Author: "OECHEL, WALTER C." / Database: OAIster - Searchworks@Jio Institute Digital Library Search Results

Your search keyword '"OECHEL, WALTER C."' showing total 64 results

Start Over Author "OECHEL, WALTER C." Database OAIster

64 results on '"OECHEL, WALTER C."'

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

Author: Zona, Donatella, Lafleur, Peter M., Hufkens, Koen, Bailey, Barbara, Gioli, Beniamino, Burba, George, Goodrich, Jordan P., Liljedahl, Anna K., Euskirchen, Eugénie S., Watts, Jennifer D., Farina, Mary, Kimball, John S., Heimann, Martin, Göckede, Mathias, Pallandt, Martijn, Christensen, Torben R., Mastepanov, Mikhail, López-Blanco, Efrén, Jackowicz-Korczynski, Marcin, Dolman, Albertus J., Marchesini, Luca Belelli, Commane, Roisin, Wofsy, Steven C., Miller, Charles E., Lipson, David A., Hashemi, Josh, Arndt, Kyle A., Kutzbach, Lars, Holl, David, Boike, Julia, Wille, Christian, Sachs, Torsten, Kalhori, Aram, Song, Xia, Xu, Xiaofeng, Humphreys, Elyn R., Koven, Charles D., Sonnentag, Oliver, Meyer, Gesa, Gosselin, Gabriel H., Marsh, Philip, Oechel, Walter C., Zona, Donatella, Lafleur, Peter M., Hufkens, Koen, Bailey, Barbara, Gioli, Beniamino, Burba, George, Goodrich, Jordan P., Liljedahl, Anna K., Euskirchen, Eugénie S., Watts, Jennifer D., Farina, Mary, Kimball, John S., Heimann, Martin, Göckede, Mathias, Pallandt, Martijn, Christensen, Torben R., Mastepanov, Mikhail, López-Blanco, Efrén, Jackowicz-Korczynski, Marcin, Dolman, Albertus J., Marchesini, Luca Belelli, Commane, Roisin, Wofsy, Steven C., Miller, Charles E., Lipson, David A., Hashemi, Josh, Arndt, Kyle A., Kutzbach, Lars, Holl, David, Boike, Julia, Wille, Christian, Sachs, Torsten, Kalhori, Aram, Song, Xia, Xu, Xiaofeng, Humphreys, Elyn R., Koven, Charles D., Sonnentag, Oliver, Meyer, Gesa, Gosselin, Gabriel H., Marsh, Philip, and Oechel, 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

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

Author: Zona, Donatella, Zona, Donatella, Lafleur, Peter M, Hufkens, Koen, Bailey, Barbara, Gioli, Beniamino, Burba, George, Goodrich, Jordan P, Liljedahl, Anna K, Euskirchen, Eugénie S, Watts, Jennifer D, Farina, Mary, Kimball, John S, Heimann, Martin, Göckede, Mathias, Pallandt, Martijn, Christensen, Torben R, Mastepanov, Mikhail, López-Blanco, Efrén, Jackowicz-Korczynski, Marcin, Dolman, Albertus J, Marchesini, Luca Belelli, Commane, Roisin, Wofsy, Steven C, Miller, Charles E, Lipson, David A, Hashemi, Josh, Arndt, Kyle A, Kutzbach, Lars, Holl, David, Boike, Julia, Wille, Christian, Sachs, Torsten, Kalhori, Aram, Song, Xia, Xu, Xiaofeng, Humphreys, Elyn R, Koven, Charles D, Sonnentag, Oliver, Meyer, Gesa, Gosselin, Gabriel H, Marsh, Philip, Oechel, Walter C, Zona, Donatella, Zona, Donatella, Lafleur, Peter M, Hufkens, Koen, Bailey, Barbara, Gioli, Beniamino, Burba, George, Goodrich, Jordan P, Liljedahl, Anna K, Euskirchen, Eugénie S, Watts, Jennifer D, Farina, Mary, Kimball, John S, Heimann, Martin, Göckede, Mathias, Pallandt, Martijn, Christensen, Torben R, Mastepanov, Mikhail, López-Blanco, Efrén, Jackowicz-Korczynski, Marcin, Dolman, Albertus J, Marchesini, Luca Belelli, Commane, Roisin, Wofsy, Steven C, Miller, Charles E, Lipson, David A, Hashemi, Josh, Arndt, Kyle A, Kutzbach, Lars, Holl, David, Boike, Julia, Wille, Christian, Sachs, Torsten, Kalhori, Aram, Song, Xia, Xu, Xiaofeng, Humphreys, Elyn R, Koven, Charles D, Sonnentag, Oliver, Meyer, Gesa, Gosselin, Gabriel H, Marsh, Philip, and Oechel, 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

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

Author: Zona, Donatella, Zona, Donatella, Lafleur, Peter M, Hufkens, Koen, Bailey, Barbara, Gioli, Beniamino, Burba, George, Goodrich, Jordan P, Liljedahl, Anna K, Euskirchen, Eugénie S, Watts, Jennifer D, Farina, Mary, Kimball, John S, Heimann, Martin, Göckede, Mathias, Pallandt, Martijn, Christensen, Torben R, Mastepanov, Mikhail, López-Blanco, Efrén, Jackowicz-Korczynski, Marcin, Dolman, Albertus J, Marchesini, Luca Belelli, Commane, Roisin, Wofsy, Steven C, Miller, Charles E, Lipson, David A, Hashemi, Josh, Arndt, Kyle A, Kutzbach, Lars, Holl, David, Boike, Julia, Wille, Christian, Sachs, Torsten, Kalhori, Aram, Song, Xia, Xu, Xiaofeng, Humphreys, Elyn R, Koven, Charles D, Sonnentag, Oliver, Meyer, Gesa, Gosselin, Gabriel H, Marsh, Philip, Oechel, Walter C, Zona, Donatella, Zona, Donatella, Lafleur, Peter M, Hufkens, Koen, Bailey, Barbara, Gioli, Beniamino, Burba, George, Goodrich, Jordan P, Liljedahl, Anna K, Euskirchen, Eugénie S, Watts, Jennifer D, Farina, Mary, Kimball, John S, Heimann, Martin, Göckede, Mathias, Pallandt, Martijn, Christensen, Torben R, Mastepanov, Mikhail, López-Blanco, Efrén, Jackowicz-Korczynski, Marcin, Dolman, Albertus J, Marchesini, Luca Belelli, Commane, Roisin, Wofsy, Steven C, Miller, Charles E, Lipson, David A, Hashemi, Josh, Arndt, Kyle A, Kutzbach, Lars, Holl, David, Boike, Julia, Wille, Christian, Sachs, Torsten, Kalhori, Aram, Song, Xia, Xu, Xiaofeng, Humphreys, Elyn R, Koven, Charles D, Sonnentag, Oliver, Meyer, Gesa, Gosselin, Gabriel H, Marsh, Philip, and Oechel, 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

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

Author: Zona, Donatella, Lafleur, Peter M., Hufkens, Koen, Bailey, Barbara, Gioli, Beniamino, Burba, George, Goodrich, Jordan P., Liljedahl, Anna K., Euskirchen, Eugénie S., Watts, Jennifer D., Farina, Mary, Kimball, John S., Heimann, Martin, Göckede, Mathias, Pallandt, Martijn, Christensen, Torben R., Mastepanov, Mikhail, López-Blanco, Efrén, Jackowicz-Korczynski, Marcin, Dolman, Albertus J., Marchesini, Luca Belelli, Commane, Roisin, Wofsy, Steven C., Miller, Charles E., Lipson, David A., Hashemi, Josh, Arndt, Kyle A., Kutzbach, Lars, Holl, David, Boike, Julia, Wille, Christian, Sachs, Torsten, Kalhori, Aram, Song, Xia, Xu, Xiaofeng, Humphreys, Elyn R., Koven, Charles D., Sonnentag, Oliver, Meyer, Gesa, Gosselin, Gabriel H., Marsh, Philip, Oechel, Walter C., Zona, Donatella, Lafleur, Peter M., Hufkens, Koen, Bailey, Barbara, Gioli, Beniamino, Burba, George, Goodrich, Jordan P., Liljedahl, Anna K., Euskirchen, Eugénie S., Watts, Jennifer D., Farina, Mary, Kimball, John S., Heimann, Martin, Göckede, Mathias, Pallandt, Martijn, Christensen, Torben R., Mastepanov, Mikhail, López-Blanco, Efrén, Jackowicz-Korczynski, Marcin, Dolman, Albertus J., Marchesini, Luca Belelli, Commane, Roisin, Wofsy, Steven C., Miller, Charles E., Lipson, David A., Hashemi, Josh, Arndt, Kyle A., Kutzbach, Lars, Holl, David, Boike, Julia, Wille, Christian, Sachs, Torsten, Kalhori, Aram, Song, Xia, Xu, Xiaofeng, Humphreys, Elyn R., Koven, Charles D., Sonnentag, Oliver, Meyer, Gesa, Gosselin, Gabriel H., Marsh, Philip, and Oechel, 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

5. Using atmospheric observations to quantify annual biogenic carbon dioxide fluxes on the Alaska North Slope

Author: Schiferl, Luke D, Schiferl, Luke D, Watts, Jennifer D, Larson, Erik JL, Arndt, Kyle A, Biraud, Sébastien C, Euskirchen, Eugénie S, Goodrich, Jordan P, Henderson, John M, Kalhori, Aram, McKain, Kathryn, Mountain, Marikate E, Munger, J William, Oechel, Walter C, Sweeney, Colm, Yi, Yonghong, Zona, Donatella, Commane, Róisín, Schiferl, Luke D, Schiferl, Luke D, Watts, Jennifer D, Larson, Erik JL, Arndt, Kyle A, Biraud, Sébastien C, Euskirchen, Eugénie S, Goodrich, Jordan P, Henderson, John M, Kalhori, Aram, McKain, Kathryn, Mountain, Marikate E, Munger, J William, Oechel, Walter C, Sweeney, Colm, Yi, Yonghong, Zona, Donatella, and Commane, Róisín
Abstract: The continued warming of the Arctic could release vast stores of carbon into the atmosphere from high-latitude ecosystems, especially from thawing permafrost. Increasing uptake of carbon dioxide (CO2) by vegetation during longer growing seasons may partially offset such release of carbon. However, evidence of significant net annual release of carbon from site-level observations and model simulations across tundra ecosystems has been inconclusive. To address this knowledge gap, we combined top-down observations of atmospheric CO2 concentration enhancements from aircraft and a tall tower, which integrate ecosystem exchange over large regions, with bottom-up observed CO2 fluxes from tundra environments and found that the Alaska North Slope is not a consistent net source nor net sink of CO2 to the atmosphere (ranging from -6 to +6TgCyr-1 for 2012-2017). Our analysis suggests that significant biogenic CO2 fluxes from unfrozen terrestrial soils, and likely inland waters, during the early cold season (September-December) are major factors in determining the net annual carbon balance of the North Slope, implying strong sensitivity to the rapidly warming freeze-up period. At the regional level, we find no evidence of the previously reported large late-cold-season (January-April) CO2 emissions to the atmosphere during the study period. Despite the importance of the cold-season CO2 emissions to the annual total, the interannual variability in the net CO2 flux is driven by the variability in growing season fluxes. During the growing season, the regional net CO2 flux is also highly sensitive to the distribution of tundra vegetation types throughout the North Slope. This study shows that quantification and characterization of year-round CO2 fluxes from the heterogeneous terrestrial and aquatic ecosystems in the Arctic using both site-level and atmospheric observations are important to accurately project the Earth system response to future warming.
Published: 2022

6. Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions.

Author: Chang, Kuang-Yu, Chang, Kuang-Yu, Riley, William J, Knox, Sara H, Jackson, Robert B, McNicol, Gavin, Poulter, Benjamin, Aurela, Mika, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I, Cescatti, Alessandro, Chu, Housen, Delwiche, Kyle B, Desai, Ankur R, Euskirchen, Eugenie, Friborg, Thomas, Goeckede, Mathias, Helbig, Manuel, Hemes, Kyle S, Hirano, Takashi, Iwata, Hiroki, Kang, Minseok, Keenan, Trevor, Krauss, Ken W, Lohila, Annalea, Mammarella, Ivan, Mitra, Bhaskar, Miyata, Akira, Nilsson, Mats B, Noormets, Asko, Oechel, Walter C, Papale, Dario, Peichl, Matthias, Reba, Michele L, Rinne, Janne, Runkle, Benjamin RK, Ryu, Youngryel, Sachs, Torsten, Schäfer, Karina VR, Schmid, Hans Peter, Shurpali, Narasinha, Sonnentag, Oliver, Tang, Angela CI, Torn, Margaret S, Trotta, Carlo, Tuittila, Eeva-Stiina, Ueyama, Masahito, Vargas, Rodrigo, Vesala, Timo, Windham-Myers, Lisamarie, Zhang, Zhen, Zona, Donatella, Chang, Kuang-Yu, Chang, Kuang-Yu, Riley, William J, Knox, Sara H, Jackson, Robert B, McNicol, Gavin, Poulter, Benjamin, Aurela, Mika, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I, Cescatti, Alessandro, Chu, Housen, Delwiche, Kyle B, Desai, Ankur R, Euskirchen, Eugenie, Friborg, Thomas, Goeckede, Mathias, Helbig, Manuel, Hemes, Kyle S, Hirano, Takashi, Iwata, Hiroki, Kang, Minseok, Keenan, Trevor, Krauss, Ken W, Lohila, Annalea, Mammarella, Ivan, Mitra, Bhaskar, Miyata, Akira, Nilsson, Mats B, Noormets, Asko, Oechel, Walter C, Papale, Dario, Peichl, Matthias, Reba, Michele L, Rinne, Janne, Runkle, Benjamin RK, Ryu, Youngryel, Sachs, Torsten, Schäfer, Karina VR, Schmid, Hans Peter, Shurpali, Narasinha, Sonnentag, Oliver, Tang, Angela CI, Torn, Margaret S, Trotta, Carlo, Tuittila, Eeva-Stiina, Ueyama, Masahito, Vargas, Rodrigo, Vesala, Timo, Windham-Myers, Lisamarie, Zhang, Zhen, and Zona, Donatella
Abstract: Wetland methane (CH4) emissions ([Formula: see text]) are important in global carbon budgets and climate change assessments. Currently, [Formula: see text] projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent [Formula: see text] temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that [Formula: see text] are often controlled by factors beyond temperature. Here, we evaluate the relationship between [Formula: see text] and temperature using observations from the FLUXNET-CH4 database. Measurements collected across the globe show substantial seasonal hysteresis between [Formula: see text] and temperature, suggesting larger [Formula: see text] sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH4 production are thus needed to improve global CH4 budget assessments.
Published: 2021

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

Author: Delwiche, Kyle B., Knox, Sara Helen, Malhotra, Avni, Fluet-Chouinard, Etienne, McNicol, Gavin, Feron, Sarah, Ouyang, Zutao, Papale, Dario, Trotta, Carlo, Canfora, Eleonora, Cheah, You-Wei, Christianson, Danielle, Alberto, Ma. Carmelita R., Alekseychik, Pavel, Aurela, Mika, Baldocchi, Dennis, Bansal, Sheel, Billesbach, David P., Bohrer, Gil, Bracho, Rosvel, Buchmann, Nina, Campbell, David I., Celis, Gerardo, Chen, Jiquan, Chen, Weinan, Chu, Housen, Dalmagro, Higo J., Dengel, Sigrid, Desai, Ankur R., Detto, Matteo, Dolman, Han, Eichelmann, Elke, Euskirchen, Eugenie, Famulari, Daniela, Fuchs, Kathrin, Goeckede, Mathias, Gogo, Sébastien, Gondwe, Mangaliso J., Goodrich, Jordan P., Gottschalk, Pia, Graham, Scott L., Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S., Hirano, Takashi, Hollinger, David, Hörtnagl, Lukas, Iwata, Hiroki, Jacotot, Adrien, Jurasinski, Gerald, Kang, Minseok, Kasak, Kuno, King, John, Klatt, Janina, Koebsch, Franziska, Krauss, Ken W., Lai, Derrick Y.F., Lohila, Annalea, Mammarella, Ivan, Belelli Marchesini, Luca, Manca, Giovanni, Matthes, Jaclyn Hatala, Maximov, Trofim, Merbold, Lutz, Mitra, Bhaskar, Morin, Timothy H., Nemitz, Eiko, Nilsson, Mats B., Niu, Shuli, Oechel, Walter C., Oikawa, Patricia Y., Ono, Keisuke, Peichl, Matthias, Peltola, Olli, Reba, Michele L., Richardson, Andrew D., Riley, William, Runkle, Benjamin R.K., Ryu, Youngryel, Sachs, Torsten, Sakabe, Ayaka, Sanchez, Camilo Rey, Schuur, Edward A., Schäfer, Karina V.R., Sonnentag, Oliver, Sparks, Jed P., Stuart-Haëntjens, Ellen, Sturtevant, Cove, Sullivan, Ryan C., Szutu, Daphne J., Thom, Jonathan E., Torn, Margaret S., Tuittila, Eeva-Stiina, Turner, Jessica, Ueyama, Masahito, Valach, Alex C., Vargas, Rodrigo, Varlagin, Andrej, Vazquez-Lule, Alma, Verfaillie, Joseph G., Vesala, Timo, Vourlitis, George L., Ward, Eric J., Wille, Christian, Wohlfahrt, Georg, Wong, Guan Xhuan, Zhang, Zhen, Zona, Donatella, Windham-Myers, Lisamarie, Poulter, Benjamin, Jackson, Robert B., Delwiche, Kyle B., Knox, Sara Helen, Malhotra, Avni, Fluet-Chouinard, Etienne, McNicol, Gavin, Feron, Sarah, Ouyang, Zutao, Papale, Dario, Trotta, Carlo, Canfora, Eleonora, Cheah, You-Wei, Christianson, Danielle, Alberto, Ma. Carmelita R., Alekseychik, Pavel, Aurela, Mika, Baldocchi, Dennis, Bansal, Sheel, Billesbach, David P., Bohrer, Gil, Bracho, Rosvel, Buchmann, Nina, Campbell, David I., Celis, Gerardo, Chen, Jiquan, Chen, Weinan, Chu, Housen, Dalmagro, Higo J., Dengel, Sigrid, Desai, Ankur R., Detto, Matteo, Dolman, Han, Eichelmann, Elke, Euskirchen, Eugenie, Famulari, Daniela, Fuchs, Kathrin, Goeckede, Mathias, Gogo, Sébastien, Gondwe, Mangaliso J., Goodrich, Jordan P., Gottschalk, Pia, Graham, Scott L., Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S., Hirano, Takashi, Hollinger, David, Hörtnagl, Lukas, Iwata, Hiroki, Jacotot, Adrien, Jurasinski, Gerald, Kang, Minseok, Kasak, Kuno, King, John, Klatt, Janina, Koebsch, Franziska, Krauss, Ken W., Lai, Derrick Y.F., Lohila, Annalea, Mammarella, Ivan, Belelli Marchesini, Luca, Manca, Giovanni, Matthes, Jaclyn Hatala, Maximov, Trofim, Merbold, Lutz, Mitra, Bhaskar, Morin, Timothy H., Nemitz, Eiko, Nilsson, Mats B., Niu, Shuli, Oechel, Walter C., Oikawa, Patricia Y., Ono, Keisuke, Peichl, Matthias, Peltola, Olli, Reba, Michele L., Richardson, Andrew D., Riley, William, Runkle, Benjamin R.K., Ryu, Youngryel, Sachs, Torsten, Sakabe, Ayaka, Sanchez, Camilo Rey, Schuur, Edward A., Schäfer, Karina V.R., Sonnentag, Oliver, Sparks, Jed P., Stuart-Haëntjens, Ellen, Sturtevant, Cove, Sullivan, Ryan C., Szutu, Daphne J., Thom, Jonathan E., Torn, Margaret S., Tuittila, Eeva-Stiina, Turner, Jessica, Ueyama, Masahito, Valach, Alex C., Vargas, Rodrigo, Varlagin, Andrej, Vazquez-Lule, Alma, Verfaillie, Joseph G., Vesala, Timo, Vourlitis, George L., Ward, Eric J., Wille, Christian, Wohlfahrt, Georg, Wong, Guan Xhuan, Zhang, Zhen, Zona, Donatella, Windham-Myers, Lisamarie, Poulter, Benjamin, and Jackson, Robert B.
Abstract: Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20∘ S to 20∘ N) the spring onset of elevated CH4 emissions starts 3 d earlier, and the CH4 emission season lasts 4 d longe
Published: 2021

