), Schneider, K. (Karl), Schrader, F. (Frederik), Schroder, I. (Ivan), Scott, R. L. (Russell L.), Sedlak, P. (Pavel), Serrano-Ortiz, P. (Penelope), Shao, C. (Changliang), Shi, P. (Peili), Shironya, I. (Ivan), Siebicke, L. (Lukas), Sigut, L. (Ladislav), Silberstein, R. (Richard), Sirca, C. (Costantino), Spano, D. (Donatella), Steinbrecher, R. (Rainer), Stevens, R. M. (Robert M.), Sturtevant, C. (Cove), Suyker, A. (Andy), Tagesson, T. (Torbern), Takanashi, S. (Satoru), Tang, Y. (Yanhong), Tapper, N. (Nigel), Thom, J. (Jonathan), Tiedemann, F. (Frank), Tomassucci, M. (Michele), Tuovinen, J.-P. (Juha-Pekka), Urbanski, S. (Shawn), Valentini, R. (Riccardo), van der Molen, M. (Michiel), van Gorsel, E. (Eva), van Huissteden, K. (Ko), Varlagin, A. (Andrej), Verfaillie, J. (Joseph), Vesala, T. (Timo), Vincke, C. (Caroline), Vitale, D. (Domenico), Vygodskaya, N. (Natalia), Walker, J. P. (Jeffrey P.), Walter-Shea, E. (Elizabeth), Wang, H. (Huimin), Weber, R. (Robin), Westermann, S. (Sebastian), Wille, C. (Christian), Wofsy, S. (Steven), Wohlfahrt, G. (Georg), Wolf, S. (Sebastian), Woodgate, W. (William), Li, Y. (Yuelin), Zampedri, R. (Roberto), Zhang, J. (Junhui), Zhou, G. (Guoyi), Zona, D. (Donatella), Agarwal, D. (Deb), Biraud, S. (Sebastien), Torn, M. (Margaret), and Papale, D. (Dario)
Abstract: The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.
Published: 2020

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

Author: Pastorello G, Trotta C, Canfora E, Chu H, Christianson D, Cheah Y-W, Poindexter C, Chen J, Elbashandy A, Humphrey M, Isaac P, Polidori D, Ribeca A, van Ingen C, Zhang L, Amiro B, Ammann C, Arain MA, Ardö J, Arkebauer T, Arndt SK, Arriga N, Aubinet M, Aurela M, Baldocchi D, Barr A, Beamesderfer E, Marchesini LB, Bergeron O, Beringer J, Bernhofer C, Berveiller D, Billesbach D, Black TA, Blanken PD, Bohrer G, Boike J, Bolstad PV, Bonal D, Bonnefond J-M, Bowling DR, Bracho R, Brodeur J, Brümmer C, Buchmann N, Burban B, Burns SP, Buysse P, Cale P, Cavagna M, Cellier P, Chen S, Chini I, Christensen TR, Cleverly J, Collalti A, Consalvo C, Cook BD, Cook D, Coursolle C, Cremonese E, Curtis PS, D'Andrea E, da Rocha H, Dai X, Davis KJ, De Cinti B, de Grandcourt A, De Ligne A, De Oliveira RC, Delpierre N, Desai AR, Di Bella CM, di Tommasi P, Dolman H, Domingo F, Dong G, Dore S, Duce P, Dufrêne E, Dunn A, Dušek J, Eamus D, Eichelmann U, ElKhidir HAM, Eugster W, Ewenz CM, Ewers B, Famulari D, Fares S, Feigenwinter I, Feitz A, Fensholt R, Filippa G, Fischer M, Frank J, Galvagno M, Gharun M, Gianelle D, Gielen B, Gioli B, Gitelson A, Goded I, Goeckede M, Goldstein AH, Gough CM, Goulden ML, Graf A, Griebel A, Gruening C, Grünwald T, Hammerle A, Han S, Han X, Hansen BU, Hanson C, Hatakka J, He Y, Hehn M, Heinesch B, Hinko-Najera N, Hörtnagl L, Hutley L, Ibrom A, Ikawa H, Jackowicz-Korczynski M, Janouš D, Jans W, Jassal R, Jiang S, Kato T, Khomik M, Klatt J, Knohl A, Knox S, Kobayashi H, Koerber G, Kolle O, Kosugi Y, Kotani A, Kowalski A, Kruijt B, Kurbatova J, Kutsch WL, Kwon H, Launiainen S, Laurila T, Law B, Leuning R, Li Y, Liddell M, Limousin J-M, Lion M, Liska AJ, Lohila A, López-Ballesteros A, López-Blanco E, Loubet B, Loustau D, Lucas-Moffat A, Lüers J, Ma S, Macfarlane C, Magliulo V, Maier R, Mammarella I, Manca G, Marcolla B, Margolis HA, Marras S, Massman W, Mastepanov M, Matamala R, Matthes JH, Mazzenga F, McCaughey H, McHugh I, McMillan AMS, Merbold L, Meyer W, Meyers T, Miller SD, Minerbi S, Moderow U, Monson RK, Montagnani L, Moore CE, Moors E, Moreaux V, Moureaux C, Munger JW, Nakai T, Neirynck J, Nesic Z, Nicolini G, Noormets A, Northwood M, Nosetto M, Nouvellon Y, Novick K, Oechel W, Olesen JE, Ourcival J-M, Papuga SA, Parmentier F-J, Paul-Limoges E, Pavelka M, Peichl M, Pendall E, Phillips RP, Pilegaard K, Pirk N, Posse G, Powell T, Prasse H, Prober SM, Rambal S, Rannik Ü, Raz-Yaseef N, Reed D, de Dios VR, Restrepo-Coupe N, Reverter BR, Roland M, Sabbatini S, Sachs T, Saleska SR, Sánchez-Cañete EP, Sanchez-Mejia ZM, Schmid HP, Schmidt M, Schneider K, Schrader F, Schroder I, Scott RL, Sedlák P, Serrano-Ortíz P, Shao C, Shi P, Shironya I, Siebicke L, Šigut L, Silberstein R, Sirca C, Spano D, Steinbrecher R, Stevens RM, Sturtevant C, Suyker A, Tagesson T, Takanashi S, Tang Y, Tapper N, Thom J, Tiedemann F, Tomassucci M, Tuovinen J-P, Urbanski S, Valentini R, van der Molen M, van Gorsel E, van Huissteden K, Varlagin A, Verfaillie J, Vesala T, Vincke C, Vitale D, Vygodskaya N, Walker JP, Walter-Shea E, Wang H, Weber R, Westermann S, Wille C, Wofsy S, Wohlfahrt G, Wolf S, Woodgate W, Zampedri R, Zhang J, Zhou G, Zona D, Agarwal D, Biraud S, Torn M, Papale D, Pastorello