8. Gap-filling eddy covariance methane fluxes: comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Author: Irvin, Jeremy, Zhou, Sharon, McNicol, Gavin, Lu, Fred, Liu, Vincent, Fluet-Chouinard, Etienne, Ouyang, Zutao, Knox, Sara Helen, Lucas-Moffat, Antje, Trotta, Carlo, Papale, Dario, Vitale, Domenico, Mammarella, Ivan, Alekseychik, Pavel, Aurela, Mika, Avati, Anand, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I., Chen, Jiquan, Chu, Housen, Dalmagro, Higo J., Delwiche, Kyle B., Desai, Ankur R., Euskirchen, Eugenie, Feron, Sarah, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S., Hirano, Takashi, Iwata, Hiroki, Jurasinski, Gerald, Kalhori, Aram, Kondrich, Andrew, Lai, Derrick Y.F., Lohila, Annalea, Malhotra, Avni, Merbold, Lutz, Mitra, Bhaskar, Ng, Andrew, Nilsson, Mats B., Noormets, Asko, Peichl, Matthias, Rey-Sanchez, A. Camilo, Richardson, Andrew D., Runkle, Benjamin R.K., Schäfer, Karina V.R., Sonnentag, Oliver, Stuart-Haëntjens, Ellen, Sturtevant, Cove, Ueyama, Masahito, Valach, Alex C., Vargas, Rodrigo, Vourlitis, George L., Ward, Eric J., Wong, Guan Xhuan, Zona, Donatella, Alberto, Ma. Carmelita R., Billesbach, David P., Celis, Gerardo, Dolman, Han, Friborg, Thomas, Fuchs, Kathrin, Gogo, Sébastien, Gondwe, Mangaliso J., Goodrich, Jordan P., Gottschalk, Pia, Hörtnagl, Lukas, Jacotot, Adrien, Koebsch, Franziska, Kasak, Kuno, Maier, Regine, Morin, Timothy H., Nemitz, Eiko, Oechel, Walter C., Oikawa, Patricia Y., Ono, Keisuke, Sachs, Torsten, Sakabe, Ayaka, Schuur, Edward A., Shortt, Robert, Sullivan, Ryan C., Szutu, Daphne J., Tuittila, Eeva-Stiina, Varlagin, Andrej, Verfaillie, Joeseph G., Wille, Christian, Windham-Myers, Lisamarie, Poulter, Benjamin, Jackson, Robert B., Irvin, Jeremy, Zhou, Sharon, McNicol, Gavin, Lu, Fred, Liu, Vincent, Fluet-Chouinard, Etienne, Ouyang, Zutao, Knox, Sara Helen, Lucas-Moffat, Antje, Trotta, Carlo, Papale, Dario, Vitale, Domenico, Mammarella, Ivan, Alekseychik, Pavel, Aurela, Mika, Avati, Anand, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I., Chen, Jiquan, Chu, Housen, Dalmagro, Higo J., Delwiche, Kyle B., Desai, Ankur R., Euskirchen, Eugenie, Feron, Sarah, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S., Hirano, Takashi, Iwata, Hiroki, Jurasinski, Gerald, Kalhori, Aram, Kondrich, Andrew, Lai, Derrick Y.F., Lohila, Annalea, Malhotra, Avni, Merbold, Lutz, Mitra, Bhaskar, Ng, Andrew, Nilsson, Mats B., Noormets, Asko, Peichl, Matthias, Rey-Sanchez, A. Camilo, Richardson, Andrew D., Runkle, Benjamin R.K., Schäfer, Karina V.R., Sonnentag, Oliver, Stuart-Haëntjens, Ellen, Sturtevant, Cove, Ueyama, Masahito, Valach, Alex C., Vargas, Rodrigo, Vourlitis, George L., Ward, Eric J., Wong, Guan Xhuan, Zona, Donatella, Alberto, Ma. Carmelita R., Billesbach, David P., Celis, Gerardo, Dolman, Han, Friborg, Thomas, Fuchs, Kathrin, Gogo, Sébastien, Gondwe, Mangaliso J., Goodrich, Jordan P., Gottschalk, Pia, Hörtnagl, Lukas, Jacotot, Adrien, Koebsch, Franziska, Kasak, Kuno, Maier, Regine, Morin, Timothy H., Nemitz, Eiko, Oechel, Walter C., Oikawa, Patricia Y., Ono, Keisuke, Sachs, Torsten, Sakabe, Ayaka, Schuur, Edward A., Shortt, Robert, Sullivan, Ryan C., Szutu, Daphne J., Tuittila, Eeva-Stiina, Varlagin, Andrej, Verfaillie, Joeseph G., Wille, Christian, Windham-Myers, Lisamarie, Poulter, Benjamin, and Jackson, Robert B.
Abstract: Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an impro
Published: 2021

9. Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions.

Author: Chang, Kuang-Yu, Chang, Kuang-Yu, Riley, William J, Knox, Sara H, Jackson, Robert B, McNicol, Gavin, Poulter, Benjamin, Aurela, Mika, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I, Cescatti, Alessandro, Chu, Housen, Delwiche, Kyle B, Desai, Ankur R, Euskirchen, Eugenie, Friborg, Thomas, Goeckede, Mathias, Helbig, Manuel, Hemes, Kyle S, Hirano, Takashi, Iwata, Hiroki, Kang, Minseok, Keenan, Trevor, Krauss, Ken W, Lohila, Annalea, Mammarella, Ivan, Mitra, Bhaskar, Miyata, Akira, Nilsson, Mats B, Noormets, Asko, Oechel, Walter C, Papale, Dario, Peichl, Matthias, Reba, Michele L, Rinne, Janne, Runkle, Benjamin RK, Ryu, Youngryel, Sachs, Torsten, Schäfer, Karina VR, Schmid, Hans Peter, Shurpali, Narasinha, Sonnentag, Oliver, Tang, Angela CI, Torn, Margaret S, Trotta, Carlo, Tuittila, Eeva-Stiina, Ueyama, Masahito, Vargas, Rodrigo, Vesala, Timo, Windham-Myers, Lisamarie, Zhang, Zhen, Zona, Donatella, Chang, Kuang-Yu, Chang, Kuang-Yu, Riley, William J, Knox, Sara H, Jackson, Robert B, McNicol, Gavin, Poulter, Benjamin, Aurela, Mika, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I, Cescatti, Alessandro, Chu, Housen, Delwiche, Kyle B, Desai, Ankur R, Euskirchen, Eugenie, Friborg, Thomas, Goeckede, Mathias, Helbig, Manuel, Hemes, Kyle S, Hirano, Takashi, Iwata, Hiroki, Kang, Minseok, Keenan, Trevor, Krauss, Ken W, Lohila, Annalea, Mammarella, Ivan, Mitra, Bhaskar, Miyata, Akira, Nilsson, Mats B, Noormets, Asko, Oechel, Walter C, Papale, Dario, Peichl, Matthias, Reba, Michele L, Rinne, Janne, Runkle, Benjamin RK, Ryu, Youngryel, Sachs, Torsten, Schäfer, Karina VR, Schmid, Hans Peter, Shurpali, Narasinha, Sonnentag, Oliver, Tang, Angela CI, Torn, Margaret S, Trotta, Carlo, Tuittila, Eeva-Stiina, Ueyama, Masahito, Vargas, Rodrigo, Vesala, Timo, Windham-Myers, Lisamarie, Zhang, Zhen, and Zona, Donatella
Abstract: Wetland methane (CH4) emissions ([Formula: see text]) are important in global carbon budgets and climate change assessments. Currently, [Formula: see text] projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent [Formula: see text] temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that [Formula: see text] are often controlled by factors beyond temperature. Here, we evaluate the relationship between [Formula: see text] and temperature using observations from the FLUXNET-CH4 database. Measurements collected across the globe show substantial seasonal hysteresis between [Formula: see text] and temperature, suggesting larger [Formula: see text] sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH4 production are thus needed to improve global CH4 budget assessments.
Published: 2021

10. Gap-filling eddy covariance methane fluxes:Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Author: Irvin, Jeremy, Zhou, Sharon, Mcnicol, Gavin, Lu, Fred, Liu, Vincent, Fluet-chouinard, Etienne, Ouyang, Zutao, Knox, Sara Helen, Lucas-moffat, Antje, Trotta, Carlo, Papale, Dario, Vitale, Domenico, Mammarella, Ivan, Alekseychik, Pavel, Aurela, Mika, Avati, Anand, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I, Chen, Jiquan, Chu, Housen, Dalmagro, Higo J, Delwiche, Kyle B, Desai, Ankur R, Euskirchen, Eugenie, Feron, Sarah, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S, Hirano, Takashi, Iwata, Hiroki, Jurasinski, Gerald, Kalhori, Aram, Kondrich, Andrew, Lai, Derrick Yf, Lohila, Annalea, Malhotra, Avni, Merbold, Lutz, Mitra, Bhaskar, Ng, Andrew, Nilsson, Mats B, Noormets, Asko, Peichl, Matthias, Rey-sanchez, A. Camilo, Richardson, Andrew D, Runkle, Benjamin Rk, Schäfer, Karina Vr, Sonnentag, Oliver, Stuart-haëntjens, Ellen, Sturtevant, Cove, Ueyama, Masahito, Valach, Alex C, Vargas, Rodrigo, Vourlitis, George L, Ward, Eric J, Wong, Guan Xhuan, Zona, Donatella, Alberto, Ma. Carmelita R, Billesbach, David P, Celis, Gerardo, Dolman, Han, Friborg, Thomas, Fuchs, Kathrin, Gogo, Sébastien, Gondwe, Mangaliso J, Goodrich, Jordan P, Gottschalk, Pia, Hörtnagl, Lukas, Jacotot, Adrien, Koebsch, Franziska, Kasak, Kuno, Maier, Regine, Morin, Timothy H, Nemitz, Eiko, Oechel, Walter C, Oikawa, Patricia Y, Ono, Keisuke, Sachs, Torsten, Sakabe, Ayaka, Schuur, Edward A, Shortt, Robert, Sullivan, Ryan C, Szutu, Daphne J, Tuittila, Eeva-stiina, Varlagin, Andrej, Verfaillie, Joeseph G, Wille, Christian, Windham-myers, Lisamarie, Poulter, Benjamin, Jackson, Robert B, Irvin, Jeremy, Zhou, Sharon, Mcnicol, Gavin, Lu, Fred, Liu, Vincent, Fluet-chouinard, Etienne, Ouyang, Zutao, Knox, Sara Helen, Lucas-moffat, Antje, Trotta, Carlo, Papale, Dario, Vitale, Domenico, Mammarella, Ivan, Alekseychik, Pavel, Aurela, Mika, Avati, Anand, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I, Chen, Jiquan, Chu, Housen, Dalmagro, Higo J, Delwiche, Kyle B, Desai, Ankur R, Euskirchen, Eugenie, Feron, Sarah, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S, Hirano, Takashi, Iwata, Hiroki, Jurasinski, Gerald, Kalhori, Aram, Kondrich, Andrew, Lai, Derrick Yf, Lohila, Annalea, Malhotra, Avni, Merbold, Lutz, Mitra, Bhaskar, Ng, Andrew, Nilsson, Mats B, Noormets, Asko, Peichl, Matthias, Rey-sanchez, A. Camilo, Richardson, Andrew D, Runkle, Benjamin Rk, Schäfer, Karina Vr, Sonnentag, Oliver, Stuart-haëntjens, Ellen, Sturtevant, Cove, Ueyama, Masahito, Valach, Alex C, Vargas, Rodrigo, Vourlitis, George L, Ward, Eric J, Wong, Guan Xhuan, Zona, Donatella, Alberto, Ma. Carmelita R, Billesbach, David P, Celis, Gerardo, Dolman, Han, Friborg, Thomas, Fuchs, Kathrin, Gogo, Sébastien, Gondwe, Mangaliso J, Goodrich, Jordan P, Gottschalk, Pia, Hörtnagl, Lukas, Jacotot, Adrien, Koebsch, Franziska, Kasak, Kuno, Maier, Regine, Morin, Timothy H, Nemitz, Eiko, Oechel, Walter C, Oikawa, Patricia Y, Ono, Keisuke, Sachs, Torsten, Sakabe, Ayaka, Schuur, Edward A, Shortt, Robert, Sullivan, Ryan C, Szutu, Daphne J, Tuittila, Eeva-stiina, Varlagin, Andrej, Verfaillie, Joeseph G, Wille, Christian, Windham-myers, Lisamarie, Poulter, Benjamin, and Jackson, Robert B
Abstract: Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an impro
Published: 2021

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

Author: Delwiche, Kyle B., Knox, Sara Helen, Malhotra, Avni, Fluet-Chouinard, Etienne, McNicol, Gavin, Feron, Sarah, Ouyang, Zutao, Papale, Dario, Trotta, Carlo, Canfora, Eleonora, Cheah, You-Wei, Christianson, Danielle, Alberto, Ma. Carmelita R., Alekseychik, Pavel, Aurela, Mika, Baldocchi, Dennis, Bansal, Sheel, Billesbach, David P., Bohrer, Gil, Bracho, Rosvel, Buchmann, Nina, Campbell, David I., Celis, Gerardo, Chen, Jiquan, Chen, Weinan, Chu, Housen, Dalmagro, Higo J., Dengel, Sigrid, Desai, Ankur R., Detto, Matteo, Dolman, Han, Eichelmann, Elke, Euskirchen, Eugenie, Famulari, Daniela, Fuchs, Kathrin, Goeckede, Mathias, Gogo, Sébastien, Gondwe, Mangaliso J., Goodrich, Jordan P., Gottschalk, Pia, Graham, Scott L., Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S., Hirano, Takashi, Hollinger, David, Hörtnagl, Lukas, Iwata, Hiroki, Jacotot, Adrien, Jurasinski, Gerald, Kang, Minseok, Kasak, Kuno, King, John, Klatt, Janina, Koebsch, Franziska, Krauss, Ken W., Lai, Derrick Y.F., Lohila, Annalea, Mammarella, Ivan, Belelli Marchesini, Luca, Manca, Giovanni, Matthes, Jaclyn Hatala, Maximov, Trofim, Merbold, Lutz, Mitra, Bhaskar, Morin, Timothy H., Nemitz, Eiko, Nilsson, Mats B., Niu, Shuli, Oechel, Walter C., Oikawa, Patricia Y., Ono, Keisuke, Peichl, Matthias, Peltola, Olli, Reba, Michele L., Richardson, Andrew D., Riley, William, Runkle, Benjamin R.K., Ryu, Youngryel, Sachs, Torsten, Sakabe, Ayaka, Sanchez, Camilo Rey, Schuur, Edward A., Schäfer, Karina V.R., Sonnentag, Oliver, Sparks, Jed P., Stuart-Haëntjens, Ellen, Sturtevant, Cove, Sullivan, Ryan C., Szutu, Daphne J., Thom, Jonathan E., Torn, Margaret S., Tuittila, Eeva-Stiina, Turner, Jessica, Ueyama, Masahito, Valach, Alex C., Vargas, Rodrigo, Varlagin, Andrej, Vazquez-Lule, Alma, Verfaillie, Joseph G., Vesala, Timo, Vourlitis, George L., Ward, Eric J., Wille, Christian, Wohlfahrt, Georg, Wong, Guan Xhuan, Zhang, Zhen, Zona, Donatella, Windham-Myers, Lisamarie, Poulter, Benjamin, Jackson, Robert B., Delwiche, Kyle B., Knox, Sara Helen, Malhotra, Avni, Fluet-Chouinard, Etienne, McNicol, Gavin, Feron, Sarah, Ouyang, Zutao, Papale, Dario, Trotta, Carlo, Canfora, Eleonora, Cheah, You-Wei, Christianson, Danielle, Alberto, Ma. Carmelita R., Alekseychik, Pavel, Aurela, Mika, Baldocchi, Dennis, Bansal, Sheel, Billesbach, David P., Bohrer, Gil, Bracho, Rosvel, Buchmann, Nina, Campbell, David I., Celis, Gerardo, Chen, Jiquan, Chen, Weinan, Chu, Housen, Dalmagro, Higo J., Dengel, Sigrid, Desai, Ankur R., Detto, Matteo, Dolman, Han, Eichelmann, Elke, Euskirchen, Eugenie, Famulari, Daniela, Fuchs, Kathrin, Goeckede, Mathias, Gogo, Sébastien, Gondwe, Mangaliso J., Goodrich, Jordan P., Gottschalk, Pia, Graham, Scott L., Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S., Hirano, Takashi, Hollinger, David, Hörtnagl, Lukas, Iwata, Hiroki, Jacotot, Adrien, Jurasinski, Gerald, Kang, Minseok, Kasak, Kuno, King, John, Klatt, Janina, Koebsch, Franziska, Krauss, Ken W., Lai, Derrick Y.F., Lohila, Annalea, Mammarella, Ivan, Belelli Marchesini, Luca, Manca, Giovanni, Matthes, Jaclyn Hatala, Maximov, Trofim, Merbold, Lutz, Mitra, Bhaskar, Morin, Timothy H., Nemitz, Eiko, Nilsson, Mats B., Niu, Shuli, Oechel, Walter C., Oikawa, Patricia Y., Ono, Keisuke, Peichl, Matthias, Peltola, Olli, Reba, Michele L., Richardson, Andrew D., Riley, William, Runkle, Benjamin R.K., Ryu, Youngryel, Sachs, Torsten, Sakabe, Ayaka, Sanchez, Camilo Rey, Schuur, Edward A., Schäfer, Karina V.R., Sonnentag, Oliver, Sparks, Jed P., Stuart-Haëntjens, Ellen, Sturtevant, Cove, Sullivan, Ryan C., Szutu, Daphne J., Thom, Jonathan E., Torn, Margaret S., Tuittila, Eeva-Stiina, Turner, Jessica, Ueyama, Masahito, Valach, Alex C., Vargas, Rodrigo, Varlagin, Andrej, Vazquez-Lule, Alma, Verfaillie, Joseph G., Vesala, Timo, Vourlitis, George L., Ward, Eric J., Wille, Christian, Wohlfahrt, Georg, Wong, Guan Xhuan, Zhang, Zhen, Zona, Donatella, Windham-Myers, Lisamarie, Poulter, Benjamin, and Jackson, Robert B.
Abstract: Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20∘ S to 20∘ N) the spring onset of elevated CH4 emissions starts 3 d earlier, and the CH4 emission season lasts 4 d longe
Published: 2021

12. Gap-filling eddy covariance methane fluxes: comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Author: Irvin, Jeremy, Zhou, Sharon, McNicol, Gavin, Lu, Fred, Liu, Vincent, Fluet-Chouinard, Etienne, Ouyang, Zutao, Knox, Sara Helen, Lucas-Moffat, Antje, Trotta, Carlo, Papale, Dario, Vitale, Domenico, Mammarella, Ivan, Alekseychik, Pavel, Aurela, Mika, Avati, Anand, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I., Chen, Jiquan, Chu, Housen, Dalmagro, Higo J., Delwiche, Kyle B., Desai, Ankur R., Euskirchen, Eugenie, Feron, Sarah, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S., Hirano, Takashi, Iwata, Hiroki, Jurasinski, Gerald, Kalhori, Aram, Kondrich, Andrew, Lai, Derrick Y.F., Lohila, Annalea, Malhotra, Avni, Merbold, Lutz, Mitra, Bhaskar, Ng, Andrew, Nilsson, Mats B., Noormets, Asko, Peichl, Matthias, Rey-Sanchez, A. Camilo, Richardson, Andrew D., Runkle, Benjamin R.K., Schäfer, Karina V.R., Sonnentag, Oliver, Stuart-Haëntjens, Ellen, Sturtevant, Cove, Ueyama, Masahito, Valach, Alex C., Vargas, Rodrigo, Vourlitis, George L., Ward, Eric J., Wong, Guan Xhuan, Zona, Donatella, Alberto, Ma. Carmelita R., Billesbach, David P., Celis, Gerardo, Dolman, Han, Friborg, Thomas, Fuchs, Kathrin, Gogo, Sébastien, Gondwe, Mangaliso J., Goodrich, Jordan P., Gottschalk, Pia, Hörtnagl, Lukas, Jacotot, Adrien, Koebsch, Franziska, Kasak, Kuno, Maier, Regine, Morin, Timothy H., Nemitz, Eiko, Oechel, Walter C., Oikawa, Patricia Y., Ono, Keisuke, Sachs, Torsten, Sakabe, Ayaka, Schuur, Edward A., Shortt, Robert, Sullivan, Ryan C., Szutu, Daphne J., Tuittila, Eeva-Stiina, Varlagin, Andrej, Verfaillie, Joeseph G., Wille, Christian, Windham-Myers, Lisamarie, Poulter, Benjamin, Jackson, Robert B., Irvin, Jeremy, Zhou, Sharon, McNicol, Gavin, Lu, Fred, Liu, Vincent, Fluet-Chouinard, Etienne, Ouyang, Zutao, Knox, Sara Helen, Lucas-Moffat, Antje, Trotta, Carlo, Papale, Dario, Vitale, Domenico, Mammarella, Ivan, Alekseychik, Pavel, Aurela, Mika, Avati, Anand, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I., Chen, Jiquan, Chu, Housen, Dalmagro, Higo J., Delwiche, Kyle B., Desai, Ankur R., Euskirchen, Eugenie, Feron, Sarah, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S., Hirano, Takashi, Iwata, Hiroki, Jurasinski, Gerald, Kalhori, Aram, Kondrich, Andrew, Lai, Derrick Y.F., Lohila, Annalea, Malhotra, Avni, Merbold, Lutz, Mitra, Bhaskar, Ng, Andrew, Nilsson, Mats B., Noormets, Asko, Peichl, Matthias, Rey-Sanchez, A. Camilo, Richardson, Andrew D., Runkle, Benjamin R.K., Schäfer, Karina V.R., Sonnentag, Oliver, Stuart-Haëntjens, Ellen, Sturtevant, Cove, Ueyama, Masahito, Valach, Alex C., Vargas, Rodrigo, Vourlitis, George L., Ward, Eric J., Wong, Guan Xhuan, Zona, Donatella, Alberto, Ma. Carmelita R., Billesbach, David P., Celis, Gerardo, Dolman, Han, Friborg, Thomas, Fuchs, Kathrin, Gogo, Sébastien, Gondwe, Mangaliso J., Goodrich, Jordan P., Gottschalk, Pia, Hörtnagl, Lukas, Jacotot, Adrien, Koebsch, Franziska, Kasak, Kuno, Maier, Regine, Morin, Timothy H., Nemitz, Eiko, Oechel, Walter C., Oikawa, Patricia Y., Ono, Keisuke, Sachs, Torsten, Sakabe, Ayaka, Schuur, Edward A., Shortt, Robert, Sullivan, Ryan C., Szutu, Daphne J., Tuittila, Eeva-Stiina, Varlagin, Andrej, Verfaillie, Joeseph G., Wille, Christian, Windham-Myers, Lisamarie, Poulter, Benjamin, and Jackson, Robert B.
Abstract: Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an impro
Published: 2021