G, Trotta C, Canfora E, Chu H, Christianson D, Cheah Y-W, Poindexter C, Chen J, Elbashandy A, Humphrey M, Isaac P, Polidori D, Ribeca A, van Ingen C, Zhang L, Amiro B, Ammann C, Arain MA, Ardö J, Arkebauer T, Arndt SK, Arriga N, Aubinet M, Aurela M, Baldocchi D, Barr A, Beamesderfer E, Marchesini LB, Bergeron O, Beringer J, Bernhofer C, Berveiller D, Billesbach D, Black TA, Blanken PD, Bohrer G, Boike J, Bolstad PV, Bonal D, Bonnefond J-M, Bowling DR, Bracho R, Brodeur J, Brümmer C, Buchmann N, Burban B, Burns SP, Buysse P, Cale P, Cavagna M, Cellier P, Chen S, Chini I, Christensen TR, Cleverly J, Collalti A, Consalvo C, Cook BD, Cook D, Coursolle C, Cremonese E, Curtis PS, D'Andrea E, da Rocha H, Dai X, Davis KJ, De Cinti B, de Grandcourt A, De Ligne A, De Oliveira RC, Delpierre N, Desai AR, Di Bella CM, di Tommasi P, Dolman H, Domingo F, Dong G, Dore S, Duce P, Dufrêne E, Dunn A, Dušek J, Eamus D, Eichelmann U, ElKhidir HAM, Eugster W, Ewenz CM, Ewers B, Famulari D, Fares S, Feigenwinter I, Feitz A, Fensholt R, Filippa G, Fischer M, Frank J, Galvagno M, Gharun M, Gianelle D, Gielen B, Gioli B, Gitelson A, Goded I, Goeckede M, Goldstein AH, Gough CM, Goulden ML, Graf A, Griebel A, Gruening C, Grünwald T, Hammerle A, Han S, Han X, Hansen BU, Hanson C, Hatakka J, He Y, Hehn M, Heinesch B, Hinko-Najera N, Hörtnagl L, Hutley L, Ibrom A, Ikawa H, Jackowicz-Korczynski M, Janouš D, Jans W, Jassal R, Jiang S, Kato T, Khomik M, Klatt J, Knohl A, Knox S, Kobayashi H, Koerber G, Kolle O, Kosugi Y, Kotani A, Kowalski A, Kruijt B, Kurbatova J, Kutsch WL, Kwon H, Launiainen S, Laurila T, Law B, Leuning R, Li Y, Liddell M, Limousin J-M, Lion M, Liska AJ, Lohila A, López-Ballesteros A, López-Blanco E, Loubet B, Loustau D, Lucas-Moffat A, Lüers J, Ma S, Macfarlane C, Magliulo V, Maier R, Mammarella I, Manca G, Marcolla B, Margolis HA, Marras S, Massman W, Mastepanov M, Matamala R, Matthes JH, Mazzenga F, McCaughey H, McHugh I, McMillan AMS, Merbold L, Meyer W, Meyers T, Miller SD, Minerbi S, Moderow U, Monson RK, Montagnani L, Moore CE, Moors E, Moreaux V, Moureaux C, Munger JW, Nakai T, Neirynck J, Nesic Z, Nicolini G, Noormets A, Northwood M, Nosetto M, Nouvellon Y, Novick K, Oechel W, Olesen JE, Ourcival J-M, Papuga SA, Parmentier F-J, Paul-Limoges E, Pavelka M, Peichl M, Pendall E, Phillips RP, Pilegaard K, Pirk N, Posse G, Powell T, Prasse H, Prober SM, Rambal S, Rannik Ü, Raz-Yaseef N, Reed D, de Dios VR, Restrepo-Coupe N, Reverter BR, Roland M, Sabbatini S, Sachs T, Saleska SR, Sánchez-Cañete EP, Sanchez-Mejia ZM, Schmid HP, Schmidt M, Schneider K, Schrader F, Schroder I, Scott RL, Sedlák P, Serrano-Ortíz P, Shao C, Shi P, Shironya I, Siebicke L, Šigut L, Silberstein R, Sirca C, Spano D, Steinbrecher R, Stevens RM, Sturtevant C, Suyker A, Tagesson T, Takanashi S, Tang Y, Tapper N, Thom J, Tiedemann F, Tomassucci M, Tuovinen J-P, Urbanski S, Valentini R, van der Molen M, van Gorsel E, van Huissteden K, Varlagin A, Verfaillie J, Vesala T, Vincke C, Vitale D, Vygodskaya N, Walker JP, Walter-Shea E, Wang H, Weber R, Westermann S, Wille C, Wofsy S, Wohlfahrt G, Wolf S, Woodgate W, Zampedri R, Zhang J, Zhou G, Zona D, Agarwal D, Biraud S, Torn M, and Papale D
Abstract: The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.
Published: 2020

25. Multiple Ecosystem Effects of Extreme Weather Events in the Arctic

Author: Christensen, T. R., primary, Lund, M., additional, Skov, K., additional, Abermann, J., additional, López-Blanco, E., additional, Scheller, J., additional, Scheel, M., additional, Jackowicz-Korczynski, M., additional, Langley, K., additional, Murphy, M. J., additional, and Mastepanov, M., additional
Published: 2020
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26. A New Process-Based Soil Methane Scheme:Evaluation Over Arctic Field Sites With the ISBA Land Surface Model

Author: Morel, X., Decharme, B., Delire, C., Krinner, G., Lund, M., Hansen, B. U., Mastepanov, M., Morel, X., Decharme, B., Delire, C., Krinner, G., Lund, M., Hansen, B. U., and Mastepanov, M.
Abstract: Permafrost soils and arctic wetlands methane emissions represent an important challenge for modeling the future climate. Here we present a process-based model designed to correctly represent the main thermal, hydrological, and biogeochemical processes related to these emissions for general land surface modeling. We propose a new multilayer soil carbon and gas module within the Interaction Soil-Biosphere-Atmosphere (ISBA) land-surface model (LSM). This module represents carbon pools, vertical carbon dynamics, and both oxic and anoxic organic matter decomposition. It also represents the soil gas processes for CH4, CO2, and O2 through the soil column. We base CH4 production and oxydation on an O2 control instead of the classical water table level strata approach used in state-of-the-art soil CH4 models. We propose a new parametrization of CH4 oxydation using recent field experiments and use an explicit O2 limitation for soil carbon decomposition. Soil gas transport is computed explicitly, using a revisited formulation of plant-mediated transport, a new representation of gas bulk diffusivity in porous media closer to experimental observations, and an innovative advection term for ebullition. We evaluate this advanced model on three climatically distinct sites : two in Greenland (Nuuk and Zackenberg) and one in Siberia (Chokurdakh). The model realistically reproduces methane and carbon dioxide emissions from both permafrosted and nonpermafrosted sites. The evolution and vertical characteristics of the underground processes leading to these fluxes are consistent with current knowledge. Results also show that physics is the main driver of methane fluxes, and the main source of variability appears to be the water table depth.
Published: 2019

27. A New Process‐Based Soil Methane Scheme: Evaluation Over Arctic Field Sites With the ISBA Land Surface Model

Author: Morel, X., primary, Decharme, B., additional, Delire, C., additional, Krinner, G., additional, Lund, M., additional, Hansen, B. U., additional, and Mastepanov, M., additional
Published: 2019
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28. Spatial variability of CO2 uptake in polygonal tundra: assessing low-frequency disturbances in eddy covariance flux estimates

Author: Pirk, N., Sievers, J., Mertes, J., Parmentier, F.-J. W., Mastepanov, M., and Christensen, T. R.
Subjects: lcsh:Geology, lcsh:QH501-531, lcsh:QH540-549.5, lcsh:QE1-996.5, lcsh:Life, lcsh:Ecology
Abstract: The large spatial variability in Arctic tundra complicates the representative assessment of CO2 budgets. Accurate measurements of these heterogeneous landscapes are, however, essential to understanding their vulnerability to climate change. We surveyed a polygonal tundra lowland on Svalbard with an unmanned aerial vehicle (UAV) that mapped ice-wedge morphology to complement eddy covariance (EC) flux measurements of CO2. The analysis of spectral distributions showed that conventional EC methods do not accurately capture the turbulent CO2 exchange with a spatially heterogeneous surface that typically features small flux magnitudes. Nonlocal (low-frequency) flux contributions were especially pronounced during snowmelt and introduced a large bias of −46 gC m−2 to the annual CO2 budget in conventional methods (the minus sign indicates a higher uptake by the ecosystem). Our improved flux calculations with the ogive optimization method indicated that the site was a strong sink for CO2 in 2015 (−82 gC m−2). Due to differences in light-use efficiency, wetter areas with low-centered polygons sequestered 47 % more CO2 than drier areas with flat-centered polygons. While Svalbard has experienced a strong increase in mean annual air temperature of more than 2 K in the last few decades, historical aerial photographs from the site indicated stable ice-wedge morphology over the last 7 decades. Apparently, warming has thus far not been sufficient to initiate strong ice-wedge degradation, possibly due to the absence of extreme heat episodes in the maritime climate on Svalbard. However, in Arctic regions where ice-wedge degradation has already initiated the associated drying of landscapes, our results suggest a weakening of the CO2 sink in polygonal tundra.
Published: 2017

29. Reducing Uncertainty in Methane Emission Estimates from Permafrost Environments

Author: Christensen, TR, Mastepanov, M, Lund, M, Tamstorf, MP, Parmentier, FJW, Rysgård, S, and Lilienthal, AJ
Published: 2014

30. Effects of interannual variability in snow accumulation on energy partitioning and surface energy exchange in a high-Arctic tundra ecosystem

Author: Stiegler, C., primary, Lund, M., additional, Christensen, T. R., additional, Mastepanov, M., additional, and Lindroth, A., additional
Published: 2016
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31. Late season CH4 and CO2 emissions in North-Eastern Greenland: a missing link in Arctic greenhouse gas exchange?