13. Gap-filling eddy covariance methane fluxes:Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Author: Irvin, Jeremy, Zhou, Sharon, Mcnicol, Gavin, Lu, Fred, Liu, Vincent, Fluet-chouinard, Etienne, Ouyang, Zutao, Knox, Sara Helen, Lucas-moffat, Antje, Trotta, Carlo, Papale, Dario, Vitale, Domenico, Mammarella, Ivan, Alekseychik, Pavel, Aurela, Mika, Avati, Anand, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I, Chen, Jiquan, Chu, Housen, Dalmagro, Higo J, Delwiche, Kyle B, Desai, Ankur R, Euskirchen, Eugenie, Feron, Sarah, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S, Hirano, Takashi, Iwata, Hiroki, Jurasinski, Gerald, Kalhori, Aram, Kondrich, Andrew, Lai, Derrick Yf, Lohila, Annalea, Malhotra, Avni, Merbold, Lutz, Mitra, Bhaskar, Ng, Andrew, Nilsson, Mats B, Noormets, Asko, Peichl, Matthias, Rey-sanchez, A. Camilo, Richardson, Andrew D, Runkle, Benjamin Rk, Schäfer, Karina Vr, Sonnentag, Oliver, Stuart-haëntjens, Ellen, Sturtevant, Cove, Ueyama, Masahito, Valach, Alex C, Vargas, Rodrigo, Vourlitis, George L, Ward, Eric J, Wong, Guan Xhuan, Zona, Donatella, Alberto, Ma. Carmelita R, Billesbach, David P, Celis, Gerardo, Dolman, Han, Friborg, Thomas, Fuchs, Kathrin, Gogo, Sébastien, Gondwe, Mangaliso J, Goodrich, Jordan P, Gottschalk, Pia, Hörtnagl, Lukas, Jacotot, Adrien, Koebsch, Franziska, Kasak, Kuno, Maier, Regine, Morin, Timothy H, Nemitz, Eiko, Oechel, Walter C, Oikawa, Patricia Y, Ono, Keisuke, Sachs, Torsten, Sakabe, Ayaka, Schuur, Edward A, Shortt, Robert, Sullivan, Ryan C, Szutu, Daphne J, Tuittila, Eeva-stiina, Varlagin, Andrej, Verfaillie, Joeseph G, Wille, Christian, Windham-myers, Lisamarie, Poulter, Benjamin, Jackson, Robert B, Irvin, Jeremy, Zhou, Sharon, Mcnicol, Gavin, Lu, Fred, Liu, Vincent, Fluet-chouinard, Etienne, Ouyang, Zutao, Knox, Sara Helen, Lucas-moffat, Antje, Trotta, Carlo, Papale, Dario, Vitale, Domenico, Mammarella, Ivan, Alekseychik, Pavel, Aurela, Mika, Avati, Anand, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I, Chen, Jiquan, Chu, Housen, Dalmagro, Higo J, Delwiche, Kyle B, Desai, Ankur R, Euskirchen, Eugenie, Feron, Sarah, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Helfter, Carole, Hemes, Kyle S, Hirano, Takashi, Iwata, Hiroki, Jurasinski, Gerald, Kalhori, Aram, Kondrich, Andrew, Lai, Derrick Yf, Lohila, Annalea, Malhotra, Avni, Merbold, Lutz, Mitra, Bhaskar, Ng, Andrew, Nilsson, Mats B, Noormets, Asko, Peichl, Matthias, Rey-sanchez, A. Camilo, Richardson, Andrew D, Runkle, Benjamin Rk, Schäfer, Karina Vr, Sonnentag, Oliver, Stuart-haëntjens, Ellen, Sturtevant, Cove, Ueyama, Masahito, Valach, Alex C, Vargas, Rodrigo, Vourlitis, George L, Ward, Eric J, Wong, Guan Xhuan, Zona, Donatella, Alberto, Ma. Carmelita R, Billesbach, David P, Celis, Gerardo, Dolman, Han, Friborg, Thomas, Fuchs, Kathrin, Gogo, Sébastien, Gondwe, Mangaliso J, Goodrich, Jordan P, Gottschalk, Pia, Hörtnagl, Lukas, Jacotot, Adrien, Koebsch, Franziska, Kasak, Kuno, Maier, Regine, Morin, Timothy H, Nemitz, Eiko, Oechel, Walter C, Oikawa, Patricia Y, Ono, Keisuke, Sachs, Torsten, Sakabe, Ayaka, Schuur, Edward A, Shortt, Robert, Sullivan, Ryan C, Szutu, Daphne J, Tuittila, Eeva-stiina, Varlagin, Andrej, Verfaillie, Joeseph G, Wille, Christian, Windham-myers, Lisamarie, Poulter, Benjamin, and Jackson, Robert B
Abstract: Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an impro
Published: 2021

14. Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions

Author: Chang, Kuang-yu, Riley, William J., Knox, Sara H., Jackson, Robert B., Mcnicol, Gavin, Poulter, Benjamin, Aurela, Mika, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I., Cescatti, Alessandro, Chu, Housen, Delwiche, Kyle B., Desai, Ankur R., Euskirchen, Eugenie, Friborg, Thomas, Goeckede, Mathias, Helbig, Manuel, Hemes, Kyle S., Hirano, Takashi, Iwata, Hiroki, Kang, Minseok, Keenan, Trevor, Krauss, Ken W., Lohila, Annalea, Mammarella, Ivan, Mitra, Bhaskar, Miyata, Akira, Nilsson, Mats B., Noormets, Asko, Oechel, Walter C., Papale, Dario, Peichl, Matthias, Reba, Michele L., Rinne, Janne, Runkle, Benjamin R. K., Ryu, Youngryel, Sachs, Torsten, Schäfer, Karina V. R., Schmid, Hans Peter, Shurpali, Narasinha, Sonnentag, Oliver, Tang, Angela C. I., Torn, Margaret S., Trotta, Carlo, Tuittila, Eeva-stiina, Ueyama, Masahito, Vargas, Rodrigo, Vesala, Timo, Windham-myers, Lisamarie, Zhang, Zhen, Zona, Donatella, Chang, Kuang-yu, Riley, William J., Knox, Sara H., Jackson, Robert B., Mcnicol, Gavin, Poulter, Benjamin, Aurela, Mika, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I., Cescatti, Alessandro, Chu, Housen, Delwiche, Kyle B., Desai, Ankur R., Euskirchen, Eugenie, Friborg, Thomas, Goeckede, Mathias, Helbig, Manuel, Hemes, Kyle S., Hirano, Takashi, Iwata, Hiroki, Kang, Minseok, Keenan, Trevor, Krauss, Ken W., Lohila, Annalea, Mammarella, Ivan, Mitra, Bhaskar, Miyata, Akira, Nilsson, Mats B., Noormets, Asko, Oechel, Walter C., Papale, Dario, Peichl, Matthias, Reba, Michele L., Rinne, Janne, Runkle, Benjamin R. K., Ryu, Youngryel, Sachs, Torsten, Schäfer, Karina V. R., Schmid, Hans Peter, Shurpali, Narasinha, Sonnentag, Oliver, Tang, Angela C. I., Torn, Margaret S., Trotta, Carlo, Tuittila, Eeva-stiina, Ueyama, Masahito, Vargas, Rodrigo, Vesala, Timo, Windham-myers, Lisamarie, Zhang, Zhen, and Zona, Donatella
Published: 2021

15. Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions

Author: Chang, Kuang-yu, Riley, William J., Knox, Sara H., Jackson, Robert B., Mcnicol, Gavin, Poulter, Benjamin, Aurela, Mika, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I., Cescatti, Alessandro, Chu, Housen, Delwiche, Kyle B., Desai, Ankur R., Euskirchen, Eugenie, Friborg, Thomas, Goeckede, Mathias, Helbig, Manuel, Hemes, Kyle S., Hirano, Takashi, Iwata, Hiroki, Kang, Minseok, Keenan, Trevor, Krauss, Ken W., Lohila, Annalea, Mammarella, Ivan, Mitra, Bhaskar, Miyata, Akira, Nilsson, Mats B., Noormets, Asko, Oechel, Walter C., Papale, Dario, Peichl, Matthias, Reba, Michele L., Rinne, Janne, Runkle, Benjamin R. K., Ryu, Youngryel, Sachs, Torsten, Schäfer, Karina V. R., Schmid, Hans Peter, Shurpali, Narasinha, Sonnentag, Oliver, Tang, Angela C. I., Torn, Margaret S., Trotta, Carlo, Tuittila, Eeva-stiina, Ueyama, Masahito, Vargas, Rodrigo, Vesala, Timo, Windham-myers, Lisamarie, Zhang, Zhen, Zona, Donatella, Chang, Kuang-yu, Riley, William J., Knox, Sara H., Jackson, Robert B., Mcnicol, Gavin, Poulter, Benjamin, Aurela, Mika, Baldocchi, Dennis, Bansal, Sheel, Bohrer, Gil, Campbell, David I., Cescatti, Alessandro, Chu, Housen, Delwiche, Kyle B., Desai, Ankur R., Euskirchen, Eugenie, Friborg, Thomas, Goeckede, Mathias, Helbig, Manuel, Hemes, Kyle S., Hirano, Takashi, Iwata, Hiroki, Kang, Minseok, Keenan, Trevor, Krauss, Ken W., Lohila, Annalea, Mammarella, Ivan, Mitra, Bhaskar, Miyata, Akira, Nilsson, Mats B., Noormets, Asko, Oechel, Walter C., Papale, Dario, Peichl, Matthias, Reba, Michele L., Rinne, Janne, Runkle, Benjamin R. K., Ryu, Youngryel, Sachs, Torsten, Schäfer, Karina V. R., Schmid, Hans Peter, Shurpali, Narasinha, Sonnentag, Oliver, Tang, Angela C. I., Torn, Margaret S., Trotta, Carlo, Tuittila, Eeva-stiina, Ueyama, Masahito, Vargas, Rodrigo, Vesala, Timo, Windham-myers, Lisamarie, Zhang, Zhen, and Zona, Donatella
Published: 2021

16. FLUXNET-CH4 Synthesis Activity : Objectives, Observations, and Future Directions

Author: Knox, Sara H., Jackson, Robert B., Poulter, Benjamin, McNicol, Gavin, Fluet-Chouinard, Etienne, Zhang, Zhen, Hugelius, Gustaf, Bousquet, Philippe, Canadell, Josep G., Saunois, Marielle, Papale, Dario, Chu, Housen, Keenan, Trevor F., Baldocchi, Dennis, Torn, Margaret S., Mammarella, Ivan, Trotta, Carlo, Aurela, Mika, Bohrer, Gil, Campbell, David, Cescatti, Alessandro, Chamberlain, Samuel, Chen, Jiquan, Chen, Weinan, Dengel, Sigrid, Desai, Ankur R., Euskirchen, Eugenie, Friborg, Thomas, Gasbarra, Daniele, Goded, Ignacio, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Hirano, Takashi, Hollinger, David Y., Iwata, Hiroki, Kang, Minseok, Klatt, Janina, Krauss, Ken W., Kutzbach, Lars, Lohila, Annalea, Mitra, Bhaskar, Morin, Timothy H., Nilsson, Mats B., Niu, Shuli, Noormets, Asko, Oechel, Walter C., Peichl, Matthias, Peltola, Olli, Reba, Michele L., Richardson, Andrew D., Runkle, Benjamin R. K., Ryu, Youngryel, Sachs, Torsten, Schaefer, Karina V. R., Schmid, Hans Peter, Shurpali, Narasinha, Sonnentag, Oliver, Tang, Angela C., Ueyama, Masahito, Vargas, Rodrigo, Vesala, Timo, Ward, Eric J., Windham-Myers, Lisamarie, Wohlfahrt, Georg, Zona, Donatella, Knox, Sara H., Jackson, Robert B., Poulter, Benjamin, McNicol, Gavin, Fluet-Chouinard, Etienne, Zhang, Zhen, Hugelius, Gustaf, Bousquet, Philippe, Canadell, Josep G., Saunois, Marielle, Papale, Dario, Chu, Housen, Keenan, Trevor F., Baldocchi, Dennis, Torn, Margaret S., Mammarella, Ivan, Trotta, Carlo, Aurela, Mika, Bohrer, Gil, Campbell, David, Cescatti, Alessandro, Chamberlain, Samuel, Chen, Jiquan, Chen, Weinan, Dengel, Sigrid, Desai, Ankur R., Euskirchen, Eugenie, Friborg, Thomas, Gasbarra, Daniele, Goded, Ignacio, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Hirano, Takashi, Hollinger, David Y., Iwata, Hiroki, Kang, Minseok, Klatt, Janina, Krauss, Ken W., Kutzbach, Lars, Lohila, Annalea, Mitra, Bhaskar, Morin, Timothy H., Nilsson, Mats B., Niu, Shuli, Noormets, Asko, Oechel, Walter C., Peichl, Matthias, Peltola, Olli, Reba, Michele L., Richardson, Andrew D., Runkle, Benjamin R. K., Ryu, Youngryel, Sachs, Torsten, Schaefer, Karina V. R., Schmid, Hans Peter, Shurpali, Narasinha, Sonnentag, Oliver, Tang, Angela C., Ueyama, Masahito, Vargas, Rodrigo, Vesala, Timo, Ward, Eric J., Windham-Myers, Lisamarie, Wohlfahrt, Georg, and Zona, Donatella
Abstract: This paper describes the formation of, and initial results for, a new FLUXNET coordination network for ecosystem-scale methane (CH4) measurements at 60 sites globally, organized by the Global Carbon Project in partnership with other initiatives and regional flux tower networks. The objectives of the effort are presented along with an overview of the coverage of eddy covariance (EC) CH4 flux measurements globally, initial results comparing CH4 fluxes across the sites, and future research directions and needs. Annual estimates of net CH4 fluxes across sites ranged from -0.2 +/- 0.02 g C m(-2) yr(-1) for an upland forest site to 114.9 +/- 13.4 g C m(-2) yr(-1) for an estuarine freshwater marsh, with fluxes exceeding 40 g C m(-2) yr(-1) at multiple sites. Average annual soil and air temperatures were found to be the strongest predictor of annual CH4 flux across wetland sites globally. Water table position was positively correlated with annual CH4 emissions, although only for wetland sites that were not consistently inundated throughout the year. The ratio of annual CH4 fluxes to ecosystem respiration increased significantly with mean site temperature. Uncertainties in annual CH4 estimates due to gap-filling and random errors were on average +/- 1.6 g C m(-2) yr(-1) at 95% confidence, with the relative error decreasing exponentially with increasing flux magnitude across sites. Through the analysis and synthesis of a growing EC CH4 flux database, the controls on ecosystem CH4 fluxes can be better understood, used to inform and validate Earth system models, and reconcile differences between land surface model- and atmospheric-based estimates of CH4 emissions.
Published: 2019
Full Text: View/download PDF

17. Large loss of CO2 in winter observed across the northern permafrost region

Author: Natali, Susan M., Watts, Jennifer D., Rogers, Brendan M., Potter, Stefano, Ludwig, Sarah M., Selbmann, Anne-Katrin, Sullivan, Patrick F., Abbott, Benjamin W., Arndt, Kyle A., Birch, Leah, Björkman, Mats P., Bloom, A. Anthony, Celis, Gerardo, Christensen, Torben R., Christiansen, Casper T., Commane, Roisin, Cooper, Elisabeth J., Crill, Patrick, Czimczik, Claudia, Davydov, Sergey, Du, Jinyang, Egan, Jocelyn E., Elberling, Bo, Euskirchen, Eugenie S., Friborg, Thomas, Genet, Hélène, Göckede, Mathias, Goodrich, Jordan P., Grogan, Paul, Helbig, Manuel, Jafarov, Elchin E., Jastrow, Julie D., Kalhori, Aram A. M., Kim, Yongwon, Kimball, John S., Kutzbach, Lars, Lara, Mark J., Larsen, Klaus S., Lee, Bang-Yong, Liu, Zhihua, Loranty, Michael M., Lund, Magnus, Lupascu, Massimo, Madani, Nima, Malhotra, Avni, Matamala, Roser, McFarland, Jack, McGuire, A. David, Michelsen, Anders, Minions, Christina, Oechel, Walter C., Olefeldt, David, Parmentier, Frans-Jan W., Pirk, Norbert, Poulter, Ben, Quinton, William, Rezanezhad, Fereidoun, Risk, David, Sachs, Torsten, Schaefer, Kevin, Schmidt, Niels M., Schuur, Edward A. G., Semenchuk, Philipp R., Shaver, Gaius, Sonnentag, Oliver, Starr, Gregory, Treat, Claire C., Waldrop, Mark P., Wang, Yihui, Welker, Jeffrey, Wille, Christian, Xu, Xiaofeng, Zhang, Zhen, Zhuang, Qianlai, Zona, Donatella, Natali, Susan M., Watts, Jennifer D., Rogers, Brendan M., Potter, Stefano, Ludwig, Sarah M., Selbmann, Anne-Katrin, Sullivan, Patrick F., Abbott, Benjamin W., Arndt, Kyle A., Birch, Leah, Björkman, Mats P., Bloom, A. Anthony, Celis, Gerardo, Christensen, Torben R., Christiansen, Casper T., Commane, Roisin, Cooper, Elisabeth J., Crill, Patrick, Czimczik, Claudia, Davydov, Sergey, Du, Jinyang, Egan, Jocelyn E., Elberling, Bo, Euskirchen, Eugenie S., Friborg, Thomas, Genet, Hélène, Göckede, Mathias, Goodrich, Jordan P., Grogan, Paul, Helbig, Manuel, Jafarov, Elchin E., Jastrow, Julie D., Kalhori, Aram A. M., Kim, Yongwon, Kimball, John S., Kutzbach, Lars, Lara, Mark J., Larsen, Klaus S., Lee, Bang-Yong, Liu, Zhihua, Loranty, Michael M., Lund, Magnus, Lupascu, Massimo, Madani, Nima, Malhotra, Avni, Matamala, Roser, McFarland, Jack, McGuire, A. David, Michelsen, Anders, Minions, Christina, Oechel, Walter C., Olefeldt, David, Parmentier, Frans-Jan W., Pirk, Norbert, Poulter, Ben, Quinton, William, Rezanezhad, Fereidoun, Risk, David, Sachs, Torsten, Schaefer, Kevin, Schmidt, Niels M., Schuur, Edward A. G., Semenchuk, Philipp R., Shaver, Gaius, Sonnentag, Oliver, Starr, Gregory, Treat, Claire C., Waldrop, Mark P., Wang, Yihui, Welker, Jeffrey, Wille, Christian, Xu, Xiaofeng, Zhang, Zhen, Zhuang, Qianlai, and Zona, Donatella
Abstract: Recent warming in the Arctic, which has been amplified during the winter(1-3), greatly enhances microbial decomposition of soil organic matter and subsequent release of carbon dioxide (CO2)(4). However, the amount of CO2 released in winter is not known and has not been well represented by ecosystem models or empirically based estimates(5,6). Here we synthesize regional in situ observations of CO2 flux from Arctic and boreal soils to assess current and future winter carbon losses from the northern permafrost domain. We estimate a contemporary loss of 1,662 TgC per year from the permafrost region during the winter season (October-April). This loss is greater than the average growing season carbon uptake for this region estimated from process models (-1,032 TgC per year). Extending model predictions to warmer conditions up to 2100 indicates that winter CO2 emissions will increase 17% under a moderate mitigation scenario-Representative Concentration Pathway 4.5-and 41% under business-as-usual emissions scenario-Representative Concentration Pathway 8.5. Our results provide a baseline for winter CO2 emissions from northern terrestrial regions and indicate that enhanced soil CO2 loss due to winter warming may offset growing season carbon uptake under future climatic conditions.
Published: 2019
Full Text: View/download PDF

18. Large loss of CO2 in winter observed across the northern permafrost region.

Author: Natali, Susan M, Natali, Susan M, Watts, Jennifer D, Rogers, Brendan M, Potter, Stefano, Ludwig, Sarah M, Selbmann, Anne-Katrin, Sullivan, Patrick F, Abbott, Benjamin W, Arndt, Kyle A, Birch, Leah, Björkman, Mats P, Bloom, A Anthony, Celis, Gerardo, Christensen, Torben R, Christiansen, Casper T, Commane, Roisin, Cooper, Elisabeth J, Crill, Patrick, Czimczik, Claudia, Davydov, Sergey, Du, Jinyang, Egan, Jocelyn E, Elberling, Bo, Euskirchen, Eugenie S, Friborg, Thomas, Genet, Hélène, Göckede, Mathias, Goodrich, Jordan P, Grogan, Paul, Helbig, Manuel, Jafarov, Elchin E, Jastrow, Julie D, Kalhori, Aram AM, Kim, Yongwon, Kimball, John, Kutzbach, Lars, Lara, Mark J, Larsen, Klaus S, Lee, Bang-Yong, Liu, Zhihua, Loranty, Michael M, Lund, Magnus, Lupascu, Massimo, Madani, Nima, Malhotra, Avni, Matamala, Roser, McFarland, Jack, McGuire, A David, Michelsen, Anders, Minions, Christina, Oechel, Walter C, Olefeldt, David, Parmentier, Frans-Jan W, Pirk, Norbert, Poulter, Ben, Quinton, William, Rezanezhad, Fereidoun, Risk, David, Sachs, Torsten, Schaefer, Kevin, Schmidt, Niels M, Schuur, Edward AG, Semenchuk, Philipp R, Shaver, Gaius, Sonnentag, Oliver, Starr, Gregory, Treat, Claire C, Waldrop, Mark P, Wang, Yihui, Welker, Jeffrey, Wille, Christian, Xu, Xiaofeng, Zhang, Zhen, Zhuang, Qianlai, Zona, Donatella, Natali, Susan M, Natali, Susan M, Watts, Jennifer D, Rogers, Brendan M, Potter, Stefano, Ludwig, Sarah M, Selbmann, Anne-Katrin, Sullivan, Patrick F, Abbott, Benjamin W, Arndt, Kyle A, Birch, Leah, Björkman, Mats P, Bloom, A Anthony, Celis, Gerardo, Christensen, Torben R, Christiansen, Casper T, Commane, Roisin, Cooper, Elisabeth J, Crill, Patrick, Czimczik, Claudia, Davydov, Sergey, Du, Jinyang, Egan, Jocelyn E, Elberling, Bo, Euskirchen, Eugenie S, Friborg, Thomas, Genet, Hélène, Göckede, Mathias, Goodrich, Jordan P, Grogan, Paul, Helbig, Manuel, Jafarov, Elchin E, Jastrow, Julie D, Kalhori, Aram AM, Kim, Yongwon, Kimball, John, Kutzbach, Lars, Lara, Mark J, Larsen, Klaus S, Lee, Bang-Yong, Liu, Zhihua, Loranty, Michael M, Lund, Magnus, Lupascu, Massimo, Madani, Nima, Malhotra, Avni, Matamala, Roser, McFarland, Jack, McGuire, A David, Michelsen, Anders, Minions, Christina, Oechel, Walter C, Olefeldt, David, Parmentier, Frans-Jan W, Pirk, Norbert, Poulter, Ben, Quinton, William, Rezanezhad, Fereidoun, Risk, David, Sachs, Torsten, Schaefer, Kevin, Schmidt, Niels M, Schuur, Edward AG, Semenchuk, Philipp R, Shaver, Gaius, Sonnentag, Oliver, Starr, Gregory, Treat, Claire C, Waldrop, Mark P, Wang, Yihui, Welker, Jeffrey, Wille, Christian, Xu, Xiaofeng, Zhang, Zhen, Zhuang, Qianlai, and Zona, Donatella
Abstract: Recent warming in the Arctic, which has been amplified during the winter1-3, greatly enhances microbial decomposition of soil organic matter and subsequent release of carbon dioxide (CO2)4. However, the amount of CO2 released in winter is highly uncertain and has not been well represented by ecosystem models or by empirically-based estimates5,6. Here we synthesize regional in situ observations of CO2 flux from arctic and boreal soils to assess current and future winter carbon losses from the northern permafrost domain. We estimate a contemporary loss of 1662 Tg C yr-1 from the permafrost region during the winter season (October through April). This loss is greater than the average growing season carbon uptake for this region estimated from process models (-1032 Tg C yr-1). Extending model predictions to warmer conditions in 2100 indicates that winter CO2 emissions will increase 17% under a moderate mitigation scenario-Representative Concentration Pathway (RCP) 4.5-and 41% under business-as-usual emissions scenario-RCP 8.5. Our results provide a new baseline for winter CO2 emissions from northern terrestrial regions and indicate that enhanced soil CO2 loss due to winter warming may offset growing season carbon uptake under future climatic conditions.
Published: 2019

19. FLUXNET-CH4 Synthesis Activity:Objectives, Observations, and Future Directions

Author: Knox, Sara H., Jackson, Robert B., Poulter, Benjamin, McNicol, Gavin, Fluet-Chouinard, Etienne, Zhang, Zhen, Hugelius, Gustaf, Bousquet, Philippe, Canadell, Josep G., Saunois, Marielle, Papale, Dario, Chu, Housen, Keenan, Trevor F., Baldocchi, Dennis, Torn, Margaret S., Mammarella, Ivan, Trotta, Carlo, Aurela, Mika, Bohrer, Gil, Campbell, David, I, Cescatti, Alessandro, Chamberlain, Samuel, Chen, Jiquan, Chen, Weinan, Dengel, Sigrid, Desai, Ankur R., Euskirchen, Eugenie, Friborg, Thomas, Gasbarra, Daniele, Goded, Ignacio, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Hirano, Takashi, Hollinger, David Y., Iwata, Hiroki, Kang, Minseok, Klatt, Janina, Krauss, Ken W., Kutzbach, Lars, Lohila, Annalea, Mitra, Bhaskar, Morin, Timothy H., Nilsson, Mats B., Niu, Shuli, Noormets, Asko, Oechel, Walter C., Peichl, Matthias, Peltola, Olli, Reba, Michele L., Richardson, Andrew D., Runkle, Benjamin R. K., Ryu, Youngryel, Sachs, Torsten, Schaefer, Karina V. R., Schmid, Hans Peter, Shurpali, Narasinha, Sonnentag, Oliver, Tang, Angela C., I, Ueyama, Masahito, Vargas, Rodrigo, Vesala, Timo, Ward, Eric J., Windham-Myers, Lisamarie, Wohlfahrt, Georg, Zona, Donatella, Knox, Sara H., Jackson, Robert B., Poulter, Benjamin, McNicol, Gavin, Fluet-Chouinard, Etienne, Zhang, Zhen, Hugelius, Gustaf, Bousquet, Philippe, Canadell, Josep G., Saunois, Marielle, Papale, Dario, Chu, Housen, Keenan, Trevor F., Baldocchi, Dennis, Torn, Margaret S., Mammarella, Ivan, Trotta, Carlo, Aurela, Mika, Bohrer, Gil, Campbell, David, I, Cescatti, Alessandro, Chamberlain, Samuel, Chen, Jiquan, Chen, Weinan, Dengel, Sigrid, Desai, Ankur R., Euskirchen, Eugenie, Friborg, Thomas, Gasbarra, Daniele, Goded, Ignacio, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Hirano, Takashi, Hollinger, David Y., Iwata, Hiroki, Kang, Minseok, Klatt, Janina, Krauss, Ken W., Kutzbach, Lars, Lohila, Annalea, Mitra, Bhaskar, Morin, Timothy H., Nilsson, Mats B., Niu, Shuli, Noormets, Asko, Oechel, Walter C., Peichl, Matthias, Peltola, Olli, Reba, Michele L., Richardson, Andrew D., Runkle, Benjamin R. K., Ryu, Youngryel, Sachs, Torsten, Schaefer, Karina V. R., Schmid, Hans Peter, Shurpali, Narasinha, Sonnentag, Oliver, Tang, Angela C., I, Ueyama, Masahito, Vargas, Rodrigo, Vesala, Timo, Ward, Eric J., Windham-Myers, Lisamarie, Wohlfahrt, Georg, and Zona, Donatella
Published: 2019

20. Large loss of CO2 in winter observed across the northern permafrost region:[incl. correction]

Author: Natali, Susan M., Watts, Jennifer D., Rogers, Brendan M., Potter, Stefano, Ludwig, Sarah M., Selbmann, Anne-Katrin, Sullivan, Patrick F., Abbott, Benjamin W., Arndt, Kyle A., Birch, Leah, Björkman, Mats P., Bloom, A. Anthony, Celis, Gerardo, Christensen, Torben R., Christiansen, Casper T., Commane, Roisin, Cooper, Elisabeth J., Crill, Patrick, Czimczik, Claudia, Davydov, Sergey P., Du, Jinyang, Egan, Jocelyn E., Elberling, Bo, Euskirchen, Eugenie S., Friborg, Thomas, Genet, Hélène, Göckede, Mathias, Goodrich, Jordan P., Grogan, Paul, Helbig, Manuel, Jafarov, Elchin E., Jastrow, Julie D., Kalhori, Aram A. M., Kim, Yongwon, Kimball, John S., Kutzbach, Lars, Lara, J. Mark, Larsen, Klaus Steenberg, Lee, Bang-Yong, Liu, Zhihua, Loranty, Michael M., Lund, Magnus, Lupascu, Massimo, Madani, Nima, Malhotra, Avni, Matamala, Roser, McFarland, Jack, McGuire, A. David, Michelsen, Anders, Minions, Christina, Oechel, Walter C., Olefeldt, David, Parmentier, Frans-Jan W., Pirk, Norbert, Poulter, Ben, Quinton, William, Rezanezhad, Fereidoun, Risk, David, Sachs, Torsten, Schaefer, Kevin, M. Schmidt, Niels, Schuur, Edward A.G., Semenchuk, Philipp R., Shaver, Gaius R., Sonnentag, Oliver, Starr, Gregory, Treat, Claire C., Waldrop, Mark P., Wang, Yihui, Welker, Jeffrey M., Wille, Christian, Xue, Xiaofeng, Zhang, Zhen, Zhuang, Qianlai, Zona, Donatella, Natali, Susan M., Watts, Jennifer D., Rogers, Brendan M., Potter, Stefano, Ludwig, Sarah M., Selbmann, Anne-Katrin, Sullivan, Patrick F., Abbott, Benjamin W., Arndt, Kyle A., Birch, Leah, Björkman, Mats P., Bloom, A. Anthony, Celis, Gerardo, Christensen, Torben R., Christiansen, Casper T., Commane, Roisin, Cooper, Elisabeth J., Crill, Patrick, Czimczik, Claudia, Davydov, Sergey P., Du, Jinyang, Egan, Jocelyn E., Elberling, Bo, Euskirchen, Eugenie S., Friborg, Thomas, Genet, Hélène, Göckede, Mathias, Goodrich, Jordan P., Grogan, Paul, Helbig, Manuel, Jafarov, Elchin E., Jastrow, Julie D., Kalhori, Aram A. M., Kim, Yongwon, Kimball, John S., Kutzbach, Lars, Lara, J. Mark, Larsen, Klaus Steenberg, Lee, Bang-Yong, Liu, Zhihua, Loranty, Michael M., Lund, Magnus, Lupascu, Massimo, Madani, Nima, Malhotra, Avni, Matamala, Roser, McFarland, Jack, McGuire, A. David, Michelsen, Anders, Minions, Christina, Oechel, Walter C., Olefeldt, David, Parmentier, Frans-Jan W., Pirk, Norbert, Poulter, Ben, Quinton, William, Rezanezhad, Fereidoun, Risk, David, Sachs, Torsten, Schaefer, Kevin, M. Schmidt, Niels, Schuur, Edward A.G., Semenchuk, Philipp R., Shaver, Gaius R., Sonnentag, Oliver, Starr, Gregory, Treat, Claire C., Waldrop, Mark P., Wang, Yihui, Welker, Jeffrey M., Wille, Christian, Xue, Xiaofeng, Zhang, Zhen, Zhuang, Qianlai, and Zona, Donatella
Published: 2019

21. Large loss of CO2 in winter observed across the northern permafrost region.

Author: Natali, Susan M, Natali, Susan M, Watts, Jennifer D, Rogers, Brendan M, Potter, Stefano, Ludwig, Sarah M, Selbmann, Anne-Katrin, Sullivan, Patrick F, Abbott, Benjamin W, Arndt, Kyle A, Birch, Leah, Björkman, Mats P, Bloom, A Anthony, Celis, Gerardo, Christensen, Torben R, Christiansen, Casper T, Commane, Roisin, Cooper, Elisabeth J, Crill, Patrick, Czimczik, Claudia, Davydov, Sergey, Du, Jinyang, Egan, Jocelyn E, Elberling, Bo, Euskirchen, Eugenie S, Friborg, Thomas, Genet, Hélène, Göckede, Mathias, Goodrich, Jordan P, Grogan, Paul, Helbig, Manuel, Jafarov, Elchin E, Jastrow, Julie D, Kalhori, Aram AM, Kim, Yongwon, Kimball, John, Kutzbach, Lars, Lara, Mark J, Larsen, Klaus S, Lee, Bang-Yong, Liu, Zhihua, Loranty, Michael M, Lund, Magnus, Lupascu, Massimo, Madani, Nima, Malhotra, Avni, Matamala, Roser, McFarland, Jack, McGuire, A David, Michelsen, Anders, Minions, Christina, Oechel, Walter C, Olefeldt, David, Parmentier, Frans-Jan W, Pirk, Norbert, Poulter, Ben, Quinton, William, Rezanezhad, Fereidoun, Risk, David, Sachs, Torsten, Schaefer, Kevin, Schmidt, Niels M, Schuur, Edward AG, Semenchuk, Philipp R, Shaver, Gaius, Sonnentag, Oliver, Starr, Gregory, Treat, Claire C, Waldrop, Mark P, Wang, Yihui, Welker, Jeffrey, Wille, Christian, Xu, Xiaofeng, Zhang, Zhen, Zhuang, Qianlai, Zona, Donatella, Natali, Susan M, Natali, Susan M, Watts, Jennifer D, Rogers, Brendan M, Potter, Stefano, Ludwig, Sarah M, Selbmann, Anne-Katrin, Sullivan, Patrick F, Abbott, Benjamin W, Arndt, Kyle A, Birch, Leah, Björkman, Mats P, Bloom, A Anthony, Celis, Gerardo, Christensen, Torben R, Christiansen, Casper T, Commane, Roisin, Cooper, Elisabeth J, Crill, Patrick, Czimczik, Claudia, Davydov, Sergey, Du, Jinyang, Egan, Jocelyn E, Elberling, Bo, Euskirchen, Eugenie S, Friborg, Thomas, Genet, Hélène, Göckede, Mathias, Goodrich, Jordan P, Grogan, Paul, Helbig, Manuel, Jafarov, Elchin E, Jastrow, Julie D, Kalhori, Aram AM, Kim, Yongwon, Kimball, John, Kutzbach, Lars, Lara, Mark J, Larsen, Klaus S, Lee, Bang-Yong, Liu, Zhihua, Loranty, Michael M, Lund, Magnus, Lupascu, Massimo, Madani, Nima, Malhotra, Avni, Matamala, Roser, McFarland, Jack, McGuire, A David, Michelsen, Anders, Minions, Christina, Oechel, Walter C, Olefeldt, David, Parmentier, Frans-Jan W, Pirk, Norbert, Poulter, Ben, Quinton, William, Rezanezhad, Fereidoun, Risk, David, Sachs, Torsten, Schaefer, Kevin, Schmidt, Niels M, Schuur, Edward AG, Semenchuk, Philipp R, Shaver, Gaius, Sonnentag, Oliver, Starr, Gregory, Treat, Claire C, Waldrop, Mark P, Wang, Yihui, Welker, Jeffrey, Wille, Christian, Xu, Xiaofeng, Zhang, Zhen, Zhuang, Qianlai, and Zona, Donatella
Abstract: Recent warming in the Arctic, which has been amplified during the winter1-3, greatly enhances microbial decomposition of soil organic matter and subsequent release of carbon dioxide (CO2)4. However, the amount of CO2 released in winter is highly uncertain and has not been well represented by ecosystem models or by empirically-based estimates5,6. Here we synthesize regional in situ observations of CO2 flux from arctic and boreal soils to assess current and future winter carbon losses from the northern permafrost domain. We estimate a contemporary loss of 1662 Tg C yr-1 from the permafrost region during the winter season (October through April). This loss is greater than the average growing season carbon uptake for this region estimated from process models (-1032 Tg C yr-1). Extending model predictions to warmer conditions in 2100 indicates that winter CO2 emissions will increase 17% under a moderate mitigation scenario-Representative Concentration Pathway (RCP) 4.5-and 41% under business-as-usual emissions scenario-RCP 8.5. Our results provide a new baseline for winter CO2 emissions from northern terrestrial regions and indicate that enhanced soil CO2 loss due to winter warming may offset growing season carbon uptake under future climatic conditions.
Published: 2019

22. FLUXNET-CH4 Synthesis Activity:Objectives, Observations, and Future Directions

Author: Knox, Sara H., Jackson, Robert B., Poulter, Benjamin, McNicol, Gavin, Fluet-Chouinard, Etienne, Zhang, Zhen, Hugelius, Gustaf, Bousquet, Philippe, Canadell, Josep G., Saunois, Marielle, Papale, Dario, Chu, Housen, Keenan, Trevor F., Baldocchi, Dennis, Torn, Margaret S., Mammarella, Ivan, Trotta, Carlo, Aurela, Mika, Bohrer, Gil, Campbell, David, I, Cescatti, Alessandro, Chamberlain, Samuel, Chen, Jiquan, Chen, Weinan, Dengel, Sigrid, Desai, Ankur R., Euskirchen, Eugenie, Friborg, Thomas, Gasbarra, Daniele, Goded, Ignacio, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Hirano, Takashi, Hollinger, David Y., Iwata, Hiroki, Kang, Minseok, Klatt, Janina, Krauss, Ken W., Kutzbach, Lars, Lohila, Annalea, Mitra, Bhaskar, Morin, Timothy H., Nilsson, Mats B., Niu, Shuli, Noormets, Asko, Oechel, Walter C., Peichl, Matthias, Peltola, Olli, Reba, Michele L., Richardson, Andrew D., Runkle, Benjamin R. K., Ryu, Youngryel, Sachs, Torsten, Schaefer, Karina V. R., Schmid, Hans Peter, Shurpali, Narasinha, Sonnentag, Oliver, Tang, Angela C., I, Ueyama, Masahito, Vargas, Rodrigo, Vesala, Timo, Ward, Eric J., Windham-Myers, Lisamarie, Wohlfahrt, Georg, Zona, Donatella, Knox, Sara H., Jackson, Robert B., Poulter, Benjamin, McNicol, Gavin, Fluet-Chouinard, Etienne, Zhang, Zhen, Hugelius, Gustaf, Bousquet, Philippe, Canadell, Josep G., Saunois, Marielle, Papale, Dario, Chu, Housen, Keenan, Trevor F., Baldocchi, Dennis, Torn, Margaret S., Mammarella, Ivan, Trotta, Carlo, Aurela, Mika, Bohrer, Gil, Campbell, David, I, Cescatti, Alessandro, Chamberlain, Samuel, Chen, Jiquan, Chen, Weinan, Dengel, Sigrid, Desai, Ankur R., Euskirchen, Eugenie, Friborg, Thomas, Gasbarra, Daniele, Goded, Ignacio, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Hirano, Takashi, Hollinger, David Y., Iwata, Hiroki, Kang, Minseok, Klatt, Janina, Krauss, Ken W., Kutzbach, Lars, Lohila, Annalea, Mitra, Bhaskar, Morin, Timothy H., Nilsson, Mats B., Niu, Shuli, Noormets, Asko, Oechel, Walter C., Peichl, Matthias, Peltola, Olli, Reba, Michele L., Richardson, Andrew D., Runkle, Benjamin R. K., Ryu, Youngryel, Sachs, Torsten, Schaefer, Karina V. R., Schmid, Hans Peter, Shurpali, Narasinha, Sonnentag, Oliver, Tang, Angela C., I, Ueyama, Masahito, Vargas, Rodrigo, Vesala, Timo, Ward, Eric J., Windham-Myers, Lisamarie, Wohlfahrt, Georg, and Zona, Donatella
Published: 2019

23. Large loss of CO2 in winter observed across the northern permafrost region:[incl. correction]

Author: Natali, Susan M., Watts, Jennifer D., Rogers, Brendan M., Potter, Stefano, Ludwig, Sarah M., Selbmann, Anne-Katrin, Sullivan, Patrick F., Abbott, Benjamin W., Arndt, Kyle A., Birch, Leah, Björkman, Mats P., Bloom, A. Anthony, Celis, Gerardo, Christensen, Torben R., Christiansen, Casper T., Commane, Roisin, Cooper, Elisabeth J., Crill, Patrick, Czimczik, Claudia, Davydov, Sergey P., Du, Jinyang, Egan, Jocelyn E., Elberling, Bo, Euskirchen, Eugenie S., Friborg, Thomas, Genet, Hélène, Göckede, Mathias, Goodrich, Jordan P., Grogan, Paul, Helbig, Manuel, Jafarov, Elchin E., Jastrow, Julie D., Kalhori, Aram A. M., Kim, Yongwon, Kimball, John S., Kutzbach, Lars, Lara, J. Mark, Larsen, Klaus Steenberg, Lee, Bang-Yong, Liu, Zhihua, Loranty, Michael M., Lund, Magnus, Lupascu, Massimo, Madani, Nima, Malhotra, Avni, Matamala, Roser, McFarland, Jack, McGuire, A. David, Michelsen, Anders, Minions, Christina, Oechel, Walter C., Olefeldt, David, Parmentier, Frans-Jan W., Pirk, Norbert, Poulter, Ben, Quinton, William, Rezanezhad, Fereidoun, Risk, David, Sachs, Torsten, Schaefer, Kevin, M. Schmidt, Niels, Schuur, Edward A.G., Semenchuk, Philipp R., Shaver, Gaius R., Sonnentag, Oliver, Starr, Gregory, Treat, Claire C., Waldrop, Mark P., Wang, Yihui, Welker, Jeffrey M., Wille, Christian, Xue, Xiaofeng, Zhang, Zhen, Zhuang, Qianlai, Zona, Donatella, Natali, Susan M., Watts, Jennifer D., Rogers, Brendan M., Potter, Stefano, Ludwig, Sarah M., Selbmann, Anne-Katrin, Sullivan, Patrick F., Abbott, Benjamin W., Arndt, Kyle A., Birch, Leah, Björkman, Mats P., Bloom, A. Anthony, Celis, Gerardo, Christensen, Torben R., Christiansen, Casper T., Commane, Roisin, Cooper, Elisabeth J., Crill, Patrick, Czimczik, Claudia, Davydov, Sergey P., Du, Jinyang, Egan, Jocelyn E., Elberling, Bo, Euskirchen, Eugenie S., Friborg, Thomas, Genet, Hélène, Göckede, Mathias, Goodrich, Jordan P., Grogan, Paul, Helbig, Manuel, Jafarov, Elchin E., Jastrow, Julie D., Kalhori, Aram A. M., Kim, Yongwon, Kimball, John S., Kutzbach, Lars, Lara, J. Mark, Larsen, Klaus Steenberg, Lee, Bang-Yong, Liu, Zhihua, Loranty, Michael M., Lund, Magnus, Lupascu, Massimo, Madani, Nima, Malhotra, Avni, Matamala, Roser, McFarland, Jack, McGuire, A. David, Michelsen, Anders, Minions, Christina, Oechel, Walter C., Olefeldt, David, Parmentier, Frans-Jan W., Pirk, Norbert, Poulter, Ben, Quinton, William, Rezanezhad, Fereidoun, Risk, David, Sachs, Torsten, Schaefer, Kevin, M. Schmidt, Niels, Schuur, Edward A.G., Semenchuk, Philipp R., Shaver, Gaius R., Sonnentag, Oliver, Starr, Gregory, Treat, Claire C., Waldrop, Mark P., Wang, Yihui, Welker, Jeffrey M., Wille, Christian, Xue, Xiaofeng, Zhang, Zhen, Zhuang, Qianlai, and Zona, Donatella
Published: 2019

24. Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations

Author: Peltola, Olli, Vesala, Timo, Gao, Yao, Raty, Olle, Alekseychik, Pavel, Aurela, Mika, Chojnicki, Bogdan, Desai, Ankur R., Dolman, Albertus J., Euskirchen, Eugenie S., Friborg, Thomas, Goeckede, Mathias, Helbig, Manuel, Humphreys, Elyn, Jackson, Robert B., Jocher, Georg, Joos, Fortunat, Klatt, Janina, Knox, Sara H., Kowalska, Natalia, Kutzbach, Lars, Lienert, Sebastian, Lohila, Annalea, Mammarella, Ivan, Nadeau, Daniel F., Nilsson, Mats B., Oechel, Walter C., Peichl, Matthias, Pypker, Thomas, Quinton, William, Rinne, Janne, Sachs, Torsten, Samson, Mateusz, Schmid, Hans Peter, Sonnentag, Oliver, Wille, Christian, Zona, Donatella, Aalto, Tuula, Peltola, Olli, Vesala, Timo, Gao, Yao, Raty, Olle, Alekseychik, Pavel, Aurela, Mika, Chojnicki, Bogdan, Desai, Ankur R., Dolman, Albertus J., Euskirchen, Eugenie S., Friborg, Thomas, Goeckede, Mathias, Helbig, Manuel, Humphreys, Elyn, Jackson, Robert B., Jocher, Georg, Joos, Fortunat, Klatt, Janina, Knox, Sara H., Kowalska, Natalia, Kutzbach, Lars, Lienert, Sebastian, Lohila, Annalea, Mammarella, Ivan, Nadeau, Daniel F., Nilsson, Mats B., Oechel, Walter C., Peichl, Matthias, Pypker, Thomas, Quinton, William, Rinne, Janne, Sachs, Torsten, Samson, Mateusz, Schmid, Hans Peter, Sonnentag, Oliver, Wille, Christian, Zona, Donatella, and Aalto, Tuula
Published: 2019

25. Large loss of CO2 in winter observed across the northern permafrost region:[incl. correction]

Author: Natali, Susan M., Watts, Jennifer D., Rogers, Brendan M., Potter, Stefano, Ludwig, Sarah M., Selbmann, Anne-Katrin, Sullivan, Patrick F., Abbott, Benjamin W., Arndt, Kyle A., Birch, Leah, Björkman, Mats P., Bloom, A. Anthony, Celis, Gerardo, Christensen, Torben R., Christiansen, Casper T., Commane, Roisin, Cooper, Elisabeth J., Crill, Patrick, Czimczik, Claudia, Davydov, Sergey P., Du, Jinyang, Egan, Jocelyn E., Elberling, Bo, Euskirchen, Eugenie S., Friborg, Thomas, Genet, Hélène, Göckede, Mathias, Goodrich, Jordan P., Grogan, Paul, Helbig, Manuel, Jafarov, Elchin E., Jastrow, Julie D., Kalhori, Aram A. M., Kim, Yongwon, Kimball, John S., Kutzbach, Lars, Lara, J. Mark, Larsen, Klaus Steenberg, Lee, Bang-Yong, Liu, Zhihua, Loranty, Michael M., Lund, Magnus, Lupascu, Massimo, Madani, Nima, Malhotra, Avni, Matamala, Roser, McFarland, Jack, McGuire, A. David, Michelsen, Anders, Minions, Christina, Oechel, Walter C., Olefeldt, David, Parmentier, Frans-Jan W., Pirk, Norbert, Poulter, Ben, Quinton, William, Rezanezhad, Fereidoun, Risk, David, Sachs, Torsten, Schaefer, Kevin, M. Schmidt, Niels, Schuur, Edward A.G., Semenchuk, Philipp R., Shaver, Gaius R., Sonnentag, Oliver, Starr, Gregory, Treat, Claire C., Waldrop, Mark P., Wang, Yihui, Welker, Jeffrey M., Wille, Christian, Xue, Xiaofeng, Zhang, Zhen, Zhuang, Qianlai, Zona, Donatella, Natali, Susan M., Watts, Jennifer D., Rogers, Brendan M., Potter, Stefano, Ludwig, Sarah M., Selbmann, Anne-Katrin, Sullivan, Patrick F., Abbott, Benjamin W., Arndt, Kyle A., Birch, Leah, Björkman, Mats P., Bloom, A. Anthony, Celis, Gerardo, Christensen, Torben R., Christiansen, Casper T., Commane, Roisin, Cooper, Elisabeth J., Crill, Patrick, Czimczik, Claudia, Davydov, Sergey P., Du, Jinyang, Egan, Jocelyn E., Elberling, Bo, Euskirchen, Eugenie S., Friborg, Thomas, Genet, Hélène, Göckede, Mathias, Goodrich, Jordan P., Grogan, Paul, Helbig, Manuel, Jafarov, Elchin E., Jastrow, Julie D., Kalhori, Aram A. M., Kim, Yongwon, Kimball, John S., Kutzbach, Lars, Lara, J. Mark, Larsen, Klaus Steenberg, Lee, Bang-Yong, Liu, Zhihua, Loranty, Michael M., Lund, Magnus, Lupascu, Massimo, Madani, Nima, Malhotra, Avni, Matamala, Roser, McFarland, Jack, McGuire, A. David, Michelsen, Anders, Minions, Christina, Oechel, Walter C., Olefeldt, David, Parmentier, Frans-Jan W., Pirk, Norbert, Poulter, Ben, Quinton, William, Rezanezhad, Fereidoun, Risk, David, Sachs, Torsten, Schaefer, Kevin, M. Schmidt, Niels, Schuur, Edward A.G., Semenchuk, Philipp R., Shaver, Gaius R., Sonnentag, Oliver, Starr, Gregory, Treat, Claire C., Waldrop, Mark P., Wang, Yihui, Welker, Jeffrey M., Wille, Christian, Xue, Xiaofeng, Zhang, Zhen, Zhuang, Qianlai, and Zona, Donatella
Published: 2019

26. FLUXNET-CH4 Synthesis Activity:Objectives, Observations, and Future Directions

Author: Knox, Sara H., Jackson, Robert B., Poulter, Benjamin, McNicol, Gavin, Fluet-Chouinard, Etienne, Zhang, Zhen, Hugelius, Gustaf, Bousquet, Philippe, Canadell, Josep G., Saunois, Marielle, Papale, Dario, Chu, Housen, Keenan, Trevor F., Baldocchi, Dennis, Torn, Margaret S., Mammarella, Ivan, Trotta, Carlo, Aurela, Mika, Bohrer, Gil, Campbell, David, I, Cescatti, Alessandro, Chamberlain, Samuel, Chen, Jiquan, Chen, Weinan, Dengel, Sigrid, Desai, Ankur R., Euskirchen, Eugenie, Friborg, Thomas, Gasbarra, Daniele, Goded, Ignacio, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Hirano, Takashi, Hollinger, David Y., Iwata, Hiroki, Kang, Minseok, Klatt, Janina, Krauss, Ken W., Kutzbach, Lars, Lohila, Annalea, Mitra, Bhaskar, Morin, Timothy H., Nilsson, Mats B., Niu, Shuli, Noormets, Asko, Oechel, Walter C., Peichl, Matthias, Peltola, Olli, Reba, Michele L., Richardson, Andrew D., Runkle, Benjamin R. K., Ryu, Youngryel, Sachs, Torsten, Schaefer, Karina V. R., Schmid, Hans Peter, Shurpali, Narasinha, Sonnentag, Oliver, Tang, Angela C., I, Ueyama, Masahito, Vargas, Rodrigo, Vesala, Timo, Ward, Eric J., Windham-Myers, Lisamarie, Wohlfahrt, Georg, Zona, Donatella, Knox, Sara H., Jackson, Robert B., Poulter, Benjamin, McNicol, Gavin, Fluet-Chouinard, Etienne, Zhang, Zhen, Hugelius, Gustaf, Bousquet, Philippe, Canadell, Josep G., Saunois, Marielle, Papale, Dario, Chu, Housen, Keenan, Trevor F., Baldocchi, Dennis, Torn, Margaret S., Mammarella, Ivan, Trotta, Carlo, Aurela, Mika, Bohrer, Gil, Campbell, David, I, Cescatti, Alessandro, Chamberlain, Samuel, Chen, Jiquan, Chen, Weinan, Dengel, Sigrid, Desai, Ankur R., Euskirchen, Eugenie, Friborg, Thomas, Gasbarra, Daniele, Goded, Ignacio, Goeckede, Mathias, Heimann, Martin, Helbig, Manuel, Hirano, Takashi, Hollinger, David Y., Iwata, Hiroki, Kang, Minseok, Klatt, Janina, Krauss, Ken W., Kutzbach, Lars, Lohila, Annalea, Mitra, Bhaskar, Morin, Timothy H., Nilsson, Mats B., Niu, Shuli, Noormets, Asko, Oechel, Walter C., Peichl, Matthias, Peltola, Olli, Reba, Michele L., Richardson, Andrew D., Runkle, Benjamin R. K., Ryu, Youngryel, Sachs, Torsten, Schaefer, Karina V. R., Schmid, Hans Peter, Shurpali, Narasinha, Sonnentag, Oliver, Tang, Angela C., I, Ueyama, Masahito, Vargas, Rodrigo, Vesala, Timo, Ward, Eric J., Windham-Myers, Lisamarie, Wohlfahrt, Georg, and Zona, Donatella
Published: 2019

27. Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations

Author: Peltola, Olli, Vesala, Timo, Gao, Yao, Raty, Olle, Alekseychik, Pavel, Aurela, Mika, Chojnicki, Bogdan, Desai, Ankur R., Dolman, Albertus J., Euskirchen, Eugenie S., Friborg, Thomas, Goeckede, Mathias, Helbig, Manuel, Humphreys, Elyn, Jackson, Robert B., Jocher, Georg, Joos, Fortunat, Klatt, Janina, Knox, Sara H., Kowalska, Natalia, Kutzbach, Lars, Lienert, Sebastian, Lohila, Annalea, Mammarella, Ivan, Nadeau, Daniel F., Nilsson, Mats B., Oechel, Walter C., Peichl, Matthias, Pypker, Thomas, Quinton, William, Rinne, Janne, Sachs, Torsten, Samson, Mateusz, Schmid, Hans Peter, Sonnentag, Oliver, Wille, Christian, Zona, Donatella, Aalto, Tuula, Peltola, Olli, Vesala, Timo, Gao, Yao, Raty, Olle, Alekseychik, Pavel, Aurela, Mika, Chojnicki, Bogdan, Desai, Ankur R., Dolman, Albertus J., Euskirchen, Eugenie S., Friborg, Thomas, Goeckede, Mathias, Helbig, Manuel, Humphreys, Elyn, Jackson, Robert B., Jocher, Georg, Joos, Fortunat, Klatt, Janina, Knox, Sara H., Kowalska, Natalia, Kutzbach, Lars, Lienert, Sebastian, Lohila, Annalea, Mammarella, Ivan, Nadeau, Daniel F., Nilsson, Mats B., Oechel, Walter C., Peichl, Matthias, Pypker, Thomas, Quinton, William, Rinne, Janne, Sachs, Torsten, Samson, Mateusz, Schmid, Hans Peter, Sonnentag, Oliver, Wille, Christian, Zona, Donatella, and Aalto, Tuula
Published: 2019

28. Upscaling CH4 fluxes using high-resolution imagery in Arctic tundra ecosystems

Author: Davidson, Scott J; https://orcid.org/0000-0001-8327-2121, Santos, Maria J, Sloan, Victoria L, Reuss-Schmidt, Kassandra, Phoenix, Gareth K, Oechel, Walter C; https://orcid.org/0000-0002-3504-026X, Zona, Donatella, Davidson, Scott J; https://orcid.org/0000-0001-8327-2121, Santos, Maria J, Sloan, Victoria L, Reuss-Schmidt, Kassandra, Phoenix, Gareth K, Oechel, Walter C; https://orcid.org/0000-0002-3504-026X, and Zona, Donatella
Abstract: Arctic tundra ecosystems are a major source of methane (CH4), the variability of which is affected by local environmental and climatic factors, such as water table depth, microtopography, and the spatial heterogeneity of the vegetation communities present. There is a disconnect between the measurement scales for CH4 fluxes, which can be measured with chambers at one-meter resolution and eddy covariance towers at 100–1000 m, whereas model estimates are typically made at the ~100 km scale. Therefore, it is critical to upscale site level measurements to the larger scale for model comparison. As vegetation has a critical role in explaining the variability of CH4 fluxes across the tundra landscape, we tested whether remotely-sensed maps of vegetation could be used to upscale fluxes to larger scales. The objectives of this study are to compare four different methods for mapping and two methods for upscaling plot-level CH4 emissions to the measurements from EC towers. We show that linear discriminant analysis (LDA) provides the most accurate representation of the tundra vegetation within the EC tower footprints (classification accuracies of between 65% and 88%). The upscaled CH4 emissions using the areal fraction of the vegetation communities showed a positive correlation (between 0.57 and 0.81) with EC tower measurements, irrespective of the mapping method. The area-weighted footprint model outperformed the simple area-weighted method, achieving a correlation of 0.88 when using the vegetation map produced with the LDA classifier. These results suggest that the high spatial heterogeneity of the tundra vegetation has a strong impact on the flux, and variation indicates the potential impact of environmental or climatic parameters on the fluxes. Nonetheless, assimilating remotely-sensed vegetation maps of tundra in a footprint model was successful in upscaling fluxes across scales.
Published: 2017

29. Terrestrial carbon balance in a drier world: the effects of water availability in southwestern North America.

Author: Biederman, Joel A, Biederman, Joel A, Scott, Russell L, Goulden, Michael L, Vargas, Rodrigo, Litvak, Marcy E, Kolb, Thomas E, Yepez, Enrico A, Oechel, Walter C, Blanken, Peter D, Bell, Tom W, Garatuza-Payan, Jaime, Maurer, Gregory E, Dore, Sabina, Burns, Sean P, Biederman, Joel A, Biederman, Joel A, Scott, Russell L, Goulden, Michael L, Vargas, Rodrigo, Litvak, Marcy E, Kolb, Thomas E, Yepez, Enrico A, Oechel, Walter C, Blanken, Peter D, Bell, Tom W, Garatuza-Payan, Jaime, Maurer, Gregory E, Dore, Sabina, and Burns, Sean P
Abstract: Global modeling efforts indicate semiarid regions dominate the increasing trend and interannual variation of net CO2 exchange with the atmosphere, mainly driven by water availability. Many semiarid regions are expected to undergo climatic drying, but the impacts on net CO2 exchange are poorly understood due to limited semiarid flux observations. Here we evaluated 121 site-years of annual eddy covariance measurements of net and gross CO2 exchange (photosynthesis and respiration), precipitation, and evapotranspiration (ET) in 21 semiarid North American ecosystems with an observed range of 100 - 1000 mm in annual precipitation and records of 4-9 years each. In addition to evaluating spatial relationships among CO2 and water fluxes across sites, we separately quantified site-level temporal relationships, representing sensitivity to interannual variation. Across the climatic and ecological gradient, photosynthesis showed a saturating spatial relationship to precipitation, whereas the photosynthesis-ET relationship was linear, suggesting ET was a better proxy for water available to drive CO2 exchanges after hydrologic losses. Both photosynthesis and respiration showed similar site-level sensitivity to interannual changes in ET among the 21 ecosystems. Furthermore, these temporal relationships were not different from the spatial relationships of long-term mean CO2 exchanges with climatic ET. Consequently, a hypothetical 100-mm change in ET, whether short term or long term, was predicted to alter net ecosystem production (NEP) by 64 gCm(-2) yr(-1). Most of the unexplained NEP variability was related to persistent, site-specific function, suggesting prioritization of research on slow-changing controls. Common temporal and spatial sensitivity to water availability increases our confidence that site-level responses to interannual weather can be extrapolated for prediction of CO2 exchanges over decadal and longer timescales relevant to societal response to climate change.
Published: 2016

30. Potential and limitations of inferring ecosystem photosynthetic capacity from leaf functional traits

Author: University of Helsinki, Department of Physics, Musavi, Talie, Migliavacca, Mirco, van de Weg, Martine Janet, Kattge, Jens, Wohlfahrt, Georg, van Bodegom, Peter M., Reichstein, Markus, Bahn, Michael, Carrara, Arnaud, Domingues, Tomas F., Gavazzi, Michael, Gianelle, Damiano, Gimeno, Cristina, Granier, Andre, Gruening, Carsten, Havrankova, Katerina, Herbst, Mathias, Hrynkiw, Charmaine, Kalhori, Aram, Kaminski, Thomas, Klumpp, Katja, Kolari, Pasi, Longdoz, Bernard, Minerbi, Stefano, Montagnani, Leonardo, Moors, Eddy, Oechel, Walter C., Reich, Peter B., Rohatyn, Shani, Rossi, Alessandra, Rotenberg, Eyal, Varlagin, Andrej, Wilkinson, Matthew, Wirth, Christian, Mahecha, Miguel D., University of Helsinki, Department of Physics, Musavi, Talie, Migliavacca, Mirco, van de Weg, Martine Janet, Kattge, Jens, Wohlfahrt, Georg, van Bodegom, Peter M., Reichstein, Markus, Bahn, Michael, Carrara, Arnaud, Domingues, Tomas F., Gavazzi, Michael, Gianelle, Damiano, Gimeno, Cristina, Granier, Andre, Gruening, Carsten, Havrankova, Katerina, Herbst, Mathias, Hrynkiw, Charmaine, Kalhori, Aram, Kaminski, Thomas, Klumpp, Katja, Kolari, Pasi, Longdoz, Bernard, Minerbi, Stefano, Montagnani, Leonardo, Moors, Eddy, Oechel, Walter C., Reich, Peter B., Rohatyn, Shani, Rossi, Alessandra, Rotenberg, Eyal, Varlagin, Andrej, Wilkinson, Matthew, Wirth, Christian, and Mahecha, Miguel D.
Abstract: The aim of this study was to systematically analyze the potential and limitations of using plant functional trait observations from global databases versus in situ data to improve our understanding of vegetation impacts on ecosystem functional properties (EFPs). Using ecosystem photosynthetic capacity as an example, we first provide an objective approach to derive robust EFP estimates from gross primary productivity (GPP) obtained from eddy covariance flux measurements. Second, we investigate the impact of synchronizing EFPs and plant functional traits in time and space to evaluate their relationships, and the extent to which we can benefit from global plant trait databases to explain the variability of ecosystem photosynthetic capacity. Finally, we identify a set of plant functional traits controlling ecosystem photosynthetic capacity at selected sites. Suitable estimates of the ecosystem photosynthetic capacity can be derived from light response curve of GPP responding to radiation (photosynthetically active radiation or absorbed photosynthetically active radiation). Although the effect of climate is minimized in these calculations, the estimates indicate substantial interannual variation of the photosynthetic capacity, even after removing site-years with confounding factors like disturbance such as fire events. The relationships between foliar nitrogen concentration and ecosystem photosynthetic capacity are tighter when both of the measurements are synchronized in space and time. When using multiple plant traits simultaneously as predictors for ecosystem photosynthetic capacity variation, the combination of leaf carbon to nitrogen ratio with leaf phosphorus content explains the variance of ecosystem photosynthetic capacity best (adjusted R-2 = 0.55). Overall, this study provides an objective approach to identify links between leaf level traits and canopy level processes and highlights the relevance of the dynamic nature of ecosystems. Synchronizing measurements o
Published: 2016

31. Terrestrial carbon balance in a drier world: the effects of water availability in southwestern North America.

Author: Biederman, Joel A, Biederman, Joel A, Scott, Russell L, Goulden, Michael L, Vargas, Rodrigo, Litvak, Marcy E, Kolb, Thomas E, Yepez, Enrico A, Oechel, Walter C, Blanken, Peter D, Bell, Tom W, Garatuza-Payan, Jaime, Maurer, Gregory E, Dore, Sabina, Burns, Sean P, Biederman, Joel A, Biederman, Joel A, Scott, Russell L, Goulden, Michael L, Vargas, Rodrigo, Litvak, Marcy E, Kolb, Thomas E, Yepez, Enrico A, Oechel, Walter C, Blanken, Peter D, Bell, Tom W, Garatuza-Payan, Jaime, Maurer, Gregory E, Dore, Sabina, and Burns, Sean P
Abstract: Global modeling efforts indicate semiarid regions dominate the increasing trend and interannual variation of net CO2 exchange with the atmosphere, mainly driven by water availability. Many semiarid regions are expected to undergo climatic drying, but the impacts on net CO2 exchange are poorly understood due to limited semiarid flux observations. Here we evaluated 121 site-years of annual eddy covariance measurements of net and gross CO2 exchange (photosynthesis and respiration), precipitation, and evapotranspiration (ET) in 21 semiarid North American ecosystems with an observed range of 100 - 1000 mm in annual precipitation and records of 4-9 years each. In addition to evaluating spatial relationships among CO2 and water fluxes across sites, we separately quantified site-level temporal relationships, representing sensitivity to interannual variation. Across the climatic and ecological gradient, photosynthesis showed a saturating spatial relationship to precipitation, whereas the photosynthesis-ET relationship was linear, suggesting ET was a better proxy for water available to drive CO2 exchanges after hydrologic losses. Both photosynthesis and respiration showed similar site-level sensitivity to interannual changes in ET among the 21 ecosystems. Furthermore, these temporal relationships were not different from the spatial relationships of long-term mean CO2 exchanges with climatic ET. Consequently, a hypothetical 100-mm change in ET, whether short term or long term, was predicted to alter net ecosystem production (NEP) by 64 gCm(-2) yr(-1). Most of the unexplained NEP variability was related to persistent, site-specific function, suggesting prioritization of research on slow-changing controls. Common temporal and spatial sensitivity to water availability increases our confidence that site-level responses to interannual weather can be extrapolated for prediction of CO2 exchanges over decadal and longer timescales relevant to societal response to climate change.
Published: 2016