Author: Mastepanov, M., Christensen, T.R., Sigsgaard, C., Tamstorf, Mikkel Peter, Ström, L., Tagesson, T., and Lund, Carl Magnus
Published: 2011

32. Calculations of automatic chamber flux measurements of methane and carbon dioxide using short time series of concentrations

Author: Pirk, N., primary, Mastepanov, M., additional, Parmentier, F.-J. W., additional, Lund, M., additional, Crill, P., additional, and Christensen, T. R., additional
Published: 2015
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33. Supplementary material to "Calculations of automatic chamber flux measurements of methane and carbon dioxide using short time series of concentrations"

Author: Pirk, N., primary, Mastepanov, M., additional, Parmentier, F.-J. W., additional, Lund, M., additional, Crill, P., additional, and Christensen, T. R., additional
Published: 2015
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34. Increased Gross Primary Production in a Greenlandic High Arctic Fen Area 1992-2008

Author: Tagesson, T., Ström, L., Mastepanov, M., Tamstorf, Mikkel Peter, and Eklundh, L.
Published: 2010

35. Tundra Methane Burst During Onset of Freezing: Following the IPY Finding

Author: Mastepanov, M., Sigsgaard, Charlotte, Tagesson, T., Strom, L., Tamstorf, Mikkel Peter, and Christensen, T.R.
Published: 2010

36. Seasonal Variation in CH4 Fluxes from a Greenlandic High Arctic Fen

Author: Tagesson, T., Mölder, M., Mastepanov, M., Pirk, N., Lindroth, A., Christensen, T.R., Ström, L., Sigsgaard, Charlotte, Tamstorf, Mikkel Peter, Falk, J.M., and Lund, M.
Published: 2010

37. CO2 and CH4 balances for several high arctic vegetation types

Author: Tagesson, T, Ström, L, Mastepanov, M, Tamstorf, M, Eklundh, L, and Christensen, TR
Published: 2008

38. Zackenberg Basic: The Climate Basis and GeoBasis programmes

Author: Sigsgaard, C., Thorsøe, K., Fugl, A. W., Mastepanov, M., Friborg, T., Tamstorf, M. P., Hansen, B. U., Ström, L., Christensen, T. R., Klitgaard, A. B., Rasch, M., and Caning, K.
Published: 2007

39. Revisiting factors controlling methane emissions from high-Arctic tundra

Author: Mastepanov, M., Sigsgaard, Charlotte, Tagesson, Håkan Torbern, Ström, L., Tamstorf, Mikkel P., Lund, Magnus, Christensen, T.R., Mastepanov, M., Sigsgaard, Charlotte, Tagesson, Håkan Torbern, Ström, L., Tamstorf, Mikkel P., Lund, Magnus, and Christensen, T.R.
Abstract: The northern latitudes are experiencing disproportionate warming relative to the mid-latitudes, and there is growing concern about feedbacks between this warming and methane production and release from high-latitude soils. Studies of methane emissions carried out in the Arctic, particularly those with measurements made outside the growing season, are underrepresented in the literature. Here we present results of 5 yr (2006-2010) of automatic chamber measurements at a high-Arctic location in Zackenberg, NE Greenland, covering both the growing seasons and two months of the following freeze-in periods. The measurements show clear seasonal dynamics in methane emission. The start of the growing season and the increase in CH4 fluxes were strongly related to the date of snowmelt. Within each particular growing season, CH4 fluxes were highly correlated with the soil temperature (R-2 > 0.75), which is probably explained by high seasonality of both variables, and weakly correlated with the water table. The greatest variability in fluxes between the study years was observed during the first part of the growing season. Somewhat surprisingly, this variability could not be explained by commonly known factors controlling methane emission, i.e. temperature and water table position. Late in the growing season CH4 emissions were found to be very similar between the study years (except the extremely dry 2010) despite large differences in climatic factors (temperature and water table). Late-season bursts of CH4 coinciding with soil freezing in the autumn were observed during at least three years. The cumulative emission during the freeze-in CH4 bursts was comparable in size with the growing season emission for the year 2007, and about one third of the growing season emissions for the years 2009 and 2010. In all three cases the CH4 burst was accompanied by a corresponding episodic increase in CO2 emission, which can compose a significant contribution to the annual CO2 flux budget. Th
Published: 2013