32. Potential and limitations of inferring ecosystem photosynthetic capacity from leaf functional traits

Author: Musavi, Talie, Migliavacca, Mirco, van de Weg, Martine Janet, Kattge, Jens, Wohlfahrt, Georg, van Bodegom, Peter M., Reichstein, Markus, Bahn, Michael, Carrara, Arnaud, Domingues, Tomas F., Gavazzi, Michael, Gianelle, Damiano, Gimeno, Cristina, Granier, André, Gruening, Carsten, Havránková, Kateřina, Herbst, Mathias, Hrynkiw, Charmaine, Kalhori, Aram, Kaminski, Thomas, Klumpp, Katja, Kolari, Pasi, Longdoz, Bernard, Minerbi, Stefano, Montagnani, Leonardo, Moors, Eddy, Oechel, Walter C., Reich, Peter B., Rohatyn, Shani, Rossi, Alessandra, Rotenberg, Eyal, Varlagin, Andrej, Wilkinson, Matthew, Wirth, Christian, Mahecha, Miguel D., Musavi, Talie, Migliavacca, Mirco, van de Weg, Martine Janet, Kattge, Jens, Wohlfahrt, Georg, van Bodegom, Peter M., Reichstein, Markus, Bahn, Michael, Carrara, Arnaud, Domingues, Tomas F., Gavazzi, Michael, Gianelle, Damiano, Gimeno, Cristina, Granier, André, Gruening, Carsten, Havránková, Kateřina, Herbst, Mathias, Hrynkiw, Charmaine, Kalhori, Aram, Kaminski, Thomas, Klumpp, Katja, Kolari, Pasi, Longdoz, Bernard, Minerbi, Stefano, Montagnani, Leonardo, Moors, Eddy, Oechel, Walter C., Reich, Peter B., Rohatyn, Shani, Rossi, Alessandra, Rotenberg, Eyal, Varlagin, Andrej, Wilkinson, Matthew, Wirth, Christian, and Mahecha, Miguel D.
Abstract: The aim of this study was to systematically analyze the potential and limitations of using plant functional trait observations from global databases versus in situ data to improve our understanding of vegetation impacts on ecosystem functional properties (EFPs). Using ecosystem photosynthetic capacity as an example, we first provide an objective approach to derive robust EFP estimates from gross primary productivity (GPP) obtained from eddy covariance flux measurements. Second, we investigate the impact of synchronizing EFPs and plant functional traits in time and space to evaluate their relationships, and the extent to which we can benefit from global plant trait databases to explain the variability of ecosystem photosynthetic capacity. Finally, we identify a set of plant functional traits controlling ecosystem photosynthetic capacity at selected sites. Suitable estimates of the ecosystem photosynthetic capacity can be derived from light response curve of GPP responding to radiation (photosynthetically active radiation or absorbed photosynthetically active radiation). Although the effect of climate is minimized in these calculations, the estimates indicate substantial interannual variation of the photosynthetic capacity, even after removing site-years with confounding factors like disturbance such as fire events. The relationships between foliar nitrogen concentration and ecosystem photosynthetic capacity are tighter when both of the measurements are synchronized in space and time. When using multiple plant traits simultaneously as predictors for ecosystem photosynthetic capacity variation, the combination of leaf carbon to nitrogen ratio with leaf phosphorus content explains the variance of ecosystem photosynthetic capacity best (adjusted R2 = 0.55). Overall, this study provides an objective approach to identify links between leaf level traits and canopy level processes and highlights the relevance of the dynamic nature of ecosystems. Synchronizing measurements of
Published: 2016

33. The uncertain climate footprint of wetlands under human pressure

Author: Petrescu, Ana Maria Roxana, Lohila, Annalea, Tuovinen, Juha-Pekka, Baldocchi, Dennis D., Desai, Ankur R., Roulet, Nigel T., Vesala, Timo, Dolman, Albertus Johannes, Oechel, Walter C., Marcolla, Barbara, Friborg, Thomas, Rinne, Janne, Matthes, Jaclyn Hatala, Merbold, Lutz, Meijide, Ana, Kiely, Gerard, Sottocornola, Matteo, Sachs, Torsten, Zona, Donatella, Varlagin, Andrej, Lai, Derrick Y.F., Veenendaal, Elmar, Parmentier, Frans-Jan W., Skiba, Ute, Lund, Magnus, Hensen, Arjan, van Huissteden, Jacobus, Flanagan, Lawrence B., Shurpali, Narasinha J., Grünwald, Thomas, Humphreys, Elyn R., Jackowicz-Korczyński, Marcin, Aurela, Mika A., Laurila, Tuomas, Grüning, Carsten, Corradi, Chiara A.R., Schrier-Uijl, Arina P., Christensen, Torben R., Tamstorf, Mikkel P., Mastepanov, Mikhail, Martikainen, Pertti J., Verma, Shashi B., Bernhofer, Christian, Cescatti, Alessandro, Petrescu, Ana Maria Roxana, Lohila, Annalea, Tuovinen, Juha-Pekka, Baldocchi, Dennis D., Desai, Ankur R., Roulet, Nigel T., Vesala, Timo, Dolman, Albertus Johannes, Oechel, Walter C., Marcolla, Barbara, Friborg, Thomas, Rinne, Janne, Matthes, Jaclyn Hatala, Merbold, Lutz, Meijide, Ana, Kiely, Gerard, Sottocornola, Matteo, Sachs, Torsten, Zona, Donatella, Varlagin, Andrej, Lai, Derrick Y.F., Veenendaal, Elmar, Parmentier, Frans-Jan W., Skiba, Ute, Lund, Magnus, Hensen, Arjan, van Huissteden, Jacobus, Flanagan, Lawrence B., Shurpali, Narasinha J., Grünwald, Thomas, Humphreys, Elyn R., Jackowicz-Korczyński, Marcin, Aurela, Mika A., Laurila, Tuomas, Grüning, Carsten, Corradi, Chiara A.R., Schrier-Uijl, Arina P., Christensen, Torben R., Tamstorf, Mikkel P., Mastepanov, Mikhail, Martikainen, Pertti J., Verma, Shashi B., Bernhofer, Christian, and Cescatti, Alessandro
Abstract: Significant climate risks are associated with a positive carbon–temperature feedback in northern latitude carbon-rich ecosystems, making an accurate analysis of human impacts on the net greenhouse gas balance of wetlands a priority. Here, we provide a coherent assessment of the climate footprint of a network of wetland sites based on simultaneous and quasi-continuous ecosystem observations of CO2 and CH4 fluxes. Experimental areas are located both in natural and in managed wetlands and cover a wide range of climatic regions, ecosystem types, and management practices. Based on direct observations we predict that sustained CH4 emissions in natural ecosystems are in the long term (i.e., several centuries) typically offset by CO2 uptake, although with large spatiotemporal variability. Using a space-for-time analogy across ecological and climatic gradients, we represent the chronosequence from natural to managed conditions to quantify the “cost” of CH4 emissions for the benefit of net carbon sequestration. With a sustained pulse–response radiative forcing model, we found a significant increase in atmospheric forcing due to land management, in particular for wetland converted to cropland. Our results quantify the role of human activities on the climate footprint of northern wetlands and call for development of active mitigation strategies for managed wetlands and new guidelines of the Intergovernmental Panel on Climate Change (IPCC) accounting for both sustained CH4 emissions and cumulative CO2 exchange.
Published: 2015

34. The uncertain climate footprint of wetlands under human pressure

Author: Petrescu, Ana Maria Roxana, Lohila, Annalea, Tuovinen, Juha-Pekka, Baldocchi, Dennis D., Desai, Ankur R., Roulet, Nigel T., Vesala, Timo, Dolman, Albertus Johannes, Oechel, Walter C., Marcolla, Barbara, Friborg, Thomas, Rinne, Janne, Matthes, Jaclyn Hatala, Merbold, Lutz, Meijide, Ana, Kiely, Gerard, Sottocornola, Matteo, Sachs, Torsten, Zona, Donatella, Varlagin, Andrej, Lai, Derrick Y. F., Veenendaal, Elmar, Parmentier, Frans-Jan W., Skiba, Ute, Lund, Magnus, Hensen, Arjan, Van Huissteden, Jacobus, Flanagan, Lawrence B., Shurpali, Narasinha J., Grunwald, Thomas, Humphreys, Elyn R., Jackowicz-Korczynski, Marcin, Aurela, Mika A., Laurila, Tuomas, Gruning, Carsten, Corradi, Chiara A. R., Schrier-Uijl, Arina P., Christensen, Torben R., Tamstorf, Mikkel P., Mastepanov, Mikhail, Martikainen, Pertti J., Verma, Shashi B., Bernhofer, Christian, Cescatti, Alessandro, Petrescu, Ana Maria Roxana, Lohila, Annalea, Tuovinen, Juha-Pekka, Baldocchi, Dennis D., Desai, Ankur R., Roulet, Nigel T., Vesala, Timo, Dolman, Albertus Johannes, Oechel, Walter C., Marcolla, Barbara, Friborg, Thomas, Rinne, Janne, Matthes, Jaclyn Hatala, Merbold, Lutz, Meijide, Ana, Kiely, Gerard, Sottocornola, Matteo, Sachs, Torsten, Zona, Donatella, Varlagin, Andrej, Lai, Derrick Y. F., Veenendaal, Elmar, Parmentier, Frans-Jan W., Skiba, Ute, Lund, Magnus, Hensen, Arjan, Van Huissteden, Jacobus, Flanagan, Lawrence B., Shurpali, Narasinha J., Grunwald, Thomas, Humphreys, Elyn R., Jackowicz-Korczynski, Marcin, Aurela, Mika A., Laurila, Tuomas, Gruning, Carsten, Corradi, Chiara A. R., Schrier-Uijl, Arina P., Christensen, Torben R., Tamstorf, Mikkel P., Mastepanov, Mikhail, Martikainen, Pertti J., Verma, Shashi B., Bernhofer, Christian, and Cescatti, Alessandro
Published: 2015

35. The uncertain climate footprint of wetlands under human pressure.

Author: Petrescu, Ana Maria Roxana, Petrescu, Ana Maria Roxana, Lohila, Annalea, Tuovinen, Juha-Pekka, Baldocchi, Dennis D, Desai, Ankur R, Roulet, Nigel T, Vesala, Timo, Dolman, Albertus Johannes, Oechel, Walter C, Marcolla, Barbara, Friborg, Thomas, Rinne, Janne, Matthes, Jaclyn Hatala, Merbold, Lutz, Meijide, Ana, Kiely, Gerard, Sottocornola, Matteo, Sachs, Torsten, Zona, Donatella, Varlagin, Andrej, Lai, Derrick YF, Veenendaal, Elmar, Parmentier, Frans-Jan W, Skiba, Ute, Lund, Magnus, Hensen, Arjan, van Huissteden, Jacobus, Flanagan, Lawrence B, Shurpali, Narasinha J, Grünwald, Thomas, Humphreys, Elyn R, Jackowicz-Korczyński, Marcin, Aurela, Mika A, Laurila, Tuomas, Grüning, Carsten, Corradi, Chiara AR, Schrier-Uijl, Arina P, Christensen, Torben R, Tamstorf, Mikkel P, Mastepanov, Mikhail, Martikainen, Pertti J, Verma, Shashi B, Bernhofer, Christian, Cescatti, Alessandro, Petrescu, Ana Maria Roxana, Petrescu, Ana Maria Roxana, Lohila, Annalea, Tuovinen, Juha-Pekka, Baldocchi, Dennis D, Desai, Ankur R, Roulet, Nigel T, Vesala, Timo, Dolman, Albertus Johannes, Oechel, Walter C, Marcolla, Barbara, Friborg, Thomas, Rinne, Janne, Matthes, Jaclyn Hatala, Merbold, Lutz, Meijide, Ana, Kiely, Gerard, Sottocornola, Matteo, Sachs, Torsten, Zona, Donatella, Varlagin, Andrej, Lai, Derrick YF, Veenendaal, Elmar, Parmentier, Frans-Jan W, Skiba, Ute, Lund, Magnus, Hensen, Arjan, van Huissteden, Jacobus, Flanagan, Lawrence B, Shurpali, Narasinha J, Grünwald, Thomas, Humphreys, Elyn R, Jackowicz-Korczyński, Marcin, Aurela, Mika A, Laurila, Tuomas, Grüning, Carsten, Corradi, Chiara AR, Schrier-Uijl, Arina P, Christensen, Torben R, Tamstorf, Mikkel P, Mastepanov, Mikhail, Martikainen, Pertti J, Verma, Shashi B, Bernhofer, Christian, and Cescatti, Alessandro
Abstract: Significant climate risks are associated with a positive carbon-temperature feedback in northern latitude carbon-rich ecosystems, making an accurate analysis of human impacts on the net greenhouse gas balance of wetlands a priority. Here, we provide a coherent assessment of the climate footprint of a network of wetland sites based on simultaneous and quasi-continuous ecosystem observations of CO2 and CH4 fluxes. Experimental areas are located both in natural and in managed wetlands and cover a wide range of climatic regions, ecosystem types, and management practices. Based on direct observations we predict that sustained CH4 emissions in natural ecosystems are in the long term (i.e., several centuries) typically offset by CO2 uptake, although with large spatiotemporal variability. Using a space-for-time analogy across ecological and climatic gradients, we represent the chronosequence from natural to managed conditions to quantify the "cost" of CH4 emissions for the benefit of net carbon sequestration. With a sustained pulse-response radiative forcing model, we found a significant increase in atmospheric forcing due to land management, in particular for wetland converted to cropland. Our results quantify the role of human activities on the climate footprint of northern wetlands and call for development of active mitigation strategies for managed wetlands and new guidelines of the Intergovernmental Panel on Climate Change (IPCC) accounting for both sustained CH4 emissions and cumulative CO2 exchange.
Published: 2015

36. The uncertain climate footprint of wetlands under human pressure

Author: Petrescu, Ana Maria Roxana, Lohila, Annalea, Tuovinen, Juha-Pekka, Baldocchi, Dennis D., Desai, Ankur R., Roulet, Nigel T., Vesala, Timo, Dolman, Albertus Johannes, Oechel, Walter C., Marcolla, Barbara, Friborg, Thomas, Rinne, Janne, Matthes, Jaclyn Hatala, Merbold, Lutz, Meijide, Ana, Kiely, Gerard, Sottocornola, Matteo, Sachs, Torsten, Zona, Donatella, Varlagin, Andrej, Lai, Derrick Y.F., Veenendaal, Elmar, Parmentier, Frans-Jan W., Skiba, Ute, Lund, Magnus, Hensen, Arjan, van Huissteden, Jacobus, Flanagan, Lawrence B., Shurpali, Narasinha J., Grünwald, Thomas, Humphreys, Elyn R., Jackowicz-Korczyński, Marcin, Aurela, Mika A., Laurila, Tuomas, Grüning, Carsten, Corradi, Chiara A.R., Schrier-Uijl, Arina P., Christensen, Torben R., Tamstorf, Mikkel P., Mastepanov, Mikhail, Martikainen, Pertti J., Verma, Shashi B., Bernhofer, Christian, Cescatti, Alessandro, Petrescu, Ana Maria Roxana, Lohila, Annalea, Tuovinen, Juha-Pekka, Baldocchi, Dennis D., Desai, Ankur R., Roulet, Nigel T., Vesala, Timo, Dolman, Albertus Johannes, Oechel, Walter C., Marcolla, Barbara, Friborg, Thomas, Rinne, Janne, Matthes, Jaclyn Hatala, Merbold, Lutz, Meijide, Ana, Kiely, Gerard, Sottocornola, Matteo, Sachs, Torsten, Zona, Donatella, Varlagin, Andrej, Lai, Derrick Y.F., Veenendaal, Elmar, Parmentier, Frans-Jan W., Skiba, Ute, Lund, Magnus, Hensen, Arjan, van Huissteden, Jacobus, Flanagan, Lawrence B., Shurpali, Narasinha J., Grünwald, Thomas, Humphreys, Elyn R., Jackowicz-Korczyński, Marcin, Aurela, Mika A., Laurila, Tuomas, Grüning, Carsten, Corradi, Chiara A.R., Schrier-Uijl, Arina P., Christensen, Torben R., Tamstorf, Mikkel P., Mastepanov, Mikhail, Martikainen, Pertti J., Verma, Shashi B., Bernhofer, Christian, and Cescatti, Alessandro
Abstract: Significant climate risks are associated with a positive carbon–temperature feedback in northern latitude carbon-rich ecosystems, making an accurate analysis of human impacts on the net greenhouse gas balance of wetlands a priority. Here, we provide a coherent assessment of the climate footprint of a network of wetland sites based on simultaneous and quasi-continuous ecosystem observations of CO2 and CH4 fluxes. Experimental areas are located both in natural and in managed wetlands and cover a wide range of climatic regions, ecosystem types, and management practices. Based on direct observations we predict that sustained CH4 emissions in natural ecosystems are in the long term (i.e., several centuries) typically offset by CO2 uptake, although with large spatiotemporal variability. Using a space-for-time analogy across ecological and climatic gradients, we represent the chronosequence from natural to managed conditions to quantify the “cost” of CH4 emissions for the benefit of net carbon sequestration. With a sustained pulse–response radiative forcing model, we found a significant increase in atmospheric forcing due to land management, in particular for wetland converted to cropland. Our results quantify the role of human activities on the climate footprint of northern wetlands and call for development of active mitigation strategies for managed wetlands and new guidelines of the Intergovernmental Panel on Climate Change (IPCC) accounting for both sustained CH4 emissions and cumulative CO2 exchange.
Published: 2015

37. The uncertain climate footprint of wetlands under human pressure

Author: Roxana Petrescu, Ana Maria, Lohila, Annalea, Tuovinen, Juha-Pekka, Baldocchi, Dennis D., Desai, Ankur R., Roulet, Nigel T., Vesala, Timo, Dolman, Albertus Johannes, Oechel, Walter C., Marcolla, Barbara, Friborg, Thomas, Rinne, Janne, Hatala Matthes, Jaclyn, Merbold, Lutz, Meijide, Ana, Kiely, Gerard, Sottocornola, Matteo, Sachs, Torsten, Zona, Donatella, Varlagin, Andrej, Lai, Derrick Y.F., Veenendaal, Elmar, Parmentier, Frans-Jan W., Skiba, Ute, Land, Magnus, Hensen, Arjan, van Huissteden, Jacobus, Flanagan, Lawrence B., Shurpali, Narasinha J., Grünwald, Thomas, Humphreys, Elyn R., Jackowicz-Korczynski, Marcin, Aurela, Mika A., Laurila, Tuomas, Grüning, Carsten, Corradi, Chiara A.R., Schrier-Uijl, Arina P., Christensen, Torben R., Tamstorf, Mikkel P., Mastepanov, Mikhail, Martikainen, Pertti J., Verma, Shashi, Bernhofer, Christian, Cescatti, Alessandro, Roxana Petrescu, Ana Maria, Lohila, Annalea, Tuovinen, Juha-Pekka, Baldocchi, Dennis D., Desai, Ankur R., Roulet, Nigel T., Vesala, Timo, Dolman, Albertus Johannes, Oechel, Walter C., Marcolla, Barbara, Friborg, Thomas, Rinne, Janne, Hatala Matthes, Jaclyn, Merbold, Lutz, Meijide, Ana, Kiely, Gerard, Sottocornola, Matteo, Sachs, Torsten, Zona, Donatella, Varlagin, Andrej, Lai, Derrick Y.F., Veenendaal, Elmar, Parmentier, Frans-Jan W., Skiba, Ute, Land, Magnus, Hensen, Arjan, van Huissteden, Jacobus, Flanagan, Lawrence B., Shurpali, Narasinha J., Grünwald, Thomas, Humphreys, Elyn R., Jackowicz-Korczynski, Marcin, Aurela, Mika A., Laurila, Tuomas, Grüning, Carsten, Corradi, Chiara A.R., Schrier-Uijl, Arina P., Christensen, Torben R., Tamstorf, Mikkel P., Mastepanov, Mikhail, Martikainen, Pertti J., Verma, Shashi, Bernhofer, Christian, and Cescatti, Alessandro
Abstract: Significant climate risks are associated with a positive carbon–temperature feedback in northern latitude carbon-rich ecosystems,making an accurate analysis of human impacts on the net greenhouse gas balance of wetlands a priority. Here, we provide a coherent assessment of the climate footprint of a network of wetland sites based on simultaneous and quasi-continuous ecosystem observations of CO2 and CH4 fluxes. Experimental areas are located both in natural and in managed wetlands and cover a wide range of climatic regions, ecosystem types, and management practices. Based on direct observations we predict that sustained CH4 emissions in natural ecosystems are in the long term (i.e., several centuries) typically offset by CO2 uptake, although with large spatiotemporal variability. Using a space-for-time analogy across ecological and climatic gradients, we represent the chronosequence from natural to managed conditions to quantify the “cost” of CH4 emissions for the benefit of net carbon sequestration. With a sustained pulse– response radiative forcing model, we found a significant increase in atmospheric forcing due to land management, in particular for wetland converted to cropland. Our results quantify the role of human activities on the climate footprint of northern wetlands and call for development of active mitigation strategies for managed wetlands and new guidelines of the Intergovernmental Panel on Climate Change (IPCC) accounting for both sustained CH4 emissions and cumulative CO2 exchange.
Published: 2015