40. BVOC ecosystem flux measurements at a high latitude wetland site

Author: Holst, T., Arneth, A., Hayward, S., Ekberg, A., Mastepanov, M., Jackowicz-Korczynski, M., Friborg, T., Crill, Patrick M., Bäckstrand, Kristina, Holst, T., Arneth, A., Hayward, S., Ekberg, A., Mastepanov, M., Jackowicz-Korczynski, M., Friborg, T., Crill, Patrick M., and Bäckstrand, Kristina
Abstract: In this study, we present summertime concentrations and fluxes of biogenic volatile organic compounds (BVOCs) measured at a sub-arctic wetland in northern Sweden using a disjunct eddy-covariance (DEC) technique based on a proton transfer reaction mass spectrometer (PTR-MS). The vegetation at the site was dominated by Sphagnum, Carex and Eriophorum spp. The measurements reported here cover a period of 50 days (1 August to 19 September 2006), approximately one half of the growing season at the site, and allowed to investigate the effect of day-to-day variation in weather as well as of vegetation senescence on daily BVOC fluxes, and on their temperature and light responses. The sensitivity drift of the DEC system was assessed by comparing H3O+-ion cluster formed with water molecules (H3O+(H2O) at m37) with water vapour concentration measurements made using an adjacent humidity sensor, and the applicability of the DEC method was analysed by a comparison of sensible heat fluxes for high frequency and DEC data obtained from the sonic anemometer. These analyses showed no significant PTR-MS sensor drift over a period of several weeks and only a small flux-loss due to high-frequency spectrum omissions. This loss was within the range expected from other studies and the theoretical considerations. Standardised (20 degrees C and 1000 mu mol m(-2) s(-1) PAR) summer isoprene emission rates found in this study of 329 mu g Cm-2 (ground area) h(-1) were comparable with findings from more southern boreal forests, and fen-like ecosystems. On a diel scale, measured fluxes indicated a stronger temperature dependence than emissions from temperate or (sub) tropical ecosystems. For the first time, to our knowledge, we report ecosystem methanol fluxes from a sub-arctic ecosystem. Maximum daytime emission fluxes were around 270 mu g m(-2) h(-1) (ca. 100 mu g Cm-2 h(-1)), and during most nights small negative fluxes directed from the atmosphere to the surface were observed., authorCount :9
Published: 2010

41. Annual carbon gas budget for a subarctic peatland, northern Sweden

Author: Bäckstrand, Kristina, Crill, P. M., Jackowicz-Korczyñski, M., Mastepanov, M., Christensen, T. R., Bastviken, David, Bäckstrand, Kristina, Crill, P. M., Jackowicz-Korczyñski, M., Mastepanov, M., Christensen, T. R., and Bastviken, David
Abstract: Temperatures in the Arctic regions are rising, thawing permafrost and exposing previously stable soil organic carbon (OC) to decomposition. This can result in northern latitude soils, which have accumulated large amounts of OC potentially shifting from atmospheric C sinks to C sources with positive feedback on climate warming. In this paper, we estimate the annual net C gas balance (NCB) of the subarctic mire Stordalen, based on automatic chamber measurements of CO2 and total hydrocarbon (THC; CH4 and NMVOCs) exchange. We studied the dominant vegetation communities with different moisture and permafrost characteristics; a dry Palsa underlain by permafrost, an intermediate thaw site with Sphagnum spp. and a wet site with Eriophorum spp. where the soil thaws completely. Whole year accumulated fluxes of CO2 were estimated to 29.7, −35.3 and −34.9 gC m−2 respectively for the Palsa, Sphagnum and Eriophorum sites (positive flux indicates an addition of C to the atmospheric pool). The corresponding annual THC emissions were 0.5, 6.2 and 31.8 gC m−2 for the same sites. Therefore, the NCB for each of the sites was 30.2, −29.1 and −3.1 gC m−2 respectively for the Palsa, Sphagnum and Eriophorum site. On average, the whole mire was a CO2 sink of 2.6 gC m−2 and a THC source of 6.4 gC m−2 over a year. Consequently, the mire was a net source of C to the atmosphere by 3.9 gC m−2 (based on area weighted estimates for each of the three plant communities). Early and late snow season efflux of CO2 and THC emphasize the importance of winter measurements for complete annual C budgets. Decadal vegetation changes at Stordalen indicate that both the productivity and the THC emissions increased between 1970 and 2000. Considering the GWP100 of CH4, the net radiative forcing on climate increased 21% over the same time. In conclusion, reduced C compounds in these environments have high importance for both the annual C balance and climate.
Published: 2010
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42. A catchment scale process study of carbon and greenhouse gas exchange in a subarctic landscape.

Author: Christensen, T.R., Johansson, T.J., Olsrud, M., Ström, L., Lindroth, A., Mastepanov, M, Malmer, N., Friborg, T., Crill, Patrick, Callaghan, T., Christensen, T.R., Johansson, T.J., Olsrud, M., Ström, L., Lindroth, A., Mastepanov, M, Malmer, N., Friborg, T., Crill, Patrick, and Callaghan, T.
Published: 2009

43. Annual cycles of methane emission from a subarctic peatland

Author: Jackowicz-Korczyňski, M., Christensen, T. R., Bäckstrand, K., Crill, P. M., Friborg, T., Mastepanov, M., Ström, L., Jackowicz-Korczyňski, M., Christensen, T. R., Bäckstrand, K., Crill, P. M., Friborg, T., Mastepanov, M., and Ström, L.
Abstract: Although much attention in recent years has been devoted to methane (CH4) emissions from northern wetlands, measurement based datasets providing full annual budgets are still limited in number. This study was designed to help fill the gap of year-round measurements of CH4 emissions from subarctic mires. We report continuous eddy correlation CH 4 flux measurements made during 2006 and 2007 over the Stordalen mire in subarctic Sweden (68°20'N, 19°03'E, alt. 351 m) using a cryocooled tunable diode laser (TDL). The landscape scale CH4 fluxes originated mainly from the permafrost free wet parts of the mire dominated by tall graminoid vegetation. The midseason average CH4 emission mean was 6.2±2.6 mg m-2 h-1. A detailed footprint analysis indicates an additional strong influence on the flux by the nearby the shallow Lake Villasjön (0.17 km2, max depth 1.3 m). A stable bimodal distribution of wind flow from either the easier or the west allowed separating the lake and mire vegetation signals. The midseason lake emission rates were as high as 12.3±3.3 mg m-2 h-1. Fluxes from a homogeneous area dominated by Eriophorum augustifolium agree well with automatic chamber measurements located in similar vegetation in the wet minerotrophic parts of the peatland. The high fluxes observed from this vegetation type are significant because the areal distribution of this source in the mire is expanding due to ongoing thawing of the permafrost. A simple peat temperature relationship with CH4 emissions was used to fill data gaps to construct a complete annual budget of CH4 fluxes over the studied area. The calculated annual CH4 emissions in 2006 and 2007 equaled 24.5 and 29.5 g CH4 m-2 y-1 respectively. These are considerably higher annual sums than what has earlier been estimated for this mire based on manual cha
Published: 2009

44. Correction for Johnson et al., Ancient bacteria show evidence of DNA repair

Author: Johnson, S.S., Hebsgaard, M.B., Christensen, T.R., Mastepanov, M., Nielsen, R., Munch, K., Brand, T., Gilbert, M.T.P., Zuber, M.T., Bunce, M., Ronn, R., Gilichinsky, D., Froese, D., Willerslev, E., Johnson, S.S., Hebsgaard, M.B., Christensen, T.R., Mastepanov, M., Nielsen, R., Munch, K., Brand, T., Gilbert, M.T.P., Zuber, M.T., Bunce, M., Ronn, R., Gilichinsky, D., Froese, D., and Willerslev, E.
Abstract: No Abstract Available
Published: 2008

45. A catchment scale process study of carbon and greenhouse gas exchange in a subarctic landscape

Author: Christensen, T. R., Johansson, Paul Torbjörn, Olsrud, M., Ström, L., Lindroth, A., Mastepanov, M., Malmer, N., Friborg, Thomas, Crill, P. M., Callaghan, T. V., Christensen, T. R., Johansson, Paul Torbjörn, Olsrud, M., Ström, L., Lindroth, A., Mastepanov, M., Malmer, N., Friborg, Thomas, Crill, P. M., and Callaghan, T. V.
Published: 2008