38. Biotic and climatic controls on interannual variability in carbon fluxes across terrestrial ecosystems

Author: Shao, Junjiong, Zhou, Xuhui, Luo, Yiqi, Li, Bo, Aurela, Mika, Billesbach, David, Blanken, Peter D., Bracho, Rosvel, Chen, Jiquan, Fischer, Marc L., Fu, Yuling, Gu, Lianhong, Han, Shijie, He, Yongtao, Kolb, Thomas, Li, Yingnian, Nagy, Zoltan, Niu, Shuli, Oechel, Walter C., Pinter, Krisztina, Shi, Peili, Suyker, Andrew E., Torn, Margaret, Varlagin, Andrej, Wang, Huimin, Yan, Junhua, Yu, Guirui, Zhang, Junhui, Shao, Junjiong, Zhou, Xuhui, Luo, Yiqi, Li, Bo, Aurela, Mika, Billesbach, David, Blanken, Peter D., Bracho, Rosvel, Chen, Jiquan, Fischer, Marc L., Fu, Yuling, Gu, Lianhong, Han, Shijie, He, Yongtao, Kolb, Thomas, Li, Yingnian, Nagy, Zoltan, Niu, Shuli, Oechel, Walter C., Pinter, Krisztina, Shi, Peili, Suyker, Andrew E., Torn, Margaret, Varlagin, Andrej, Wang, Huimin, Yan, Junhua, Yu, Guirui, and Zhang, Junhui
Abstract: Interannual variability (IAV, represented by standard deviation) in net ecosystem exchange of CO2 (NEE) is mainly driven by climatic drivers and biotic variations (i.e., the changes in photosynthetic and respiratory responses to climate), the effects of which are referred to as climatic (CE) and biotic effects (BE), respectively. Evaluating the relative contributions of CE and BE to the IAV in carbon (C) fluxes and understanding their controlling mechanisms are critical in projecting ecosystem changes in the future climate. In this study, we applied statistical methods with flux data from 65 sites located in the Northern Hemisphere to address this issue. Our results showed that the relative contribution of BE (CnBE) and CE (CnCE) to the IAV in NEE was 57%±14% and 43%±14%, respectively. The discrepancy in the CnBE among sites could be largely explained by water balance index (WBI). Across water-stressed ecosystems, the CnBE decreased with increasing aridity (slope = 0.18%mm−1). In addition, the CnBE tended to increase and the uncertainty reduced as time span of available data increased from 5 to 15 years. Inter-site variation of the IAV in NEE mainly resulted from the IAV in BE (72%) compared to that in CE (37%). Interestingly, positive correlations between BE and CE occurred in grasslands and dry ecosystems (r > 0.45, P < 0.05) but not in other ecosystems. These results highlighted the importance of BE in determining the IAV in NEE and the ability of ecosystems to regulate C fluxes under climate change might decline when the ecosystems experience more severe water stress in the future.
Published: 2015

39. The uncertain climate footprint of wetlands under human pressure

Author: Petrescu, Ana Maria Roxana, Lohila, Annalea, Tuovinen, Juha-Pekka, Baldocchi, Dennis D., Desai, Ankur R., Roulet, Nigel T., Vesala, Timo, Dolman, Albertus Johannes, Oechel, Walter C., Marcolla, Barbara, Friborg, Thomas, Rinne, Janne, Matthes, Jaclyn Hatala, Merbold, Lutz, Meijide, Ana, Kiely, Gerard, Sottocornola, Matteo, Sachs, Torsten, Zona, Donatella, Varlagin, Andrej, Lai, Derrick Y. F., Veenendaal, Elmar, Parmentier, Frans-Jan W., Skiba, Ute, Lund, Magnus, Hensen, Arjan, Van Huissteden, Jacobus, Flanagan, Lawrence B., Shurpali, Narasinha J., Grunwald, Thomas, Humphreys, Elyn R., Jackowicz-Korczynski, Marcin, Aurela, Mika A., Laurila, Tuomas, Gruning, Carsten, Corradi, Chiara A. R., Schrier-Uijl, Arina P., Christensen, Torben R., Tamstorf, Mikkel P., Mastepanov, Mikhail, Martikainen, Pertti J., Verma, Shashi B., Bernhofer, Christian, Cescatti, Alessandro, Petrescu, Ana Maria Roxana, Lohila, Annalea, Tuovinen, Juha-Pekka, Baldocchi, Dennis D., Desai, Ankur R., Roulet, Nigel T., Vesala, Timo, Dolman, Albertus Johannes, Oechel, Walter C., Marcolla, Barbara, Friborg, Thomas, Rinne, Janne, Matthes, Jaclyn Hatala, Merbold, Lutz, Meijide, Ana, Kiely, Gerard, Sottocornola, Matteo, Sachs, Torsten, Zona, Donatella, Varlagin, Andrej, Lai, Derrick Y. F., Veenendaal, Elmar, Parmentier, Frans-Jan W., Skiba, Ute, Lund, Magnus, Hensen, Arjan, Van Huissteden, Jacobus, Flanagan, Lawrence B., Shurpali, Narasinha J., Grunwald, Thomas, Humphreys, Elyn R., Jackowicz-Korczynski, Marcin, Aurela, Mika A., Laurila, Tuomas, Gruning, Carsten, Corradi, Chiara A. R., Schrier-Uijl, Arina P., Christensen, Torben R., Tamstorf, Mikkel P., Mastepanov, Mikhail, Martikainen, Pertti J., Verma, Shashi B., Bernhofer, Christian, and Cescatti, Alessandro
Published: 2015

40. Annual patterns and budget of CO2 flux in an Arctic tussock tundra ecosystem

Author: Oechel, Walter C., Laskowski, Cheryl A., Burba, George, Gioli, Beniamino, Kalhori, Aram A. M., Oechel, Walter C., Laskowski, Cheryl A., Burba, George, Gioli, Beniamino, and Kalhori, Aram A. M.
Abstract: The functioning of Arctic ecosystems is not only critically affected by climate change, but it also has the potential for major positive feedback on climate. There is, however, relatively little information on the role, patterns, and vulnerabilities of CO2 fluxes during the nonsummer seasons in Arctic ecosystems. Presented here is a year-round study of CO2 fluxes in an Alaskan Arctic tussock tundra ecosystem, and key environmental controls on these fluxes. Important controls on fluxes vary by season. This paper also presents a new empirical quantification of seasons in the Arctic based on net radiation. The fluxes were computed using standard FluxNet methodology and corrected using standard Webb-Pearman-Leuning density terms adjusted for influences of open-path instrument surface heating. The results showed that the nonsummer season comprises a significant source of carbon to the atmosphere. The summer period was a net sink of 24.3 g Cm-2, while the nonsummer seasons released 37.9 g Cm-2. This release is 1.6 times the summer uptake, resulting in a net annual source of +13.6 g Cm-2 to the atmosphere. These findings support early observations of a change in this particular region of the Arctic from a long-term annual sink of CO2 to an annual source from the terrestrial ecosystem and soils to the atmosphere. The results presented here demonstrate that nearly continuous observations may be required in order to accurately calculate the annual net ecosystem CO2 exchange of Arctic ecosystems and to build predictive understanding that can be used to estimate, with confidence, Arctic fluxes under future conditions.
Published: 2014

41. Assessing net ecosystem carbon exchange of U.S. terrestrial ecosystems by integrating eddy covariance flux measurements and satellite observations

Author: Xiao, Jingfeng, Zhuang, Qianlai, Law, Beverly E., Baldocchi, Dennis D., Chen, Jiquan, Richardson, Andrew D., Melillo, Jerry M., Davis, Kenneth J., Hollinger, David Y., Wharton, Sonia, Oren, Ram, Noormets, Asko, Fischer, Marc L., Verma, Shashi, Cook, David R., Sun, Ge, McNulty, Steve, Wofsy, Steven C., Bolstad, Paul V., Burns, Sean P., Curtis, Peter S., Drake, Bert G., Falk, Matthias, Foster, David R., Gu, Lianhong, Hadley, Julian L., Katul, Gabriel G., Litvak, Marcy, Ma, Siyan, Martin, Timothy A., Matamala, Roser, Meyers, Tilden P., Monson, Russell K., Munger, J. William, Oechel, Walter C., Kyaw Tha Paw, U., Schmid, Hans Peter, Scott, Russell L., Starr, Gregory, Suyker, Andrew E., Torn, Margaret S., Xiao, Jingfeng, Zhuang, Qianlai, Law, Beverly E., Baldocchi, Dennis D., Chen, Jiquan, Richardson, Andrew D., Melillo, Jerry M., Davis, Kenneth J., Hollinger, David Y., Wharton, Sonia, Oren, Ram, Noormets, Asko, Fischer, Marc L., Verma, Shashi, Cook, David R., Sun, Ge, McNulty, Steve, Wofsy, Steven C., Bolstad, Paul V., Burns, Sean P., Curtis, Peter S., Drake, Bert G., Falk, Matthias, Foster, David R., Gu, Lianhong, Hadley, Julian L., Katul, Gabriel G., Litvak, Marcy, Ma, Siyan, Martin, Timothy A., Matamala, Roser, Meyers, Tilden P., Monson, Russell K., Munger, J. William, Oechel, Walter C., Kyaw Tha Paw, U., Schmid, Hans Peter, Scott, Russell L., Starr, Gregory, Suyker, Andrew E., and Torn, Margaret S.
Abstract: More accurate projections of future carbon dioxide concentrations in the atmosphere and associated climate change depend on improved scientific understanding of the terrestrial carbon cycle. Despite the consensus that U.S. terrestrial ecosystems provide a carbon sink, the size, distribution, and interannual variability of this sink remain uncertain. Here we report a terrestrial carbon sink in the conterminous U.S. at 0.63 pg C yr−1 with the majority of the sink in regions dominated by evergreen and deciduous forests and savannas. This estimate is based on our continuous estimates of net ecosystem carbon exchange (NEE) with high spatial (1 km) and temporal (8-day) resolutions derived from NEE measurements from eddy covariance flux towers and wall-to-wall satellite observations from Moderate Resolution Imaging Spectroradiometer (MODIS). We find that the U.S. terrestrial ecosystems could offset a maximum of 40% of the fossil-fuel carbon emissions. Our results show that the U.S. terrestrial carbon sink varied between 0.51 and 0.70 pg C yr−1 over the period 2001–2006. The dominant sources of interannual variation of the carbon sink included extreme climate events and disturbances. Droughts in 2002 and 2006 reduced the U.S. carbon sink by ∼20% relative to a normal year. Disturbances including wildfires and hurricanes reduced carbon uptake or resulted in carbon release at regional scales. Our results provide an alternative, independent, and novel constraint to the U.S. terrestrial carbon sink.
Published: 2011

42. A model-data intercomparison of CO2 exchange across North America: results from the North American Carbon Program site synthesis

Author: Schwalm, Christopher R., Williams, Christopher A., Schaefer, Kevin, Anderson, Ryan S., Arain, M. Altaf, Baker, Ian T., Barr, Alan G., Black, T. Andrew, Chen, Guangsheng, Chen, Jing M., Ciais, Philippe, Davis, Kenneth J., Desai, Ankur R., Dietze, Michael C., Dragoni, Danilo, Fischer, Marc L., Flanagan, Larry B., Grant, Robert F., Gu, Lianhong, Hollinger, David Y., Izaurralde, R. Cesar, Kucharik, Christopher J., Lafleur, Peter M., Law, Beverly E., Li, Longhui, Li, Zhengpeng, Liu, Shuguang, Lokupitiya, Erandathie, Luo, Yiqi, Ma, Siyan, Margolis, Hank, Matamala, Roser, McCaughey, Harry, Monson, Russell K., Oechel, Walter C., Peng, Changhui, Poulter, Benjamin, Price, David T., Ricciuto, Daniel M., Riley, William J., Sahoo, Alok Kumar, Sprintsin, Michael, Sun, Jianfeng, Tian, Hanqin, Tonitto, Christina, Verbeeck, Hans, Verma, Shashi B., Schwalm, Christopher R., Williams, Christopher A., Schaefer, Kevin, Anderson, Ryan S., Arain, M. Altaf, Baker, Ian T., Barr, Alan G., Black, T. Andrew, Chen, Guangsheng, Chen, Jing M., Ciais, Philippe, Davis, Kenneth J., Desai, Ankur R., Dietze, Michael C., Dragoni, Danilo, Fischer, Marc L., Flanagan, Larry B., Grant, Robert F., Gu, Lianhong, Hollinger, David Y., Izaurralde, R. Cesar, Kucharik, Christopher J., Lafleur, Peter M., Law, Beverly E., Li, Longhui, Li, Zhengpeng, Liu, Shuguang, Lokupitiya, Erandathie, Luo, Yiqi, Ma, Siyan, Margolis, Hank, Matamala, Roser, McCaughey, Harry, Monson, Russell K., Oechel, Walter C., Peng, Changhui, Poulter, Benjamin, Price, David T., Ricciuto, Daniel M., Riley, William J., Sahoo, Alok Kumar, Sprintsin, Michael, Sun, Jianfeng, Tian, Hanqin, Tonitto, Christina, Verbeeck, Hans, and Verma, Shashi B.
Abstract: Our current understanding of terrestrial carbon processes is represented in various models used to integrate and scale measurements of CO2 exchange from remote sensing and other spatiotemporal data. Yet assessments are rarely conducted to determine how well models simulate carbon processes across vegetation types and environmental conditions. Using standardized data from the North American Carbon Program we compare observed and simulated monthly CO2 exchange from 44 eddy covariance flux towers in North America and 22 terrestrial biosphere models. The analysis period spans ∼220 site‐years, 10 biomes, and includes two large‐scale drought events, providing a natural experiment to evaluate model skill as a function of drought and seasonality. We evaluate models’ ability to simulate the seasonal cycle of CO2 exchange using multiple model skill metrics and analyze links between model characteristics, site history, and model skill. Overall model performance was poor; the difference between observations and simulations was ∼10 times observational uncertainty, with forested ecosystems better predicted than nonforested. Model‐data agreement was highest in summer and in temperate evergreen forests. In contrast, model performance declined in spring and fall, especially in ecosystems with large deciduous components, and in dry periods during the growing season. Models used across multiple biomes and sites, the mean model ensemble, and a model using assimilated parameter values showed high consistency with observations. Models with the highest skill across all biomes all used prescribed canopy phenology, calculated NEE as the difference between GPP and ecosystem respiration, and did not use a daily time step.
Published: 2010

43. A model-data intercomparison of CO2 exchange across North America: results from the North American Carbon Program site synthesis

Author: Schwalm, Christopher R., Williams, Christopher A., Schaefer, Kevin, Anderson, Ryan S., Arain, M. Altaf, Baker, Ian T., Barr, Alan G., Black, T. Andrew, Chen, Guangsheng, Chen, Jing M., Ciais, Philippe, Davis, Kenneth J., Desai, Ankur R., Dietze, Michael C., Dragoni, Danilo, Fischer, Marc L., Flanagan, Larry B., Grant, Robert F., Gu, Lianhong, Hollinger, David Y., Izaurralde, R. Cesar, Kucharik, Christopher J., Lafleur, Peter M., Law, Beverly E., Li, Longhui, Li, Zhengpeng, Liu, Shuguang, Lokupitiya, Erandathie, Luo, Yiqi, Ma, Siyan, Margolis, Hank, Matamala, Roser, McCaughey, Harry, Monson, Russell K., Oechel, Walter C., Peng, Changhui, Poulter, Benjamin, Price, David T., Ricciuto, Daniel M., Riley, William J., Sahoo, Alok Kumar, Sprintsin, Michael, Sun, Jianfeng, Tian, Hanqin, Tonitto, Christina, Verbeeck, Hans, Verma, Shashi B., Schwalm, Christopher R., Williams, Christopher A., Schaefer, Kevin, Anderson, Ryan S., Arain, M. Altaf, Baker, Ian T., Barr, Alan G., Black, T. Andrew, Chen, Guangsheng, Chen, Jing M., Ciais, Philippe, Davis, Kenneth J., Desai, Ankur R., Dietze, Michael C., Dragoni, Danilo, Fischer, Marc L., Flanagan, Larry B., Grant, Robert F., Gu, Lianhong, Hollinger, David Y., Izaurralde, R. Cesar, Kucharik, Christopher J., Lafleur, Peter M., Law, Beverly E., Li, Longhui, Li, Zhengpeng, Liu, Shuguang, Lokupitiya, Erandathie, Luo, Yiqi, Ma, Siyan, Margolis, Hank, Matamala, Roser, McCaughey, Harry, Monson, Russell K., Oechel, Walter C., Peng, Changhui, Poulter, Benjamin, Price, David T., Ricciuto, Daniel M., Riley, William J., Sahoo, Alok Kumar, Sprintsin, Michael, Sun, Jianfeng, Tian, Hanqin, Tonitto, Christina, Verbeeck, Hans, and Verma, Shashi B.
Abstract: Our current understanding of terrestrial carbon processes is represented in various models used to integrate and scale measurements of CO2 exchange from remote sensing and other spatiotemporal data. Yet assessments are rarely conducted to determine how well models simulate carbon processes across vegetation types and environmental conditions. Using standardized data from the North American Carbon Program we compare observed and simulated monthly CO2 exchange from 44 eddy covariance flux towers in North America and 22 terrestrial biosphere models. The analysis period spans ∼220 site‐years, 10 biomes, and includes two large‐scale drought events, providing a natural experiment to evaluate model skill as a function of drought and seasonality. We evaluate models’ ability to simulate the seasonal cycle of CO2 exchange using multiple model skill metrics and analyze links between model characteristics, site history, and model skill. Overall model performance was poor; the difference between observations and simulations was ∼10 times observational uncertainty, with forested ecosystems better predicted than nonforested. Model‐data agreement was highest in summer and in temperate evergreen forests. In contrast, model performance declined in spring and fall, especially in ecosystems with large deciduous components, and in dry periods during the growing season. Models used across multiple biomes and sites, the mean model ensemble, and a model using assimilated parameter values showed high consistency with observations. Models with the highest skill across all biomes all used prescribed canopy phenology, calculated NEE as the difference between GPP and ecosystem respiration, and did not use a daily time step.
Published: 2010

44. A model-data intercomparison of CO2 exchange across North America: results from the North American Carbon Program site synthesis

Author: Schwalm, Christopher R., Williams, Christopher A., Schaefer, Kevin, Anderson, Ryan S., Arain, M. Altaf, Baker, Ian T., Barr, Alan G., Black, T. Andrew, Chen, Guangsheng, Chen, Jing M., Ciais, Philippe, Davis, Kenneth J., Desai, Ankur R., Dietze, Michael C., Dragoni, Danilo, Fischer, Marc L., Flanagan, Larry B., Grant, Robert F., Gu, Lianhong, Hollinger, David Y., Izaurralde, R. Cesar, Kucharik, Christopher J., Lafleur, Peter M., Law, Beverly E., Li, Longhui, Li, Zhengpeng, Liu, Shuguang, Lokupitiya, Erandathie, Luo, Yiqi, Ma, Siyan, Margolis, Hank, Matamala, Roser, McCaughey, Harry, Monson, Russell K., Oechel, Walter C., Peng, Changhui, Poulter, Benjamin, Price, David T., Ricciuto, Daniel M., Riley, William J., Sahoo, Alok Kumar, Sprintsin, Michael, Sun, Jianfeng, Tian, Hanqin, Tonitto, Christina, Verbeeck, Hans, Verma, Shashi B., Schwalm, Christopher R., Williams, Christopher A., Schaefer, Kevin, Anderson, Ryan S., Arain, M. Altaf, Baker, Ian T., Barr, Alan G., Black, T. Andrew, Chen, Guangsheng, Chen, Jing M., Ciais, Philippe, Davis, Kenneth J., Desai, Ankur R., Dietze, Michael C., Dragoni, Danilo, Fischer, Marc L., Flanagan, Larry B., Grant, Robert F., Gu, Lianhong, Hollinger, David Y., Izaurralde, R. Cesar, Kucharik, Christopher J., Lafleur, Peter M., Law, Beverly E., Li, Longhui, Li, Zhengpeng, Liu, Shuguang, Lokupitiya, Erandathie, Luo, Yiqi, Ma, Siyan, Margolis, Hank, Matamala, Roser, McCaughey, Harry, Monson, Russell K., Oechel, Walter C., Peng, Changhui, Poulter, Benjamin, Price, David T., Ricciuto, Daniel M., Riley, William J., Sahoo, Alok Kumar, Sprintsin, Michael, Sun, Jianfeng, Tian, Hanqin, Tonitto, Christina, Verbeeck, Hans, and Verma, Shashi B.
Abstract: Our current understanding of terrestrial carbon processes is represented in various models used to integrate and scale measurements of CO2 exchange from remote sensing and other spatiotemporal data. Yet assessments are rarely conducted to determine how well models simulate carbon processes across vegetation types and environmental conditions. Using standardized data from the North American Carbon Program we compare observed and simulated monthly CO2 exchange from 44 eddy covariance flux towers in North America and 22 terrestrial biosphere models. The analysis period spans ∼220 site‐years, 10 biomes, and includes two large‐scale drought events, providing a natural experiment to evaluate model skill as a function of drought and seasonality. We evaluate models’ ability to simulate the seasonal cycle of CO2 exchange using multiple model skill metrics and analyze links between model characteristics, site history, and model skill. Overall model performance was poor; the difference between observations and simulations was ∼10 times observational uncertainty, with forested ecosystems better predicted than nonforested. Model‐data agreement was highest in summer and in temperate evergreen forests. In contrast, model performance declined in spring and fall, especially in ecosystems with large deciduous components, and in dry periods during the growing season. Models used across multiple biomes and sites, the mean model ensemble, and a model using assimilated parameter values showed high consistency with observations. Models with the highest skill across all biomes all used prescribed canopy phenology, calculated NEE as the difference between GPP and ecosystem respiration, and did not use a daily time step.
Published: 2010