46. Total hydrocarbon flux dynamics at a subarctic mire in northern Sweden

Author: Backstrand, K., Crill, P. M., Mastepanov, M., Christensen, T. R., Bastviken, D., Backstrand, K., Crill, P. M., Mastepanov, M., Christensen, T. R., and Bastviken, D.
Abstract: This is a study of the spatial and temporal variability of total hydrocarbon (THC) emissions from vegetation and soil at a subarctic mire, northern Sweden. THCs include methane (CH4) and nonmethane volatile organic compounds (NMVOCs), both of which are atmospherically important trace gases and constitute a significant proportion of the carbon exchange between biosphere and atmosphere. Reliable characterization of the magnitude and the dynamics of the THC fluxes from high latitude peatlands are important when considering to what extent trace gas emissions from such ecosystems may change and feed back on climate regulation as a result of warmer climate and melting permafrost. High frequency measurements of THC and carbon dioxide (CO2) were conducted during four sequential growing seasons in three localities representing the trophic range of plant communities at the mire. The magnitude of the THC flux followed the moisture gradient with increasing emissions from a dry Palsa site (2.2 +/- 0.1 mgC m(-2) d(-1)), to a wet intermediate melt feature with Sphagnum spp. (28 +/- 0.3 mgC m(-2) d(-1)) and highest emissions from a wet Eriophorum spp. site (122 +/- 1.4 mgC m(-2) d(-1)) (overall mean +/- 1 SE, n = 2254, 2231 and 2137). At the Palsa site, daytime THC flux was most strongly related to air temperature while daytime THC emissions at the Sphagnum site had a stronger relation to ground temperature. THC emissions at both the wet sites were correlated to net ecosystem exchange of CO2. An overall spatial correlation indicated that areas with highly productive vegetation communities also had high THC emission potential., Baeckstrand, Kristina Crill, Patrick M. Mastepanov, Mikhail Christensen, Torben R. Bastviken, David
Published: 2008
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47. Non-methane volatile organic compound flux from a subarctic mire in Northern Sweden

Author: Backstrand, K., Crill, P. M., Mastepanov, M., Christensen, T. R., Bastviken, D., Backstrand, K., Crill, P. M., Mastepanov, M., Christensen, T. R., and Bastviken, D.
Abstract: Biogenic NMVOCs are mainly formed by plants and microorganisms. They have strong impact on the local atmospheric chemistry when emitted to the atmosphere. The objective of this study was to determine if there are significant emissions of non-methane volatile organic compounds (NMVOCs) from a subarctic mire in northern Sweden. Subarctic peatlands in discontinuous permafrost regions are undergoing substantial environmental changes due to their high sensitivity to climate warming and there is need for including NMVOCs in the overall carbon budget. Automatic and manual chamber measurements were used to estimate NMVOC fluxes from three dominating subhabitats on the mire during three growing seasons. Emission rates varied and were related to plant species distribution and seasonal net ecosystem exchange of carbon dioxide. The highest fluxes were observed from wetter sites dominated by Eriophorum and Sphagnum spp. Total NMVOC emissions from the mire (similar to 17 ha) is estimated to consist of similar to 150 kgC during a growing season with 150 d. NMVOC fluxes can account for similar to 5% of total net carbon exchange (-3177 kgC) at the mire during the same period. NMVOC emissions are therefore a significant component in a local carbon budget for peatlands., Backstrand, Kristina Crill, Patrick M. Mastepanov, Mikhail Christensen, Torben R. Bastviken, David
Published: 2008
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48. Revisiting factors controlling methane emissions from high-Arctic tundra

Author: Mastepanov, M., primary, Sigsgaard, C., additional, Tagesson, T., additional, Ström, L., additional, Tamstorf, M. P., additional, Lund, M., additional, and Christensen, T. R., additional
Published: 2013
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49. A catchment scale carbon and greenhouse gas budget of a subarctic landscape

Author: Christensen, T, Johansson, T, Olsrud, M, Ström, L, Lindroth, A, Mastepanov, M, Malmer, N, Friborg, T, Crill, P, Callaghan, T, Christensen, T, Johansson, T, Olsrud, M, Ström, L, Lindroth, A, Mastepanov, M, Malmer, N, Friborg, T, Crill, P, and Callaghan, T
Published: 2007

50. Correction for Johnson et al., Ancient bacteria show evidence of DNA repair

Author: Johnson, S.S., Hebsgaard, M.B., Christensen, T.R., Mastepanov, M., Nielsen, R., Munch, K., Brand, T., Gilbert, M.T.P., Zuber, M.T., Bunce, M., Ronn, R., Gilichinsky, D., Froese, D., Willerslev, E., Johnson, S.S., Hebsgaard, M.B., Christensen, T.R., Mastepanov, M., Nielsen, R., Munch, K., Brand, T., Gilbert, M.T.P., Zuber, M.T., Bunce, M., Ronn, R., Gilichinsky, D., Froese, D., and Willerslev, E.
Abstract: No Abstract Available
Published: 2007

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