45. A model-data intercomparison of CO2 exchange across North America: results from the North American Carbon Program site synthesis

Author: Schwalm, Christopher R., Williams, Christopher A., Schaefer, Kevin, Anderson, Ryan S., Arain, M. Altaf, Baker, Ian T., Barr, Alan G., Black, T. Andrew, Chen, Guangsheng, Chen, Jing M., Ciais, Philippe, Davis, Kenneth J., Desai, Ankur R., Dietze, Michael C., Dragoni, Danilo, Fischer, Marc L., Flanagan, Larry B., Grant, Robert F., Gu, Lianhong, Hollinger, David Y., Izaurralde, R. Cesar, Kucharik, Christopher J., Lafleur, Peter M., Law, Beverly E., Li, Longhui, Li, Zhengpeng, Liu, Shuguang, Lokupitiya, Erandathie, Luo, Yiqi, Ma, Siyan, Margolis, Hank, Matamala, Roser, McCaughey, Harry, Monson, Russell K., Oechel, Walter C., Peng, Changhui, Poulter, Benjamin, Price, David T., Ricciuto, Daniel M., Riley, William J., Sahoo, Alok Kumar, Sprintsin, Michael, Sun, Jianfeng, Tian, Hanqin, Tonitto, Christina, Verbeeck, Hans, Verma, Shashi B., Schwalm, Christopher R., Williams, Christopher A., Schaefer, Kevin, Anderson, Ryan S., Arain, M. Altaf, Baker, Ian T., Barr, Alan G., Black, T. Andrew, Chen, Guangsheng, Chen, Jing M., Ciais, Philippe, Davis, Kenneth J., Desai, Ankur R., Dietze, Michael C., Dragoni, Danilo, Fischer, Marc L., Flanagan, Larry B., Grant, Robert F., Gu, Lianhong, Hollinger, David Y., Izaurralde, R. Cesar, Kucharik, Christopher J., Lafleur, Peter M., Law, Beverly E., Li, Longhui, Li, Zhengpeng, Liu, Shuguang, Lokupitiya, Erandathie, Luo, Yiqi, Ma, Siyan, Margolis, Hank, Matamala, Roser, McCaughey, Harry, Monson, Russell K., Oechel, Walter C., Peng, Changhui, Poulter, Benjamin, Price, David T., Ricciuto, Daniel M., Riley, William J., Sahoo, Alok Kumar, Sprintsin, Michael, Sun, Jianfeng, Tian, Hanqin, Tonitto, Christina, Verbeeck, Hans, and Verma, Shashi B.
Abstract: Our current understanding of terrestrial carbon processes is represented in various models used to integrate and scale measurements of CO2 exchange from remote sensing and other spatiotemporal data. Yet assessments are rarely conducted to determine how well models simulate carbon processes across vegetation types and environmental conditions. Using standardized data from the North American Carbon Program we compare observed and simulated monthly CO2 exchange from 44 eddy covariance flux towers in North America and 22 terrestrial biosphere models. The analysis period spans ∼220 site‐years, 10 biomes, and includes two large‐scale drought events, providing a natural experiment to evaluate model skill as a function of drought and seasonality. We evaluate models’ ability to simulate the seasonal cycle of CO2 exchange using multiple model skill metrics and analyze links between model characteristics, site history, and model skill. Overall model performance was poor; the difference between observations and simulations was ∼10 times observational uncertainty, with forested ecosystems better predicted than nonforested. Model‐data agreement was highest in summer and in temperate evergreen forests. In contrast, model performance declined in spring and fall, especially in ecosystems with large deciduous components, and in dry periods during the growing season. Models used across multiple biomes and sites, the mean model ensemble, and a model using assimilated parameter values showed high consistency with observations. Models with the highest skill across all biomes all used prescribed canopy phenology, calculated NEE as the difference between GPP and ecosystem respiration, and did not use a daily time step.
Published: 2010

46. A model-data intercomparison of CO2 exchange across North America: results from the North American Carbon Program site synthesis

Author: Schwalm, Christopher R., Williams, Christopher A., Schaefer, Kevin, Anderson, Ryan S., Arain, M. Altaf, Baker, Ian T., Barr, Alan G., Black, T. Andrew, Chen, Guangsheng, Chen, Jing M., Ciais, Philippe, Davis, Kenneth J., Desai, Ankur R., Dietze, Michael C., Dragoni, Danilo, Fischer, Marc L., Flanagan, Larry B., Grant, Robert F., Gu, Lianhong, Hollinger, David Y., Izaurralde, R. Cesar, Kucharik, Christopher J., Lafleur, Peter M., Law, Beverly E., Li, Longhui, Li, Zhengpeng, Liu, Shuguang, Lokupitiya, Erandathie, Luo, Yiqi, Ma, Siyan, Margolis, Hank, Matamala, Roser, McCaughey, Harry, Monson, Russell K., Oechel, Walter C., Peng, Changhui, Poulter, Benjamin, Price, David T., Ricciuto, Daniel M., Riley, William J., Sahoo, Alok Kumar, Sprintsin, Michael, Sun, Jianfeng, Tian, Hanqin, Tonitto, Christina, Verbeeck, Hans, Verma, Shashi B., Schwalm, Christopher R., Williams, Christopher A., Schaefer, Kevin, Anderson, Ryan S., Arain, M. Altaf, Baker, Ian T., Barr, Alan G., Black, T. Andrew, Chen, Guangsheng, Chen, Jing M., Ciais, Philippe, Davis, Kenneth J., Desai, Ankur R., Dietze, Michael C., Dragoni, Danilo, Fischer, Marc L., Flanagan, Larry B., Grant, Robert F., Gu, Lianhong, Hollinger, David Y., Izaurralde, R. Cesar, Kucharik, Christopher J., Lafleur, Peter M., Law, Beverly E., Li, Longhui, Li, Zhengpeng, Liu, Shuguang, Lokupitiya, Erandathie, Luo, Yiqi, Ma, Siyan, Margolis, Hank, Matamala, Roser, McCaughey, Harry, Monson, Russell K., Oechel, Walter C., Peng, Changhui, Poulter, Benjamin, Price, David T., Ricciuto, Daniel M., Riley, William J., Sahoo, Alok Kumar, Sprintsin, Michael, Sun, Jianfeng, Tian, Hanqin, Tonitto, Christina, Verbeeck, Hans, and Verma, Shashi B.
Abstract: Our current understanding of terrestrial carbon processes is represented in various models used to integrate and scale measurements of CO2 exchange from remote sensing and other spatiotemporal data. Yet assessments are rarely conducted to determine how well models simulate carbon processes across vegetation types and environmental conditions. Using standardized data from the North American Carbon Program we compare observed and simulated monthly CO2 exchange from 44 eddy covariance flux towers in North America and 22 terrestrial biosphere models. The analysis period spans ∼220 site‐years, 10 biomes, and includes two large‐scale drought events, providing a natural experiment to evaluate model skill as a function of drought and seasonality. We evaluate models’ ability to simulate the seasonal cycle of CO2 exchange using multiple model skill metrics and analyze links between model characteristics, site history, and model skill. Overall model performance was poor; the difference between observations and simulations was ∼10 times observational uncertainty, with forested ecosystems better predicted than nonforested. Model‐data agreement was highest in summer and in temperate evergreen forests. In contrast, model performance declined in spring and fall, especially in ecosystems with large deciduous components, and in dry periods during the growing season. Models used across multiple biomes and sites, the mean model ensemble, and a model using assimilated parameter values showed high consistency with observations. Models with the highest skill across all biomes all used prescribed canopy phenology, calculated NEE as the difference between GPP and ecosystem respiration, and did not use a daily time step.
Published: 2010

47. A model-data intercomparison of CO2 exchange across North America: results from the North American Carbon Program site synthesis

Author: Schwalm, Christopher R., Williams, Christopher A., Schaefer, Kevin, Anderson, Ryan S., Arain, M. Altaf, Baker, Ian T., Barr, Alan G., Black, T. Andrew, Chen, Guangsheng, Chen, Jing M., Ciais, Philippe, Davis, Kenneth J., Desai, Ankur R., Dietze, Michael C., Dragoni, Danilo, Fischer, Marc L., Flanagan, Larry B., Grant, Robert F., Gu, Lianhong, Hollinger, David Y., Izaurralde, R. Cesar, Kucharik, Christopher J., Lafleur, Peter M., Law, Beverly E., Li, Longhui, Li, Zhengpeng, Liu, Shuguang, Lokupitiya, Erandathie, Luo, Yiqi, Ma, Siyan, Margolis, Hank, Matamala, Roser, McCaughey, Harry, Monson, Russell K., Oechel, Walter C., Peng, Changhui, Poulter, Benjamin, Price, David T., Ricciuto, Daniel M., Riley, William J., Sahoo, Alok Kumar, Sprintsin, Michael, Sun, Jianfeng, Tian, Hanqin, Tonitto, Christina, Verbeeck, Hans, Verma, Shashi B., Schwalm, Christopher R., Williams, Christopher A., Schaefer, Kevin, Anderson, Ryan S., Arain, M. Altaf, Baker, Ian T., Barr, Alan G., Black, T. Andrew, Chen, Guangsheng, Chen, Jing M., Ciais, Philippe, Davis, Kenneth J., Desai, Ankur R., Dietze, Michael C., Dragoni, Danilo, Fischer, Marc L., Flanagan, Larry B., Grant, Robert F., Gu, Lianhong, Hollinger, David Y., Izaurralde, R. Cesar, Kucharik, Christopher J., Lafleur, Peter M., Law, Beverly E., Li, Longhui, Li, Zhengpeng, Liu, Shuguang, Lokupitiya, Erandathie, Luo, Yiqi, Ma, Siyan, Margolis, Hank, Matamala, Roser, McCaughey, Harry, Monson, Russell K., Oechel, Walter C., Peng, Changhui, Poulter, Benjamin, Price, David T., Ricciuto, Daniel M., Riley, William J., Sahoo, Alok Kumar, Sprintsin, Michael, Sun, Jianfeng, Tian, Hanqin, Tonitto, Christina, Verbeeck, Hans, and Verma, Shashi B.
Abstract: Our current understanding of terrestrial carbon processes is represented in various models used to integrate and scale measurements of CO2 exchange from remote sensing and other spatiotemporal data. Yet assessments are rarely conducted to determine how well models simulate carbon processes across vegetation types and environmental conditions. Using standardized data from the North American Carbon Program we compare observed and simulated monthly CO2 exchange from 44 eddy covariance flux towers in North America and 22 terrestrial biosphere models. The analysis period spans ∼220 site‐years, 10 biomes, and includes two large‐scale drought events, providing a natural experiment to evaluate model skill as a function of drought and seasonality. We evaluate models’ ability to simulate the seasonal cycle of CO2 exchange using multiple model skill metrics and analyze links between model characteristics, site history, and model skill. Overall model performance was poor; the difference between observations and simulations was ∼10 times observational uncertainty, with forested ecosystems better predicted than nonforested. Model‐data agreement was highest in summer and in temperate evergreen forests. In contrast, model performance declined in spring and fall, especially in ecosystems with large deciduous components, and in dry periods during the growing season. Models used across multiple biomes and sites, the mean model ensemble, and a model using assimilated parameter values showed high consistency with observations. Models with the highest skill across all biomes all used prescribed canopy phenology, calculated NEE as the difference between GPP and ecosystem respiration, and did not use a daily time step.
Published: 2010

48. A model‐data intercomparison of CO2 exchange across North America: Results from the North American Carbon Program site synthesis

Author: Schwalm, Christopher R., Williams, Christopher A., Schaefer, Kevin, Anderson, Ryan S., Arain, M. Altaf, Baker, Ian, Barr, Alan, Black, T. Andrew, Chen, Guangsheng, Chen, Jing Ming, Ciais, Philippe, Davis, Kenneth J., Desai, Ankur R., Dietze, Michael, Dragoni, Danilo, Fischer, Marc L., Flanagan, Lawrence B., Grant, Robert, Gu, Lianhong, Hollinger, David, Izaurralde, R. Cesar, Kucharik, Chris, Lafleur, Peter, Law, Beverly E., Li, Longhui, Li, Zhengpeng, Liu, Shuguang, Lokupitiya, Erandathie, Luo, Yiqi, Ma, Siyan, Margolis, Hank, Matamala, Roser, McCaughey, Harry, Monson, Russell K., Oechel, Walter C., Peng, Changhui, Poulter, Benjamin, Price, David T., Riciutto, Dan M., Riley, William, Sahoo, Alok Kumar, Sprintsin, Michael, Sun, Jianfeng, Tian, Hanqin, Tonitto, Christian, Verbeeck, Hans, Verma, Shashi B., Schwalm, Christopher R., Williams, Christopher A., Schaefer, Kevin, Anderson, Ryan S., Arain, M. Altaf, Baker, Ian, Barr, Alan, Black, T. Andrew, Chen, Guangsheng, Chen, Jing Ming, Ciais, Philippe, Davis, Kenneth J., Desai, Ankur R., Dietze, Michael, Dragoni, Danilo, Fischer, Marc L., Flanagan, Lawrence B., Grant, Robert, Gu, Lianhong, Hollinger, David, Izaurralde, R. Cesar, Kucharik, Chris, Lafleur, Peter, Law, Beverly E., Li, Longhui, Li, Zhengpeng, Liu, Shuguang, Lokupitiya, Erandathie, Luo, Yiqi, Ma, Siyan, Margolis, Hank, Matamala, Roser, McCaughey, Harry, Monson, Russell K., Oechel, Walter C., Peng, Changhui, Poulter, Benjamin, Price, David T., Riciutto, Dan M., Riley, William, Sahoo, Alok Kumar, Sprintsin, Michael, Sun, Jianfeng, Tian, Hanqin, Tonitto, Christian, Verbeeck, Hans, and Verma, Shashi B.
Abstract: Our current understanding of terrestrial carbon processes is represented in various models used to integrate and scale measurements of CO2 exchange from remote sensing and other spatiotemporal data. Yet assessments are rarely conducted to determine how well models simulate carbon processes across vegetation types and environmental conditions. Using standardized data from the North American Carbon Program we compare observed and simulated monthly CO2 exchange from 44 eddy covariance flux towers in North America and 22 terrestrial biosphere models. The analysis period spans ~220 site‐years, 10 biomes, and includes two large‐scale drought events, providing a natural experiment to evaluate model skill as a function of drought and seasonality. We evaluate models’ ability to simulate the seasonal cycle of CO2 exchange using multiple model skill metrics and analyze links between model characteristics, site history, and model skill. Overall model performance was poor; the difference between observations and simulations was ~10 times observational uncertainty, with forested ecosystems better predicted than nonforested. Model‐data agreement was highest in summer and in temperate evergreen forests. In contrast, model performance declined in spring and fall, especially in ecosystems with large deciduous components, and in dry periods during the growing season. Models used across multiple biomes and sites, the mean model ensemble, and a model using assimilated parameter values showed high consistency with observations. Models with the highest skill across all biomes all used prescribed canopy phenology, calculated NEE as the difference between GPP and ecosystem respiration, and did not use a daily time step.
Published: 2010

49. Estimation of Net Ecosystem Carbon Exchange for the Conterminous United States by Combining MODIS and AmeriFlux Data

Author: Xiao, Jingfeng, Zhuang, Qianlai, Baldocchi, Dennis D., Law, Beverly E., Richardson, Andrew D., Chen, Jiquan, Oren, Ram, Starr, Gregory, Noormets, Asko, Ma, Siyan, Verma, Shashi, Wharton, Sonia, Wofsy, Steven C., Bolstad, Paul V., Burns, Sean P., Cook, David R., Curtis, Peter S., Drake, Bert G., Falk, Matthias, Fischer, Marc L., Foster, David R., Gu, Lianhong, Hadley, Julian L., Hollinger, David Y., Katul, Gabriel G., Litvak, Marcy, Martin, Timothy A., Matamala, Roser, McNulty, Steve, Meyers, Tilden P., Monson, Russell K., Munger, J. William, Oechel, Walter C., Tha Paw U, Kyaw, Schmid, Hans Peter, Scott, Russell L., Sun, Ge, Suyker, Andrew E., Torn, Margaret S., Xiao, Jingfeng, Zhuang, Qianlai, Baldocchi, Dennis D., Law, Beverly E., Richardson, Andrew D., Chen, Jiquan, Oren, Ram, Starr, Gregory, Noormets, Asko, Ma, Siyan, Verma, Shashi, Wharton, Sonia, Wofsy, Steven C., Bolstad, Paul V., Burns, Sean P., Cook, David R., Curtis, Peter S., Drake, Bert G., Falk, Matthias, Fischer, Marc L., Foster, David R., Gu, Lianhong, Hadley, Julian L., Hollinger, David Y., Katul, Gabriel G., Litvak, Marcy, Martin, Timothy A., Matamala, Roser, McNulty, Steve, Meyers, Tilden P., Monson, Russell K., Munger, J. William, Oechel, Walter C., Tha Paw U, Kyaw, Schmid, Hans Peter, Scott, Russell L., Sun, Ge, Suyker, Andrew E., and Torn, Margaret S.
Abstract: Eddy covariance flux towers provide continuous measurements of net ecosystem carbon exchange (NEE) for a wide range of climate and biome types. However, these measurements only represent the carbon fluxes at the scale of the tower footprint. To quantify the net exchange of carbon dioxide between the terrestrial biosphere and the atmosphere for regions or continents, flux tower measurements need to be extrapolated to these large areas. Here we used remotely sensed data from the Moderate Resolution Imaging Spectrometer (MODIS) instrument on board the National Aeronautics and Space Administration’s (NASA) Terra satellite to scale up AmeriFlux NEE measurements to the continental scale.We first combined MODIS and AmeriFlux data for representative U.S. ecosystems to develop a predictive NEE model using a modified regression tree approach. The predictive model was trained and validated using eddy flux NEE data over the periods 2000–2004 and 2005–2006, respectively. We found that the model predicted NEE well (r = 0.73, p < 0.001). We then applied the model to the continental scale and estimated NEE for each 1 km x 1 km cell across the conterminous U.S. for each 8-day interval in 2005 using spatially explicit MODIS data. The model generally captured the expected spatial and seasonal patterns of NEE as determined from measurements and the literature. Our study demonstrated that our empirical approach is effective for scaling up eddy flux NEE measurements to the continental scale and producing wall-to-wall NEE estimates across multiple biomes. Our estimates may provide an independent dataset from simulations with biogeochemical models and inverse modeling approaches for examining the spatiotemporal patterns of NEE and constraining terrestrial carbon budgets over large areas.
Published: 2008

50. On the use of MODIS EVI to assess gross primary productivity of North American ecosystems

Author: Sims, Daniel A., Rahman, Abdullah F., Cordova, Vicente D., El-Masri, Bassil Z., Baldocchi, Dennis D., Flanagan, Larry B., Goldstein, Allen H., Hollinger, David Y., Misson, Laurent, Monson, Russell K., Oechel, Walter C., Schmid, Hans P., Wofsy, Steven C., Xu, Liukang, Sims, Daniel A., Rahman, Abdullah F., Cordova, Vicente D., El-Masri, Bassil Z., Baldocchi, Dennis D., Flanagan, Larry B., Goldstein, Allen H., Hollinger, David Y., Misson, Laurent, Monson, Russell K., Oechel, Walter C., Schmid, Hans P., Wofsy, Steven C., and Xu, Liukang
Abstract: Carbon flux models based on light use efficiency (LUE), such as the MOD17 algorithm, have proved difficult to parameterize because of uncertainties in the LUE term, which is usually estimated from meteorological variables available only at large spatial scales. In search of simpler models based entirely on remote-sensing data, we examined direct relationships between the enhanced vegetation index (EVI) and gross primary productivity (GPP) measured at nine eddy covariance flux tower sites across North America. When data from the winter period of inactive photosynthesis were excluded, the overall relationship between EVI and tower GPP was better than that between MOD17 GPP and tower GPP. However, the EVI/GPP relationships vary between sites. Correlations between EVI and GPP were generally greater for deciduous than for evergreen sites. However, this correlation declined substantially only for sites with the smallest seasonal variation in EVI, suggesting that this relationship can be used for all but the most evergreen sites. Within sites dominated by either evergreen or deciduous species, seasonal variation in EVI was best explained by the severity of summer drought. Our results demonstrate that EVI alone can provide estimates of GPP that are as good as, if not better than, current versions of the MOD17 algorithm for many sites during the active period of photosynthesis. Preliminary data suggest that inclusion of other remote-sensing products in addition to EVI, such as the MODIS land surface temperature (LST), may result in more robust models of carbon balance based entirely on remote-sensing data
Published: 2006

Catalog

Books, media, physical & digital resources

See catalog results

Searchworks

Select search scope, currently: Articles Catalog books, media & more in Jio Institute collections Articles journal articles & other e-resources

Search

Search Constraints

Refine your results

Search Limiters

Publication Year Range

Publication Type

Database

Publisher

64 results on '"OECHEL, WALTER C."'

Search Results

Catalog

Select search scope, currently: Articles

Catalog

books, media & more in Jio Institute collections

Articles

journal articles & other e-resources